@misc{GoetschelMaierhoferMuelleretal.2016, author = {G{\"o}tschel, Sebastian and Maierhofer, Christiane and M{\"u}ller, Jan P. and Rothbart, Nick and Weiser, Martin}, title = {Quantitative Defect Reconstruction in Active Thermography for Fiber-Reinforced Composites}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-58374}, year = {2016}, abstract = {Carbon-fiber reinforced composites are becoming more and more important in the production of light-weight structures, e.g., in the automotive and aerospace industry. Thermography is often used for non-destructive testing of these products, especially to detect delaminations between different layers of the composite. In this presentation, we aim at methods for defect reconstruction from thermographic measurements of such carbon-fiber reinforced composites. The reconstruction results shall not only allow to locate defects, but also give a quantitative characterization of the defect properties. We discuss the simulation of the measurement process using finite element methods, as well as the experimental validation on flat bottom holes. Especially in pulse thermography, thin boundary layers with steep temperature gradients occurring at the heated surface need to be resolved. Here we use the combination of a 1D analytical solution combined with numerical solution of the remaining defect equation. We use the simulations to identify material parameters from the measurements. Finally, fast heuristics for reconstructing defect geometries are applied to the acquired data, and compared for their accuracy and utility in detecting different defects like back surface defects or delaminations.}, language = {en} } @misc{GoetschelHoehneKolkoorietal.2016, author = {G{\"o}tschel, Sebastian and H{\"o}hne, Christian and Kolkoori, Sanjeevareddy and Mitzscherling, Steffen and Prager, Jens and Weiser, Martin}, title = {Ray Tracing Boundary Value Problems: Simulation and SAFT Reconstruction for Ultrasonic Testing}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-58386}, year = {2016}, abstract = {The application of advanced imaging techniques for the ultrasonic inspection of inhomogeneous anisotropic materials like austenitic and dissimilar welds requires information about acoustic wave propagation through the material, in particular travel times between two points in the material. Forward ray tracing is a popular approach to determine traveling paths and arrival times but is ill suited for inverse problems since a large number of rays have to be computed in order to arrive at prescribed end points. In this contribution we discuss boundary value problems for acoustic rays, where the ray path between two given points is determined by solving the eikonal equation. The implementation of such a two point boundary value ray tracer for sound field simulations through an austenitic weld is described and its efficiency as well as the obtained results are compared to those of a forward ray tracer. The results are validated by comparison with experimental results and commercially available UT simulation tools. As an application, we discuss an implementation of the method for SAFT (Synthetic Aperture Focusing Technique) reconstruction. The ray tracer calculates the required travel time through the anisotropic columnar grain structure of the austenitic weld. There, the formulation of ray tracing as a boundary value problem allows a straightforward derivation of the ray path from a given transducer position to any pixel in the reconstruction area and reduces the computational cost considerably.}, language = {en} } @book{Weiser2016, author = {Weiser, Martin}, title = {Inside Finite Elements}, publisher = {De Gruyter}, year = {2016}, abstract = {All relevant implementation aspects of finite element methods are discussed in this book. The focus is on algorithms and data structures as well as on their concrete implementation. Theory is covered as far as it gives insight into the construction of algorithms.Throughout the exercises a complete FE-solver for scalar 2D problems will be implemented in Matlab/Octave.}, language = {en} } @misc{VolkweinWeiser2000, author = {Volkwein, Stefan and Weiser, Martin}, title = {Affine Invariant Convergence Analysis for Inexact Augmented Lagrangian-SQP Methods}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6243}, number = {00-56}, year = {2000}, abstract = {An affine invariant convergence analysis for inexact augmented Lagrangian-SQP methods is presented. The theory is used for the construction of an accuracy matching between iteration errors and truncation errors, which arise from the inexact linear system solves. The theoretical investigations are illustrated numerically by an optimal control problem for the Burgers equation.}, language = {en} } @misc{WeiserDeuflhard2001, author = {Weiser, Martin and Deuflhard, Peter}, title = {The Central Path towards the Numerical Solution of Optimal Control Problems}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6380}, number = {01-12}, year = {2001}, abstract = {A new approach to the numerical solution of optimal control problems including control and state constraints is presented. Like hybrid methods, the approach aims at combining the advantages of direct and indirect methods. Unlike hybrid methods, however, our method is directly based on interior-point concepts in function space --- realized via an adaptive multilevel scheme applied to the complementarity formulation and numerical continuation along the central path. Existence of the central path and its continuation towards the solution point is analyzed in some theoretical detail. An adaptive stepsize control with respect to the duality gap parameter is worked out in the framework of affine invariant inexact Newton methods. Finally, the performance of a first version of our new type of algorithm is documented by the successful treatment of the well-known intricate windshear problem.