APPROVED: Weihuan Zhao, Major Professor Xiaohua Li, Committee Member Kuruvilla John, Committee Member and

Chair of the Department of Mechanical and Energy Engineering

Yan Huang, Interim Dean of the College of Engineering

Victor Prybutok, Dean of the Toulouse Graduate School

USE OF BIO-PRODUCT/PHASE CHANGE MATERIAL COMPOSITE IN THE

BUILDING ENVELOPE FOR BUILDING THERMAL CONTROL

AND ENERGY SAVINGS

Aravind Reddy Boozula

Thesis Prepared for the Degree of

MASTER OF SCIENCE

UNIVERSITY OF NORTH TEXAS

August 2018

Boozula, Aravind Reddy. Use of Bio-Product/Phase Change Material Composite in the

Building Envelope for Building Thermal Control and Energy Savings. Master of Science

(Mechanical and Energy Engineering), August 2018, 92 pp., 6 tables, 30 figures, 42 numbered

references.

This research investigates the bio-products/phase change material (PCM) composites for

the building envelope application. Bio-products, such as wood and herb, are porous medium,

which can be applied in the building envelope for thermal insulation purpose. PCM is infiltrated

into the bio-product (porous medium) to form a composite material. The PCM can absorb/release

large amount of latent heat of fusion from/to the building environment during the

melting/solidification process. Hence, the PCM-based composite material in the building

envelope can efficiently adjust the building interior temperature by utilizing the phase change

process, which improves the thermal insulation, and therefore, reduces the load on the HVAC

system. Paraffin wax was considered as the PCM in the current studies. The building energy

savings were investigated by comparing the composite building envelope material with the

conventional material in a unique Zero-Energy (ZØE) Research Lab building at University of

North Texas (UNT) through building energy simulation programs (i.e., eQUEST and

EnergyPlus). The exact climatic conditions of the local area (Denton, Texas) were used as the

input values in the simulations. It was found that the EnergyPlus building simulation program

was more suitable for the PCM based building envelope using the latent heat property.

Therefore, based on the EnergyPlus simulations, when the conventional structure insulated panel

(SIP) in the roof and wall structures were replaced by the herb panel or herb/PCM composite, it

was found that around 16.0% of energy savings in heating load and 11.0% in cooling load were

obtained by using PCM in the bio-product porous medium.

ii

Copyright 2018

By

Aravind Reddy Boozula

iii

ACKNOWLEDGMENTS

I would like to appreciate my major professor Dr. Weihuan Zhao for her guidance,

motivation, and suggestions, which facilitated me to perform my thesis successfully. And also, I

appreciate my professor for encouraging me to publish and present my work in the 3rd Thermal

and Fluids Engineering Conference where many scientists and researchers came to express their

thoughts and respective works.

I would also like to thank Dr. Sheldon Q. Shi and Dr. Liping Cai for helping me prepare

the infiltrated bio-product samples for the experimental testing.

iv

TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ............................................................................................................. iii

LIST OF TABLES ......................................................................................................................... vi

LIST OF FIGURES ...................................................................................................................... vii

CHAPTER 1. INTRODUCTION ................................................................................................... 1

1.1 Background of Buildings and their Performances .................................................. 1

1.2 Research, Goal and Objectives ............................................................................... 3

CHAPTER 2. LITERATURE REVIEW ........................................................................................ 5

2.1 Demand and Scope for Insulation in Buildings Envelope ...................................... 5

2.2 Usage of PCM in Wall Boards................................................................................ 5

2.3 PCM Infiltration into the Porous Materials Making a Composite .......................... 7

2.4 PCM Replacement with Wall Composites ............................................................. 8

2.5 Composite Encapsulation Techniques .................................................................. 10

2.6 Results and their Feasibility Obtained in the Simulation...................................... 11

2.7 Energy Savings with Different Techniques .......................................................... 12

2.8 Influence of Location and Climatic Conditions in Choosing PCM ...................... 13

2.9 Uniqueness of this Research ................................................................................. 14

CHAPTER 3. METHODOLOGY ................................................................................................ 15

3.1 Open Porosity Measurement by Pycnometer ........................................................ 15

3.2 Hot Disk Thermal Constant Analyzer for Thermal Conductivity Measurement .. 16

3.3 Heat Capacity Measurement by Differential Scanning Calorimeter (DSC) ......... 20

3.4 Temperature Variation Measurements .................................................................. 22

3.5 eQUEST Energy Simulations ............................................................................... 23

3.5.1 HVAC System in Zero Energy Building (GSHP) .................................... 23

3.5.2 Wall Layers in ZØE Building ................................................................... 24

3.5.3 Conduction Transfer Function (CTF) for Heat Transfer Equations ......... 25

3.6 EnergyPlus Simulations ........................................................................................ 27

CHAPTER 4. CHARACTERIZATIONS OF THE BIO-PRODUCT/PCM COMPOSITES’ THERMAL PROPERTIES ........................................................................................................... 29

v

4.1 Open Porosities and Densities of Bio-Product and Bio-Product/PCM Composites............................................................................................................................... 29

4.1.1 Non-Infiltrated Samples ............................................................................ 29

4.1.2 Infiltration Samples ................................................................................... 30

4.1.3 Half-Cut Samples ...................................................................................... 30

4.2 Thermal Conductivities ......................................................................................... 32

4.3 Specific Heat and Latent Heat of Fusion .............................................................. 33

4.4 Temperature Control by Using Bio-Product/PCM composites ............................ 38

4.4.1 Infiltrated and Infiltrated Pine Samples .................................................... 38

4.4.2 Non-Infiltrated and Infiltrated Cherry Samples ........................................ 39

4.4.3 Space Temperature Control by Using Herb/PCM Composites ................ 40

4.4.4 Temperature Difference Comparison between Pine, Cherry and Herb/PCM Composites ................................................................................................ 41

4.4 Alternatives to Overcome Inflamability of Paraffin Wax..................................... 42 CHAPTER 5. BUILDING ENERGY SIMULATION RESULTS .............................................. 44

5.1 Results on eQUEST .............................................................................................. 44

5.2 Results Obtained on EnergyPlus ........................................................................... 47

5.2.1 Comparison of the Heating and Cooling Loads between Conventional and Bio-Product/PCM Composite Embedded Building Envelopes ................ 47

5.2.2 Replacing SIP Layer by Composite Materials .......................................... 49

5.2.3 Replacement and Addition of Composite Materials for Wall and Roof Structures .................................................................................................. 52

5.2.4 Inside and Outside Wall Face Temperature Distribution (Hourly) for a Single Hot and Cold Days of the Year...................................................... 55

CHAPTER 6. CONCLUSIONS AND FUTURE RESEARCH ................................................... 61

6.1 Conclusions ........................................................................................................... 61

6.2 Future Research .................................................................................................... 61 APPENDIX A. RAW MATERIAL DATA .................................................................................. 63 APPENDIX B. eQUEST ENERGY INPUTS .............................................................................. 72 APPENDIX C. ENERGYPLUS INPUTS .................................................................................... 79 REFERENCES ............................................................................................................................. 89

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LIST OF TABLES

Page

Table 3.1: Specifications of TPS 1500 [35] .................................................................................. 17

Table 3.2: Wall construction layers for the ZØE lab .................................................................... 24

Table 4.1: Summary of porosities and densities ........................................................................... 31

Table 4.2: Summary of average latent heat of fusions for various bio-product composites ........ 38

Table 5.1: Summary of typical energy savings in eQUEST ......................................................... 46

Table 5.2: Summary of typical Energy savings in EnergyPlus .................................................... 55

vii

LIST OF FIGURES

Page

Figure 3.1: Pycnometer (Ultra-Foam 1200e) ................................................................................ 16

Figure 3.2: (a) Hot plate thermal constant analyzer setup, (b) TPS 1500, (c) Dynamic sensor ... 20

Figure 3.3: Schematic DSC test on PCM [37] .............................................................................. 21

Figure 3.4: (a) DSC chamber set-up (b) Chiller ........................................................................... 21

Figure 3.5: (a) sample containers placed on the hot plate which is set to 100oC (b) DAQ (c) DAQ software which tracks the temperature variation. ......................................................................... 22

Figure 3.6: 3D Extruded image, .................................................................................................... 23

Figure 3.7: 3D HVAC (water circulation) in eQUEST. ............................................................... 24

Figure 3.8: ZØE building designed in SketchUp for EnergyPlus simulation............................... 27

Figure 4.1: Open porosity of non- infiltrated pine and cherry woods .......................................... 29

Figure 4.2: Open porosity of infiltrated pine and cherry woods ................................................... 30

Figure 4.3: Open porosity of sliced infiltrated woods .................................................................. 31

Figure 4.4: Thermal conductivity measurements for various types of woods and infiltrated woods. (a) For non-infiltrated pine wood samples, (b) for infiltrated pine wood samples with PCM, (c) for non-infiltrated cherry wood samples, (d) for infiltrated cherry wood samples with PCM. ............................................................................................................................................. 33

Figure 4.5: Specific heat and latent heat of fusion of pure paraffin wax ...................................... 34

Figure 4.6: Specific heat and latent heat of fusion of the wood samples and the wood/PCM composite materials from the DSC measurements (a to f). .......................................................... 36

Figure 4.7: Specific heat and latent heat of fusion of the herb /PCM composite materials from the DSC measurements (a, b) ............................................................................................................. 38

Figure 4.8: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated pine woods) ........................................................................................................................................... 39

Figure 4.9: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated cherry woods)................................................................................................................................ 40

Figure 4.10: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated herbs)............................................................................................................................................. 41

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Figure 4.11: Temperature reduction using infiltrated bio-products compared to non-infiltrated ones ............................................................................................................................................... 42

Figure 5.1: Energy consumption in the ZØE lab through the eQUEST simulations (a) Annual energy consumption, (b) Energy consumption in the summer month (July). ............................... 45

Figure 5.2: (a) Monthly utility bills through out a year (b) Utility bills exclusively for the month of July (Summer) .......................................................................................................................... 45

Figure 5.3: Energy consumption in the ZØE lab when replaced with PCM composite in roof and wall constructions ......................................................................................................................... 46

Figure 5.4: (a) Monthly heating load distribution (b) Monthly cooling load distribution (c) Annual cooling power savings for different combinations with composites, compared with SIP roof ................................................................................................................................................ 49

Figure 5.5: (a) Monthly heating load distribution, (b) Annual heat load savings for different composites compared with wood/ herb......................................................................................... 50

Figure 5.6: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/ herb......................................................................................... 51

Figure 5.7: (a) Monthly heating load distribution, (b) Annual heating load savings for different composites compared with wood/ herb......................................................................................... 53

Figure 5.8: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/herb.......................................................................................... 54

Figure 5.9: Hourly temperature distributions along (a) Summer inside wall (b) Summer outside wall faces (c)Winter inside wall (d) Winter outside wall faces .................................................... 57

Figure 5.10: Hourly temperature difference between conventional SIP and herb/PCM composite roof conditions in (a) summer interior face of the roof (b) summer exterior face of the roof (c) winter interior face of the roof (d) winter exterior face of the roof .............................................. 60

1

CHAPTER 1

INTRODUCTION

Buildings have always been addressing the changing social needs of people. With the

growing demand of energy worldwide, the expected decline of energy sources and their potential

harmful effects on the environment especially the fossil fuels, a lot of research is in progress to

make buildings more energy efficient. A prominent approach to achieve energy efficiency in

buildings was addressed by the building envelope materials. Use of phase change materials

(PCMs) in building envelope is a promising approach to achieve huge amount of heat storage,

and thereby, to mitigate the peak energy consumption. Besides, improving the strength of PCM

by infiltrating it into some suitable porous mediums.

