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Abstract

High power density systems require efficient cooling to maintain their thermal performance. Despite this, as systems get larger and more complex, human expertise and insight may not suffice to determine the desired thermal management system designs. To this end, a framework for automatic architecture exploration is presented in this article for a class of single-phase, multi-split cooling systems. For this class of systems, heat generation devices are clustered based on their spatial information, and flow splits are added only when required and at the location of heat devices. To generate different architectures, candidate architectures are represented as graphs. From these graphs, dynamic physics models are created automatically using a graph-based thermal modeling framework. Then, an optimal fluid flow distribution problem is solved by addressing temperature constraints in the presence of exogenous heat loads to achieve optimal performance. The focus in this work is on the design of general multi-split heat management systems. The methods presented here can be used for diverse applications in the domain of configuration design. The multi-split algorithm can produce configurations where splitting can occur at any of the vertices. The results presented include three categories of problems and are discussed in detail.

References

1.
Rootzén
,
J.
,
Wiertzema
,
H.
,
Brolin
,
M.
, and
Fahnestock
,
J.
,
2020
, “
Electrify Everything! Challenges and Opportunities Associated with Increased Electrification of Industrial Processes
,”
Eceee Industry Proceedings
,
Gothenburg, Sweden
.
2.
El-Refaie
,
A. M.
,
2016
, “
Growing Role of Electrical Machines and Drives in Electrification
,”
XXII International Conference on Electrical Machines (ICEM)
,
Lausanne, Switzerland,
,
Sept. 4–7
, pp.
364
370
.
3.
Nadel
,
S. M.
,
2019
, “
Electrification in the Transportation, Buildings, and Industrial Sectors: A Review of Opportunities, Barriers, and Policies
,”
Curr. Sustainable/Renewable Energy Rep.
,
6
(
4
), pp.
158
168
.
4.
Mathew
,
J.
, and
Krishnan
,
S.
,
2022
, “
A Review on Transient Thermal Management of Electronic Devices
,”
ASME J. Electron. Packag.
,
144
(
1
), p.
010801
.
5.
Bayat
,
S.
,
Nejat Pishkenari
,
H.
, and
Salarieh
,
H.
,
2021
, “
Observation of Stage Position in a 2-Axis Nano-positioner Using Hybrid Kalman Filter
,”
Sci. Iran.
,
28
(
5
), pp.
2628
2638
.
6.
Smoyer
,
J. L.
, and
Norris
,
P. M.
,
2019
, “
Brief Historical Perspective in Thermal Management and the Shift Toward Management at the Nanoscale
,”
Heat. Transfer. Eng.
,
40
(
3–4
), pp.
269
282
.
7.
Wong
,
H.-S. P.
,
Akarvardar
,
K.
,
Antoniadis
,
D.
,
Bokor
,
J.
,
Hu
,
C.
,
King-Liu
,
T.-J.
,
Mitra
,
S.
,
Plummer
,
J. D.
, and
Salahuddin
,
S.
,
2020
, “
A Density Metric for Semiconductor Technology [Point of View]
,”
Proc. IEEE
,
108
(
4
), pp.
478
482
.
8.
Bayat
,
S.
,
Pishkenari
,
H. N.
, and
Salarieh
,
H.
,
2019
, “
Observer Design for a Nano-Positioning System Using Neural, Fuzzy and Anfis Networks
,”
Mechatronics
,
59
, pp.
10
24
.
9.
Ye
,
P.
,
Ernst
,
T.
, and
Khare
,
M. V.
,
2019
, “
The Last Silicon Transistor: Nanosheet Devices Could Be the Final Evolutionary Step for Moore’s Law
,”
IEEE Spectr.
,
56
(
8
), pp.
30
35
.
10.
He
,
Z.
,
Yan
,
Y.
, and
Zhang
,
Z.
,
2020
, “
Thermal Management and Temperature Uniformity Enhancement of Electronic Devices by Micro Heat Sinks: A Review
,”
Energy
,
216
(
199
), p.
119223
.
11.
Almubarak
,
A. A.
,
2017
, “
The Effects of Heat on Electronic Components
,”
Int. J. Eng. Res. Appl.
,
7
(
5
), pp.
52
57
.
12.
Mathew
,
J.
, and
Krishnan
,
S.
,
2022
, “
A Review on Transient Thermal Management of Electronic Devices
,”
ASME J. Electron. Packag.
,
144
(
1
), p.
010801
.
13.
Feng
,
C.-P.
,
Chen
,
L.-B.
,
Tian
,
G.-L.
,
Wan
,
S.-S.
,
Bai
,
L.
,
Bao
,
R.
,
Liu
,
Z.
,
Yang
,
M.
, and
Yang
,
W.
,
2019
, “
Multifunctional Thermal Management Materials With Excellent Heat Dissipation and Generation Capability for Future Electronics.
,”
ACS. Appl. Mater. Interfaces.
,
11
(
20
), pp.
18739
18745
.
14.
