Projects
Inverse-free rational Krylov methods: theory and applications KU Leuven
To keep the computational complexity of Krylov methods under control, one often switches to rational Krylov algorithms. Unfortunately rational Krylov methods still have quite some problems subjected to research in this project. We will investigate approximate rational Krylov algorithms, efficient data storage, and implicit restarts. We will test all our findings on realistic datasets stemming from applications.
Pole swapping methods for the eigenvalue problem - Rational QR algorithms KU Leuven
The matrix eigenvalue problem is often encountered in scientific computing
applications. Although it has an uncomplicated problem formulation, the best
numerical algorithms devised to solve it are far from obvious.
Computing all eigenvalues of a small to medium-sized matrix is nowadays a
routine task for an algorithm of implicit QR-type using a bulge chasing technique.
On the other hand projection methods are ...
Projection Methods for Parametrized and Multiparameter Eigenvalue Problems KU Leuven
Matrix eigenvalue problems are common in computational science and engineering. In this thesis we focus on generalisations of the eigenvalue problem, namely parametrized and multiparameter eigenvalue problems. The matrices involved are large, so calculating eigenvalues is computationally expensive. Therefore, we develop techniques that exploit the structure and properties of the underlying problem.
In each of the proposed methods in ...
Iterative and multi-level methods for Bayesian multirelational factorization with features KU Leuven
Machine Learning methods are increasingly important in society and industry. The amount of data available for these Machine Learning applications is growing exponentially. This excessive amount of data still has to be processed efficiently. Designing robust and scalable algorithms for these large-scale data sets becomes increasingly important.
Matrix factorization of an incompletely filled matrix is one of these applications which has ...
Novel Acceleration Strategies for Acoustic Boundary Element Method and Other Non-Affine Parametric Linear Systems KU Leuven
Sound is everywhere in our environment. We continuously perceive acoustic
stimuli, which can either be pleasant such as good music, or annoying such as
the traffic noise persisting in modern societies. