Optimal parameters identification and sensitivity study for abrasive waterjet milling model

DOI10.1080/17415977.2016.1273916zbMath1444.35161arXiv1605.08583OpenAlexW2963975238MaRDI QIDQ4638141

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Publication date: 3 May 2018

Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.08583

zbMATH Keywords

inverse problemsautomatic differentiationTikhonov regularizationnumerical analysisPDE constrained optimizationparameters estimationabrasive waterjet

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Ill-posed problems for PDEs (35R25) Inverse problems for PDEs (35R30) Dependence of solutions to PDEs on initial and/or boundary data and/or on parameters of PDEs (35B30) Optimality conditions (49K99) PDEs in connection with control and optimization (35Q93)

Related Items (2)

Sensitivity studies and parameters identification for noisy 3D moving AWJM model ⋮ AutoMat: automatic differentiation for generalized standard materials on GPUs

Uses Software

• L-BFGS
• TAPENADE

Cites Work

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• Lavrentiev regularization of nonlinear ill-posed problems
• Some numerical experiments with variable-storage quasi-Newton algorithms
• On the limited memory BFGS method for large scale optimization
• Iterative regularization methods for nonlinear ill-posed problems
• Numerical models for differential problems. Translated by Silvia Quarteroni.
• The Tapenade automatic differentiation tool
• The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems
• Inverse Problem Theory and Methods for Model Parameter Estimation
• Stochastic simplified modelling of abrasive waterjet footprints
• Use of the regularization method in non-linear problems

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