Peddada
,
S. R.
,
Herber
,
D. R.
,
Pangborn
,
H. C.
,
Alleyne
,
A. G.
, and
Allison
,
J. T.
,
2019
, “
Optimal Flow Control and Single Split Architecture Exploration for Fluid-Based Thermal Management
,”
ASME J. Mech. Des.
,
141
(
8
), p.
083401
.
15.
Panjeshahi
,
M.
,
Ataei
,
A.
,
Gharaie
,
M.
, and
Parand
,
R.
,
2009
, “
Optimum Design of Cooling Water Systems for Energy and Water Conservation
,”
Chem. Eng. Res. Des.
,
87
(
2
), pp.
200
209
.
16.
Muller
,
C. J.
, and
Craig
,
I. K.
,
2016
, “
Energy Reduction for a Dual Circuit Cooling Water System Using Advanced Regulatory Control
,”
Appl. Energy.
,
171
, pp.
287
295
.
17.
Ling
,
L.
,
Zhang
,
Q.
,
Yu
,
Y.
, and
Shuguang
,
L.
,
2016
, “
Experimental Investigation on the Thermal Performance of Water Cooled Multi-split Heat Pipe System (MSHPS) for Space Cooling in Modular Data Centers
,”
Appl. Therm. Eng.
,
107
, pp.
591
601
.
18.
Pangborn
,
H. C.
,
Koeln
,
J. P.
,
Williams
,
M. A.
, and
Alleyne
,
A. G.
,
2018
, “
Experimental Validation of Graph-Based Hierarchical Control for Thermal Management
,”
ASME J. Dyn. Syst. Meas. Control.
,
140
(
10
), p.
101016
.
19.
Pangborn
,
H. C.
,
Koeln
,
J. P.
, and
Alleyne
,
A. G.
,
2018
, “
Passivity and Decentralized MPC of Switched Graph-Based Power Flow Systems
,”
Annual American Control Conference (ACC)
,
Milwaukee, WI
,
June 27–29
, IEEE, pp.
198
203
.
20.
Koeln
,
J. P.
,
Williams
,
M. A.
,
Pangborn
,
H. C.
, and
Alleyne
,
A. G.
,
2016
, “
Experimental Validation of Graph-Based Modeling for Thermal Fluid Power Flow Systems
,”
Proceedings of the ASME 2016 Dynamic Systems and Control Conference
,
Minneapolis, MN
,
Oct. 12–14
.
21.
Preisig
,
H. A.
,
2009
, “
A Graph-Theory-Based Approach to the Analysis of Large-Scale Plants
,”
Comput. Chem. Eng.
,
33
(
3
), pp.
598
604
.
22.
Bennett
,
G.
,
Elwell
,
C. A.
,
Lowe
,
R.
, and
Oreszczyn
,
T.
,
2016
, “
The Importance of Heating System Transient Response in Domestic Energy Labelling
,”
Buildings
,
6
(
2
), p.
29
.
23.
Allison
,
J. T.
, and
Herber
,
D. R.
,
2014
, “
Multidisciplinary Design Optimization of Dynamic Engineering Systems
,”
AIAA. J.
,
52
(
4
), pp.
691
710
.
24.
Allison
,
J. T.
,
Guo
,
T.
, and
Han
,
Z.
,
2014
, “
Co-design of an Active Suspension Using Simultaneous Dynamic Optimization
,”
ASME J. Mech. Des.
,
136
(
8
), p.
081003
.
25.
Garcia-Sanz
,
M.
,
2019
, “
Control Co-Design: An Engineering Game Changer
,”
Adv. Control Appl.: Eng. Ind. Syst.
,
1
(
1
), p.
e18
.
26.
Bayat
,
S.
, and
Allison
,
J. T.
,
2023
, “
Control Co-design With Varying Available Information Applied to Vehicle Suspensions
,”
Proceedings of the ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
,
Boston, MA
,
Aug. 20–23
.
27.
Herber
,
D. R.
,
Guo
,
T.
, and
Allison
,
J. T.
,
2017
, “
Enumeration of Architectures With Perfect Matchings
,”
ASME J. Mech. Des.
,
139
(
5
), p.
051403
.
28.
Herber
,
D. R.
, and
Allison
,
J. T.
,
2019
, “
A Problem Class With Combined Architecture, Plant, and Control Design Applied to Vehicle Suspensions
,”
ASME J. Mech. Des.
,
141
(
10
), p.
101401
.
29.
Peddada
,
S. R. T.
,
2023
, “
Automated Interference-Free Layout Generation Methods For2D Interconnected Engineering Systems
,” Technical Report.
30.
Allison
,
J. T.
,
Cardin
,
M. -A.
,
McComb
,
C.
,
Ren
,
M. Y.
,
Selva
,
D.
,
Tucker
,
C.
,
Witherell
,
P.
, and
Zhao
,
Y. F.
,
2022
, “
Artificial Intelligence and Engineering Design
,”
ASME J. Mech. Des.