1.1 Background of Buildings and their Performances

Historically, the construction of buildings started with simple forms [1], just sheltering

people from wind, sun and rain. As time went on, the desire for better shelter grew, at the same

time the suitable materials had been identified. The best example was the vernacular architecture

for the wise and effective usage of available materials like mud, grass, bamboo, thatch or sticks

to counter the environmental fluctuations based on the understanding of the climate. As the

society was growing, the buildings evolved from slow change in the design, building materials

and construction techniques to a very high pace dictated by the requirements. For many

centuries, walls in Europe were being built with masonry (bricks), wood, or clay material.

Considering their size or massiveness, these walls were very strong and durable while providing

the thermal protection through their natural heat storage capacity and thermal insulation

properties.

2

Vernacular adobe buildings of New Mexico and Roman buildings made of bricks and

concrete related to the Trajan Baths, which was an epitome of modern building engineering

technology were built to absorb, store, and release ambient heat and captured solar energy so that

the net energy flow could be balanced for several days. In chilling climate areas where masonry

(bricks) were not available, log houses or half-timber with clay infill or earth treatments were built

for optimal insulation.

The term “building envelope” implies total wall, roof, floor and fenestration aspects of a

building structure [2]. Building envelope is the separation between the conditioned and

unconditioned environment to provide thermal resistance.

Currently, the building envelope is a composition of various thermal and permeable

layers composed of components with different structural properties. The choice of envelope is

governed by the local climate and society needs for the better efficiencies based on the ASHRAE

standards [4] and estimated by two contrary design concepts: the open frame shell and the closed

shell.

In harsh climates including noise or visual clutter, the designer most often considers the

building envelope as some closed shell and proceeds to selectively punch holes in it to make

limited and special contact with the outdoors. When external conditions are close to the desired

internal ones, the envelope often conceives as an open structural frame, which is exclusively

designed to overcome only few factors like wind, sunlight etc.

The flow of heat through the building envelope varies both by season and by the path of

the heat. These complexities must be considered by a material engineer who intends to deliver

comfort and energy optimization.

3

In order to say that a building is efficient, it is essential that a common set of

measurements be used, and the results reported must be following certain protocols [5].

American Society of Heating, Refrigerating and Air-Conditioning Engineers ASHRAE’s

Performance Measurement Protocols (PMP) for Commercial Buildings, suggested some

standardized set of protocols, for different ranges of cost and energy consumption accuracy, to

facilitate the appropriate comparison of measured water, energy and indoor environmental

quality performance of commercial buildings, while maintaining acceptable levels of building

service for the occupants and to rate the building’s quality by its performance and sends out the

feedback if the performance is not up to the design intent. Targets are included in the rules

proposed to facilitate comparison to peer buildings.

1.2 Research, Goal and Objectives

The main goal of the current study is to find the importance of bio-product infiltrated

with phase change materials (PCMs) for residential buildings and small offices in reducing the

load on HVAC systems thereby, improving the energy savings. Two types of bio-products were

investigated by this research, i.e., wood and herb. As the wood is predominantly used for the

construction purposes in the United States, the infiltration of wood could play a pivotal role in

the future. On the other hand, the herb material provides moisture-durability, pest resistance,

cavity-filling, air-movement-retarding, ecologically-sound insulation with substantial insulation

for retrofit/renovation projects. The reason of using PCM in the building envelope is for its

property of being able to absorb large amount of latent heat during the melting process and

release the heat back to the building environment during the solidification process.

Consequently, it can efficiently control the building interior temperature. Furthermore, the direct

4

infiltration of PCMs in the bio-product based porous medium will minimize the effect on the

original building envelop structure, and therefore, simplify the assembling procedure. In this

work, paraffin wax was used as the PCM embedded in two types of woods (cherry wood and

pine wood) as well as in herb cellulose chips. The bio-product/PCM composite has been

investigated for its suitability as a prospect for energy storage thereby, enhancing the thermal

insulation of the building envelope.

The effects of the composite materials on building interior temperature and energy

savings were investigated based in a Zero-Energy (ZØE) lab building at University of North

Texas (UNT). ZØE lab is a distinctive building in Texas designed mainly to test and demonstrate

various alternative energy generation technologies in order to achieve a net-zero energy power

consumption. The lab is spread over an area of 1200 square foot, including a living quarter with

a bedroom and a kitchen, and a working space. As part of its mission, the current study is mainly

concentrating on reducing the load on HVAC system by replacing one of the layers in the

structural insulated panel (SIP) wall with a bio-product/PCM composite based panel in the

building.

The objectives of this research are to (1) characterize the properties of bio-product/PCM

composites, (2) study the effect of PCM infiltrated bio-product porous materials on thermal

insulation in terms of energy savings in building through the simulation of a simple office

building-type building (the ZØE lab at UNT).

5

CHAPTER 2

LITERATURE REVIEW

2.1 Demand and Scope for Insulation in Buildings Envelope

United States is currently consuming 50% of its energy for the buildings and expected to

raise by 56% in the world between 2010 and 2040. We’re living in a world of power-hungry

equipment, resulting in electricity demand swelling [6]. Hence, the demands for the energy

savings as well as thermal comfort are increasing. Different techniques have been developed to

improve the effective usage of electricity. One way is to improve the heat capacities and thermal

resistances of the building envelope materials. Suresh B. Sadineni et al. [7] made an elaborative

technical review of the building envelope constituents which included wall materials, structure

layers, and their relevant improvements from energy savings view point. Energy efficient walls

such as Trombe walls, ventilated walls and glazed walls had been studied, with emphasis on

performance of various fenestration technologies which included aerogel, vacuum glazing and

frames. Innovations in energy efficient roofs like green roofs, photovoltaic roofs, radiant-

transmittive barrier and evaporative roof cooling systems were studied in this review paper. And

came up with a holistic design to reduce the mechanical system costing.

2.2 Usage of PCM in Wall Boards

Vineet Veer Tyagi et al. [8] made a cogent study on various methods for conditioning in

buildings, where he discussed the thermal performance of various types of systems like PCM

trombe wall as in the case of previous reference, PCM wallboards, PCM shutters, PCM building

blocks, air-based heating systems, floor heating, ceiling boards etc and materials used with

melting range of 20oC to 32oC. Later, suggested passive &active system storages for various wall

6

thicknesses and demand for heat transfer rate applications. Jaume Gasia et al. [9] explained about

phase change property in energy storage especially the usage of waste heat obtained from

industrial and domestic appliances by using RT58 as the PCM, by studying its thermal and

cycling stability, health hazard, phase change thermal range, enthalpy and specific heat, besides

analyzing the effect of heat on gravity, thermal cycling and infrared spectroscopy. Furthermore,

J.S. Sage-Lauck et al. [10] explored the use of PCMs to reduce the number of overheated hours

and improve thermal comfort for a case study of passive house duplex, which is located in

Portland, Oregon, USA. For that a duplex home was thoroughly probed to monitor indoor air

quality metrics and building energy power consumption. A unit of the duplex attached to a 130

Kgs of PCM. The performance of the PCM was evaluated through computer simulation by

EnergyPlus building energy simulation model compared with obtained experimental results. The

study observed that with PCM installation could reduce estimated overheated hours throughout

the year from 400 hours to 200 hours. Also reducing the melt temperature of the PCM below

25 °C would negatively impact human thermal comfort. Finally, location change of PCM from

behind the drywall to the interior wall surface reduced zone hours overheating by more than

60%. On the other hand, Jan Kośny et al. [11] investigated the ways to improve the thermal

design of the residential home roofs and floors to minimize the cooling energy consumption in

the cooling-dominated and mixed climatic conditions focusing on dynamic thermal

characteristics of PCM contribution towards insulation. They found that the encapsulation of

PCM into the floor and roof could provide notable reductions of thermal loads by 25% to 35% at

the attic level besides, 5-hour cooling peak load shift in time. The above analysis strengthens the

point that, temporary energy storage can lead to the reduction in power consumption by the

buildings. Talking about uniform temperature maintaining of the buildings by using PCMs,

7

Francesco Fiorito et al. [12] found that these materials, were able to supply dynamic thermal

capacity, especially in light weight building constructions to minimize the fluctuating radiant

temperatures. A test room, with naturally conditioned typical office, had been simulated in

EnergyPlus with the PCM property input. The various locations of unit within the component

and the thickness are carefully studied for optimal savings besides, thermal comfort for

desirability. Interestingly, the influence of the PCM material is directly depending on the

thickness of its layer and on the area of exposed. However, the thermal comfort is valid only for

limited thicknesses. Not only that, in some very well insulated buildings, the thermal resistance

because of the insulation, makes the PCM not effective if integrated in innermost layer

(Conventional). Shazim Ali Memon et al. [13] conducted an extensive study on the embodiment

of PCM into construction materials through various techniques including infiltration and

elements by direct incorporation, with other methods and form-stable composite PCMs. The

comparison between shape-stabilized and form-stable composite PCM has been made to find out

the optimal structure. Besides influence of materials like diatomite, expanded perlite and graphite

etc. that are used to stabilize composite PCM. To determine the chemical compatibility, thermal

properties, thermal stability and thermal conductivity of PCM composite, FT-IR, DSC, TGA and

hot wire method had been proposed and advised that, durability, fire resistance and long term

thermal behavior of PCM enhanced wallboards & concrete should be researched.

2.3 PCM Infiltration into the Porous Materials Making a Composite

The infiltration of PCMs in building envelope has been investigated for many years.

Athienitis et al. [14] have studied about the effect of wall latent heat storage on the thermal

performance of a passive solar test-room by using PCM infiltrated Gypsum inside wall lining.

8

They found that the application of PCMs in building envelope components can reduce the room

temperatures in the morning by 4°C as well as the heating load at nights, due to absorption of

solar heat in the PCM board which is in turn conjunction with melting of the butyl stearate. This

paper also gave a substantial evidence to conclude that PCM applied over a large surface area in

a passive solar building is effective for storage of solar gains and improvement of thermal

comfort. Further the study to maintain constant temperature for a long time in the buildings with

the help of PCM concentration in the building walls was studied by Amar M. Khudhair et al.

[15], summarized the investigation and analysis of thermal energy storage systems and their

efficiency. More importantly, a group headed by Mario A. Medina et al. [16] worked on heat

transfer reduction rate with the help of combining PCMs with Structural Insulated Panels (SIPs)

forming PCMSIP. The heat transfer rate per unit area reduced by the PCMSIPs of 10% and 20%

PCM were 37% and 62%, respectively. The average reductions in heat transfer rate on daily

basis across the PCMSIPs were 33% and 38% by replacing of 10% and 20% SIP with PCM,

respectively. They found that, greater the temperature difference between day and night, the

better the PCM works to reduce the heat transfer through the walls. Wang et al. [17] reviewed

the research on various phase change building materials, thermal energy storage building

envelopes and their thermal performance designs.

2.4 PCM Replacement with Wall Composites

Angela C. Evers et al. [18] incorporated PCMs in building materials for use as latent heat

storage leading to energy savings. In this work two types of PCMs namely, paraffin-based and

hydrated salt-based, were mixed into loose-fill cellulose (obtained from recycled newsprint)

insulation with concentrations of 10% and 20% in a 1.22 m × 1.22 m (48 in. × 48 in.) frame wall

9

cavity. The paraffin-based PCM-enhanced insulation reduced the average peak heat flux by up to

9.2% and total daily heat flow up to 1.2%, when thermally-enhanced frame walls were heated

and allowed to cool down in a dynamic wall simulator on a typical summer day phenomenon.

The hydrated salt-based PCM-enhanced insulation was not suitable for the building application

because of its hygroscopic behavior. Hence, they concluded that paraffin-based PCMs were a

suitable medium for thermal storage in building envelope. J.F. Belmonte et al. [19] discussed

about the importance of PCMs for cooling applications especially in buildings to reduce the

indoor air temperature fluctuations to maximum extent due to solar and internal gains, enabling

passive solar, HVAC system downsizing or off-peak cooling designs. The approach towards

studying discharging heat stored in PCM, differed from the conventional practice of

accomplishing this task by either night cooling ventilation or embedding an active heat

exchanger into the PCM of the wall. Rather in this paper, a PCM was incorporated into the floor,

and a hydronic radiant ceiling system was used as the energy discharge system. The advantages

and disadvantages of this approach in terms of cooling energy demands, thermal comforts of

occupants and design parameters were analyzed using the simulation software TRNSYS and

GenOpt. The results showed that with air-air heat recovery system saved more than 50% cooling

energy demand compared to the same building without PCM. Frédéric Kuznik et al. [20]

conducted a comprehensive review about integration of PCMs in building walls, in which

physical properties of building envelope and PCMs, phase change material integration, thermo-

physical property measurements and advantages and disadvantages of numerical studies were

particularly mentioned. M.A. Izquierdo-Barrientos et al. [21] revealed some interesting details

about the application of PCMs which helped to diminish the extent of instantaneous heat flux

across the wall during the summer due to the elevated solar radiation fluxes. However, there was

10

no noticeable reduction in the total heat lost during the winter regardless of the wall orientation

or PCM transition temperature. Inclusion of a PCM layer increased the thermal load during the

day while decreasing it during the night indicates the high thermal inertia of the walls. A one-

dimensional transient heat transfer model is developed to study the influence of PCMs in

external building walls and solved by a finite differencing method. Later, different external

building wall constructions were being analyzed for a common building wall with changing

PCM layer location, the orientation of the wall, the ambient conditions and the phase transition

temperature of the PCM between temperatures of 5oC and 35oC.

2.5 Composite Encapsulation Techniques

PCM encapsulation can be done in two ways: 1. Macro-encapsulation, 2. Micro-

encapsulation. As the PCM was infiltrated into porous medium, the composite could be

encapsulated by a sheet like membrane (e.g. plastic), which could restrict the PCM flow out of

the porous medium [22]. The plastic sheets were made into containers, sealed with plastic foils,

which were used for the encapsulation of PCM composite. It made a better suit to block all the

vents on the surface of the infiltrated porous medium to restrict the flow, besides being cost

effective. To ensure tightness in the container, the plastic foils were combined with the metallic

layers to improve its strength thereby to stop PCM to settle at the bottom of the container.

On the other hand, micro encapsulation process is simple but compared to macro-

encapsulation, not a cost-effective process. The micro-size PCM was encapsulated in a solid

shell to perform the phase change process. Mahyar Silakhori et al. [23] conducted a research on

thermal cycling of micro-encapsulated paraffin wax/polyaniline for Solar Thermal Energy

Storage, where they used paraffin wax, aniline (C6H7N) as a core (PCM) and shell materials

11

respectively in various ratios like 0.1/0.9, 0.2/0.8, 0.3/0.7, 0.7/0.3 g. The average latent heats of

melting and freezing were around 60–65 J/g for each composite, which makes them reliable in

terms of the thermal cycling test. At the same time, according to Fourier Transform Infrared

Spectrophotometer Results (FTIR), accelerated thermal cycling does not cause any degradation

in the chemical structure of the PCM. Hence, depending on the requirement the type of

encapsulation should be chosen. For current study, as the PCM was already been imbedded in

porous media, macro-encapsulation is a better option.

2.6 Results and their Feasibility Obtained in the Simulation

Zwanzig et al. [24] conducted numerical simulations of phase change material composite

wallboard in the multi-layered building envelope, and realized that the energy consumption can

be reduced, and the peak electricity load can also be shifted by using PCM composite wallboard

when used in the building. The most striking research was done by Augustin Tardieu et al. [25],

to predict the thermal performance of office size test rooms located at the Tamaki Campus,

University of Auckland, New Zealand using EnergyPlus software. Both the simulation and actual

data collected has shown that the use of phase change material wallboards improves the thermal

inertia of buildings for long-term measurements. It showed that PCM-gypsum wallboard as

internal wall linings are successful in capturing solar energy. The simulated results showed that

the additional thermal mass of the PCM could reduce up to 4°C indoor temperature fluctuations

on a typical summer day, showing the ability of the PCM to remain at the comfort level without

air-conditioning. When it comes to the veracity of the building energy estimation, experimental

studies are more accurate than the commercial software tools available in the market like Trane

trace, EnergyPlus, eQUEST, HAP etc. To find the accuracy of them, Chun-long Zhuang et al.

12

[26] surveyed the EnergyPlus constructions solution algorithm besides, heat balance method and

came up with a new conduction finite difference solution algorithm and enthalpy-temperature

function features. For that two types of envelopes are considered namely A and B. The relativity

difference on ‘A’ envelope is 12.41% and the least is 0.71% between the simulation and testing

value in 36 hours stretch, whereas on the ‘B’ envelope condition the most relativity difference is

8.33% and the least is 0.33% in sequential 72 hours. The results showed good agreement with

well-established in this simulation tools and shown that the algorithm defined in EnergyPlus

could simulate the latent heat property of PCMs in building construction. When it came to the

authenticity of the EnergyPlus simulation software, Paulo Cesar Tabares-Velasco et al, [27]

showed the procedure to verify and validate the PCM model in EnergyPlus using an approach as

dictated suggested by ASHRAE Standard 140, with analytical verification, comparative testing,

and empirical validation as part of it. This process was valuable, for the reason that, two issues

related to variable thermal conductivities which was later fixed by sizing the variable thermal

conductivity array, and version 7.1 of EnergyPlus was updated with proved PCM model effects.

Preliminary results using whole-building energy analysis showed that careful analysis should be

done when designing PCMs in homes, as their thermal performance depended on several

variables such as PCM properties and location in the building envelope. This research opened

multiple dimensions for future research on PCMs, including the ability to confidently investigate

different PCM material properties, configurations, and locations within a house.

2.7 Energy Savings with Different Techniques

Albeit performance, the investment is also a factor for a success of the product so,

Kaushik Biswas et al. [28] described in his article about a novel PCM made of naturally

13

occurring fatty acids/glycerides trapped into high density polyethylene (HDPE) pellets and its

performance in a building envelope application. The mixture of PCM–HDPE pellets with

cellulose insulation and tested for several months by placing it in the building exterior walls. To

demonstrate the savings of the PCM-enhanced cellulose insulation in reducing the building

envelope heat gains and losses, a parallel comparison was performed with another wall section

filled with only cellulose insulation. Further, numerical modeling of the test wall was performed

to determine the actual impact of the PCM–HDPE pellets on wall-generated heating and cooling

loads and the associated electricity consumption. Yassine Khar bouch et al. [29] aimed to

optimize the design of an air-conditioned multi-zone house integrated PCMs considering the

north Moroccan climate conditions. The objective of this optimization was to minimize the

heating and cooling loads. The methodology of this optimization was based on the coupling

between EnergyPlus as a dynamic simulation tool and GenOpt as an optimization tool for

parametric study. The results show that the obtained optimal design allows minimizing the

energy consumption compared to conventional envelopes.

2.8 Influence of Location and Climatic Conditions in Choosing PCM

After deciding and finding out that the PCM incorporation would have a significant effect

on the power savings, it is very much important to find out the location of it in one of the wall

layers for optimal savings. Xing Jin et al. [30] emphasized the dependence of thermal

performance on PCM location for optimal PCM location study for test system. For that, PCMs

were incorporated in walls between thermal shields, firstly it was encapsulated with polyethylene

flat bubbles then sandwiched between two layers of special custom-made Al foil called “PCM

thermal shield (PCMTS)”. The thermal performance with PCMTS was studied experimentally

14

with Conduction Finite Differentiating Algorithm by a dynamic wall simulator. The optimal

position for PCM was found out to be the farthest from the source simulator close to internal

surfaces. On the other hand, the optimal location for a PCMTS was at 1/5 times thickness of the

insulation cavity distance from the internal surface of the bounding wallboard. The average peak

heat flux reduction and load shifting time were approximately 41% and 2 hours, respectively at

the specified location. Nevertheless, much of research on PCM embedded building envelope is

focusing on PCM embedded in metal (such as aluminum), Gypsum wallboards, concrete, clay

bricks or insulation materials in the building envelope [31-34].

2.9 Uniqueness of this Research

The bio-product materials used in the current study are available in the market at low

prices compared to the other building envelope materials such as steel, aluminum, or other

metals. For this reason, bio-products, such as wood etc., are being, and have the great potential to

be, used in the most of residential building envelopes. When the paraffin wax is used directly as

one of the wall layers, as some damage occurs, the liquid PCM may drain out quickly. Whereas,

bio-product/PCM composite provides certain level of resistance against the leakage and gives

time to rectify and fill the gaps.

This research work conducted comprehensive studies on the bio-product/PCM composite

materials’ thermal properties and the building energy savings by using various bio-product based

composites.

15

CHAPTER 3

METHODOLOGY

3.1 Open Porosity Measurement by Pycnometer

The amount of PCM that could be infiltrated into the bio-products, determined by the

empty space inside it (open porosities). And the instrument called Pycnometer (Figure 3.1) could

be utilized to calculate that property. This instrument is specially designed to measure the true

volume, densities, and porosities of foam and bulk solid materials by employing Archimedes’

principle of fluid displacement and technique of gas expansion (Boyle’s law). Basically, a gas is

used as displacing fluid, since it penetrates through the finest pores with promising maximum

accuracy. Helium gas is highly recommended as fluid, since its small atomic dimensions with

assuring accuracies up to the pore sizes close to 0.2 nm in diameter.

To find the open porosities of the foam materials like woods, a specified Ultra-Foam

version in Pycnometer as shown in figure 3.1 was used which automatically measures the open

and closed cell content. For this study two types of wood samples were being tested – cherry and

pine woods. The sizes of each wood sample for the test was around 2.7cm×2.6cm×2.1cm, which

happens to be accommodated by medium size cell of about 28.9583 cm3 under 6 psi pressure.

Finally, the absolute volumes, densities and open porosities were obtained by providing the

system and sample properties like pressure, purge time, number of runs, cell size, weight and

volume. The governing equation of Pycnometer to find the absolute volume, which leads to the

calculation of open porosities is as indicated in the equation 3.1

𝑉𝑉𝑐𝑐 = Vcal + 𝑉𝑉𝐴𝐴(P2/𝑃𝑃1)−1

(3.1)

Where Vc is the volume of the whole cell (where sample can be placed), Vcal is the

calculated solid volume of the porous sample, which was later being provided to the Pycnometer,

16

VA is the absolute volume of the sample, obtained when Helium gas was passed through the

pores, P2 is the pressure in the value that was connected to the cell and P3 is the final pressure

after the value was being released.

Figure 3.1: Pycnometer (Ultra-Foam 1200e)

3.2 Hot Disk Thermal Constant Analyzer for Thermal Conductivity Measurement

Though the current research is focused on to find out the importance of latent heat

capacity of bio-products/PCM composite in improving the building envelope insulation, thermal

conductivity would help to overcome the minor energy saving errors. Hot disk thermal constant

analyzer is currently one the best instrument used to calibrate the thermal conductivity, specific

heat capacity, diffusivity and other thermal properties. It uses a transient plane source (TPS)

thermal characterization technique (procedure of a transiently heated plane sensor) for optimal

accuracy in complex materials, like Nano-particles.

17

The thermal conductivities of wood and wood/PCM composite materials were measured

on a Hot plate thermal constant analyzer (TPS 1500), with specifications mentioned as in Table

3.1. The sample was placed in such a way that two wood specimens sandwich the Kapton sensor

(has Ni spiral for heating), which is used as both the heat source and a temperature sensor (9 mm

diameter circular flat sheet for large samples). The whole set was in turn placed in an enclosure

to restrict any air current influence on readings. The test was conducted over a 160 second period

with a power of 37.6 mW and a reference resistance of 6.2 ohms to raise the temperature by 3oC.

