The second edition of Inverse Engineering Handbook includes seven new chapters and two heavily revised chapters. Four older legacy chapters are also retained.
| Chapter 1: Inverse Problems and Parameter Estimation | This often-cited article is reproduced from Measurement Science and Technology (1997) and serves as a great introduction to the Handbook |
| Chapter 2: Parameter Estimation | This chapter is a revision of Chapter 5 of Parameter Estimation in Engineering and Science by J. V. Beck and K. Arnold. Prof. Beck revised the chapter significantly over several years and the resulting text has never been published. |
| Chapter 3: Sequential Function Specification Methods | Revised and updated from the first edition and includes polynomial function assumptions beyond constant and linear. |
| Chapter 4: Tikhonov Regularization and Optimal Regularization | A new chapter and comprehensive treatment of the subject with attention paid to proper degree of regularization. |
| Chapter 5: Filter Coefficient Concepts | This new chapter on filter coefficient concepts addresses problems of multi-layers and multiple dimensions which can be solved in a near-real-time manner. |
| Chapter 6: Adjoint Method | Heavily revised and updated by Helcio R. B. Orlande. |
| Chapter 7: Effect of Correlations on Uncertain Parameters | A legacy chapter on the impact of correlations in data and models on estimates by Ashley Emery (1934-2024). |
| Chapter 8: Experimental Uncertainties in Parameter or Function Estimation | This new chapter offers insights drawn from experiments into the effects of measurement errors on estimations. |
| Chapter 9: Statistical Inference and Bayesian Analysis | This important new chapter provides a lucid presentation of statistical estimation methods. |
| Chapter 10: Machine Learning and AI for Inverse Problems | A new chapter on emerging machine learning and AI methods. |
| Chapter 11: Mollification and Space Marching | This legacy chapter is the ultimate resource for the mollification method. |
| Chapter 12: Monte Carlo Methods | A legacy chapter on random walks in heat conduction problems. |
| Chapter 13: Boundary Element Techniques | A legacy chapter on application of BEM to thermal and fluid problems. |
| Chapter 14: Optimal Experiments | An updated chapter on designing experiments to maximize information needed for parameter estimation and inverse problems. |