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UAB School of Engineering – Mechanical Engineering – Early Career Technical Journal, Volume 16 43

SECTION 6

Miscellaneous

UAB School of Engineering – Mechanical Engineering – Early Career Technical Journal, Volume 16 Page 144


Journal of UAB ECTC Volume 16, 2017

Department of Mechanical Engineering The University of Alabama, Birmingham

Birmingham, Alabama USA

INDICATORS FOR SUSTAINABILITY AND STRATEGIES FOR IMPLEMENTATION IN THE AREA OF VERTICAL TRANSPORTATION TECHOLOGY

ABSTRACT The increased demand for sustainability, energy efficiency

and effects on the conveying systems technology continues to become a further field of interest. Urbanization and continuous migration to cities that rise vertically will continue to increase the number of installed elevators to provide people flow. As a result, the energy efficiency of elevators and escalators is attracting more attention. This paper provides an overview of data for conveying systems as related to green buildings, ISO 25745-2 standard and VDI 4707 guidelines.

Indicators of sustainability are identified and explored such as: energy efficiency, energy cost, measurements, sustainability and certifications and challenges of the existing installations.

This paper is exploring sustainable factors in the area of vertical transportation, with an overview of possible credits available in two most specified green certification systems.

The conclusions of this paper can be applied to any project highlighting the importance of energy monitoring, measuring, traffic study and understanding the traffic demand and traffic pattern in the building.

KEY WORDS: Elevators, Traffic study Sustainability, LEED, BREEAM, Energy Efficiency, Challenges, Policies, Europe, Energy Cost

BUILDING CLASSIFICATION SYSTEMS AND METHODS OF ASSESEMENT

The increased demand for sustainability and energy

efficiency in the sense of the Kyoto Protocol [1] has driven the elevator industry towards developing energy efficient and green product solutions. Elevators contribute between 5-15% of a building’s total energy consumption. In the construction industry, in Europe and the U.S. the following three green building classification system methods for evaluation of sustainability and building certification are mostly specified and selected: LEED, BREEAM and Green Globes.

The American LEED (Abbrev. Leadership in Energy and Environmental Design)[2] designation is based on the early involvement in the design process promoting synergy and an integrative approach for all involved in the construction cycle, from the design team, Architect, Owner, mechanical and electrical engineer, landscape engineer. This contrasts with the conventional methods where each design member worked on the project on their particular specialty. Conventional methods were based on addressing and resolving each specialty individually without implementing an integrative approach to assure optimization in the decision making process and assessment from the project conception throughout the building’s lifecycle. The base for this method, considering People, Planet and Profit to be equally important, is implemented into the “triple bottom line” concept (Figure 1) [2]. The advantage of this approach is early involvement in and optimization of the decision making process, and addressing areas of sustainability at the project’s conception.

European BREEAM (Abbrev. Building Research

Establishment’s Environmental Assessement Method)[3] has a wide use among specifiers in Europe in comparison to the other certification systems, with an estimated 80% of buildings certified under this system. Credits can be earned in nine categories, where awarding of the credits in each category, once the design team decides to pursue that particular credit, will result into one of the following grades: Unclassified, Pass, Good, Very good, Excellent, Outstanding (Table 1).

This building classification assessment method is a fusion

between building performance and exploring areas of achieving potential credits to satisfy the established building sustainability guidelines. A BREEAM certificate is issued once all criteria for credits, procedures, and performance criteria are fulfilled for one of the desired green certification levels [4].

The section from BREEAM that addresses New Construction has 49 assessment elements divided into 9 sections, where an additional the tenth is Innovation [3]:

Magdalena Krstanoski, MSc.ME Doctoral Candidate,

Ss. Cyril and Methodius University Faculty of Mechanical Engineering,

Skopje, Macedonia


Management, Health and Wellbeing, Energy, Transport, Water, Materials, Waste, Land use and Ecology, Pollution.

The energy section with its eleven sub sections represents 19% of the overall possible rating; it addresses conveying systems (elevator and escalators). In this area a maximum of three credits can be earned, i.e. two for elevators and one for escalators and moving walks (Table 2 and Table 3).

Figure 1. LEED Triple Bottom Line [2]

The tenth category, Innovation, similar to the LEED method, addresses extra steps towards intention for innovative solutions. If the design team decides to pursue this credit, the team has to elaborate the intent, and the innovative measures that will implement on the project, in order to contribute for more sustainable system or additional energy savings.

BREEAM rating Score/Credits Unclassified < 30 Pass ≥ 30 Good ≥ 45 Very Good ≥ 55 Excellent ≥ 70 Outstanding ≥ 85

Table 1. BREEAM 2011 rating benchmark [3]

BREEAM Energy Section 01: Reduction of CO2 emissions 02: Reduction of Energy use 03: Sub metering of high energy load 04: External lighting 05: Energy efficient systems 06: Energy efficient cooling systems, building performance, air filtration 07: Solutions with low emission of carbons 08: Energy efficient transportation systems (elevators, escalators, moving) 09: Energy efficient equipment 10: Energy efficient lab systems 11: Areas for cooling, drying and heating

Table 2. Energy Section of BREEAM

CREDITS AVAILABILITY AND VERTICAL TRANSPORTATION

Sustainability as a terminology is utilized, specified and addressed in many areas of the construction industry.

One of the most widely accepted definitions of Sustainability is the definition of Sustainable Development “ … development that meets the needs of the present without compromising the ability of future generations to their own needs” [6].

This definition was developed at the World Commission on Environment and Development (WCED) in 1987[6]

The concept of Sustainability is closely related to the geographical aspects, available resources, tradition, and culture, common to that particular geographical area. For that reason, project location is an important factor when assessing Sustainability.

Sustainability is connected to a Sustainable construction, in all phases of the construction process including project conception, Schematic Design (SD), Design Development (DD), Construction Documents (CD), Bidding, Negotiation, Purchasing (B/N/P), Construction (C), and Facility Management (FM). Furthermore, when a portion of the facility becomes obsolete through technological demands, changes in regulations, or alterations, renovations or restorations, all the way to decommissioning and demolition, that will mark the end of the facility life cycle. Areas of the construction: SD, DD, CD, B/N/P, C and in some cases per project bases FM are defined in the project Specifications.

Very often references to Sustainable Construction, are understood to refer to Green Building.

The Energy section – part Ene07 & Ene08 [3] – is one of the significant areas in the BREEAM certification system where visible results can be measured and demonstrated (Table 03).

Under Ene06, whose basis is to recognize and encourage specification of the energy efficient system, the area of Air Quality compliance can be demonstrated via:

- Cab interiors with products that do not containformaldehyde

- Low emitting materials on interior paints and coatings,per standard as specified in the construction documents – no adhesives, sealants and VOC content

- Reducing indoor air contaminants, paints, sealants, cabair circulation and ventilation

- Energy monitoring as part of the BMS

PLA

NET

PRO

FIT

PEO

PLE


Energy

Ene 01 – Reduction of CO2

Ene 02 – Sub-metering of energy use

Ene 03 – External lighting

Ene 04 – Law or zero carbon technology

Ene 05 – Energy efficient cold storage

Ene 06 – Energy efficient transport systems

Ene 07 – Energy efficient lab systems

Ене 08 – Energy efficient equipment

Ene 09 – Dry systems

Table 3. Energy areas of industry per BREEAM

For elevators and escalators a maximum of two credits can

be pursued and awarded based on the following: A. One credit

1. By conducting a traffic analysis study analyzing transport demand and patterns in the building and defining number of elevators and escalators on the project

2. By comparing two systems, elaborating the differences, advantages and disadvantages of each

3. By utilizing the standby mode for escalators in European markets. Escalators enter idle/sleep mode when after certain period of time when no passengers are on the escalator, until a passenger is registered to step on the escalator

4. Variable speed on escalators or moving walks

B. Two credits (Figure 2) One credit, if already earned by pursuing any of the four items noted above, a second can be earned if: 1. Cab lights and fan are in idle mode when an

elevator is not in use within some defined period of time. Periods when passengers used the elevator to reach a destination, which after a standby mode is entered, the elevator has reduced the power consumption to a minimum level until the next traffic demand, when standby mode terminates. Standby power consumption after 30 min of inactivity per ISO/DIS 25745-2[17] is considered for energy demand calculation. In addition to cab lights, VDI 4707[15] discusses 5 categories: very low, low, medium, high to very high, based on average travel and standby. ISO/DIS 25745-2[17] discusses 6 categories: very low, low, medium, high, very high and extremely high, depending on the number of starts/stops/trips per day.

2. Selected cab lights are energy efficient. This is related to a standard palette of an elevator

company offering catalogue per EN81[16]. The level of cab lighting is addressed in EN81-1&2:1998 (item8.17)[16], which states that the car shall be provided with a lighting permanently installed requiring at least 50 lx light intensity at floor level and on any of the control surfaces.

3. Selection of motors with drive controllers VVVF – Variable Voltage Variable Frequency of the drive motor.

4. Selection of elevators with regen drive, gearless motor. Energy efficient solutions due to the low heat dissipation and no loss in transmission. A regen drive unit allows energy generated by the motor while running in the up direction empty and in down direction full to be returned back to the grid.

5. Selection of destination dispatch for a bank of elevators depending of the building type, occupancy type and project scope

Figure 2. Block diagram of credits availability Although conveying systems are not covered as much as

other specialties in the credit earning availability, once a project team is considering certification, this part of the industry will gain more visibility on overall project requirements.

ISO CD25745-1[14] addresses methods of measuring

actual energy consumption and energy during the operations of the conveying systems life cycle. Although energy consumption over the entire conveying system lifecycle starts from manufacturing installation, operational process and disposal, this standard considers the assessment of the power consumption and verification during the operation period.

ISO CD25745-2 (2015)[17] addresses the energy

calculation and classification of elevators, escalators and

Conveying systems credits

cab lights & fan

- lighting selection- standby power

consupmtion

Drive selection

-regen - gearless

- VVVF

Destination control- building type

- occupancy type- traffic demand

-

One credit

-traffic study- somparing two systems

- idle/sleep mode escalators- variable speed on escalators


moving walks. Classifications can be earned, from A-class rating, the best one for elevators, and A+++ the best rating for escalators.

The VDI 4707[15] guidelines evaluate energy efficiency,

describing calculation of the energy demands as related to the conveying system use. Energy Consumption consists of the travel traffic demand and standby energy when in waiting to proceed mode. Effects on the car, starting/stopping, i.e. energy consumed to accelerate an elevator, to reach the rated speed, than decelerate to stop at the destination and idle energy for standing at landings are equally important.

These two standards are widely used for energy efficiency

assessments of conveying systems. The same can be applied when the project is pursuing credits for building certification.

Before a project pursues credits for achieving a LEED

certification level, prerequisites must be accomplished. Energy related to conveying systems (elevators, escalators, moving walks) is referred to as a processed energy and is not subject to the minimum LEED performance requirements, where regulated energy[7] is related to heating/cooling/ventilation systems, water heating, light types.

In this certification system, similar to BREEAM, one credit can be earned with the items listed above, and a second credit, in either the materials and resources area, exemplary performance, or innovation and design.

World globalization and availability of the resources

supply and mostly driven by economics and profit, is resulting in not all parts of the conveying systems equipment to be produced in one place, but in different world areas. In many instances, for the U.S. territory, unless it is specifically stated in the project specification and contract documents, that a product must meet Made in America standards, the majority of the product’s components are made from different sources and made in different countries.

How does this translate to sustainability? If construction documents specify, all supplied project

components and equipment should meet a 500 mile radius, cradle to grave requirement, from the moment of extraction to product use. This requirement is challenging to comply with. Considering these challenges, showing compliance with Made in America requirements can be eligible to contribute for exemplary credit.

Optimization of the energy performance credit can be achieved with energy monitoring and measurements, by describing and comparing two proposed different systems if new construction is planned or by differentiating old and new ones, if existing elevators are upgraded.

