Hybrid Genetic Optimization for IC Chips Thermal Control: With MATLAB® Applications: Advances in Metaheuristics
Autor Mathew V. K., Tapano Kumar Hottaen Limba Engleză Paperback – 8 oct 2024
Hybrid Genetic Optimization for IC Chips Thermal Control: With MATLAB® Applications focuses on the detailed optimization strategy carried out to enhance the performance (temperature control) of the IC chips oriented at different positions on a switch-mode power supply (SMPS) board and cooled using air under various heat transfer modes. Seven asymmetric protruding IC chips mounted at different positions on an SMPS board are considered in the present study that is supplied with non-uniform heat fluxes.
Key Features:
- Provides guidance on performance enhancement and reliability of IC chips
- Provides a detailed hybrid optimization strategy for the optimal arrangement of IC chips on a board
- The MATLAB program for the hybrid optimization strategy along with its stability analysis is carried out in a detailed manner
- Enables thermal design engineers to identify the positioning of IC chips on the board to increase their reliability and working cycle
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Specificații
ISBN-13: 9781032036854
ISBN-10: 1032036850
Pagini: 174
Ilustrații: 160
Dimensiuni: 156 x 234 mm
Greutate: 0.32 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Advances in Metaheuristics
Locul publicării:Boca Raton, United States
ISBN-10: 1032036850
Pagini: 174
Ilustrații: 160
Dimensiuni: 156 x 234 mm
Greutate: 0.32 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Advances in Metaheuristics
Locul publicării:Boca Raton, United States
Public țintă
Academic, Postgraduate, Professional, and Undergraduate AdvancedCuprins
ACKNOWLEDGEMENT
NOMENCLATURE
ABBREVIATIONS
CHAPTER 1
INTRODUCTION
1.1 Need for electronic cooling
1.2 Printed circuit board (PCB) and Integrated circuit (IC) chips
1.3 Various cooling techniques
1.3.1 Air cooling
1.3.2 Phase change material based cooling
1.4 Optimization in heat transfer
CHAPTER 2
STATE OF THE ART STUDIES IN ELECTRONIC COOLING
2.1 Introduction
2.2 Studies pertaining to cooling of discrete IC chips
2.2.1 Studies relevant to Natural convection
2.2.2 Studies relevant to forced and mixed convection cooling of discrete IC chips
2.2.3 Studies pertaining to the phase change material (PCM) based cooling of discrete IC chips
2.3 Summary of the literature survey
2.4 Scope for development
2.5 Different parameters considered for the study
CHAPTER 3
EXPERIMENTAL FACILITY
3.1 Introduction
3.2 Selection of the IC chips and the SMPS board
3.3 Design of the IC chip and SMPS Board
3.3.1 Design of IC Chips
3.3.2 Design of the SMPS (Substrate) board
3.3.2.1 Substrate board design to carry out the laminar forced convection experiments
3.3.2.2 Substrate board design to carry out the experiments using the PCM filled mini-channels
3.4 Experimental setup and Instrumentation
3.4.1 Instruments used for the experimental analysis
3.4.1.1 DC power source
3.4.1.2 Hot wire anemometer
3.4.1.3 Temperature data-logger
3.4.1.4 Digital multimeter
3.4.1.5 Kapton tape
3.5 Experimental methodology
3.5.1 Procedure for conducting laminar forced convection steady-state experiments
3.5.2 Procedure for conducting transient experiments on the PCM filled mini-channels under the natural convection
3.6 Experimental calculations
3.6.1 Experimental calculations under laminar forced convection heat transfer mode
3.6.2 Experimental calculations for the PCM filled mini-channels under the natural convection heat transfer mode
3.7 Error analysis
CHAPTER 4
HYBRID OPTIMIZATION STRATEGY FOR THE ARRANGEMENT OF IC CHIPS UNDER THE MIXED CONVECTION
4.1 Introduction
4.2 Non-dimensional geometrics distance parameter (λ)
4.3 Numerical framework
4.3.1 Governing equations
4.3.2 Boundary conditions
4.3.3 Grid independence study
4.4 Results and discussion
4.4.1 Maximum temperature excess variation of different configurations with λ
4.4.2 Temperature variation for the IC chips of the lower (λ = 0.25103) and the upper extreme (λ = 1.87025) configurations
4.4.3 Empirical correlation
4.5 Hybrid optimization strategy
4.5.1 Artificial neural network (ANN)
4.5.2 Genetic algorithm (GA)
4.5.3 Combination of ANN and GA
4.6 Conclusions
CHAPTER 5
HYBRID OPTIMIZATION STRATEGY TO STUDY THE SUBSTRATE BOARD ORIENTATION EFFECT FOR THE COOLING OF THE IC CHIPS UNDER FORCED CONVECTION
