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Sinopsis
Unlock the true potential of advanced thermal modeling and simulation with a comprehensive, code‐driven guide that propels you beyond the basics! Designed for engineers, researchers, and graduate students, this resource transforms complex thermodynamic and heat transfer challenges into manageable, Matlab-coded solutions. Dive into dozens of in‐depth chapters where every concept is paired with full Matlab code examples that let you:
• Solve Nonlinear State Equations: Master numerical root-finding algorithms that crack the complexity of equations of state like van der Waals and Redlich-Kwong.
• Implement Finite Difference and Volume Methods: Build robust simulations for 1D to multi-dimensional heat conduction challenges.
• Model Conjugate Heat Transfer: Seamlessly couple fluid and solid thermal domains for realistic energy exchange simulations.
• Simulate Thermal Cycles: Code complete Brayton, Rankine, Otto, and Diesel cycles for enhanced system performance insights.
• Optimize Thermal Designs: Leverage Matlab’s optimization, neural networks, and genetic algorithms to fine-tune heat exchanger networks and energy systems.
• Integrate Symbolic and Numerical Techniques: Simplify and solve intricate radiative heat transfer and energy balance equations with advanced symbolic-numerical integration.
• Automate Parameter Sweeps and Sensitivity Analyses: Execute comprehensive simulations that explore the full design space, ensuring your models are both precise and robust.
Every example in this hands-on guide is meticulously engineered to bridge theory with practical application—empowering you to transform abstract equations into operational, high-precision code. Whether you’re refining forced or natural convection models, constructing thermal resistance networks, or embarking on full-cycle thermal simulations, you’ll find the cutting-edge tools you need to succeed.
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MATLAB Fundamentals for Thermodynamics and Heat Transfer (Paperback)
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Paperback. Condición: new. Paperback. Unlock the true potential of advanced thermal modeling and simulation with a comprehensive, codedriven guide that propels you beyond the basics! Designed for engineers, researchers, and graduate students, this resource transforms complex thermodynamic and heat transfer challenges into manageable, Matlab-coded solutions. Dive into dozens of indepth chapters where every concept is paired with full Matlab code examples that let you: - Solve Nonlinear State Equations: Master numerical root-finding algorithms that crack the complexity of equations of state like van der Waals and Redlich-Kwong.- Implement Finite Difference and Volume Methods: Build robust simulations for 1D to multi-dimensional heat conduction challenges.- Model Conjugate Heat Transfer: Seamlessly couple fluid and solid thermal domains for realistic energy exchange simulations.- Simulate Thermal Cycles: Code complete Brayton, Rankine, Otto, and Diesel cycles for enhanced system performance insights.- Optimize Thermal Designs: Leverage Matlab's optimization, neural networks, and genetic algorithms to fine-tune heat exchanger networks and energy systems.- Integrate Symbolic and Numerical Techniques: Simplify and solve intricate radiative heat transfer and energy balance equations with advanced symbolic-numerical integration.- Automate Parameter Sweeps and Sensitivity Analyses: Execute comprehensive simulations that explore the full design space, ensuring your models are both precise and robust. Every example in this hands-on guide is meticulously engineered to bridge theory with practical application-empowering you to transform abstract equations into operational, high-precision code. Whether you're refining forced or natural convection models, constructing thermal resistance networks, or embarking on full-cycle thermal simulations, you'll find the cutting-edge tools you need to succeed. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798313020105
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MATLAB Fundamentals for Thermodynamics and Heat Transfer (Paperback)
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