Thermal Analysis and Verification of CubeSat Designs with ...

50th International Conference on Environmental Systems ICES-2021-104 12-15 July 2021

Copyright © 2021 NLR and ISISpace

Thermal Analysis and Verification of CubeSat Designs with

ESATAN-TMS

A.K. te Nijenhuis1

Royal Netherlands Aerospace Centre, Marknesse, Flevoland, 8316PR, The Netherlands

H.S.B. Brouwer2, M. Jonsson3

ISISpace, Delft, Zuid-Holland, 2623CR, The Netherlands

and

E.A. Bloem4, G. van Donk5, B. Lamers6, A. Pauw7, and R.C. van Benthem8

Royal Netherlands Aerospace Centre, Marknesse, Flevoland, 8316PR, The Netherlands

For the competitive CubeSat market the importance of thermal analysis is often

underestimated, which can lead to temperature critical designs. Clearly, with the trend of

increasing power density for CubeSats, thermal design deserves more attention. To anticipate

on this trend, a joint effort of ISISpace and NLR - Royal Netherlands Aerospace Centre was

initiated to prepare a framework for modular thermal analysis of CubeSats designs using

ESATAN-TMS. In order to increase the accuracy of the initial model parameters used during

the verification process, dedicated tests were conducted on specific thermal properties of

CubeSats, in order to both verify and supplement literature values. These tests were primarily

focused on thermal properties of PCBs, which play a prominent role in the thermal control of

CubeSats. Additionally, conductive interfaces of 2U CubeSat assemblies were tested in a

thermal vacuum chamber at NLR, and the results were used in the correlation with thermal

models. The correlation approach used a black box optimization method for improved fitting

of the CubeSat model parameters. In this process the RMS error of the temperature

predictions of the CubeSat model is minimised by automatically adjusting a set of pre-defined

correlation parameters, amongst which are contact conductance, the thermal conductivity of

PCBs and radiative properties, within a pre-defined correlation interval. The verification

process as discussed in this paper is the starting point for the creation of a library of validated

submodels in ESATAN-TMS which can be used for thermal designs of CubeSats in the future.

Nomenclature

ESATAN-TMS = ESATAN Thermal Modelling Suite

ISIS = Innovative Solutions In Space

NLR = Royal Netherlands Aerospace Centre

OBC = On-Board Computer

PCB = Printed Circuit Board

MLI = Multi-Layer Insulation

RMS = Root Mean Square

1 R&D Engineer, Thermal Control Systems, [email protected]. 2 Systems Engineer, System Engineering, [email protected]. 3 Mechanical Systems Engineer, Mechanical Engineering, [email protected]. 4 R&D Engineer, Thermal Control Systems, [email protected]. 5 R&D Engineer, Thermal Control Systems, [email protected]. 6 Application Engineer, Thermal Control Systems, [email protected]. 7 R&D Engineer, Thermal Control Systems, [email protected]. 8 R&D Manager, Energy Management, [email protected].

mailto:[email protected]








International Conference on Environmental Systems

2

I. Introduction

his paper is a follow up on the work envisioned by the collaboration between the NLR and ISISpace. The

developments within this collaboration, specifically on ESATAN-TMS CubeSat modular thermal analysis, is

shown and discussed here. Previously, the thermal control and analysis trends for CubeSats have been discussed and

the need for quick turn-around thermal analysis solutions was defined.1

CubeSats are modular in their essence. It is common that a CubeSat designer uses modules or subsystems from

many different vendors in assembling a satellite. During this work, verified CAD models are commonly exchanged in

order to early on do mechanical fit-checks and assess mechanical properties such as mass, inertia and the needs for

structural customization and analysis. The vision of the NLR-ISISpace collaboration is that thermally verified and

validated models of the subsystems are exchanged in a similar fashion so that thermal customization and analysis

needs can be assessed with confidence very early in the projects as well. To facilitate this vision NLR and ISISpace

setup a three phase project, visualized in Figure 1. The previous paper described the project initiation, its state at the

end of Phase I, and the beginning of Phase II. This paper shows the work done in Phase II, which is about to be

concluded.