Finally, the heat supplied per unit time and unit area would be used to determine the thermal

conductivity. The experimental set-up is displayed in Fig 3.2 (a), (b) &(c).

Table 3.1: Specifications of TPS 1500 [35]

Thermal Conductivity 0.01 to 400 W/m/K.

Thermal Diffusivity 0.01 to 100 mm²/s.

Specific Heat Capacity Up to 5 MJ/m³K.

Measurement Time 20 to 5120 seconds.

Reproducibility Typically, better than 1 %.

Accuracy Better than 5 %.

Temperature Range -50 °C to 750 °C.

Core Instrument Ambient

With Furnace Up to 750 °C

With Circulator -35 °C to 200 °C.

Power Requirements Adjusted to the line voltage in the country of use.

Smallest Sample Dimensions

3 mm × 13 mm diameter or square for bulk testing. 20 mm × 7 mm diameter or square for one-dimensional testing.

Sensor Types Available Kapton sensors: 5465, 5501, 8563, 4922, 5599. Mica sensors: 5465, 5082, 4921, 4922, 5599. Teflon sensors: 5465, 5501

The governing equation for in-plane and through-plane thermal conductivities for Hot

disk thermal constant analyzer is indicated in the equation 3.2. The first term represents

18

accumulation of thermal energy, the second term radial (referred to as in-plane in our

experiments) heat conduction, the third term axial (referred to as through-plane in our

experiments) heat conduction, and the final term is a heat source.

𝜌𝜌𝐶𝐶𝑝𝑝𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕

= kin1𝑟𝑟 𝜕𝜕𝜕𝜕𝑟𝑟𝑟𝑟 𝜕𝜕𝜕𝜕

𝜕𝜕𝑟𝑟 + 𝑘𝑘𝜕𝜕ℎ𝑟𝑟𝑟𝑟

𝜕𝜕2𝜕𝜕𝜕𝜕2𝑧𝑧

+ 𝑄𝑄𝑟𝑟𝛿𝛿(𝑟𝑟 − 𝑟𝑟′)𝛿𝛿(𝑧𝑧)𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 (3.2)

where ρ is the density (kg/m3), Cp is the specific heat of the sample (J/(kg·K)), T is the

temperature (K), kin and kthru are the in-plane and through-plane thermal conductivities of the

sample (W/m·K), t is the time of the measurement (s), δ is the Dirac delta function ( 𝛿𝛿(𝑧𝑧) =

1𝑎𝑎√𝜋𝜋

𝑒𝑒−𝑧𝑧𝑎𝑎

2

, z and a indicate length through plane and amplitude of the curve, respectively), r’ is

the radius of one of the ring sources, and Qr is the power supplied to that ring per unit length of

the ring (W/m). The total power for each ring is proportional to the circumference of the ring

2𝜋𝜋r’, the cumulative of all such power for the rings together is Q (W). This total power Q is an

input parameter to the Hot Disk Thermal Constants Analyzer. The initial sample temperature was

provided in order to compare with the consecutive temperature readings.

The average transient temperature increase of the sensor is simultaneously measured by

recording the change in electrical resistance of the nickel sensor by equation 3.3:

÷÷ø

öççè

æ-=D 11

no

n

RR

Tb (3.3)

where ΔT is the change in temperature (K) at time t, β is the temperature coefficient of resistance

(TCR) of the Ni sensor material, Rno is the electrical resistance of the Ni (Ω) at time 0, Rn is the

electrical resistance of the Ni (Ω) at time t. The thermal conductivities from equation 3.2 of the

specimen is estimated by correlating temperature difference from equation 3.3 through the

following equation:

19

∆𝑇𝑇 = 𝑃𝑃

𝜋𝜋32 𝑎𝑎 𝐾𝐾𝑖𝑖𝑖𝑖𝐾𝐾𝑡𝑡ℎ𝑟𝑟𝑟𝑟

𝐹𝐹(𝜏𝜏) (3.4)

where P is the power dissipation in the probe and )(tF is a dimensionless time dependent

function of τ=(αint)/𝑎𝑎2 that describes the heat conduction of sensor with given by an integral

of a double series over the number of rings m:

ò å å úû

ùêë

é÷øö

çèæ

÷÷ø

öççè

æ +-+=

= =

--t

sss

st0 1 1

22022

2222

24exp)]1([)( d

mlkI

mklklmmF

m

l

m

k (3.5)

Equations 3.2 through 3.5 are used to determine the in-plane and through-plane thermal

conductivity of the composite. Where αin is the in-plane thermal diffusivity, a is the radius of the

largest ring (of Ni disk) and t is the time step, I0 is the modified Bessel function. To calculate the

thermal conductivity, a series of computational plots of ΔT versus F(τ) are made for a range of

αin values. The value of αin will yield a straight line for the ΔT versus F(τ) plot. This optimization

process can be done by the software until an optimized value of αin is found [36].

(a) (b)

20

(c) Figure 3.2: (a) Hot plate thermal constant analyzer setup, (b) TPS 1500, (c) Dynamic sensor

3.3 Heat Capacity Measurement by Differential Scanning Calorimeter (DSC)

In order to categorize the best bio-product/PCM composite with high latent heat capacity,

DSC helps to differentiate them based on the distribution and consistency of PCM by testing

them at various locations. The basic principle of detecting phase transformations (latent heat of

fusion) is that when the sample undergoes a phase transitions, heat needs to flow into it to

maintain the reference (sapphire) temperature close to the sample. Amount of heat flow to the

sample depends on whether the process is exothermic or endothermic. Heat addition is due to the

absorption of heat by the sample as it undergoes the endothermic phase transition from solid to

liquid to maintain equilibrium temperature with reference and vice versa in the case of

exothermic phase transformation according to the equation 3.3 and represented in Figure 3.3.

H= C·A (3.6)

where C indicates calorimetric constant and A indicates area under the latent heat curve

21

Figure 3.3: Schematic DSC test on PCM [37]

For the experiment, 5 mg specimens from various locations of the samples were tested by

placing them in a holding pan with lid. Later, the temperature was varied from 20oC to 70oC at

the heating/cooling rate of 0.5oC/min with 13 steps including 2-minute gap between each process

for almost 1.2 hours. The cooling and heating of chamber where the sample and reference were

placed, was taken care by the water bath (chiller) located beneath the equipment (Figure 3.4 (a),

(b)) with Nitrogen gas as sample purge.

(a) (b)

Figure 3.4: (a) DSC chamber set-up (b) Chiller

22

3.4 Temperature Variation Measurements

Data acquisition systems are meant to collect the information regarding some phenomena

or process of a specific quantity. For the current study the temperature variation in the different

containers (bio-product and their composites) on a hot plate maintained at 100 °C, were being

sensed by K-type thermocouple and later deciphered with the help of OMB-DAQ-2416 (device

that can read various types of electrical signals generated by thermocouple). It was found that the

latent heat capacity of the infiltrated bio-product composite takes more time, to reach a specific

temperature than the other. The containers holding different samples were identical and heated

up under the same conditions besides that, thermocouples were fixed in the same position in each

container for the comparison. The set-up is as shown in the Figure 3.5 (a), (b), (c).

(a) (c) Figure 3.5: (a) sample containers placed on the hot plate which is set to 100oC (b) DAQ (c) DAQ software which tracks the temperature variation.

(b)

23

3.5 eQUEST Energy Simulations

The effect of specific heat capacity in improving the building envelope insulation and

reducing the power consumption was primarily studied in eQUEST in which, a 2-D CAD model

was built in the Auto-CAD with the dimensions of the ZØE lab spreading across the 1200ft2 area.

The model was separated into 3 thermal zones namely living zone, working zone and rest room

zone by walls. Then, it was imported to eQUEST, where it was extruded to the height of 12ft up

above the ground as shown in the Figure 3.6.

Figure 3.6: 3D Extruded image,

3.5.1 HVAC System in Zero Energy Building (GSHP)

The ZØE lab uses the Ground Source Heat Pumps (GSHP) for temperature control in the

building. The pumps extract and imbue heat (based on the outside temperatures) to the building

by circulating fluid through buried pipes in horizontal trenches or vertical boreholes. The ground

water temperatures are usually stable throughout the year, around 17oC in the Denton, Texas

area. Therefore, the cold water is extracted to cool the lab environment in summers while the

warm water is used to heat up the lab in winters. A well designed GSHP system provides the

lowest running cost of any heating/cooling system because it uses a small amount of electricity

to transfer a large amount of energy from the ground into the lab building. The power required to

pump the water from the ground to the lab is obtained from two sources. One is from the solar

24

panels on the roof top with the 5.6kW grid capacity, the other is from a vertical wind turbine

with the capacity of 3.5 kW. Figure 3.7 indicates the HVAC system water circulation type

throughout the year. And the total power is estimated with the help of supply fan power

consumption in winter as well as summer.

Figure 3.7: 3D HVAC (water circulation) in eQUEST.

3.5.2 Wall Layers in ZØE Building

Three types of wall construction layers, namely masonry, metal panel and structural

insulated panel (SIP) were used for the ZØE lab building. Each wall type was illustrated in detail

in Table 3.2. In the present simulation study, the SIP wall structure and roof were replaced by the

infiltrated wood and non-infiltrated wood. Their impacts on the HVAC (GSHP in the ZØE lab)

load reduction were studied.

Table 3.2: Wall construction layers for the ZØE lab

Masonry wall Metal panel wall SIP wall

1. Masonry 1. Corrugated Metal Panel 1. Textured Coating

2. Building Wrap 2. Building Wrap 2. SIP (Replaced by Wood or Wood/PCM Composite)

25

Masonry wall Metal panel wall SIP wall

3. ½” THK Sheathing 3. ½” THK Sheathing 3. 43MIL MTL studs at 16” OC

4. 43MIL MTL studs at 16” OC

4. 43MIL MTL studs at 16” OC 4. 5/8” THK GYP BD

5. Full Batt Insulation 5. Full Batt Insulation 5. Sealant

6. 5/8” THK GYP BD 6. 5/8” THK GYP BD

7. J-Trim, Typ-Finish to match panel

3.5.3 Conduction Transfer Function (CTF) for Heat Transfer Equations

To find the effect of the material, there are many software tools commercially available to

energy model buildings, like eQUEST, EnergyPlus, HAP, Trane Trace etc. In this section,

eQUEST has been used for tracing out the heat transfer difference between different wall layer

compositions. There are two types of constructions in this tool, quick constructions and delayed

constructions. In reality, all constructions are delayed (i.e. constructions have thermal mass and

therefore there is a time-delay whenever temperature changes, involving specific heat capacity).

The mathematic model required to solve for heat transfer through delayed constructions is much

more complicated than a simple conduction heat transfer calculation. Instead, it uses transfer

functions to approach experimental observation.

Conduction transfer function method is one of the widely used approaches for solving

heat conduction equations. CTF coefficients are a closed form representation of conduction

response factor series that are used to calculate 1-D heat transfer through multi-layer walls, roofs

and floors. [38]. CTFs represent material’s thermal response determined by their own material

properties that include specific heat capacity. This method leads to a simple linear equation

previous and current heat fluxes and temperatures as indicated in the equations 3.8 and 3.10.

26

Whereas equations 3.7 and 3.9 indicate the current hour’s surface temperature and previous total

flux value at exterior surface

(3.7)

qo,θ=-Y0Tis,θ+X0Tos,θ+Qo (3.8)

For the inside heat flux, and

(3.9)

qi,θ=-Z0Tis,θ+Y0Tos,θ+Qi (3.10)

where:

· qo,θ and qi,θ are heat flux at exterior and interior surfaces. Xk, Yk and Zk are exterior,

cross and interior CTFs.

· Tis and Tos are the interior and exterior surface temperatures. Nx, Ny and Nz are

number of exterior, cross and interior CTFs terms.

· φk is the flux coefficient. Nφ is the number of flux history terms. The subscript θ

represents the current time, and δ is time step.