Measurement of the energy use is specific to a time frame after the project is turned over. Monitoring, measuring and verification of the operation of the conveying system over a

segment of time is important to record power usage, and potential energy savings can be noted in the manufacturing product data or required by specifications during bidding and at the time of the award.

CHALLENGES In urban environments and cities with increased

population, elevators in the tall buildings will continue to contribute significantly to the electrical use, related to the traffic demand. Elevators account for between 5-15% of the electricity use in office and residential building types, showing that they are an increasing contributor to energy consumption. CIBSE (2015) indicates that vertical transportation accounts for between 3-8% of building energy use, and in some cases for up to 15% CIBSE (2010) [5]. Energy consumption by elevators accounts for between 7-15% of overall building energy use per the estimated energy use in commercial and residential buildings in Hong Kong [18]

The benefits of specifying and supplying sustainable

conveying systems are numerous, from achieving better quality products via market competiveness, area economic development, job creation and green attributes and environment, energy efficiency for building owners, property managers and occupants.

This can be widely applied in different regions, depending

on the applicable adopted standards and statutes in effect. Applying a standby feature in elevator cabs pertaining to the cab lights and fan has benefits as an energy efficiency element but also is a subject of safety in cases when passengers are trapped in the elevators, and the cab light needs to be on. For the most part, this is not the case in Southeast European countries, where the light and fan are off most of the time when passengers are trapped in the elevators and waiting to be rescued. This standby feature and indicators in the car to acknowledge the presence of passengers in the car in the case of entrapment must be incorporated as a standard measure in South/Southeast Europe by applying additional regulations on the city level, which at present is not the case. The above mentioned measures in these geographical areas were explored by M. Krstanoski(2013)[8] and still remain to be addressed by authorities that have jurisdiction in SE Europe.

Due to the aging of the old installed equipment, there is a

high possibility of the existence of asbestos in existing installations as another challenge [8]. Herein elevator shafts and equipment installed over 20 years ago, a fire retardant that might have contained asbestos was typically used in such older elevators shafts. The Washington State Department of Labor and Industry in November 1987 [9], addresses asbestos [9], as a dangerous substance widely used in the construction industry and elevator hoistways that have been frequently coated/sprayed with fire retardants that contain asbestos. The same source [9] from 1987, refers to the developed State


regulations WAC 296-65 and WAC 296-62-077 [9], for guidance with procedures to reduce the risk on all parties involved in the elevator industry from maintenance, modernization, installation, inspection, or anyone that work with asbestos.

Figure 3 illustrates the challenges on this subject. In addition to the fire retardant used in the elevator shafts,

another elevator part that may possibly contain asbestos fibers includes friction materials for elevator brakes shoes (brake pads). First addressed in Scandinavian countries between 1970 and 1980 (Sweden passed a ban on asbestos in 1982), addressed in United States in 1982[19] and 1987[9], and Germany in 1993. The EU issues a Directive in 2005.

Figure 3. Challenges with lift modernization of older

existing installations The European Union is developing a campaign for the

upcoming 2018-2019 to focus on the dangerous substances at the work places, awareness and prevention[10].This is an opportunity to address the existing (older) conveying systems installations still in use. This is also an opportunity for developing instruments for special training, reviewing best practices and regulations to be implemented in countries not yet members of EU due to the very specialized industry, globalization of the market and using workforce and specialists from one country to another.

An example for facing and overcoming challenges of the

modernization, showing methods of implementing asbestos removal is a life building built in the seventies, and located in a very urban area of Paris, the 59-story office high-rise in Main-

Montparnasse tower in Paris, France [11]. The tower segment is a mixed use office building, where occupants are conducting regular daily work. This tower has 25 passenger elevators and 5 service elevators. These elevators were not the subject of the study. The study does not indicate if these elevators are built in shafts that contain fire retardant asbestos nor other elements other than the entire tower. The asbestos removal project was completed in November 2012 with a 90% asbestos free project [11]. The percentage of the completion of the task is an indicator of the complexity of the same and the role of the elevators in the vertical building communication. Challenges still remain in cases where asbestos was detected in the elevator shafts and elevator friction elements.

ENERGY COST AS AN INDICATOR

One of the common indicators for measuring energy efficiency is the cost of the energy. The price of the energy is related to numerous different factors starting from market needs and availability, source of energy or the supply, spending capacity or demand, tax rates, country economic policy, politics, development and research capabilities, number of total and main electricity generating companies in the countries, and availability for credits for consumers. This is per the European statistical office Eurostat’s [12] online data, the basic energy cost with and without all VAT tax levels, as well as the number of electricity generating companies, and natural gas source supply per European country.

Denmark has the highest number of electricity generating companies with reported 1550 for 2014, followed by Italy with 652, Germany and Nederland with 350, representing at least 95% of national net electricity generators [12]. Figure 4 shows the countries in Europe that have most and least electricity generating companies. This list is an indicator of the source availability, which influences the market price and levels of the commitment from the government and private sector to research energy resources and an opportunity to negotiate deals for the benefit of the consumers.

Renewable energy comes from different sources: solar, wind, geothermal, or biomass and waste. Germany is the leader of the renewable resources, followed by Italy, France, Sweden and Spain as reported in 2014[12].

The highest solar source share within the renewable energy sources from all countries is reported to have Malta, followed by Cyprus, Greece, Spain and Germany whereas the rest of the countries reported less than two digit numbers shares in this category for 2014. The highest wind source share is reported to have Ireland significantly higher followed by Denmark, Spain and UK, for 2014 [12].

Bio thermal is very specific and has the smallest share in the renewable category; not many countries reported sources. The leader is Iceland with 78.7%, Turkey with 29.3%, Italy

Challenge 1 Existing Installations Challenge 2

Elevators performace and moderinization

Challenge 3Existing

installations


22.1%, Hungary 6.3%, Macedonia 3.1%, Portugal 3.2%, Slovenia 2.7% and the rest significantly below or even 0 share.

The waste/biomass energy source has the highest share in the renewable category for 2014 as compared to the solar or wind share, with the following countries leading: Estonia, Latvia, Lithuania, Hungary.