5.1 Introduction.
5.2 Different IC chips combinations considered for the experimentation
5.3 Results and discussion
5.3.1 Temperature variation of the IC chips for different substrate board orientations
5.3.2 Temperature variation of IC chips for different air velocities
5.3.3 Maximum temperature variation of the configurations for different substrate board orientations
5.3.4 Variation of maximum heat transfer coefficient of the configurations for different substrate board orientations
5.4 Empirical Correlation
5.4.1 Correlation for θ in terms of λ
5.4.2 Correlation for θi in terms of the IC chip positions on the substrate board (Z), non-dimensional board orientation (φ) and IC chip sizes (S)
5.4.3 Correlation for Nusselt number of the IC chips in terms of fluid Reynolds number and IC chip’s size
5.5 Hybrid optimization strategy to identify the optimal board orientation and optimal configuration of the IC chips
5.5.1 Artificial Neural Network
5.5.2 Genetic algorithm
5.5.3 Combination of ANN and GA
5.6 Numerical investigation for the cooling of the seven asymmetric IC chips under the laminar forced convection
5.6.1 Computational model with governing equations
5.6.2 Boundary conditions
5.6.3 Mesh independence study
5.7 Numerical analysis for the IC chip’s temperature under the different substrate board orientations
5.8 Conclusions
CHAPTER 6
NUMERICAL AND EXPERIMENTAL INVESTIGATIONS OF PARAFFIN WAX-BASED MINI-CHANNELS FOR THE COOLING OF IC CHIPS.
6.1 Introduction
6.2 Experiment set-up
6.3 Results and discussion
6.3.1 Temperature variation of IC chips without PCM based mini-channels (WPMC)
6.3.2 Temperature variation of IC chips for case 1 with and without the PCM based mini-channels
6.3.3 Temperature variation of IC chips for case 4 with and without the PCM based mini-channels
6.3.4 Temperature variation of IC chips for all cases with PCM based mini-channels (PMC)
6.3.5 Convective heat transfer coefficient variation for all cases with PCM based mini- channels (PMC)
6.3.6 Correlation
6.4 Numerical simulation of PCM based mini-channels under natural convection
6.5 Conclusions
CHAPTER 7
CONCLUSIONS AND SCOPE FOR FUTURE WORK
7.1 Introduction
7.2 Major conclusions of the present study
7.3 Scope for future work
REFERENCES
Appendix A
MATLAB programme for generating all the possible configurations for the arrangement of 7 non-identical rectangular IC chips on a substrate board.
Appendix B
Calculation of Mixed convection considered for numerical study
Appendix C
Sample calculation for non-dimensional temperature (θ) and Fourier number (Fo)
Index
NOMENCLATURE
ABBREVIATIONS
CHAPTER 1
INTRODUCTION
1.1 Need for electronic cooling
1.2 Printed circuit board (PCB) and Integrated circuit (IC) chips
1.3 Various cooling techniques
1.3.1 Air cooling
1.3.2 Phase change material based cooling
1.4 Optimization in heat transfer
CHAPTER 2
STATE OF THE ART STUDIES IN ELECTRONIC COOLING
2.1 Introduction
2.2 Studies pertaining to cooling of discrete IC chips
2.2.1 Studies relevant to Natural convection
2.2.2 Studies relevant to forced and mixed convection cooling of discrete IC chips
2.2.3 Studies pertaining to the phase change material (PCM) based cooling of discrete IC chips
2.3 Summary of the literature survey
2.4 Scope for development
2.5 Different parameters considered for the study
CHAPTER 3
EXPERIMENTAL FACILITY
3.1 Introduction
3.2 Selection of the IC chips and the SMPS board
3.3 Design of the IC chip and SMPS Board
3.3.1 Design of IC Chips
3.3.2 Design of the SMPS (Substrate) board
3.3.2.1 Substrate board design to carry out the laminar forced convection experiments
3.3.2.2 Substrate board design to carry out the experiments using the PCM filled mini-channels
3.4 Experimental setup and Instrumentation
3.4.1 Instruments used for the experimental analysis
3.4.1.1 DC power source
3.4.1.2 Hot wire anemometer
3.4.1.3 Temperature data-logger
3.4.1.4 Digital multimeter
3.4.1.5 Kapton tape
3.5 Experimental methodology
3.5.1 Procedure for conducting laminar forced convection steady-state experiments
3.5.2 Procedure for conducting transient experiments on the PCM filled mini-channels under the natural convection
3.6 Experimental calculations
3.6.1 Experimental calculations under laminar forced convection heat transfer mode
3.6.2 Experimental calculations for the PCM filled mini-channels under the natural convection heat transfer mode
3.7 Error analysis
CHAPTER 4
HYBRID OPTIMIZATION STRATEGY FOR THE ARRANGEMENT OF IC CHIPS UNDER THE MIXED CONVECTION
4.1 Introduction
4.2 Non-dimensional geometrics distance parameter (λ)
4.3 Numerical framework
4.3.1 Governing equations
4.3.2 Boundary conditions
4.3.3 Grid independence study
4.4 Results and discussion
4.4.1 Maximum temperature excess variation of different configurations with λ
4.4.2 Temperature variation for the IC chips of the lower (λ = 0.25103) and the upper extreme (λ = 1.87025) configurations
4.4.3 Empirical correlation
4.5 Hybrid optimization strategy
4.5.1 Artificial neural network (ANN)
4.5.2 Genetic algorithm (GA)
4.5.3 Combination of ANN and GA
4.6 Conclusions
CHAPTER 5
HYBRID OPTIMIZATION STRATEGY TO STUDY THE SUBSTRATE BOARD ORIENTATION EFFECT FOR THE COOLING OF THE IC CHIPS UNDER FORCED CONVECTION