As there was no textbox to enter the property of latent heat capacity in eQUEST, a

technique of converting to specific heat by averaging was being used. i.e. the monthly enthalpy

was calculated by considering a fixed reference temperature pertaining to that month and divided

by the average temperature of Denton which happen to be 18.7oC

𝑄𝑄𝑜𝑜 = −𝑌𝑌𝑘𝑘𝑇𝑇𝑖𝑖𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁

𝑘𝑘=1

𝑋𝑋𝑘𝑘𝑇𝑇𝑜𝑜𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁

𝑘𝑘=1

𝜑𝜑𝑘𝑘𝑞𝑞𝑜𝑜 ,𝜃𝜃−𝑘𝑘𝛿𝛿 𝑁𝑁𝜑𝜑

𝑘𝑘=1

𝑄𝑄𝑖𝑖 = −𝑍𝑍𝑘𝑘𝑇𝑇𝑖𝑖𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑧𝑧

𝑘𝑘=1

𝑌𝑌𝑘𝑘𝑇𝑇𝑜𝑜𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁

𝑘𝑘=1

𝜑𝜑𝑘𝑘𝑞𝑞𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿 𝑁𝑁𝜑𝜑

𝑘𝑘=1

27

3.6 EnergyPlus Simulations

EnergyPlus is a building energy simulation program designed by the U.S. Department of

Energy. It has the capacity to perform many types of calculations for building loads, but for this

study the focus was on heating and cooling loads. The program can be set up to provide output

detailing the heating and cooling load for each zone within the building. EnergyPlus was opted

over eQUEST, as there is no scope for inputting latent heat property of PCMs.

The ZØE building was designed in the exclusive architectural commercial design

software called SketchUp with the area stretching up to 1200ft2 besides, 12ft ceiling height

(Figure 3.8). The design is made into three zones, 1. Mechanical Room 2. Electrical Room 3.

Conditioned Zone, which is relatively different from what has been considered in eQUEST.

Later with the help of extensions, the file had been converted into idf file and imported into

EnergyPlus.

The building version, schedules, people, zones, materials, construction and so on, are

defined and Conduction Finite Differencing algorithm is used for evaluating the latent heat

property to find out the envelope ‘R’ value. The outputs have been studied under Output:

variables tab as cooling and heating loads. The latent heat properties of infiltrated herbs (100.0-

121.8 J/g) and infiltrated pine (45.0 J/g) had been studied and simulated to find out the savings.

Figure 3.8: ZØE building designed in SketchUp for EnergyPlus simulation

28

The governing equation to estimate heat transfer through the wall is represented by the

equation 3.11 [39]. The Conduction Finite Differencing algorithm is used in the EnergyPlus to

solve by Crank-Nicholson solver (numerical method).

𝜕𝜕ℎ𝜕𝜕𝜕𝜕

= 𝜕𝜕𝜕𝜕𝑥𝑥𝛼𝛼 𝜕𝜕ℎ

𝜕𝜕𝑥𝑥 − 𝜌𝜌 ∗ 𝐿𝐿 𝜕𝜕𝑓𝑓

𝜕𝜕𝜕𝜕 (3.11)

where h is volumetric enthalpy, t is time, x indicates the direction heat flow (into the building), α

is the thermal diffusivity, ρ is density of the material, L is the latent heat of fusion of PCM

composite, f is liquid fraction of melt.

29

CHAPTER 4

CHARACTERIZATIONS OF THE BIO-PRODUCT/PCM COMPOSITES’ THERMAL

PROPERTIES

Bio-products, including woods and herbs, were infiltrated by the PCM (paraffin wax) to

form the bio-product based composite materials. In this chapter, the open porosity and density

which define the PCM infiltration performance, thermal conductivity, specific heat, and latent

heat of fusion of composites are characterized. And also, the investigation on temperature

variations of various composites to preliminarily demonstrate the temperature control by PCM is

presented.

4.1 Open Porosities and Densities of Bio-Product and Bio-Product/PCM Composites

4.1.1 Non-Infiltrated Samples

Four non-infiltrated wood samples, in which, two of each cherry and pine wood were

tested. The open porosities of cherry woods were around 42.5% while those of pine woods about

75.0%, as indicated in Figure 4.1.

Figure 4.1: Open porosity of non- infiltrated pine and cherry woods

Pine Cherry0

20

40

60

80

Ope

n Po

rosi

ty o

f N

on-In

filtra

ted

Woo

d Sa

mpl

es in

%

Wood types

30

4.1.2 Infiltration Samples

The wood samples (pine and cherry) were immersed in the liquid paraffin wax. As the

liquid wax was infiltrated into the wood pore through the self-diffusion process, the densities of

infiltrated samples raised. Open porosities of nine samples of each pine and cherry woods, which

were being tested, ranging from 6.7% to 14.4% and 8.7% to 14.6% respectively, as shown in

Figure 4.2. The average weights of pine and cherry woods were 6 g and 8 g compared to 8 g and

9 g for infiltrated woods, respectively. Whereas, the average densities of pine and cherry woods

were 0.40 g/cc and 0.55 g/cc compared to the infiltrated samples of 0.57 g/cc and 0.64 g/cc

respectively.

Figure 4.2: Open porosity of infiltrated pine and cherry woods

4.1.3 Half-Cut Samples

The above infiltrated samples were cut into two halves and tested for open porosities. It

was found that the infiltration was not very uniform inside the wood samples. Very little PCM

permeated to the center of the wood sample. Hence, the average open porosities of the sliced

samples were higher than those of unsliced ones due to the non-uniform infiltration, as indicated

in Figure 4.3. The porosity value increased up to 16.2% in the sliced infiltrated cherry sample,

and up to 19.8% in the sliced infiltrated pine sample.

Pine Cherry0

5

10

15

20

Ope

n Po

rosi

ty o

f In

filtra

ted

Woo

d Sa

mpl

es in

%

Wood types

31

Figure 4.3: Open porosity of sliced infiltrated woods

The porosities of woods are being characterized in Table 4.1.

Table 4.1: Summary of porosities and densities

Type of woods Open porosity ranges

Average densities

Pine 74.7% -75.1% 0.40 g/cc

Cherry 42.5% -42.8% 0.55 g/cc

Infiltrated pine 6.7% -14.4% 0.57 g/cc

Infiltrated cherry 8.7% - 14.6% 0.64g/cc

Half-cut infiltrated pine 13.1 % - 16.1%

Half-cut infiltrated cherry 8.6% -19.8%

The above open porosity measurements were conducted under certain moisture content in

the samples. By mounting them in an oven maintained at 103oC temperature for 24 hours, the

samples were dried, and therefore, the moisture content was determined in these samples. It has

7.0% to 7.1% moisture content for cherry wood samples, 8.1 to 8.3% moisture content in the

pine, and about 0.0% for herb samples by comparing the mass of these samples before and after

the drying process.

Pine Cherry

0

5

10

15

20

Ope

n Po

rosi

ty o

f H

alf-

Cut

In

filtra

ted

Woo

d Sa

mpl

es in

%

Wood types

32

4.2 Thermal Conductivities

Thermal conductivity measurements were conducted on six different samples of each

pine and cherry for four test runs. The experimental results (Figure 4.4) showed a very negligible

difference of thermal conductivities between infiltrated and non-infiltrated wood blocks. The

thermal conductivities of pine and cherry woods were in the range of 0.15-0.2 W/m-K. The same

measurement range were observed for the wood/PCM composites as displayed in Figures 4.4(b)

and (d). Hence, the PCM did not affect the original thermal resistance of the wood materials.

This phenomenon may be explained by K. Lafdi et al. [40], in which the effects of

porosity and pore size of aluminum foam on the overall thermal conductivity of the Al/PCM

composite were investigated. It was observed that, by using bigger pore size aluminum foams,

the heat transfer performance was worse than the smaller pore size foams. When PCM was

infiltrated into the foam, the natural convection of liquid PCM inside the pore can help to

enhance the heat transfer performance. On the other hand, lower porous size has greater heat

conduction through material, making heat transfer rate close to the non-infiltrated Al sample.

(a) (b)

0

0.05

0.1

0.15

0.2

1 2 3

Ther

mal

Con

duct

ivity

(W/m

K)

Infiltrated Pine Wood Samples

0

0.05

0.1

0.15

0.2

1 2 3Ther

mal

Con

duct

ivity

(W/m

K)

Non-Infiltrated Pine Wood Samples

33

(c) (d)

Figure 4.4: Thermal conductivity measurements for various types of woods and infiltrated woods. (a) For non-infiltrated pine wood samples, (b) for infiltrated pine wood samples with PCM, (c) for non-infiltrated cherry wood samples, (d) for infiltrated cherry wood samples with PCM.

4.3 Specific Heat and Latent Heat of Fusion

When the atmospheric temperature falls in the melting range of PCM, it would undergo

phase change process during which the material can absorb/release huge amount of heat while

maintaining constant temperature for efficient thermal control in the building. The latent heat of

fusion and specific heat of the bio-product/PCM composite materials were measured by the

differential scanning calorimeter (DSC). The measurement temperature range was from 20 °C to

70 °C with the heating/cooling rate of 0.5 °C/min in the DSC. Three test runs were repeated for

each test sample. The average values of the three runs were obtained for 25 samples of pine,

cherry and herb composites at various locations indicated in Figures 4.6 and 4.7

The specific heat and the latent heat of fusion measurement results for wood samples and

wood/PCM composite samples are shown in Figure 4.6. The specific heat of both pine and

cherry woods are similar based on the DSC measurements, around 2.3 J/g·°C at room

temperature as indicated in the figures 4.6(a) and (c). The latent heat of fusion of pure paraffin

wax was measured about 146 J/g with the peak melting point at 52.5 °C. Its melting temperature

0

0.05

0.1

0.15

0.2

0.25

1 2 3

Ther

mal

Con

duct

ivity

(W

/mK

)

Non-Infiltrated Cherry Wood samples

34

range was between 45 °C and 58 °C as shown in figure 4.5. The average latent heat of fusion was

around 30 J/g with the peak melting point of 54 °C for the infiltrated cherry wood while it was

approximately 45 J/g with the peak melting point of 54 °C for the infiltrated pine wood. The

results were consistent with open porosity measurements. Due to the high-volume occupation of

the PCM in the pine wood, the latent heat of fusion of the pine/PCM composite was higher than

that of the cherry/PCM composite.

However, because of the non-uniform infiltration in the wood samples, there was little

PCM filled at the center of the sample. Thus, very low latent heat values were detected at the

center of the infiltrated cherry and pine samples, as shown in Figures 4.6 (c) and (f). Wood is

usually a hydrophilic material, while wax is hydrophobic material. Therefore, the paraffin wax

did not show a good and uniform infiltration in the wood samples. In order to improve the self-

diffusion of liquid wax into wood, the temperature of the liquid was increased from 70 °C to 90

°C during the infiltration process to help the self-diffusion of molten wax into the wood porous

media. Nevertheless, it was found that the effect of liquid temperature on the infiltration process

was very minor for the wax and wood materials. Hence, to improve the infiltration of PCM into

the porous media, it is proposing to use the similar hydrophobic or hydrophilic materials for

PCM and porous media.

Figure 4.5: Specific heat and latent heat of fusion of pure paraffin wax

35

(a) Non-infiltrated cherry wood sample

(b) Infiltrated cherry wood sample

(c) Non-infiltrated pine wood sample

36

(d) Infiltrated pine wood sample

(e) Infiltration at the center in cherry

(f) Infiltration at the center in pine

Figure 4.6: Specific heat and latent heat of fusion of the wood samples and the wood/PCM composite materials from the DSC measurements (a to f).

