Introduction to research team
Preface
Nomenclature
Greek symbols
Subscripts
1．Introduction
1．1 Research background
1．2 Design process
1．3 Optimization algorithm
1．4 Classification of optimization problem
2．Modeling strategies for optimization
2．1 Modeling strategy based on finite concept
2．1．1 Introduction to research field
2．1．2 Analysis model
2．1．3 Development of analysis code suitable for preheating process
2．1．3．1 Radiative heat transfer
2．1．3．2 Convective heat transfer
2．1．3．3 Conductive heat transfer
2．1．4 Steady optimization for heater power distribution
2．1．5 Summary
2．2 Modeling strategy based on design of experiments
2．2．1 Introduction to research field
2．2．2 Numerical model and analysis conditions
2．2．3 Comparison of cases having porous material or not
2．2．4 Optimization strategy
2．2．4．1 Concept of Doptimal design
2．2．4．2 Optimization using DOE method
2．2．5 Summary
2．3 Modeling strategy based on analysis database
2．3．1 Introduction to research field
2．3．2 System setup and experimental method
2．3．3 Design of baseline vacuum furnace
2．3．3．1 Definition of shape
2．3．3．2 Comparison of cases nearly vacuum or argon gas
2．3．4 Construction of thermal analysis database
2．3．4．1 Thermal analysis of vacuum furnace
2．3．4．2 Calculation of thermal conductivity
2．3．4．3 Thermal analysis database
2．3．5 Optimal design strategy
2．3．5．1 Classification of problem
2．3．5．2 Process using thermal analysis database
2．3．6 Optimized results
2．3．6．1 Accuracy verification
2．3．6．2 Discussion of results
2．3．6．3 Feasible optimal design
2．3．7 Rebuilding of design method
2．3．8 Summary
2．4 Modeling strategy based on response surface method
2．4．1 Introduction to research field
2．4．2 Dynamic model for fuel cell
2．4．2．1 Cathode mass flow model
2．4．2．2 Anode mass flow model
2．4．2．3 Membrane hydration model
2．4．2．4 Stack voltage model
2．4．2．5 Cathode GDL model
2．4．2．6 Anode GDL model
2．4．3 Model calibration
2．4．4 Optimizatin design using RSM
2．4．4．1 Concept of response surface method
2．4．4．2 Construction of response surface
2．4．4．3 Optimal design with respnse surface
2．4．5 Summary
2．5 Modeling strategy based on analytic method
2．5．1 Optimization using analytic method
2．5．1．1 1-d analytic solution
2．5．1．2 Optimal strategy and results
2．5．2 Optimization using finite difference method
2．5．2．1 Classification of problem
2．5．2．2 Optimal results and discussion
2．5．3 Summary
3．Global optimization strategy
3．1 Global optimization strategy based on genetic algorithm
3．1．1 Construction of fitting function
3．1．2 Discussion of optimization results
3．1．3 Summary
3．2 Global optimization strategy based on DOE and GBM
3．2．1 Model descriptions
3．2．2 Time for obtaining steady state
3．2．3 Setup of fitting function
3．2．4 Global optimization
3．2．5 Summary
4．Multi-objective optimal strategy
4．1 Multi-objective strategy based on Benson method
4．1．1 Parameter study
4．1．2 Optimal strategy based on Benson method
4．1．3 Summary
4．2 Multi-objective strategy based on layered sequence method
4．2．1 Construction of fitting function
4．2．2 Multi-objective global optimization
4．2．3 Summary
4．3 Multi-objective strategy based on linear weighted method
4．3．1 Construction of response surface
4．3．2 Optimal design and discussion
4．3．3 Summary
4．4 Multi-objective strategy based on ideal point method
4．4．1 Optimal heater power distribution
4．4．2 Optimal design using ideal point method
4．4．2．1 Effect of a damaged heater
4．4．2．2 Optimal results and discussion
4．4．3 Summary
5．Conclusions
6．Acknowledgements
References
Index
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