5.1 Introduction.
5.2 Different IC chips combinations considered for the experimentation
5.3 Results and discussion
5.3.1 Temperature variation of the IC chips for different substrate board orientations
5.3.2 Temperature variation of IC chips for different air velocities
5.3.3 Maximum temperature variation of the configurations for different substrate board orientations
5.3.4 Variation of maximum heat transfer coefficient of the configurations for different substrate board orientations
5.4 Empirical Correlation
5.4.1 Correlation for θ in terms of λ
5.4.2 Correlation for θi in terms of the IC chip positions on the substrate board (Z), non-dimensional board orientation (φ) and IC chip sizes (S)
5.4.3 Correlation for Nusselt number of the IC chips in terms of fluid Reynolds number and IC chip’s size
5.5 Hybrid optimization strategy to identify the optimal board orientation and optimal configuration of the IC chips
5.5.1 Artificial Neural Network
5.5.2 Genetic algorithm
5.5.3 Combination of ANN and GA
5.6 Numerical investigation for the cooling of the seven asymmetric IC chips under the laminar forced convection
5.6.1 Computational model with governing equations
5.6.2 Boundary conditions
5.6.3 Mesh independence study
5.7 Numerical analysis for the IC chip’s temperature under the different substrate board orientations
5.8 Conclusions
CHAPTER 6
NUMERICAL AND EXPERIMENTAL INVESTIGATIONS OF PARAFFIN WAX-BASED MINI-CHANNELS FOR THE COOLING OF IC CHIPS.
6.1 Introduction
6.2 Experiment set-up
6.3 Results and discussion
6.3.1 Temperature variation of IC chips without PCM based mini-channels (WPMC)
6.3.2 Temperature variation of IC chips for case 1 with and without the PCM based mini-channels
6.3.3 Temperature variation of IC chips for case 4 with and without the PCM based mini-channels
6.3.4 Temperature variation of IC chips for all cases with PCM based mini-channels (PMC)
6.3.5 Convective heat transfer coefficient variation for all cases with PCM based mini- channels (PMC)
6.3.6 Correlation
6.4 Numerical simulation of PCM based mini-channels under natural convection
6.5 Conclusions
CHAPTER 7
CONCLUSIONS AND SCOPE FOR FUTURE WORK
7.1 Introduction
7.2 Major conclusions of the present study
7.3 Scope for future work
REFERENCES
Appendix A
MATLAB programme for generating all the possible configurations for the arrangement of 7 non-identical rectangular IC chips on a substrate board.
Appendix B
Calculation of Mixed convection considered for numerical study
Appendix C
Sample calculation for non-dimensional temperature (θ) and Fourier number (Fo)
Index
Notă biografică
Dr. Mathew V. K. holds a Ph.D. degree in Thermal Management Systems from Vellore Institute of Technology, Vellore, India; M.Tech in Heat Power from the University of Pune, India. He is working in the field of heat transfer enhancement using active and passive cooling. His research interest includes Active and passive safety, Crash energy management, Battery thermal management system, Computational fluid dynamics, Heat transfer, Numerical methods, Optimization using different algorithms (Genetic algorithm, Artificial neural network), and proficient in Experimental techniques.
Dr. Tapano Kumar Hotta is currently working as an Associate Professor in the School of Mechanical Engineering, VIT Vellore, India. He has a Ph.D. degree in Mechanical Engineering from IIT Madras in the area of Electronic cooling. His area of research in a broad sense includes; Active and passive cooling of electronic devices, Heat transfer enhancement, Optimization of thermal systems, Thermal comfort modeling, etc. Dr. Hotta has about 13 years of teaching cum research experience and has around 40 publications to his credit in journals and conferences of international repute. He has guided more than 30 undergraduates, a dozen of postgraduates, and 2 doctorate students for their project work. He has also published 2 patents. He is a member of the editorial board and reviewer for various international journals and conferences related to heat transfer.
Dr. Tapano Kumar Hotta is currently working as an Associate Professor in the School of Mechanical Engineering, VIT Vellore, India. He has a Ph.D. degree in Mechanical Engineering from IIT Madras in the area of Electronic cooling. His area of research in a broad sense includes; Active and passive cooling of electronic devices, Heat transfer enhancement, Optimization of thermal systems, Thermal comfort modeling, etc. Dr. Hotta has about 13 years of teaching cum research experience and has around 40 publications to his credit in journals and conferences of international repute. He has guided more than 30 undergraduates, a dozen of postgraduates, and 2 doctorate students for their project work. He has also published 2 patents. He is a member of the editorial board and reviewer for various international journals and conferences related to heat transfer.
Descriere
Hybrid Genetic Optimization for IC Chip Thermal Control: with MATLAB® applications focuses on the detailed optimization strategy carried out to enhance the performance (temperature control) of the IC chips oriented at different positions on an SMPS board (Switch mode power supply) and cooled using air under various heat transfer modes.