37

Therefore, another bio-product, herb cellulose chips, was investigated due to its

hydrophobic property. It was found that the infiltration rate of paraffin wax in the herb cellulose

chips was significantly increased. The mass percentage of PCM in the infiltrated herb composite

was much higher than that in the infiltrated wood composite. The mass of herb/PCM composite

samples was around 8 grams compared to that of pure herb samples before infiltration of

approximately 2 grams. Significant amount of paraffin wax was permeated into the herb porous

media because of the hydrophobic nature of the herbs. The latent heat of fusion of herb/PCM

composite reached around 100 J/g when the infiltration process was conducted under one

atmosphere pressure and increased to 121 J/g when the infiltration process was under high

pressure of 100 psi. The latent heat of fusion and specific heat of the herb/PCM composite were

depicted in the following figures (Figure 4.7). Table 4.2 summarized the latent heat of fusions of

various bio-product/PCM composite samples.

Infiltrated herb material through self-diffusion process

38

Infiltrated Bio-product material by adding additional pressure (100psi)

Figure 4.7: Specific heat and latent heat of fusion of the herb /PCM composite materials from the DSC measurements (a, b)

Table 4.2: Summary of average latent heat of fusions for various bio-product composites

Type of Bio-Product Composites Average Latent Heat of Fusion Infiltrated pine 45 J/g Infiltrated cherry 30 J/g Self-diffused herb by PCM 100 J/g Pressure- diffused herb by PCM (under 100 psi) 121 J/g

4.4 Temperature Control by Using Bio-Product/PCM composites

It was found that the temperature increase was slower in the case of bio-product/PCM

composite material, conveying that phase change process around the melting temperature range

of PCM could help to mitigate the temperature increase, and therefore, could achieve energy

savings if used in the building envelope.

4.4.1 Infiltrated and Infiltrated Pine Samples

It was observed in the graph that the surrounding temperature with the infiltrated sample

(red line) of weight 7.4 gm increased slowly compared to that with the non-infiltrated wood (blue

line) of 6.3 gm. After a period of time, the temperature inside the container reached steady state

39

and leveled off for both non-infiltrated and infiltrated pine wood sample conditions as shown in

Figure 4.8 as typical sample. Through the studies of the temperature profiles, it was found that

the PCM could help mitigate the temperature increase in the space.

Figure 4.8: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated pine woods)

4.4.2 Non-Infiltrated and Infiltrated Cherry Samples

Similar as the previous case, the infiltrated cherry wood sample of 8.7 gm could also

mitigate the temperature increase rate in the space compared to the non-infiltrated cherry sample

of 8.0 gm, as shown in Figure 4.9 as typical sample.

40

Figure 4.9: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated cherry woods)

4.4.3 Space Temperature Control by Using Herb/PCM Composites

From Figure 4.10, it is evident that the environment temperature with infiltrated herb

samples takes more time than that with non-infiltrated herbs to reach a specific temperature due

to the latent heat capacity of PCM. The herb sample was 1.8 gm, whereas maximum infiltrated

herb was 7.2 gm. As the amount of PCM is higher in this case, the curve compared to the pine

and cherry, which is more consistent.

41

Figure 4.10: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated herbs)

4.4.4 Temperature Difference Comparison between Pine, Cherry and Herb/PCM Composites

The gap i.e. temperature reduction between bio-products and their composites are being

plotted against the time to find which one of it would hold more heat. It is evident from Figure

4.11 that, herb/PCM composite absorbs more heat than pine and cherry wood composites, as the

amount of paraffin wax in it was 5.4 gm compared to 1 gm and 0.7gm for pine and cherry/PCM

composites respectively. More PCM implies higher latent heat of fusion, and this in turn

determines the resistance towards heat transfer in the walls, which is directly proportional to

energy savings.

42

Figure 4.11: Temperature reduction using infiltrated bio-products compared to non-infiltrated ones

4.4 Alternatives to Overcome Inflamability of Paraffin Wax

Though the paraffin wax performs well in storing the energy, they are inflammable, which

increases the risk of fire accidents in building envelope [41]. Using other types of PCMs, such as

inorganic PCMs or fatty acid esters could restrict to maximum extent.

Inorganic materials (such as CaCl2∙6H2O, KF∙3H2O etc.) have similar latent heat per unit

mass as organic PCMs, in fact, their volumetric latent heat values are higher because of the

higher density. The melting ranges of inorganic PCMs are from 41° to 266°F (5° to 130°C).

However, their main drawbacks are severe super cooling and separation problems.

43

On the other hand, fatty acid esters are less expensive and significantly less flammable.

They are made from waste feed stocks such as soybean oils, coconut oils, palm oils, and beef

tallow. These fatty-acid ester PCMs are expected to remain stable during thousands of phase-

change cycles with no risk of oxidation as they are fully hydrogenated [42]. Furthermore, there

are coatings available in the market to overcome fire accidents, which are water based nontoxic,

thin film intumescent fire retardant and resistant paint. These coatings can reduce the risk of fire

incidents when applied on organic PCM based composite materials.

44

CHAPTER 5

BUILDING ENERGY SIMULATION RESULTS

The effect of bio-product/PCM composite in the building envelope on the energy savings

was studied through building simulation tool (eQUEST and EnergyPlus). A unique Zero Energy

(ZØE) Research Laboratory at University of North Texas (UNT) was used as a simple

apartment-type building model for the simulations. The ZØE lab has the area of 1200ft2. Various

conditions in the lab were considered in the simulation model, including the cooling/heating

technologies, wall construction layers, lighting, glaring and other factors.

The PCM melting range is considered from 13oC to 22oC with peak of 18.7oC (Butyl

Stearate paraffin) which is an average temperature of Denton (similar to DFW area) throughout

the year.

5.1 Results on eQUEST

Through the simulations, it was found that the space cooling power consumption was

reduced by 2.7% and the spacing heating power consumption was reduced by 11.3% annually by

using the wood/PCM composite compared to using non-infiltrated wood in the SIP wall

construction as shown in Figure 5.1(a). The simulations were using Butyl Stearate paraffin as the

PCM (melting point around 18°C) considering the annual temperatures in the Texas area.

Different PCMs could be used based on the different local weather conditions. For instance,

Vinyl Stearate paraffin with melting point of 27°C was used when we just consider the reduction

of the HVAC power consumption in the summer time in the Denton, Texas area. The simulation

results show that the space cooling power consumption could be reduced by 8.1% in July

(summer season) as conveyed by Figure 5.1 (b)

45

(a) (b)

Construction layers with wax-infiltrated wood Construction layers with conventional wood

Figure 5.1: Energy consumption in the ZØE lab through the eQUEST simulations (a) Annual energy consumption, (b) Energy consumption in the summer month (July).

The following graph (figure 5.2 (a), (b)) indicates that, from November through April, the

monthly bills are significantly less for the walls with infiltrated wood which is close to 2%

savings throughout a year by comparing to the non-infiltrated wood panel in the wall structure,

and 4.1% savings for the month of July (summer season only)

(a) (b) Pure wood

Wall with wax infiltrated wood

Figure 5.2: (a) Monthly utility bills through out a year (b) Utility bills exclusively for the month of July (Summer)

46

Figure 5.3 shows the annual power consumption variation with and without PCM

(paraffin wax) in the wood in both wall structure and roof layer. It is evident that the space

heating power consumption has been reduced by 16.7%, with negligible change in the cooling

load. Finally, Table 5.1 represents the summary of savings for various wall conditions in

eQUEST.

Figure 5.3: Energy consumption in the ZØE lab when replaced with PCM composite in roof and wall constructions

Table 5.1: Summary of typical energy savings in eQUEST

Comparison between bio-products and bio-product/PCM composite composite Replacement in Cooling energy savings (%) Heating energy savings (%)

In the wall 2.7 11.3 In the wall and roof Negligible 16.7 The herb/PCM composite based building envelope was also simulated by using eQUEST,

but it showed the similar energy savings for the herb/PCM composite compared to the wood

based composite. Hence, inputting average effective specific heat value to indicate the latent heat

47

of fusion in eQUEST is not a very accurate way to find out the energy savings. The software tool

is ineffective in evaluating the importance of latent heat property of PCM when it is used in the

wall structure. So, to study the effect of latent heat on energy savings, a more sophisticated tool

i.e., EnergyPlus should be employed.

5.2 Results Obtained on EnergyPlus

5.2.1 Comparison of the Heating and Cooling Loads between Conventional and Bio-Product/PCM Composite Embedded Building Envelopes As the number of layers increase in the wall construction the percentage savings would

be reduced. Figures 5.4 (a), (b), (c) are the examples to explain this phenomena. The heating

power consumption throughout the year for SIP layer in the wall and roof was 1,602 kWh. When

it was replaced by a pressurized PCM infiltrated herb material, the consumption would be 1,561

kWh, which was reduced by 2.6%. On the other hand, when the herb composite was added to the

SIP roof, it consumed about 1,280 kWh of power annually, which is 20.0% less than the original

SIP layer roof.

The cooling power consumption in a year for only SIP Layer in the wall and roof was

5,590 kWh compared to 6,114 kWh when it was replaced by pressurized PCM infiltrated herb,

which was increased by 9.4%. Conversely, when the herb/PCM composite layer was added to

the SIP roof, it consumed 5,248 kWh of power anually, which was 6.1% less than the original

SIP roof.

48

(a)

(b)

0

100

200

300

400

500

Pow

er C

onsu

mpt

ion

Months

Space Heating Power Consumption(kWh)

Only SIP Maximum infiltrated herb SIP + maximum infiltrated herb

0200400600800

100012001400160018002000

Pow

er C

onsu

mpt

ion

Months

Space Cooling Power Consumption (kWh)

Only SIP Maximum infiltrated herb SIP + maximum infiltrated herb

49

(c)

Figure 5.4: (a) Monthly heating load distribution (b) Monthly cooling load distribution (c) Annual cooling power savings for different combinations with composites, compared with SIP roof

5.2.2 Replacing SIP Layer by Composite Materials

The SIP layers are present in both roof and SIP wall structure. When replaced with bio-

products and PCM infiltrated bio-products, the output results were obtained and plotted as shown

in the figures. Figures 5.5 (a) and (b) indicate the space heating power consumption comparison

monthly and annual savings. The results are as follows:

Annual heating power consumption was 1,561 kWh with pressurized wax infiltrated

herb in the building envelope compared to the power consumption of 1,859 kWh for non-

infiltrated bio-products imbedded building envelope, i.e., 16.0% of power savings were obtained.

Similarly, for the self-diffused wax infiltrated herb the consumption was 1,574 kWh and the

savings were 15.3%.

Only infiltrated herb

SIP + infiltrated herb with pressure

-10

-5

0

5

10

15

20Sa

ving

s (%

)

Types of wall layer materials

Load Comparision with SIP layer

Heating Load Savings (%) Cooling Load Savings (%)

50

On the other hand, for wax infiltration pine the heating power consumption was 1,652

kWh with only 11.0% of energy savings compared to non-infiltrated pine material. This shows

that the latent heat of fusion playes a crucial role in the heat load savings and could be more if

the value is higher.

(a)

(b)

Figure 5.5: (a) Monthly heating load distribution, (b) Annual heat load savings for different composites compared with wood/ herb

Figure 5.6 (a) and (b) indicates the space cooling power consumption comparison

monthly and annual savings. Annual cooling power consumption was 6,114 kWh with

0100200300400500600700

Pow

er C

onsu

mpt

ion(

KWh)

Months

Space Heating Power Consumption(kWh)

Herb with maximum infiltration Self -diffused herb

Average infiltrated pine Wood/ Herb

Herb with maximum infiltration

Herb with self-diffused infiltration

Average wax infiltrated pine

02468

1012141618

Savi

ngs(

%)

Types of Bio-Products

Heating Load Savings

51

pressurized wax infiltrated herb in the building envelope compared to the power consumption of

6,875 kWh for non-infiltrated bio-products imbedded building envelope, i.e., 11.0% of power

savings were obtained. Similarly, for self-diffused wax infiltrated herb, the consumption was

6,184 kWh and the savings were 10.0%.