,
144
(
2
), p.
020301
.
31.
Guo
,
T.
,
Herber
,
D.
, and
Allison
,
J. T.
,
2019
, “
Circuit Synthesis Using Generative Adversarial Networks (GANs)
,”
AIAA Scitech 2019 Forum
,
San Diego, CA
,
Jan. 7–11
, p.
2350
.
32.
Sloane
,
N. J.
,
2018
,
The On-Line Encyclopedia of Integer Sequences
.
33.
Athans
,
M.
, and
Falb
,
P. L.
,
2007
,
Optimal Control: An Introduction to the Theory and Its Applications
,
Courier Corporation
,
North Chelmsford, MA
.
34.
Patterson
,
M. A.
, and
Rao
,
A. V.
,
2014
, “
GPOPS-II: A Matlab Software for Solving Multiple-Phase Optimal Control Problems Using hp-Adaptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming
,”
ACM Trans. Math. Softw. (TOMS)
,
41
(
1
), pp.
1
37
.
35.
Bayat
,
S.
, and
Allison
,
J. T.
,
2023
, “
SS-MPC: A User-Friendly Software Based on Single Shooting Optimization to Solve Model Predictive Control Problems
,”
Softw. Impacts
,
17
, p.
100566
.
36.
Bayat
,
S.
, and
Allison
,
J. T.
,
2023
, “
LGR-MPC: A User-Friendly Software Based on Legendre-Gauss-Radau Pseudo Spectral Method for Solving Model Predictive Control Problems
,”
arXiv preprint
. https://arxiv.org/abs/2310.15960
37.
Gill
,
P. E.
,
Murray
,
W.
, and
Saunders
,
M. A.
,
2005
, “
Snopt: An SQP Algorithm for Large-Scale Constrained Optimization
,”
SIAM Rev.
,
47
(
1
), pp.
99
131
.
38.
Biegler
,
L. T.
, and
Zavala
,
V. M.
,
2009
, “
Large-Scale Nonlinear Programming Using Ipopt: An Integrating Framework for Enterprise-Wide Dynamic Optimization
,”
Comput. Chem. Eng.
,
33
(
3
), pp.
575
582
.
39.
Falck
,
R.
,
Gray
,
J. S.
,
Ponnapalli
,
K.
, and
Wright
,
T.
,
2021
, “
dymos: A Python Package for Optimal Control of Multidisciplinary Systems
,”
J. Open Sourc. Softw.
,
6
(
59
), p.
2809
.
40.
Bayat
,
S.
,
Shahmansouri
,
N.
,
Peddada
,
S. R.
,
Tessier
,
A.
,
Butscher
,
A.
, and
Allison
,
J. T.
,
2023
, “
Advancing Fluid-Based Thermal Management Systems Design: Leveraging Graph Neural Networks for Graph Regression and Efficient Enumeration Reduction
,”
arXiv preprint
https://arxiv.org/abs/2311.14874
41.
Bayat
,
S.
,
Shahmansouri
,
N.
,
Peddada
,
S. R.
,
Tessier
,
A.
,
Butscher
,
A.
, and
Allison
,
J. T.
,
2023
, “
Extracting Design Knowledge from Optimization Data:Enhancing Engineering Design in Fluid Based Thermal Management Systems
,”
arXiv preprint
. https://arxiv.org/abs/2310.16324
42.
Peddada
,
S. R. T.
,
Rodriguez
,
S. B.
,
James
,
K. A.
, and
Allison
,
J. T.
,
2020
, “
Automated Layout Generation Methods for 2D Spatial Packing
,”
International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
,
Virtual, Online
,
Aug. 17–19
.
43.
Peddada
,
S. R. T.
,
James
,
K. A.
, and
Allison
,
J. T.
,
2021
, “
A Novel Two-Stage Design Framework for Two-Dimensional Spatial Packing of Interconnected Components
,”
ASME J. Mech. Des.
,
143
(
3
), p.
031706
.
44.
Peddada
,
S.
,
Zeidner
,
L.
,
Ilies
,
H. T.
,
James
,
K.
, and
Allison
,
J. T.
,
2022
, “
Toward Holistic Design of Spatial Packaging of Interconnected Systems With Physical Interactions (spi2)
,”
ASME J. Mech. Des.
,
144
(
12
), p.
120801
.
45.
Peddada
,
S. R. T.
,
James
,
K. A.
, and
Allison
,
J. T.
,
2020
, “
A Novel Two-Stage Design Framework for 2D Spatial Packing of Interconnected Components
,”
Proceedings of the ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
,
Virtual Online
,
Aug. 17–19
.
46.
Peddada
,
S. R. T.
,
Dunfield
,
N. M.
,
Zeidner
,
L. E.
,
James
,
K. A.
, and
Allison
,
J. T.
,
2021
, “
Systematic Enumeration and Identification of Unique Spatial Topologies of 3D Systems Using Spatial Graph Representations
,”
Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
,
Virtual Online
,
Aug. 17–19
.
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