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Prof. Dr. Helmut Harbrecht

Department of Mathematics and Computer Sciences
Profiles & Affiliations

Projects & Collaborations

23 found
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Shape optimization under uncertainty

Research Project  | 2 Project Members

Shape optimization is indispensable for designing and constructing industrial components. Many problems that arise in application, particularly in structural mechanics and in the optimal control of distributed parameter systems, can be formulated as the minimization of functionals which are defined over a class of admissible domains. Shape optimization problems can be solved by means of gradient based minimization algorithms, which involve the shape functionals' derivative with respect to the domain under consideration. The computation of the shape gradient and the implementation of appropriate numerical optimization algorithms is meanwhile well understood, provided that the state equation's input data are given exactly. In practice, however, input data for numerical simulations in engineering are often not exactly known. One must thus address how to account for uncertain input data in the state equation. This project is concered with shape optimization under uncertainty. The uncertainty might be caused by different sources like uncertain geometric entities, uncertain loads, or uncertain material parameters.

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Basler Edition der Bernoulli-Briefwechsel (BEBB)

Research Project  | 7 Project Members

The Basler Edition der Bernoulli-Briefwechsel (BEBB) has the aim of publishing a full online edition of the letters exchanged by the mathematicians and physicists Daniel Bernoulli (1700-1782), Jacob I Bernoulli (1654-1705), Jacob II Bernoulli (1759-1789), Johann I Bernoulli (1667-1748), Johann II Bernoulli (1710-1790), Nicolaus I Bernoulli (1687-1759), Nicolaus II Bernoulli (1695-1726), and Jacob Hermann (1678-1733) with over 400 correspondents, many of them of world renown. The Bernoulli correspondence represents a central part of the scientific network of the 17th and 18th century and is an essential text source for the study of western intellectual history, particularly of the history of mathematics and physics.

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Shape optimization for microstructures

Research Project  | 2 Project Members

This project combines shape optimization and homogenization techniques by looking for the optimal design of the microstructure in composite materials and of scaffolds. The development of materials with specific properties is of huge practical interest, for example, for medical applications or for the development of light weight structures in aeronautics. In particular, the optimal design of microstructures leads to fundamental questions for porous media: what is the sensitivity of homogenized coefficients with respect to the shape of the microstructure? Based on Hadamard's shape gradient, we develop optimization algorithms and provide numerical simulations for several problems arising from the homogenization of elastic materials.

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Adaptive Boundary Element Methods Using Anisotropic Wavelets

Research Project  | 3 Project Members

This project aims at developing wavelet methods that adaptively solve boundary integral equations posed in three space dimensions. Since isotropic refinement is not optimal for the approximation of singularities which are of anisotropic nature, we will use (anisotropic) tensor wavelets for the discretization. Tensor wavelets are known to be able to resolve anisotropic singularities in an optimal way. Especially they are able to optimally resolve edge singularities which arise in case of non-smooth geometries and are typically of anisotropic nature. Therefore, the classical, isotropic adaptive wavelet algorithm has to be extended to this more general setting and necessary building blocks such as quadrature and compression routines have to be further developed. We will construct an adaptive algorithm which is optimal in the sense that it computes the approximate solution at an expense that scales proportional to the best $N$-term approximation of the unknown solution.

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Levelset-basierte Formoptimierung mit parametrischen Randelementmethoden

Research Project  | 2 Project Members

Viele Probleme in ingenieurswissenschaftlichen Anwendungen führen auf Probleme der Formoptimierung: ein Werkstück (Gebiet) soll hinsichtlich einer gewissen Eigenschaft (Kostenfunktional) unter Beachtung gewisser Eigenschaften (Zustandsgleichung und andere Nebenbedingungen) optimiert werden. Beipiele finden sich in der Baustatik, im Flugzeugdesign, etc. Insbesondere können zahlreiche freie Randprobleme und inverse Probleme als Formoptimierungsprobleme formuliert und behandelt werden. Die Entwicklung von effizienten Formoptimierungsmethoden ist unerlässlich für die computergestützte Simulation in den Ingenieurs- und Naturwissenschaften. Als Modellproblem soll in diesem Projekt Bernoullis freies Randproblem in drei Raumdimensionen betrachtet werden, wobei das gesuchte Gebiet durch eine Levelset-Funktion dargestellt werden soll. Um die zugrundeliegende Zustandsgleichung zu lösen, soll eine schnelle, parametrische Randelementmethode verwendet werden, wie etwa die adaptive Kreuzapproximation, das Multipol-Verfahren oder ein Wavelet-Galerkin- Verfahren. Hierfür muss der Rand des durch die Levelset-Funktion implizit gegebenen Gebiets extrahiert und parametrisiert werden. Speziell muss die Levelset-Funktion durch eine Diskretisierung höherer Ordnung behandelt werden.

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Basler Edition der Bernoulli-Briefwechsel

Research Project  | 7 Project Members

The Basler Edition der Bernoulli-Briefwechsel (BEBB) has the aim of publishing a full online edition of the letters exchanged by the mathematicians and physicists Daniel Bernoulli (1700-1782), Jacob I Bernoulli (1654-1705), Jacob II Bernoulli (1759-1789), Johann I Bernoulli (1667-1748), Johann II Bernoulli (1710-1790), Nicolaus I Bernoulli (1687-1759), Nicolaus II Bernoulli (1695-1726), and Jacob Hermann (1678-1733) with over 400 correspondents, many of them of world renown. The Bernoulli correspondence represents a central part of the scientific network of the 17th and 18th century and is an essential text source for the study of western intellectual history, particularly of the history of mathematics and physics.

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Big Data for Computational Chemistry: Unified machine learning and sparse grid combination technique for quantum based molecular design

Research Project  | 4 Project Members

We propose to explore an unprecedented amount of molecular data (166B molecules) with quantum chemical precision. For this, chemically accurate and transferable machine learning property models of unprecedented computational efficiency will be developed using special purpose tailored training sets designed according to unified multilevel techniques (sparse grids plus combination rules). We will subsequently apply the method to iteratively optimize molecular property objective functions which enable the routine discovery of new molecules with pre-defined specific properties - in real time. The objective for this effort is twofold: We plan to (a) provide experimental chemists with a powerful computational tool to guide design, synthesis, and characterization efforts of new and interesting molecules, and (b) gain a better understanding of the nature, landscape, and relationships among chemical structure and properties throughout chemical space.