Melvan Tan Kian Hao: Density-Based Topology Optimization for Thermal-Fluid Systems, Gebunden

Klappentext

This comprehensive guide for researchers and advanced graduate students presents density-based topology optimization methods for thermal-fluid systems, covering fundamental theory, numerical implementation, methodological improvements, practical applications and additive manufacturing.

The book systematically develops the mathematical foundations of topology optimization, including filtering, projection, interpolation, governing equations, adjoint sensitivity analysis, and optimization algorithms. These concepts are illustrated through a wide range of case studies spanning thermal conduction, fluid flow, and coupled thermal-fluid problems under forced and natural convection in both 2D and 3D configurations. Beyond classical formulations, the book places strong emphasis on method development and engineering applicability. Advanced strategies such as pseudo-3D modelling and reduced-order initialization methods are introduced to address the high computational cost of large-scale optimization. The performance and reliability of topology-optimized designs are further validated through numerical simulations and experimental studies of heat sinks, cold plates, and hybrid cooling systems, including system-level demonstrations. A dedicated section on additive manufacturing discusses fabrication processes, design constraints, and testing methods, highlighting the critical link between topology optimization and physical realization. This book equips readers with the tools to design high-performance thermal systems, develop efficient optimization workflows, and translate optimized concepts into manufacturable solutions.

Graduate students, researchers, and engineers in mechanical engineering, heat transfer, fluid mechanics, computational optimization, and thermal management will benefit from this content and approach, as will practitioners working in electronics cooling, data centers, and advanced manufacturing.