Inverse Engineering Handbook, second edition, is a comprehensive resource which details methods of determining a ‘cause’ from an observed ‘effect’, allowing readers to understand, implement, and benefit from a variety of problem-solving techniques.
Leading experts in inverse problems have joined forces to produce a new edition of the definitive reference that allows readers to understand, implement, and benefit from a variety of problem-solving techniques.The focus of most of the work in this new edition is on parabolic and elliptic problems typified by transient and steady-state heat conduction; however, the scope of application extends to any mathematically similar problems (in chemical transport, mass transfer, etc.) As well as revision to existing chapters, this second edition includes four new chapters: a new chapter on the classis Tikhonov regularization technique, a new chapter on the topic of filter coefficient concepts for linear problems, a chapter dedicated to Bayesian solution of inverse problems, and finally a new chapter on machine learning and artificial intelligence.Anyone interested in inverse problems, regardless of their specialty, will find the Inverse Engineering Handbook to be a unique and invaluable compendium of up-to-date techniques.
1. Inverse Problems and Parameter Estimation: Integration of
Measurements and Analysis 2. Matrix Analysis for Parameter
Estimation 3. Sequential Function Specification Method
4. Tikhonov
Regularization and Optimal Regularization
5. Filter Coefficients Approach for
Solving Inverse Heat Conduction Problems 6. Adjoint Method Primer
7. The
Iterative Regularization Technique Based on the Conjugate Gradient Method
with Adjoint Problem Formulation
8. The Effect of Correlations and Uncertain
Parameters on the Efficiency of Estimating and the Precision of Estimated
Parameters
9. Estimation of Parameters or Functions after Analysis of
Experimental Uncertainties
10. Statistical Inference and Bayesian Analysis
11. Machine Learning and AI for Inverse Problems
12. Mollification and Space
Marching
13. Inverse Heat Conduction Using Monte Carlo Method
14. Optimal
Experiment Design to Solve Inverse Heat Transfer Problems
Keith A. Woodbury is Professor Emeritus in Mechanical Engineering at The University of Alabama, USA. He holds BS and MS degrees in Mechanical Engineering from The University of Alabama and earned his PhD in Mechanical Engineering at Virginia Polytechnic Institute and State University (Virginia Tech) in 1984. From 1984 to 1988, Dr. Woodbury conducted research for Reynolds Aluminum in the Metallurgical Research Division, focusing primarily on thermal challenges in ingot production and hot rolling operations. He joined the faculty at the University of Alabama in 1988 and retired from active faculty after 33 years in 2021. He is a Fellow of the ASME and served as associate editor of Inverse Problems in Science and Engineering. Dr. Woodbury authored over 100 articles and 2 books, contributed 14 book chapters, and organized or co-organized countless sessions, symposia, and international conferences on inverse problems since 1990.