The available renewable resources, the number of electrical generating companies [12] and the cost of the electrical energy per country [13], present an opportunity to research ways to be applied in the construction industry, mechanical and electrical systems in building operation and maintenance cycle, and energy credits if buildings pursue certification. Figure 4. represents an indicator to measure possible market competitiveness via availability of the electricity generating sources per country, which gives an opportunity to research possible energy credits and return in investments in the construction sector and facility management/building operations and maintenance sector. European Country

Number of Electricity generating companies 2013

Number of Electricity generating companies 2014

Number of Main Electricity generating companies 2013

Number of Main Electricity generating companies 2014

Denmark 1450 1550 2 3 Italy 493 652 4 3 Germany Over 450

in 2010 Not reported

4 4

Holland 700 350 4 4 Czech Rep 215 217 2 2 Austria 169 201 4 4 Macedonia 2 1 2 1 Croatia 2 2 2 2 Slovenia 3 3 2 2 Greece 3 3 3 3 Cyprus 1 1 1 1 Malta 1 1 1 1

Figure 4. Indicators for the availability of the electricity generating sources, highest and lowest number of main and total electricity generating companies, source [12]

Nuclear energy took 29.4% of the total primary energy

production in Europe, particularly high in France, which accounted for even higher 82.8% of national production of energy, followed by Belgium 72.1% and Slovakia [12]. Germany has announced plans to close all nuclear reactors by 2022, which is an indicator of Europe moving towards renewable and alternate energy sources.

Coal as an energy source, has total share of around 19.4% of the primary production in Europe. Poland with 80.2% is the leader and second leader country is Macedonia 78% with the other 22% coming from renewable sources. [12]

In 28 European countries, out of the total production of all sources of primary energy, around 25% was from renewable resources.

Comparing Figure 4 and Figure 5, relations between these two cost indicators are evident.

Country 2016 Euro/kWh Denmark 0.308 Germany 0.298 Belgium 0.275 Portugal 0.236 Italy 0.234 Spain 0.228 Portugal 0.236 Austria 0.201

Figure 5. Electrical energy cost for domestic use, source

[13] How does this translate into conveying systems?

The cost of electrical energy in the European market is an indicator of the market share, price competitiveness, and an opportunity to research possible energy credits in the area of energy efficiency. The energy market and country economic development are indicators for country performance investing in renewable energy source, construction industry and real estate market.

Indicators such as investments in new construction based on the demand and supply and economy factor, rental cost of the residential and office space, particularly in tall building are bases for the experts to develop mechanisms to promote modernization in the existing installation.

The percentage that conveying systems have in the overall energy building use, increases the need to research the effects to reduce the energy consumption of the elevators and escalators particularly for building with high traffic demands and explore bringing an alternate energy source into the grid for energy efficiency target setting.

The aging of the vertical transportation and the number of old units installed in Europe will assist in an overall ranking of the countries in identifying relevant benchmarks for target settings, such as modernization of the equipment that will lead to replacing the old parts and units with energy efficient new ones.

CONCLUSION

Renewable energy sources will remain an important focus in Europe. Having aging buildings and limited space for new


construction is increasing the interest for energy efficiency in the area of the existing installations. The segment of new installations is equally important and will attract business developers and owners to invest in green building certifications as long as there is a country economy growth and availability of resources.

Quantifying, measuring and verifying the energy used in the buildings over the operations and maintenance cycle takes periods of time to monitor and record the frequency of use, traffic demand and passengers movements in the buildings as related to the elevators. This is related to developing methods to measure and quantify, before and after modernization, and to define an optimal period of time necessary for monitoring with suggested acceptable error in calculation.

The assumption and accuracy of estimating energy usage prior to new equipment installation is not an easy process. It requires careful identification of factors that affect the industry and selecting assumptions for data to be analyzed, herein including traffic study analysis as part of the process. With more accurate selection of the assumptions for traffic pattern, building use and estimated energy use predicted for one system during the initial phase, more close results can be expected for the subject building once the analyzed conveying system is installed, adjusted, tested, turned over, and operated for a defined period of time.

Adequate mandatory training of man power in the area of the existing installations will gear towards prevention of the asbestos risk, and dust level, risk evaluation, developing a front-end study for the project to be modernized, involving experts in different areas of workers safety, dust and pollution mitigation. In a case of the life of a building when occupants are performing their daily duties, and modernization is going on, careful assessments must be conducted. Developing policies that will be enforced, and exploring ways to renovate old buildings is another challenge.

Energy price, its source and its economics will remain major drivers for this industry. For new construction, the project budget must be formulated to illustrate all influence costs related to sustainability from preliminary studies, programming, site-related costs, project design fees, commissioning cost and construction cost.

Further analysis is needed in the area of developing a methodology for data review for energy and sustainability performance measurement factors in order to be utilized for evaluating average efficiency of the conveying systems, and research of the most optimal sustainability factors under number of energy and industry limitations for each European country.

ABBREVIATIONS

BREEAM - Building Research Establishment’s Environmental Assessement Method B/N/P Bidding, Negotiation, Purchasing C - Construction CD - Construction Documents CIBSE - Chartered Institution of Building Service Engineers DD - Design Development FM - Facility Management LEED - Leadership in Energy and Environmental Design SD - Schematic Design VAT – Value Added Tax

REFERENCES [1] http://www.kyotoprotocol.com [2] LEED Green Associate Study Guide, U.S. Green Building Council 2009, ISBN:978-1-932444-23-0 [3] BREEAM Scoring and rating (website: www.breeam.com ) [4] Michelled Cottrell, LEED AP BD+C, Guidebook to the LEED Certification process for LEED for New Construction, LEED for Core and Shell, and LEED for Commercial Interiors, John Wiley & Sons, Inc. 2011 Hoboken New Jersey, ISBN 978-0-470-52418-3 [5]"Chartered Institution of Building Service Engineers Guide D: Transportation systems in buildings. Chapter 13. CIBSE, London, 2010 [6] Liv Haselbach, The Engineering Guide to LEED-New Construction, Sustainable Construction for Engineers, 2008, McGraw-Hill Companies Inc, Printed in United States of America, ISBN 978—0-07-148993-5 [7] Green Building and LEED Core Concepts Guide, First Edition, The U.S. Green Building Council, Inc. [8] Krstanoski, M, 2013, “Concept Review of the Parameters as Related to the Green Aspects of Elevators in Decision-Making Process, ASME District F-ECTC 2013 Proceedings – Vol.12, November 2-3,2013, Birmingham, Alabama USA, 315-323 [9] Washington State Department of Labor & Industries, November 1987, 87-2, Elevator and pressure vessel workers may be exposed to asbestos hazards, available online at: http://www.lni.wa.gov/Safety/Basics/HazAlerts [10] European Agency for Safety and Heath at Work, available online at: https://osha.europa.eu/en/healthy-workplaces-campaigns/future-campaigns, [11] EU-OSHA – European Agency for Safety and Health, Case Study available online at Workfile:///C:/Users/Owner/Downloads/Tour%20Monparnasse%20case%20study.pdf [12] http://ec.europa.eu/eurostat/documents [13]http://ec.europa.eu/eurostat/statistics- explained/index.php/File:Half-yearly_electricity_prices_(EUR).png [14] https://www.iso.org [15] VDI 4707 Guidelines for Lifts Energy Efficiency, Asscociation of German Engineers 2007, http://info.wsisiz.edu.pl/~roksela/dzwigi/Energia/Energy_VDI_ENG.PDF

http://www.breeam.com/

https://osha.europa.eu/en/healthy-workplaces-campaigns/future-campaigns

https://osha.europa.eu/en/healthy-workplaces-campaigns/future-campaigns

http://ec.europa.eu/eurostat/documents

http://ec.europa.eu/eurostat/statistics-%20explained/index.php/File:Half-yearly_electricity_prices_(EUR).png



http://info.wsisiz.edu.pl/%7Eroksela/dzwigi/Energia/Energy_VDI_ENG.PDF

http://info.wsisiz.edu.pl/%7Eroksela/dzwigi/Energia/Energy_VDI_ENG.PDF


[16] EN81-1&2: 1998, European Standard, Safety rules for the construction and installation of lifts – Part 1: Electrical lifts, CEN European Committee for Standardization, Brussels [17] International Organization for Standardization ISO 25745-2:2015- Energy performance of lifts, escalators and moving walks - Part 2: Energy calculation and classification for lifts (elevators) [18] Sam C. M. Hui, Chor-Yip Yeung Analysis of standby power consumption for lifts and escalators, The 7th Greater

Pearl River Delta Conference on Building Operation and Maintenance, available online at: http://www.bsomes.org.hk/upload_pdf/GPRD2016_S1-4.pdf [19] James Bulman, N. Krussel, D. Kogley, Asbestos Substitute Performance Analysis: Revised Final Report, February 1982, U.S. Environmental Protection Agency, available online at: https://nepis.epa.gov/Exe/tiff2png.cgi/9100IJFN.PNG

http://www.bsomes.org.hk/upload_pdf/GPRD2016_S1-4.pdf


Journal of UAB ECTC Volume 16, 2017

Department of Mechanical Engineering The University of Alabama, Birmingham

Birmingham, Alabama USA

ENSEMBLE CALIBRATION OF HERTZIAN CONTACT PARAMETERS FOR A DISCRETE ELEMENT MODEL OF SAND

Gerald Pekmezi and David Littlefield Department of Mechanical Engineering, The University of Alabama at Birmingham,

Birmingham, Alabama, USA

ABSTRACT Discrete Element Modeling is a versatile tool that has, in

recent years, become quite widespread in the modeling of geomaterials. However, despite its widespread use, calibration of the various parameters that make DEM so versatile remains a challenge. Of these parameters, the contact stiffnesses are arguably the most important and influential.

The current work will describe a method for calibrating Hertzian contact parameters when using Discrete Elements as a meso-scale model of a sandy soil. The method is physically-based, accounting for the basic geology of the sand. Additionally, it makes use of Probability Theory through the use of Statistical Ensembles in order to make the calibration independent of scale.

INTRODUCTION It is common practice when modeling a particular soil in

many simulation packages to go through a three-stage calibration process. In the first stage, a relevant library fit is identified from the particle size distribution obtained using a sieve and hydrometer analysis. Next, in the second stage, the model parameters are adjusted to match the laboratory test results (triaxial, uniaxial, constant volume). Finally, in the third step, further adjustment of the many model parameters is typically required when dynamic testing results become available. Such results typically come from flyer plate experiments or Impulse Measurement Devices. The main reason for the multi-stage approach to model calibration, is that the underlying physics of soil behavior, particularly during highly-transient phenomena, is not very well understood.

The current work will explore the physical evolution of sand fabric using mesoscale simulations of the physics involved. It will do so by first creating “avatars” of the sand using the Discrete Element Method (DEM). Each avatar will essentially be a particle-based computational representation of the sand. The avatars will be created by using a particle-packing algorithm followed by an isotropic triaxial compression simulation to achieve the necessary initial physical characteristics for the granular phase. Subsequently, the DEM avatar will be calibrated to match the behavior and response

seen in physical tests as closely as possible. The calibration is a nonlinear process carried out by parametric DEM simulations of the lab tests. Additional work to be carried out in the future, will aim to build an optimization/calibration framework that will use genetic algorithms along with gradient optimization methods to calibrate DEM avatars from soil data automatically.

HOMOGENIZATION The primary assumption of any effort to quantify the

behavior of a material at the macroscale, is the existence of a Representative Volume Element (RVE). Herein, the RVE is understood in the sense of Hill [1]. The existence of the RVE is readily ascertained via a unit cell in the case of periodic microstructures, such as those constituting many matrix/fiber composites. However, the identification and determination of the RVE is rather more difficult when dealing with random heterogeneous media such as soils. Mathematically, an infinite number of grains would be required to attain the RVE scale, due to the complete randomness and heterogeneity of the grains.

Figure 1: Heterogeneous Packing of Sand Grains

Consider the random sand grain distribution of Figure 1.

The figure shows two cross-sections of the same cubic sand grain packing, and illustrates the concept of Separation of Scales. The separation suggested here and based on [2], involves three scales


1. The microscale d, which represents the size of the typical grain, or an inclusion.

2. The mesoscale L, the RVE size 3. The macroscale Lmacro, macroscopic sample size

macro

dL L

d<

<<<< (1) The inequality of Equation (8) contains two options as the

mismatch in geometry and properties may be small or great. In the current work, the mismatch is always great, requiring the use of the second form of the left-hand side of the inequality.

In addition to the concept of the RVE, it is also beneficial at this point to introduce the related concept of the Statistical Volume Element (SVE). The SVE is sometimes also called the Stochastic Volume Element, due to the randomness observed in the behavior at this scale. The SVE represents all realizations of the microscale greater than the typical grain, but smaller than the RVE. Where the RVE material properties are the same as those of the macroscale, the SVE properties are represented by statistical quantities.

THE HILL CONDITION Consider a body 𝐵𝐵𝛿𝛿(𝜔𝜔) not under the action of any body

forces or inertia and with stress and strain fields σ and ε due to some arbitrary boundary conditions. The stress/strain fields may be represented as a superposition of their means (σ and ε ) and trivial fluctuations (σ ′ and ε ′ )

( ) ( )( ) ( )

, ,

, ,

σ ω σ σ ω

ε ω ε ε ω

′= +

′= +

x x

x x (2) The volume average of the energy density over 𝐵𝐵𝛿𝛿(𝜔𝜔) may then be written as

( ) ( )( )

1, : , :12

1 1: :2 2

2 B

U dVV

U

δ ω

σ ω ε ω σ ε

σ ε σ ε

=

′ ′+

=

=

∫ x x

(3) The Hill Condition [1] is satisfied if the average of a scalar

product of stress and strain fields is equal to the product of their averages

: :σ ε σ ε= (4) which requires

: 0σ ε′ ′ = (5) Rewriting (12) in indicial notation and applying the

divergence theorem

( )( )1

ij ij i ij j i ij jV

t n u x dSV

σ ε σ ε∂

′ ′ = − − ∫ (6)

The triviality of the fluctuations is clearly satisfied for the macroscale Lmacro; however for a finite mesoscale the Hill Condition is satisfied if and when Equation (14) holds

( )( )1 0

B

dSV

δ

σ ε∂

− ⋅ − ⋅ = ∫ t n u x (7)

The condition is satisfied by three different types of uniform boundary conditions for heterogeneous media [3]:

1. uniform displacement (Dirichlet, kinematic, KUBC) boundary condition

2. uniform traction (Neumann, static, SUBC) boundary condition

3. uniform displacement-traction (orthogonal mixed, MUBC) boundary condition

THE DISCRETE ELEMENT METHOD With the significant increase in available computational

power and resources over the last decade, geomaterial modeling has seen both evolutionary and revolutionary changes. One such “revolution” has been the dramatic rise in popularity of particle methods such as the Discrete Element Method (DEM). DEM is very closely related to molecular dynamics (MD), in fact one of the more popular DEM applications (LIGGGHTS) [4] is a fork of the most widely used MD code, LAMMPS [5]. The inclusions of rotational degrees of freedom and nonlinear contact with friction are the main attributes that separate DEM from MD. DEM can be useful in modeling soils in dynamic applications considering the large deformations involved. As with any other simulation paradigm, there is a potential for misuse with DEM. The approach, methodology, and output expectations need to be weighed carefully to avoid the trap of a visually appealing, but not mechanistically meaningful model.

All DEM simulations performed in the current work are carried out using the YADE code [6]. Figure 2 shows a DEM model from Yade used in the current work.

Figure 2: A spherical particle packing of 2x106 sand

particles

CONTACT MODEL The contact force used in the discrete element particle

model may follow one of two formulations: linear contact or Hertzian contact. The Hertzian contact formulation is used herein. This formulation resembles the Hertz-Mindlin solution [7], which is valid for elastic bodies in contact. The elastic normal force in the Hertzian solution is expressed as


* * 3 2

,43n el nF E R u=

(8) where *E and *R represent the equivalent effective Young’s modulus and particle radius, respectively. The shear force is linear with respect to the relative sliding displacement at the region of contact, assuming the no micro-slip solution of Hertzian contact.

* *8s n sF G R u u= (9)

with *G being the equivalent shear modulus. Finally, the

normal and tangential contact stiffnesses can be written as

* *2n nk E R u= (10)

* *8s nk G R u= (11)

Sliding between particles is initiated once the shear force exceeds frictional resistance. This is expressed by a frictional Mohr-Coulomb equation

tan 0s nF F φ− ≤ (12) where φ denotes the friction angle between particles.

Another important aspect of particle contact modeling is cohesion between particles. Cohesion may come from capillary effects or it may come from chemical cementation. The cohesion model used herein is the Derjaguin-Muller-Toporov (DMT) model [8]. In the DMT model the contact profile is the same as for Hertzian contact but with the added assumption of adhesion outside the area of contact. The radius of contact between two spheres from DMT theory is

( )3 3= 4

4 *Ra F R

Eγπ+

(13) and the pull-off force is

4cF Rγπ= − (14) Finally, there are two ways to account for inelastic

compaction of the soil from crushing or particle deformation using the DEM model. The first is to model crushing explicitly by making large particles agglomerations of smaller particles, then splitting off the small particles at a threshold stress. The second is to lower the particle stiffness upon unloading so as to make the interparticle distance smaller. A modified version of the first method is used here; rather than splitting particles, large particles are shrunk by a factor small enough to maintain stability of the simulation, but large enough to ensure the threshold stress is not surpassed (e.g. 0.001).

In the current study, only the Hertzian contact parameters are considered important. This is because sliding and cohesion are overcome once the high mean stress of the isotropic compression test is reached. Crushing is ignored herein, but this study is a prerequisite for carrying out a calibration of the crushing parameters. This will be done in a future study.

OPTIMIZATION PROBLEM In Applied Mathematics and Computational Modeling, the

Optimization Problem is one where there is no unique solution

and the best choice of possible solutions must be identified. There are two broad types of optimization problems, Combinatorial Optimization and Continuous Optimization. Combinatorial Optimization deals with discrete values or realizations of variables. This work does not deal with Combinatorial Optimization. Continuous Optimization, on the other hand, deals with continuous variables and can include constraints and multimodality.

The standard form of a Continuous Optimization problem is [9]:

minimize ( )

subject to ( ) 0, 1, ,( ) 0, 1, ,

i

i

x f x

g x i mh x i p

≤ == =

(1.15) where ( ) : nf x → is the objective function that needs to

be minimized over x, ( ) 0ig x ≤ are inequality constraints,

and ( ) 0ih x = are equality constraints. An objective function is a function that maps values of

variables to a real number that represents the cost or reward associated with the variable value. When reward is used, the objective function is called a Reward or Profit Function, and the goal of optimization is to maximize it. When cost is used, the Objective Function is termed a Loss Function, and the goal of the optimization problem is to minimize the cost or loss number. In the context of Computational Modeling, an objective function is typically a Loss Function where the “cost” is some measure of the computational error relative to an objective measure such as experimental testing.

OPTIMIZATION METHODS Optimization algorithms include Local as well as Global

approaches. Local optimization approaches seek the local best solution or local minimum with no consideration to the possibility there may be a lower minimum in a distant region of the solution space. The local approach is well-suited to problems with a monotonic objective function. However, if the objective function is “bumpy”, then a global approach is required to ensure the optimization has not converged to a local minimum that does not represent the optimal global result.

Additionally, optimization algorithms may be classified as either Gradient-based or Derivative-free methods. Gradient-based methods have the best accuracy and convergence rates; however, they require the computational code to provide analytic gradients, which is often not possible when dealing with Computational Fluid Dynamics and Finite Element Method codes. This is where derivative-free methods are useful. They are inherently more expensive computationally then gradient-based methods; however, they benefit greatly from parallelism and can approach the speed of gradient-based methods with sufficient asynchronous concurrency [10].


STATISTICAL MECHANICS Statistical Mechanics is that branch of theoretical physics

that uses Probability Theory to quantify the uncertainties inherent to non-deterministic systems within the realm of Classical Mechanics [11]. This outlook is usually associated with the other major realm of Mechanics, the Quantum realm; however, uncertainty is present and quite important in many classical applications as well. Indeed, the term “Statistical Mechanics” is often used to refer specifically to Statistical Thermodynamics, which aims to derive classical thermodynamics from the constituent fundamental particles, i.e. atoms and molecules. This approach is easily extended to other systems composed of particles, and the Discrete Element Method is a tool that can do for geomechanics what Molecular Dynamics methods such as Dissipative Particle Dynamics (DMD) does for thermodynamics.

It is rather unfortunate that the wider DEM community has not realized the need to integrate Discrete Elements within Statistical Mechanics. Even otherwise robust and rigorous studies carried out using the Discrete Element Method, fail to consider the uncertainties associated with a system composed of a finite number of particles. These uncertainties, rather than being dismissed or ignored, can instead be quantified and accounted for by using Statistical Ensembles.

ENSEMBLE AVERAGING A Statistical Ensemble is a model composed of many

copies of a system in its different possible states, considered simultaneously. Another way to state this is that the Statistical Ensemble is a probability distribution for the state of the system [12]. For the concrete case of a particle model of a geomaterial such as the sand considered herein, the ensemble may be defined as a collection of particle packings of a finite size, wherein the cumulative distribution is like that of a single packing of a near-infinite number of particles.

The idea here may be distilled down to the simple fact that a Discrete Element Model containing a near-infinite number of particles is both impractical and computationally prohibitive. However, a large number of concurrent models of finite sizes, is quite feasible, especially so with access to High Performance Computing (HPC) resources. These models of finite size are henceforth called “realizations”, wherein each is a random realization of a possible collection of particles and properties of the constituent grains.

Ensemble Averaging is the computation of the average, or possibly the statistical distribution, of a certain quantity for an ensemble of realizations. In this study, the ensemble is a collection of Discrete Element Models, each of which represents a realization of the system of grains.

COMPUTATIONAL APPROACH The sand considered in this work is a poorly-graded sand

(SP). All data from the testing and analysis of the sand was graciously provided by the Engineer Research and Development Center (ERDC) of the US Army Corps of

Engineers. Figure 3 shows the Particle Size Distribution (PSD) reported by ERDC.

Figure 3: PSD for Poorly-Graded Sand

A histogram with 10 bins is used to build a DEM packing

of 1x108 particles, hereafter referred to as the “source” model. For reference, Figure 2 shows a DEM packing of 2x106 particles, which is realistically the number of particles that can be rendered in a reasonable amount of time and with adequate resolution.

The source model is then sampled at various times to build mesoscale DEMs of sizes. All calibrations in the current work were carried out on DEMs of 5000 particles each, sampled from the source particle model. The ensemble consists of 360 DEMs of 5000-particle DEMs. Figure 4 shows the Love-Weber stresses in a typical 5000-particle DEM at a confinement of 5 MPa. Each of these models is then loaded isotropically to a pressure of 510 MPa, which matches the greatest pressure seen in the isotropic compression test reported by ERDC. The DEM ensemble is then calibrated using the mean difference between observed volumetric strain and the DEM volumetric strain as the objective function

Figure 4: Love-Weber Stress in a DEM of 5000

spheres

Grain Size in Millimeters

Perc

ent F

iner

by

Wei

ght

0.050.10.20.30.50.712345678102020

3/4" 1/2" #3 #4 #6 #8 #12 #20 #40 #60 #100 #200U.S. Standard Sieve Sizes Hyd. Anal.

Silt or ClayGravel SandC Fine Coarse Medium Fine

0

10

20

30

40

50

60

70

80

90

100

Average of all curves

UAB School of Engineering – Mechanical Engineering – Early Career Technical Journal, Volume 16 7

RESULTS Before the results of the Ensemble Calibration are

presented, it is of benefit to investigate how good of a fit the Hertzian contact solution is for the current study. To that effect, the best source of experimental data are nano-indentation studies carried out on sand grains. The data of Figure 5 comes from such a study on Eglin sand [13], carried out using a Berkovich tip indenter. A Berkovich tip is a pyramid-shaped indenter, for which there is no Hertzian contact solution. However, it has been found that a conical tip with an angle of 70.3 degrees is a quite reasonable approximation of a Berkovich tip indenter [14]. The Hertzian contact solution can be seen to be a very good match for the indentation of sand grains.

Figure 5: Force-Displacement of Grains under

Indentation Next, an optimization is carried out for the stiffness of the

sand grains. 90% of the sand grains are assumed to belong to a normally-distributed bin with the higher Young’s modulus between 50 GPa and 500 GPa. 10% of the sand grains are assumed to belong to a normally-distributed bin with the lower Young’s modulus between 500 MPa and 10 GPa. The higher moduli represent the minerals that form the main component of the sand, while the lower moduli represent the softer components of the sand such as coral and seashells. The standard deviation of the Young’s modulus distribution is assumed to be half the mean for each bin. Note that the normal distribution used here is a “truncated” normal distribution, so that the minimum possible Young’s modulus allowed is 100 MPa.

The optimization uses an evolutionary algorithm to conduct parallel simultaneous simulations of the DEM ensembles. Different values of the High Modulus and Low Modulus are used for each ensemble simulation, and the fitness evaluated using the objective function described previously. The number of ensemble simulations carried out was 240, with each ensemble consisting of 360 DEM realizations for a total of 1.6e106 DEM simulations. Figure 6 shows the results of the optimization plotted as a surface of the objective function as a function of the moduli. In the end, the moduli that showed the

best fitness was achieved with values of 282 GPa for the high modulus, and 461 MPa for the low modulus.

Figure 6: Objective Function Design Surface

The isotropic compression unloading curve for the

optimized moduli is plotted along with the experimental curve in Figure 7. Also shown, for reference, are unloading curves for single-valued “stiff” and “soft” moduli of 240 GPa and 80 GPa respectively. This chart illustrates the value of using statistically-distributed parameters for the ensemble, as well as how well optimization can serve in calibrating ensemble parameters.

Figure 7: Objective Function Design Surface

CONCLUSIONS A large number of simulations were carried out using

random samples of spherical particles using a Discrete Element formulation. The DEM avatar was built to closely emulate a real sand. It was demonstrated that through this computational optimization framework, reasonable values may be found for a Discrete Element Model of the sand mesoscale. This is an important result, since the use of the Discrete Element Method as a meso-scale simulation tool for soil is in its nascent stages. It is therefore quite important for the model to be meaningful in a physical and geological sense.

0

5

10

15

20

25

30

35

0 200 400 600

Forc

e (m

N)

Displacement (nm)

HertzianExp.

-14

-12

-10

-8

-6

-4

-2

01 10 100

Volu

met

ric S

trai

n (%

)

Confinement Pressure (MPa)

softstiffexpOptimized


This study is the first of a series of studies with the overall aim of introducing the methods of Statistical Mechanics to the heretofore deterministic and non-statistical outlook in the field of geomechanics. Optimization of contact parameters will be carried out in future works for different types of soils and other geomaterials, such as concrete and rock. This calibration framework will then serve to facilitate broader study of geomaterials at the mesoscale.

REFERENCES [1] R. Hill, Elastic properties of reinforced solids: some theoretical principles, Journal of the Mechanics and Physics of Solids 11(5) (1963) 357-372. [2] M. Ostoja-Starzewski, Microstructural randomness and scaling in mechanics of materials, CRC Press2007. [3] M. Ostoja-Starzewski, Material spatial randomness: From statistical to representative volume element, Probabilistic Engineering Mechanics 21(2) (2006) 112-132. [4] C. Kloss, C. Goniva, LIGGGHTS–open source discrete element simulations of granular materials based on Lammps, Supplemental Proceedings: Materials Fabrication, Properties, Characterization, and Modeling, Volume 2 (2011) 781-788. [5] S. Plimpton, P. Crozier, A. Thompson, LAMMPS-large-scale atomic/molecular massively parallel simulator, Sandia National Laboratories 18 (2007). [6] V. Šmilauer, E. Catalano, B. Chareyre, S. Dorofeenko, J. Duriez, A. Gladky, J. Kozicki, C. Modenese, L. Scholtès, L. Sibille, Yade reference documentation, Yade Documentation 474 (2010). [7] R. Mindlin, Compliance of elastic bodies in contact, Journal of applied mechanics 16 (1949). [8] B.V. Derjaguin, V.M. Muller, Y.P. Toporov, Effect of contact deformations on the adhesion of particles, Journal of Colloid and interface science 53(2) (1975) 314-326. [9] S. Boyd, L. Vandenberghe, Convex optimization, Cambridge university press2004. [10] B.M. Adams, W. Bohnhoff, K. Dalbey, J. Eddy, M. Eldred, D. Gay, K. Haskell, P.D. Hough, L. Swiler, DAKOTA, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: version 5.0 user’s manual, Sandia National Laboratories, Tech. Rep. SAND2010-2183 (2009). [11] R. Fitzpatrick, Thermodynamics and Statistical Mechanics: An intermediate level course. Lulu Enterprises, Inc, 2006. [12] J.W. Gibbs, The collected works of J. Willard Gibbs, Yale Univ. Press, 1948. [13] F. Wang, B. Fu, H. Luo, S. Staggs, R.A. Mirshams, W.L. Cooper, S.Y. Park, M.J. Kim, C. Hartley, H. Lu, Characterization of the Grain-Level Mechanical Behavior of Eglin Sand by Nanoindentation, Experimental Mechanics 54(5) (2014) 871-884. [14] N. Sakharova, J. Fernandes, J. Antunes, M. Oliveira, Comparison between Berkovich, Vickers and conical indentation tests: A three-dimensional numerical simulation study, International Journal of Solids and Structures 46(5) (2009) 1095-1104.

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