On the other hand, for wax infiltrated pine space cooling power consumption was 6,456

kWh with only 6.0% of energy savings compared to non-infiltrated pine material. Once again it

proves that the latent heat of fusion plays a crucial role in the savings.

(a)

(b)

Figure 5.6: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/ herb

0500

100015002000

Pow

er C

onsu

mpt

ion(

KWh)

Months

Space Cooling Power Consumption (kWh)

Herb with maximum infiltration Self-diffused infiltrated herb

Averagewax infiltrated pine Wood/Herb

Herb with maximim infiltration

Herb with self-diffused infiltration

Average wax infiltrated pine

0

2

4

6

8

10

12

14

Savi

ngs

(%)

Types of Wood

Cooling load Savings

52

5.2.3 Replacement and Addition of Composite Materials for Wall and Roof Structures

In this case the SIP layer in one of the wall structure was replaced with the bio-

product/PCM composites. For the roof, another composite layer was added on the SIP. Figures

5.7 (a) and (b) indicate the monthly space heating power consumption and annual savings,

respectively.

Annual heating power consumption was 1,280 kWh with pressurized wax infiltrated herb

in the building envelope compared to the power consumption of 1,374 kWh for non-infiltrated

bio-products embedded building envelope, i.e., 6.9% of power savings were obtained. For self-

diffused wax infiltrated herb the consumption was 1,286 kWh and the savings were 6.4%. On the

other hand, for wax infiltrated pine space heating power consumption was 1,328 kWh with 3.4%

savings only. It was quite evident that when number of insulating layers increased in walls, the

percentage of savings by PCM would be reduced, because the SIP layer was already efficient for

the indoor thermal control.

(a)

0

100

200

300

400

500

Pow

er C

onsu

mpt

ion

(KW

h)

Months

Space Heating Power Consumption(kWh)

Herb with maximum infiltration Self diffused infiltrated herbAverage wax infiltrated pine wood Wood/ Herb

53

(b)

Figure 5.7: (a) Monthly heating load distribution, (b) Annual heating load savings for different composites compared with wood/ herb

Figures 5.8 (a) and (b) indicate the monthly space cooling power consumption and annual

savings, respectively. Annual cooling power consumption was 5,248 kWh for the pressurized

wax infiltrated herb imbedded building envelope compared to the power consumption of 5,459

kWh for the non-infiltrated bio-products based envelope structure, i.e., 3.9% of power savings

were obtained by using PCM. For the self-diffused wax infiltrated herb, the power consumption

was 5,266 kWh and savings were 3.5%. On the other hand, for wax infiltrated pine wood space

cooling power consumption was 5,342 kWh with 2.2% of energy savings only.

The range of energy savings for maximum infiltrated herb, self-diffused herb was

comparitively less in all cases between 0.05 to 0.15%, because of their consistant wax

infiltration. Whereas, for average infiltrated pine, the range was from 0.1 to 0.3%.

Herb with maximum infiltration

Herb with self-diffused infiltration

Average wax infiltrated pine

0

1

2

3

4

5

6

7

8(%

) Sav

ings

Types of Wood

Savings Heating (%)

54

(a)

(b)

Figure 5.8: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/herb

Specifically, in all cases the heating and cooling load savings were higher for the months

of April, October and November as the average temperatures are falling in the range of PCM

melting temperature, i.e., 18.7oC (average annual temperature of Denton, TX). Nevertheless, for

0200400600800

1000120014001600

Pow

erCo

nsum

ptio

n(K

Wh)

Months

Space Cooling Power Consumption(kWh)

Herb with maximum infiltration Self-diffused infiltration

Average wax infiltrated pine Wood/Herb

Herb with maximum infiltration

Herb with self-diffused infiltration

Average wax …0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

(%) S

avin

gs

Types of Woods

Savings Cooling (%)

55

the months of June, July and August which have the average temperatures above 25oC, the

savings were less. Table 5.2 represents the summary of savings for various cases.

Table 5.2: Summary of typical Energy savings in EnergyPlus

Replaced by composites in SIP wall structure and compared with conventional building envelope Case 1 (Maximum infiltrated herb) Heating load savings (%) Cooling load savings (%) Composite Added to the roof 20.0 6.1 SIP replaced by composite in the roof 2.6 -9.4 Replaced SIP layer in SIP wall construction, roof by bio-products and compared with composite bio-products Case 2 (All bio-product types) Heating load savings (%) Cooling load savings (%) Maximum infiltrated herb 16.0 11.0 Self-diffused herb 15.3 10.0 Average infiltrated pine 11.0 6.0 Replaced SIP layer in SIP wall structure by bio-products, added to roof and compared with composite bio-products Case 3 (All bio-product types) Heating load savings (%) Cooling load savings (%) Maximum infiltrated herb 6.9 3.9 Self-diffused herb 6.4 3.5 Average infiltrated pine 3.4 2.2

5.2.4 Inside and Outside Wall Face Temperature Distribution (Hourly) for a Single Hot and

Cold Days of the Year Figures 5.9 (a), (b), (c), (d) indicate the hourly temperature distribution at inside and

outside faces of a wall on hot day (July 28th) and cold day (December 7th) in DFW area. The

yellow curve distribution (SIP replaced by maximum infiltrated herb in SIP and roof structures)

in all graphs represent more consistancy (or stability) than others, the second position would be

for SIP replacent by maximum infiltrated herb in wall and roof structures. This test proves that,

latent heat property relates to thermal control of the building envelope.

56

With usage of herb/PCM composite ,the total of heat gained at the exterior position of

the walls, to be reduced by a drastic amount which results in lower heat gains to the conditioned

space (as the temperature on the interior walls is low).

The energy savings obtained for the herb/PCM composite in the wall and roof, is based

on the net peak load shift. In figure 5.9 (a) from 8:00AM to 7:00PM (summer) the peak load has

been mitigated, however, in the night during heat rejection, interior wall temperature raised. This

overall shift during the day and nights would determine the energy savings. And vice versa

would the case for winters.

(a)

(b)

20

22

24

26

28

30

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM

PERA

TURE

(CEL

SIU

S)

HOURS

SUMMER INSIDE ROOF SIP conventional

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

0

50

100

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM

PERA

TURE

(CEL

SIU

S)

HOURS

SUMMER OUTSIDE ROOFSIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature

57

(c)

(d)

Figure 5.9: Hourly temperature distributions along (a) Summer inside wall (b) Summer outside wall faces (c)Winter inside wall (d) Winter outside wall faces

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

(CEL

SIU

S)

HOURS

WINTER INSIDE ROOFSIP conventional

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

-5

0

5

10

15

20

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

WINTER OUTSIDE ROOFSIP conventional

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

outside air temperature

58

Figures 5.10 (a), (b), (c), (d) represent the temperature difference at the interior and

exterior roof faces between conventional SIP roof and herb/PCM composite roof conditions in

summer and winter days (i.e., the temperature difference is equal to temperature for conventional

SIP roof condition minus that for herb/PCM composite roof condition). The “yellow curve”

condition has much more temperature reduction during summer peak hours while less

temperature increase in the nights due to the peak temperature shift. On the other hand, for

winter day, the interior face temperatures would raise at nights when outside roof face

temperatures are low because of the same effect of peak temperature shift. The simulation results

demonstrate that the PCM can effectively mitigate the peak temperature during a day to save the

building HVAC energy consumption.

(a)

-4

-3

-2

-1

0

1

2

3

4

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

RED

UCT

ION

(CEL

SIU

S)

HOURS

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

59

(b)

(c)

-10

-5

0

5

10

15

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

-1

-0.5

0

0.5

1

1.5

2

2.5

3

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

60

(d)

Figure 5.10: Hourly temperature difference between conventional SIP and herb/PCM composite roof conditions in (a) summer interior face of the roof (b) summer exterior face of the roof (c) winter interior face of the roof (d) winter exterior face of the roof

-8

-6

-4

-2

0

2

4

6

8

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

61

CHAPTER 6

CONCLUSIONS AND FUTURE RESEARCH

6.1 Conclusions

The main observations from the current study are as follows:

· PCMs involve in large amount of heat storing through phase changing process, which

increases the overall heat capacity of the material, and therefore, helps to reduce the rate of

temperature modulation by using the bio-product/PCM composite. The heat capacity of bio-

product/PCM composites in the current study was increased by 2 to 5 times than traditional non-

infiltrated bio-products when adding the latent heat of fusion of paraffin wax.

· The main function of PCM is to reduce the indoor and outdoor temperature

fluctuations and thereby, to shift the peak temperatures from high to low temperature hours for

effective thermal control. Simulation results implied that, the peak temperatures could be

mitigated by 0.5oC to 4oC using bio-product/PCM composite layer compared to conventional SIP

layer in all seasons.

· Annually, the heating and cooling load savings could range up to 20% and 11%

respectively based on the various bio-product/PCM composite wall layer conditions, comparison

with conventional SIP and non-infiltrated bio-product layer conditions. Specifically, for the

months of April, October and November, the energy savings are ranging from 25% to over 40%,

as the average temperatures for those months are falling in the range of PCM melting

temperature.

6.2 Future Research

Future work in this area should focus on study of wetting behavior between porous

62

medium and PCMs to obtain higher infiltration rate thereby, improving the latent heat property

of the composite, as it was inferred from the EnergyPlus simulations that, the amount of PCM

inside the composite material would determine the energy savings. A comprehensive study has to

be made to find out the bio-product pore size and porosity influence on thermal conductivity,

although there is some information (on Aluminum) available about the effect of porosity and

pore size on thermal conductivities. As paraffin wax happened to be an inflammable material,

research has to be extended to fatty acid esters as PCMs, which are less expensive and

significantly less flammable, also are not prone to super-cooling, separation problems as

inorganic PCMs. Boundary sealing encapsulation techniques for the bio-product/PCM composite

based wall panel have to be studied, to prevent the leaking of molten PCMs from the building

envelope surface.

Build and test the bio-product/PCM composite wall panel at real physical building

structure (i.e., ZØE lab at UNT) to seek the potential savings on HVAC system and verify the

simulation model for future more complicated building simulations. Besides, optimizing the wall

structure layers containing PCM to maximize the HVAC system energy savings, as embedding

bio-product/PCM composite in different wall structure layers may have different savings on

HVAC systems. Finally, Cost analysis should be conducted to determine whether the bio-

product/PCM composite based wall structure is economically suitable for the building

applications.

63

APPENDIX A

RAW MATERIAL DATA

64

Various pine, cherry and their composite’s open porosity, absolute density values

represented in tables (a) and (b) and Pycnometer parameters are indicated in Table (c).