}, language = {en} } @misc{Weiser2002, author = {Weiser, Martin}, title = {Linear convergence of an interior point method for linear control constrained optimal control problems}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6809}, number = {02-13}, year = {2002}, abstract = {The paper provides a detailed analysis of a short step interior point algorithm applied to linear control constrained optimal control problems. Using an affine invariant local norm and an inexact Newton corrector, the well-known convergence results from finite dimensional linear programming can be extended to the infinite dimensional setting of optimal control. The present work complements a recent paper of Weiser and Deuflhard, where convergence rates have not been derived. The choice of free parameters, i.e. the corrector accuracy and the number of corrector steps, is discussed.}, language = {en} } @misc{Weiser2007, author = {Weiser, Martin}, title = {Pointwise Nonlinear Scaling for Reaction-Diffusion-Equations}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10493}, number = {07-45}, year = {2007}, abstract = {Parabolic reaction-diffusion systems may develop sharp moving reaction fronts which pose a challenge even for adaptive finite element methods. We propose a method to transform the equation into an equivalent form that usually exhibits solutions which are easier to discretize, giving higher accuracy for a given number of degrees of freedom. The transformation is realized as an efficiently computable pointwise nonlinear scaling that is optimized for prototypical planar travelling wave solutions of the underlying reaction-diffusion equation. The gain in either performance or accuracy is demonstrated on different numerical examples.}, language = {en} } @misc{SchenkWaechterWeiser2007, author = {Schenk, Olaf and W{\"a}chter, Andreas and Weiser, Martin}, title = {Inertia Revealing Preconditioning For Large-Scale Nonconvex Constrained Optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10314}, number = {07-32}, year = {2007}, abstract = {Fast nonlinear programming methods following the all-at-once approach usually employ Newton's method for solving linearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, the Newton direction is only guaranteed to be a descent direction if the Hessian of the Lagrange function is positive definite on the nullspace of the active constraints, otherwise some modifications to Newton's method are necessary. This condition can be verified using the signs of the KKT's eigenvalues (inertia), which are usually available from direct solvers for the arising linear saddle point problems. Iterative solvers are mandatory for very large-scale problems, but in general do not provide the inertia. Here we present a preconditioner based on a multilevel incomplete \$LBL^T\$ factorization, from which an approximation of the inertia can be obtained. The suitability of the heuristics for application in optimization methods is verified on an interior point method applied to the CUTE and COPS test problems, on large-scale 3D PDE-constrained optimal control problems, as well as 3D PDE-constrained optimization in biomedical cancer hyperthermia treatment planning. The efficiency of the preconditioner is demonstrated on convex and nonconvex problems with \$150^3\$ state variables and \$150^2\$ control variables, both subject to bound constraints.}, language = {en} } @misc{GriesseWeiser2005, author = {Griesse, Roland and Weiser, Martin}, title = {On the Interplay Between Interior Point Approximation and Parametric Sensitivities in Optimal Control}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8773}, number = {05-44}, year = {2005}, abstract = {This paper is concerned with the sensitivities of function space oriented interior point approximations in parameter dependent problems. For an abstract setting that covers control constrained optimal control problems, the convergence of interior point sensitivities to the sensitivities of the optimal solution is shown. Error bounds for \$L_q\$ norms are derived and illustrated with numerical examples.}, language = {en} } @misc{WeiserHubigShanmugamSubramaniam2025, author = {Weiser, Martin and Hubig, Michael and Shanmugam Subramaniam, Jayant}, title = {Reconstructing Ambient Temperature Changes in Death Time Estimation with a Bayesian Double-Exponential Approach}, journal = {Zenodo}, doi = {10.5281/zenodo.17702240}, year = {2025}, abstract = {Code and data for the reconstruction of ambient temperature drop in time of death estimation We provide Octave code and temperature measurement data for - empirircally estimating thermal sensor likelihood - estimating time and amplitude of a single sudden ambient temperature drop from temperature measurement data in two thermally different compartments.}, language = {en} } @misc{VillaniWeiser2024, author = {Villani, Paolo and Weiser, Martin}, title = {Adaptive Gaussian process regression for inverse problems. ALGORITMY 2024}, year = {2024}, abstract = {This submission contains the code used for the proceedings paper for ALGORITMY 2024, concerning surrogate model-based inverse problems. Version 2 modified plot appearances and fixed some minor typos.}, language = {en} } @inproceedings{SemlerWeiser2025, author = {Semler, Phillip and Weiser, Martin}, title = {Adaptive gradient-enhanced Gaussian process surrogates for inverse problems}, booktitle = {Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023}, editor = {Fackeldey, Konstantin and Kannan, Aswin and Pokutta, Sebastian and Sharma, Kartikey and Walter, Daniel and Walther, Andrea and Weiser, Martin}, publisher = {De Gruyter}, arxiv = {http://arxiv.org/abs/2404.01864}, doi = {10.1515/9783111376776-005}, pages = {59 -- 78}, year = {2025}, abstract = {Generating simulated training data needed for constructing sufficiently accurate surrogate models to be used for efficient optimization or parameter identification can incur a huge computational effort in the offline phase. We consider a fully adaptive greedy approach to the computational design of experiments problem using gradient-enhanced Gaussian process regression as surrogates. Designs are incrementally defined by solving an optimization problem for accuracy given a certain computational budget. We address not only the choice of evaluation points but also of required simulation accuracy, both of values and gradients of the forward model. Numerical results show a significant reduction of the computational effort compared to just position-adaptive and static designs as well as a clear benefit of including gradient information into the surrogate training.}, language = {en} }