Figure 1 – The three phases of the project aiming to standardize thermal control on CubeSats and provide

the thermal engineer a process to verify and validate ESATAN models.1

II. CubeSat Thermal Analysis Verification

In our previous paper1 we showed the ESATAN-TMS modelling of the pilot subsystems and the plan for how to

verify their thermal parameters. This process of verification is shown in Figure 2. Here, the refinement and execution

of that plan together with the results of the analysis, the performed tests, and their correlation with the model is

presented.

The second phase of the project consists of setting up a library of CubeSat subsystem ESATAN-TMS models

whose thermal properties have been verified. The library would consist of all required submodules needed to build up

an ESATAN-TMS model of any CubeSat in a very quick and effective way. To achieve this, some of the common

ISIS subsystems were selected as pilot cases for the process but the idea is that this process can be generally applied

to any subsystem.

Phase IExploration

Phase IIVerification

Phase IIIValidation

Thermal Need Exploration

Feasibility of ESATAN

Thermal modelling of subsystems

Set up CubeSat thermal model

library

Thermal modelling of satellite

Validation of thermal model with

in-orbit data

Verification of thermal model with

thermal testing

CubeSat Modular Thermal Modelling in ESATAN-TMS

T


3

Figure 2 – The verification process to set up a library full of thermally verified subsystems visualized.1

In parallel of this project phase and within the collaboration between NLR and ISISpace, research has also been

performed in the area of thermal control systems and applying them to CubeSats. In specific, water heat pipes2,3,

phase-change material4, and the mini-mechanically pumped loop.5 While this research has primarily focused on their

feasibility such thermal control systems are foreseen to be able to follow the same process as above and be included

in the thermal library.

Verification is the first step in improving the knowledge of the CubeSat thermal engineer. As of yet, many

uncertainties pertain specifically related to CubeSat common- and generic interfaces. Earlier conducted tests on

CubeSat constituents have already shown that empirical relations are not always applicable.6 Hence, it is important

that more data is gathered to find the common values for parameters like contact conductances and even better overall

conductive couplings for common CubeSat interfaces. Thanks to the CubeSat’s standardized interfaces, the latter

would tremendously aid the thermal engineers while performing CubeSat thermal analyses at an early (and later!)

design stage.

Hence, another goal of this second phase, next to verifying the process of setting up a thermal library, is to find

the cause of major discrepancies between the ESATAN-TMS thermal model and the test results and be able to relate

them to specific thermal parameters (contact conductance, material properties, etc.).

III. ESATAN-modelling and simulations

In the presented project, we used a 2U CubeSat as a benchmark case for setting up the correlation procedure. The

chosen 2U CubeSat design consists of ISIS commercially available hardware: (1) an aluminum 2U frame, (2)

aluminum side-, top- and bottom panels, at all faces of the satellite, (3) an On-Board Computer, abbreviated as OBC,

and (4) aluminum spacers that clamp the OBC to its position in the frame. This set of hardware was both used in the

experimental tests, as in the ESATAN-TMS model.

Submodule Identification

Thermal Parameters Identification

Submodule modelling

ESATAN-TMS

Assess validity of submodule

Sufficient

Improvement through testing

Insufficient

Verify Parameters

Literature or experimental

results

Verify modelling

Submodule level thermal vacuum

tests

Assembly level thermal vacuum

tests

Component focus Interface focus

Addition of submodule to Library


4

Figure 3 – The benchmark 2U CubeSat design in

ESATAN-TMS.

Figure 4 – ESATAN-TMS model of a 2U CubeSat

placed in a cylinder that represents a thermal

vacuum facility.

The ESATAN-TMS model (Figure 3) was assembled by means of the submodelling procedure as presented in Te

Nijenhuis, Brouwer et al.1. The first stage of this procedure is to create the building blocks based on the mentioned

hardware. Only thermally relevant details were taken into account. Therefore, the ESATAN-TMS model of the OBC

consists of elements that either dissipate heat, have a high heat capacity, or are relevant for the thermal pathways from

the heat dissipation location to other parts in the CubeSat-design. In Figure 5 the commercially available ISIS OBC is

shown. In Figure 6 the ESATAN-TMS model of the OBC is shown, which resembles a thermally simplified version

of the hardware. In this model, the orange square on top of the OBC processor represents a dummy heater, relevant

for testing purposes. The grey cylinders represent the aluminum spacers in direct contact with the OBC.

Figure 5 – ISIS OBC.

Figure 6 – ESATAN-TMS model of ISIS OBC.

Assembly of the submodels into the full ESATAN-TMS model of the 2U CubeSat design was completed by setting

contact conductances at the interfaces between submodels. Therefore, an estimation of the contact conductances

between spacers, frame structure elements, and panels, was done. In contrast to the contact conductances, bulk material

properties as thermal conductivity and emissivity were already implemented in the submodels, and thus readily

available during the assembly of the 2U CubeSat ESATAN-TMS model.

For the simulations, a representative test surrounding was designed in ESATAN-TMS; a hollow cylinder with

high-emissivity walls. The surrounding resembles the thermal vacuum facility as used in the testing phase. Correct

view factors were achieved by placing the CubeSat in the middle of the cylindrical surrounding, as shown in Figure

4. Only the inner face of the cylinder was set as thermally active.


5

Steady state simulations were performed in ESATAN-TMS, in which two boundary conditions were varied: the

heat load on the OBC dummy heater, and the cylinder wall temperature. Results of the simulations will be discussed

in section VI.

IV. 2U CubeSat testing

The ESATAN-TMS model shown in section III was made to represent the test-object. This test-object is shown

in Figure 7. It contains an ISIS OBC clamped in a frame by aluminum spacers. As opposed to the design in the figure,

during tests all panels were attached to the frame elements, which provides radiation surface at all faces of the CubeSat.

Radiation from the OBC was suppressed by means of Multi-Layer Insulation (MLI), with a well-known emissivity.

Hence, only by conduction the heat load of the OBC could transfer through the Printed Circuit Board (PCB).

Figure 7 – Test object instrumented with thermocouples. The numbers correspond to the thermocouples

numbers as shown in Figure 9.

Thermocouples were placed throughout the entire design. The temperature evolution at interfaces between PCB

and spacer, spacer and frame rib, and frame rib and side panel were monitored by pairs of thermocouples. Additionally,

temperature evolutions through single materials, like the aluminum frame structure elements, were monitored by pairs

of thermocouples. Lastly, the surroundings of the experiment were measured by thermocouples, and controlled via a

feedback-loop.

In Figure 8 the placement of the power resistor is shown. This dummy heater was clamped on the OBC processor

with bolts and a metal bridge. Its power dissipation was controlled by a power supply outside of the vacuum chamber.

The advantage of using a dummy heater over the OBC’s in-operation power dissipation is the ease of controlling the

power dissipation, and knowing the exact location of the heat dissipation.

1: Heater

2: PCB end

3: Spacer Bottom

4: Spacer Top

8: Support Rib Mid B

7: Frame Rib Bottom

6: Support Rib End

5: Support Rib Mid A

9: Sidepanel Mid

10: Sidepanel Top

11: Frame Rib Top-Mid

12: Frame Rib Top

13: Toppanel


6

Figure 8 – Placement of dummy heater on the OBC.

A set of steady-state tests were performed, with ambient temperatures ranging from -30°C to 50°C, and heat loads

ranging from 0.5 W to 4.0 W. All steady-state tests resulted in steady-state temperatures measured by the

thermocouples. In Figure 9 the temperature evolution of all thermocouples is shown, between steady states. At t=0 s

the steady-state with heat dissipation controlled at 1.5 W is shown; at t=8300s the steady-state with heat dissipation

controlled at 1.0 W is shown. The ambient temperature was controlled at 50°C.

Figure 9 – Temperature evolution from a thermal vacuum test with steady-state results for a heat dissipation

of 1.5 W (t=0 s) to a thermal vacuum test with heat dissipation controlled at 1.0 W (t>0 s), which reached

steady-state at t=8300 s. The ambient temperature was controlled at 50°C.

V. Additional testing for distinct thermal properties

Critical thermal properties of the 2U CubeSat assembly are the (1) contact conductances at interfaces of spacers,

frame structure elements, and panels, (2) thermal conductivities of the PCB and frame structure elements, and (3)

emissivity of the aluminum panels. In order to increase the reliability and quickness of the correlation, as described in

section VI, narrow ranges of the fitting parameters are needed. These ranges can be narrowed in the state before

laboratory testing.

For (1), the contact conductance, literature research was performed6, to narrow value of the contact conductances

between aluminum interfaces with specified torque. For (2), the thermal conductivities of PCB-samples, dedicated

tests have been performed as part of this project. For (3), the emissivity of aluminum panels, a literature search was

done, as well as a short series of emissivity measurements, not explicitly described in this paper.

The methods described below, serve as a framework for future investigations of in-plane conductivity and through-

plane conductivity of various PCB designs.


7

A. PCB in-plane thermal conductivity

The in-plane thermal conductivity of PCB samples was measured with the radiating fin method, based on the work

of Sarvar et al.7. The PCB was hung in the middle of a thermal vacuum facility. A spun copper wire provided heat

input at one end of the PCB sample, controlled at a temperature of 60°C. Since the test was performed in a thermal

vacuum facility, controlled at 20°C, heat transfer in the sample occurred only by radiation to the surroundings, and

conduction in the PCB-plane. The PCB was painted black with Nextel Velvet Coating 811-21, which has an emissivity

of 0.96 ± 0.01. as found by Koirala8. With knowledge of the geometry, temperature and emissivity, the radiation can

be accurately determined. All other heat transfer from temperature node to temperature node is conduction. Hence,

the in-plane thermal conductivity can be estimated based on geometrical properties, emissivity and temperature

measurements. In equation (1) below, the energy balance at temperature node i is given, where the difference in

incoming and outgoing conductance is equal to the node’s radiation.

𝑘𝐴𝑇i+1−𝑇i

𝛥𝑥− 𝑘𝐴

𝑇i−𝑇i-1

𝛥𝑥= 𝜎𝜖(𝑃𝛥𝑥)(𝑇i

4 − 𝑇amb4 ) (1)

In this equation, Ti is the temperature at node i, k is the in-plane thermal conductivity, A is the cross-section of the

sample, Δx is the distance between nodes, σ is the Stefan-Boltzmann constant, ϵ is the sample’s emissivity, P is the

perimeter of the sample, and Tamb is the ambient temperature of the test environment. Note that the in-plane thermal

conductivity in equation (1) is temperature-dependent.

In Figure 10 a schematic of the radiation fin method setup is given. The rectangular surface represents a PCB-

sample. Thermocouples are placed along the longitudinal direction of the sample. In the test board, show in Figure

11, the right half of the PCB is used as a guard, to prevent heat leak via the thermocouples. Power input is provided

by a spun copper wire at the left end of the sample.

Figure 10 - Schematic of the radiating fin method setup,

reprinted from Sarvar et al.7.

Figure 11 – PCB sample, with heater wire

at the top, and 10 thermocouples.

Two samples of a single ISIS PCB type were

tested with this method, in different directions.

The PCB was characterized in terms of copper

volume percentage, thickness of PCB-layers and

number of layers (see Figure 12), which impact

the in-plane thermal conductivity. The

conductivity found was 24.6 W/mK in one

direction (first sample), and 22.7 W/mK in the

perpendicular direction (second sample), with an

estimated error of ±5%, based on a RMS error of

several measurement conditions. We observe little influence of the applied power at the top

end of the PCB, as shown in Table 1. Although the properties of the samples are equal, the

directionality is different, since in the first sample copper channels are in the same direction

as the array of thermocouple sensors.

Sample P [W] k [W/mK]

PCB #1 in x-dir. 1.0 24.7

PCB #1 in x-dir. 2.3 24.7

PCB #1 in x-dir. 3.9 24.5

PCB #2 in y-dir. 1.0 22.7

PCB #2 in y-dir. 2.4 22.7

PCB #2 in y-dir. 3.8 22.6

Table 1 – Overview of test results of

PCB through-plane conductivity.

Figure 12 –

Typical PCB

build-up


8

B. PCB through-plane thermal conductivity

The through-plane thermal conductivity of PCB samples (D=75 mm, see Figure 14) was measured with the Lees’

Disc Apparatus method, based on the work of Sarvar et al.7. In Figure 15 the setup is shown. A circular PCB sample

was clamped between two brass cylinders (Cp = 380 J/kgK, k = 109 W/mK). Contact between the brass cylinders and

PCB sample was improved by means of a heavy mass on top of the setup, and thermal paste (Dow Corning 340, k =

0.67 W/mK) at the interface of brass and PCB. A circular foil heater (D=70 mm) was attached on top of the brass

cylinders, which directly heats the top brass cylinder. On top of the foil heater was an isolating material, in order to

maximize heat transfer from foil heater to the brass. The high thermal conductivity of the brass provides temperature

uniformity for the brass cylinders. Therefore, the temperature can be measured in the middle of the cylinders with a

Pt100 temperature sensor. The entire experiment took place in a temperature-controlled room, with marginal air flow.

To determine the through-plane conductivity, equation (2) was used. In this equation, Q is the heat flow, k is the

through-plane conductivity of the sample, dT/dx is the spatial temperature gradient between top and bottom cylinder,

dT/dt is the temporal temperature gradient of the bottom cylinder, m is the brass cylinders’ mass, and Cp is the brass

heat capacity.

𝑄 = (𝑘𝐴𝑑𝑇

𝑑𝑥)𝑡=𝑡𝑎

= (𝑚𝐶𝑝𝑑𝑇

𝑑𝑡)𝑡=𝑡𝑏

(2)

In the first measurement stage, the foil heater power is fixed. At time ta a steady-state is reached, and the

temperatures of the top and bottom cylinder are probed, from which dT/dx, was derived. In the second measurement

stage, the top brass cylinder was replaced by a cylinder of low-conductivity material. Subsequently, the power was

increased by extra heater power up to a pre-determined temperature, and then the temperature was decreased by

switching off the heater power. During the cooling process, the temporal temperature gradient, dT/dt, was probed at

time tb.

The equation above relies on the approach that both measurements were done at the same temperature. Therefore,

time tb was determined as the incidence where the cooling curve crossed the temperature as registered in the bottom

cylinder at time ta. A typical resulting temperature curve, with identification of measurement stages, is shown in Figure

13.

Figure 13 – A typical temperature progression of the Lees’ Disc Apparatus method is shown. The first black

dashed line represents time ta. The second dashed line represents time tb.

In Table 2 the results of the measurements with the Lees’ Disc Apparatus are shown. Two PCB samples and a

reference Teflon sample were measured. Again, the PCB samples have different copper composition and volume

percentage, which influence the through-plane conductivity. All samples were tested at a set of ambient temperatures:


9

40°C, 60°C and 80°C. However, the ambient temperature turns out to have negligible effect on the measured

conductivity. The light green PCB, given on the right in Figure 14, has a higher copper volume percentage, and

therefore higher through-plane conductivity, than the dark green PCB. The layer thickness and number of layers was

constant. The measurement of the Teflon reference sample resulted in a value conform with literature. The error in

the measurement of thermal conductivity of the PCB is estimated to be ±5%.

Figure 14 – Two circular PCB samples of which the

through-plane conductivity was measured.

Figure 15 – Lees’ Disc Apparatus setup during

first measurement stage. The PCB-sample is

clamped between brass cylinders.

Sample Temperature k [W/mK]

Teflon 80°C 0.229

Teflon 60°C 0.228

Teflon 40°C 0.237

Dark green PCB 80°C 0.373



Light green PCB 80°C 0.464



Table 2 – Overview of test results of PCB

through-plane conductivity.

VI. Correlation between testing and simulations

The correlation between testing and simulation is based on minimizing the Root Mean Square (RMS) error of a

set of nodes in the ESATAN-TMS model. Each of these nodes was chosen based on a mapping between the simulation

geometry and the thermocouples in the test setup. During the tests 13 thermocouples were monitored, resulting in 13

mapped correlation locations.

The RMS error served as a metric of the discrepancy between thermal testing results and simulation result, as

described by ecorr in equation (3). Here, a summation over the squared differences between the simulation temperature

nodes and experimentally measured temperature nodes is averaged over all n locations (n=13), and thereafter rooted.

𝑒corr = √1

𝑛∑ (𝑇𝑖,sim − 𝑇𝑖,test)

2𝑛𝑖=1 (3)

This discrepancy between simulation temperature and experimentally measured temperature was reduced by an

iterative process of performing the ESATAN-TMS simulations, calculating the RMS error at each node, and

reconfiguring the ESATAN-TMS model accordingly. The used optimization model was the MATSuMoTo

optimization code9. A schematic overview of the process is given in Figure 16.


10

Figure 16 – Schematic overview of iterative process of improving model correlation.

In order to achieve a highly accurate resemblance between model and test results, several assumptions were made.

One of the assumptions was the symmetry among frame ribs, spacers, and panels, in terms of contact conductance,

conductivity and emissivity. Furthermore, isotropic materials were assumed, except for the PCB, whose directionality

has been experimentally assessed in section V.

Figure 17 – Progression from 2U CubeSat mechanical design to thermal simulation result.

In Figure 17 the progression from the test mechanical model towards a correlated thermal ESATAN-TMS

simulation model is shown. The achieved temperature accuracy between experimental results and simulation results

has maximum deviations of 10°C between nodes. This was achieved after optimizing the contact conductances at the

following interfaces: heater-PCB, PCB-spacer, spacer-spacer, spacer-rib, rib-rib, rib-panel, with results in the order of

105 W/m2K.

Improved accuracy can be obtained by better determination of the interfaces, in terms of for example contact

pressure and surface area. This will result in a more accurate estimation of the contact conductance a priori, which

helps determining the contact conductance by the optimization algorithm. Furthermore, emissivity remains a hard

parameter to measure and determine by correlation, which induces and uncertainty into the thermal mathematical

model. Lastly, more temperature sensors (i.e. more correlation locations), repeated measurements, and more heater

power conditions, will ultimately improve accuracy.


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VII. Conclusion

In this study, we successfully replicated a 2U CubeSat design in ESATAN-TMS, using the submodelling

procedure as discussed by Te Nijenhuis, Brouwer et al.1. Additionally, a test campaign was held in which a 2U CubeSat

was tested under several ambient and heat dissipation conditions. A second focus during the test campaign was

improving the parameter range of several thermal properties of the CubeSat assembly, by means of stand-alone tests.

Lastly, a correlation between thermal vacuum test results and ESATAN-TMS simulation results was performed,

resulting in an accuracy of 10°C between simulations and test results. This is our current modelling accuracy; however,

we are expecting higher accuracy correlation by increasing modelling experience.

The verification process as discussed in this paper is the starting point for the creation of a library of validated

submodels in ESATAN-TMS which can be used for thermal designs of CubeSats in the future. In the next phase of

the project the described framework will be used to validate several other thermal submodels, which eventually give

us a toolbox to thermally validate a full CubeSat model.

References 1Te Nijenhuis, A.K., Brouwer, H.S.B, Jonsson, M., Van Benthem, R.C., Bloem, E.A., Vollmuller, G.J., “Thermal Modelling

of CubeSats in ESATAN-TMS: A Modular Approach,” 49th International Conference on Environmental Systems (ICES), ICES-

2020-286, Lisbon, 2020; 2Brouwer, H.S.B., De Groot, Z., Van Gerner, H.J., Guo, J., “Solving the Thermal Challenge in Power-Dense CubeSats with

Water Heat Pipes,” 31st Annual AIAA/USU Conference on Small Satellites, Logan, Utah, 2017; 3Van Gerner, H.J., Brouwer, H.S.B., De Groot, Z., Guo, J., “Water-Filled Heat Pipes for CubeSat Thermal Control,” 19th

International Heat Pipe Conference and 13th International Heat Pipe Symposium, Pisa, Italy, 2018; 4Sawyer, S.E., Master Thesis, “Heat Storage and Management with Phase Change Material in CubeSats,”, Delft University of

Technology, 2020; 5Van Es, J., Van den Berg, T.H., Ganzeboom, T.V., Van Vliet, A., Brouwer, H.S.B., Elvik, S., “Mini Mechanically Pumped

Loop Modelling and Design for Standardized CubeSat Thermal Control,” 50th International Conference on Environmental Systems

(ICES), Lisbon, Portugal, 2021; 6Hager, P., Flecht, T., Janzer, K., Brouwer, H.S.B., Jonsson, M., Pérez, L.L., “Contact Conductance in Common CubeSat

Stacks,” 49th International Conference on Environmental Systems (ICES), Boston, Massachusetts, 2019; 7Sarvar, F., Poole, N.J., Witting, P.A., “PCB Glass-Fibre Laminates: Thermal Conductivity Measurements and Their Effect on

Simulation,” Journal of Electronic Materials, Vol. 19, No. 12, 1990; 8Koirala, L.R., PhD Thesis, “FTIR-Spectroscopic Measurement of Directional Spectral Emissivities of Microstructured

Surfaces,” Helmut-Schmidt University, Hamburg, 2004. 9Müller, J., “MATSuMoTo: The MATLAB Surrogate Model Toolbox For Computationally Expensive Black-Box Global

Optimization Problems,” ArXiv: 1404.4261, Cornell University, 2014.

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