Cherry wood material properties Samples Open cell

porosity(avg)% Closed cell porosity(avg)%

Absolute densities (avg)g/cc

Standard deviation of open cell (avg)%

Density deviation (cc)

C1 10.97% 89.03% 0.8386 0.144 0.0014 C2 8.703 91.296 0.9294 0.1194 0.0012 C3 11.31 88.688 0.9902 0.1197 0.0013 C4 10.5077 89.492 0.9236 0.5516 0.0057 C5 14.6447 85.355 0.926 0.1012 0.0011 C6 13.2761 86.274 0.6788 0.1693 0.0013 C7 10.0681 89.932 0.7196 0.2368 0.0019 C8 10.1144 89.886 0.6491 0.7112 0.0051 C9 11.9946 88.005 0.6429 0.6028 0.0044 C10 10.343 89.657 0.7205 0.4578 0.0037 C21 (Non-infiltrated)

42.5108 57.489 0.915 0.3453 0.0055

C22(Non-infiltrated)

48.0007 51.999 1.1516 0.296 0.0066

C2L 13.0926 86.907 0.9226 0.0561 0.0006 C3L 14.0305 85.969 0.9999 0.0502 0.0006 C5L 14.9541 85.046 0.9446 0.0786 0.0009 C6L 16.1998 83.8 0.6952 0.058 0.0005 C7L 11.3877 88.612 0.7283 0.0501 0.0004 C2R 15.0940 84.906 0.9403 0.0737 0.0008 C3R 13.2336 86.766 0.9835 0.1024 0.0012 C5R 16.1164 83.334 0.9069 0.0987 0.0016 C6R 14.6314 85.369 0.6752 0.1894 0.0015

‘L’ indicates left half of the samples ‘R’ indicates right half of the samples ’C’ indicates cherry wood Pine wood material properties

Samples Open cell porosity(avg)%

Closed cell porosity(Avg)%

Density (avg) g/cc

Standard deviation %

Density deviation (cc)

P1 8.2255 91.775 0.9344 0.1454 0.0015 P2 14.443 85.557 0.7043 0.076 0.0006 P3 12.485 87.515 0.8411 0.1364 0.0013

65

P4 12.5833 87.417 0.6859 0.0789 0.0006 P5 11.5418 88.458 0.9018 0.1063 0.0011 P6 8.5516 91.448 0.5819 0.0435 0.0003 P7 14.9913 85.005 0.5177 0.157 0.001 P8 12.951 87.049 0.5197 0.0334 0.0002 P9 13.1337 86.866 0.5624 0.0622 0.0044 P10 6.7915 93.209 0.4899 0.0663 0.0003 P24(Non-infiltrated)

74.748 25.252 1.5694 0.0751 0.0047

P25(Non-infiltrated)

75.0811 24.919 1.574 0.1042 0.0066

P1L 13.747 86.253 0.8918 0.0.2081 0.0022 P2L 18.3213 81.679 0.761 0.0904 0.0008 P5L 15.7078 84.292 0.9178 0.1272 0.0014 P7L 19.6636 80.336 0.5305 0.1735 0.0011 P10L 10.5193 89.481 0.5015 0.1115 0.0006 P1R 18.8024 81.198 0.9577 0.2321 0.0027 P2R 14.4606 85.539 0.6592 0.2251 0.0017 P5R 12.2712 87.729 0.8829 0.2331 0.0023 P7R 14.2278 85.772 0.5429 0.1985 0.0013 P10R 8.6895 91.310 0.4988 0.1175 0.0006

‘P’ indicates pine wood Analysis parameters

Parameters Inputs Pressure 6 psi Purge time 3 minutes Purge type Flow Number of runs 10 Cell size Medium

Figures (a) to (e) indicate the approach in providing the material properties of the samples

for the thermal conductivity testing in the Hot Disk Thermal Constant Analyzer.

66

Material type selection

Identity of the sample and probe depth

67

Test parameter inputting window

Advanced parameter inputting window

68

Main window

Thermal material properties and their residues are indicated in the Tables (d) and (e) that

are obtained in the Hot Disk Thermal Constant Analyzer.

Thermal conductivities of pine and cherry woods

Other variables calculated by measuring device

Non- infiltrated cherryFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Cherry_1 24.0 °C 0.1973 W/mK 0.2787 mm²/s 0.7077 MJ/m³K 373.6 Ws¹´²/(m²K) 9.44 mm 2.96 KE:\C3.hotbCherry_2 24.4 °C 0.1962 W/mK 0.2834 mm²/s 0.6921 MJ/m³K 368.5 Ws¹´²/(m²K) 9.52 mm 3.03 KE:\C4.hotbCherry_3 24.4 °C 0.1891 W/mK 0.2809 mm²/s 0.6732 MJ/m³K 356.8 Ws¹´²/(m²K) 9.48 mm 3.030 K

Infiltrated CherryFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Cherry_1 24.0 °C 0.1878 W/mK 0.2518 mm²/s 0.7458 MJ/m³K 374.2 Ws¹´²/(m²K) 8.98 mm 2.96 KE:\C5.hotbCherry_2 24.4 °C 0.2068 W/mK 0.2267 mm²/s 0.9119 MJ/m³K 434.2 Ws¹´²/(m²K) 8.52 mm 3.030 KE:\C6.hotbCherry_3 24.4 °C 0.2002 W/mK 0.2185 mm²/s 0.9162 MJ/m³K 428.3 Ws¹´²/(m²K) 8.36 mm 3.03 K

Non- infiltrated PineFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Pine_1 24.0 °C 0.1629 W/mK 0.3125 mm²/s 0.5213 MJ/m³K 291.4 Ws¹´²/(m²K) 10.00 mm 2.96 KE:\P3.hotbPine_2 24.4 °C 0.1653 W/mK 0.3102 mm²/s 0.5328 MJ/m³K 296.7 Ws¹´²/(m²K) 9.96 mm 3.03 KE:\P4.hotbPine_3 24.4 °C 0.1619 W/mK 0.2922 mm²/s 0.5540 MJ/m³K 299.5 Ws¹´²/(m²K) 9.67 mm 3.03 K

Infiltrated PineFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Pine_1 24.0 °C 0.1466 W/mK 0.2658 mm²/s 0.5516 MJ/m³K 284.4 Ws¹´²/(m²K) 9.22 mm 2.96 KE:\P5.hotbPine_2 24.4 °C 0.1612 W/mK 0.2954 mm²/s 0.5455 MJ/m³K 296.5 Ws¹´²/(m²K) 9.72 mm 3.04 KE:\P6.hotbPine_3 24.4 °C 0.1570 W/mK 0.2933 mm²/s 0.5352 MJ/m³K 289.9 Ws¹´²/(m²K) 9.69 mm 3.04 K

Total/Temp.Incr. Total/Char.Time Time Corr. Mean Dev. Disk Res. Calc settings3.64 K 0.543 0.100 s 1.740E-4 K 12.570699 Ω Standard Start:28 End:200, Time corr, default heat capacity3.13 K 0.552 0.100 s 1.286E-4 K 12.569883 Ω Standard Start:59 End:200, Time corr, default heat capacity3.24 K 0.547 0.1000 s 1.562E-4 K 12.557056 Ω Standard Start:63 End:200, Time corr, default heat capacity

69

The gap between the bio-product and infiltrated bio-product samples depends on the

amount of paraffin wax present, conditions under which the test was being conducted, the

location of the thermocouple placed to trace the temperature variation. It takes longer time for

the infiltrated bio-products to reach a specific temperature than non-infiltrated products due to

the latent heat of fusion property of PCM. This occurrence is illustrated in following figures (j),

(f), and (h). Figure (i) Indicates the temperature reduction between bio-products and their

composites. This plot is to find which one of the bio-product/PCM composites has higher heat

capacities. Due to the higher weight percentage of PCM, herb composite could hold more heat

than bio-product composites.

(a) Temperature vs time curves (comparison between pine and infiltrated pine woods)

70

(b) Temperature vs time curves (comparison between cherry and infiltrated cherry)

(c) Temperature vs time curves (comparison between herb and infiltrated herb)

71

(d) Temperature reduction using infiltrated bio-products compared to non-infiltrated ones

72

APPENDIX B

eQUEST ENERGY INPUTS

73

Below figures (a)-(j) indicate the inputs given starting from building footprint to wall

layer allocation. In the first figure, foot print shapes and zones are customized by manually

specifying the contours besides, mentioning the floor height to be extruded and lighting

schedule.

Figures (b) and (e) indicate the window and door types respectively. As of the ZOE

building all those are made of low emissive glasses (with emissivity of 0.3). Further the specific

position of their location is also specified by clicking on the “Custom Door/ Window placement”

button.

Figure (c) indicates the building operation schedule. Currently, the building which is

being considered for simulation is a “low use type” with working hours - 8:00AM to 5:00PM

from Monday through Friday. Whereas, closed on the weekends. One main aspect of the

building simulation is the thermostat set points, which is divided in to two parts 1. Occupied 2.

Unoccupied settings 76oF and 82oF respectively for cooling the zones, 70oF and 64oF for

heating. In order to maintain that temperature, the supply air should be designed with optimal

supply parameters (0.5 cfm/ ft2) as mentioned in the figure 4.2 (d). Electric utility charges are

specified in the last slide of schematic wizard as mentioned in the figure 4.2 (f) ranging from

$0.0781 to $0.1165 / kWh.

Figure (g) indicates the hourly building lighting schedule with no lighting before 6:00AM

and almost negligible after 6:00PM. The total lighting in all zones are estimated as 0.375W/ft2.

So the ratios mentioned in the figures are multiplied with the estimated lighting power to get the

actual usage of power per square foot.

Figure (h) indicates the layer which was being replaced with the infiltrated pine wood

with specified latent heat capacity average in terms of specific heat capacity. Lighting capacity is

74

indicated in the figure (i) with 0.3225 W/ft2. It could be calculated by considering the lighting

equipment capacity and dividing it by the total area of the building.

(a) Building footprint

(b) Exterior windows

75

(c) Building schedules

(d) Temperature set points

76

(e) Exterior door material allocation

(f) Electric Utility Charges (ECU)

77

(g) Daily lighting schedule

(h) Layer replaced in SIP

SIP layer replaced

78

(i) Material property input window

(j) Lighting (W/ft2) for the ZOE building

79

APPENDIX C

ENERGYPLUS INPUTS

80

Figures from (a) to (h) indicate the main input windows of EnergyPlus simulation tool, in

which figure (a) and (b) indicates the algorithm and its solving technique i.e. Conduction Finite

Difference Algorithm and Crank Nicolson Second Order solver. For the current study, DFW area

had been simulated and the details of the location are mentioned in the Figure (c). To create the

24-hour weather profile used for sizing and to test the other simulation parameters, Design Day

window is helps to estimate a typical summer and winter days as shown in the Figure (d). To

simulate the desired days of the month throughout the year run period tab in the window was

utilized as shown in the Figure (e). The PCM effect and other building construction material

properties inputting windows respectively is indicated in Figure (f) and (g). Finally, the three

zones, conditioned, mechanical and electrical thermal zones and people were provided in order

to distinguish the degree of conditioning for the simulator as shown in the Figures (h) and (i).

(a) Conduction Finite Difference algorithm allocation

81

(b) Surface heat transfer modelling

(c) Site location

82

(d) Typical design day

(e) Days considered in all months for the test

83

(f) Wall constructions

(g) PCM properties input window

84

(h) Thermal Zones

(i) People in conditioned space

85

The outside roof temperatures are higher than the outside wall temperatures, because of

the direct solar radiation and represented in the following Figures (j), (k), (l), (m). Figs (n), (o),

(p), and (q) represents the temperature difference between conventional SIP wall and herb/PCM

composite wall conditions of interior and exterior faces in summer and winter days (i.e., the

temperature difference is equal to temperature for conventional SIP wall condition minus that for

herb/PCM composite wall condition.).

(j)

(k)

20

22

24

26

28

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

(CEL

SIU

S)

HOURS

SUMMER INSIDE WALLSIP conventional

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

(CEL

SIU

S)

TIME (HOURS)

SUMMER OUTSIDE WALLSIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature

86

(l)

(m)

10

11

12

13

14

15

16

17

18

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

(CEL

SIU

S)

HOURS

WINTER WALL INTERIOR

SIP conventional

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

-3

2

7

12

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

(CEL

SIU

S)

TIME (HOURS)

WINTER OUTSIDE WALL SIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature

87

(n)

(o)

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL

CONDITIONS IN SUMMER AT INSIDE WALL FACE

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

-4-202468

10121416

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS IN SUMMER AT OUTSIDE WALL FACE

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

88

(p)

(q)

0

0.5

1

1.5

2

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS IN WINTER AT INSIDE WALL FACE

SIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

-5

-4

-3

-2

-1

0

1

2

3

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4

TEM

PERA

TURE

DIF

FERE

NCE

(CEL

SIU

S)

HOURS

TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS

IN WINTER AT OUTSIDE WALL FACESIP replaced with max.infiltrated herb

Infiltrated herb replaces the SIP wall and adds above the SIP in the roof

89

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