Inverse Heat Transfer

Fundamentals and Applications

AvHelcio R.B. Orlande

Häftad, Engelska, 2025

Del i serien Heat Transfer

787 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

Inbunden

2 040 kr

E-bok

939 kr

E-bok

891 kr

Beskrivning

This book introduces the fundamental concepts of inverse heat transfer solutions and their applications for solving problems in convective, conductive, radiative, and multi-physics problems. Inverse Heat Transfer: Fundamentals and Applications, Second Edition includes techniques within the Bayesian framework of statistics for the solution of inverse problems. By modernizing the classic work of the late Professor M. Necati Özisik and adding new examples and problems, this new edition provides a powerful tool for instructors, researchers, and graduate students studying thermal-fluid systems and heat transfer.FEATURES Introduces the fundamental concepts of inverse heat transfer Presents in systematic fashion the basic steps of powerful inverse solution techniques Develops inverse techniques of parameter estimation, function estimation, and state estimation Applies these inverse techniques to the solution of practical inverse heat transfer problems Shows inverse techniques for conduction, convection, radiation, and multi-physics phenomenaM. Necati Özisik (1923–2008) retired in 1998 as Professor Emeritus of North Carolina State University’s Mechanical and Aerospace Engineering Department.Helcio R. B. Orlande is a Professor of Mechanical Engineering at the Federal University of Rio de Janeiro (UFRJ), where he was the Department Head from 2006 to 2007.

Produktinformation

Utgivningsdatum:2025-09-28
Mått:178 x 254 x 16 mm
Vikt:1 100 g
Format:Häftad
Språk:Engelska
Serie:Heat Transfer
Antal sidor:277
Upplaga:2
Förlag:Taylor & Francis Ltd
ISBN:9780367725266

Utforska kategorier

Mer om författaren

M. Necati Özisik (1923–2008) retired in 1998 as Professor Emeritus of North Carolina State University’s Mechanical and Aerospace Engineering Department, where he spent most of his academic career. Professor Özisik dedicated his life to education and research in heat transfer. His outstanding contributions earned him numerous awards, including the Outstanding Engineering Educator Award from the American Society for Engineering Education in 1992. He authored eleven books, many of which were published in different languages.Helcio R. B. Orlande earned a BS in mechanical engineering at the Federal University of Rio de Janeiro (UFRJ) in 1987 and an MS in mechanical engineering from the same university in 1989. After earning a PhD in mechanical engineering in 1993 at North Carolina State University, he joined the Department of Mechanical Engineering of UFRJ, where he was the Department Head from 2006 to 2007. His research areas of interest include the solution of inverse heat and mass transfer problems as well as the use of numerical, analytical and hybrid numerical-analytical methods of solution of direct heat and mass transfer problems. He is a member of the Scientific Council of the International Centre for Heat and Mass Transfer and a Delegate in the Assembly for International Heat Transfer Conferences. He serves as an Associate Editor for the journals Heat Transfer Engineering, Inverse Problems in Science and Engineering, High Temperatures – High Pressures and International Journal of Thermal Sciences.

Innehållsförteckning

Part I: Introduction and Parameter Estimation 1. Basic Concepts 2. Parameter Estimation: Minimization of an Objective Function without Prior Information about the Unknown Parameters 3. Parameter Estimation: Minimization of an Objective Function with Prior Information about the Unknown Parameters 4. Parameter Estimation: Stochastic Simulation with Prior Information about the Unknown Parameters Part II: Function Estimation 5. Function Estimation: Minimization of an Objective Functional without Prior Information about the Unknown Functions 6. Function Estimation: Solution within the Bayesian Framework of Statistics with Prior Information about the Unknown Functions Part III: State Estimation 7. State Estimation: Kalman Filter 8. State Estimation: Particle Filter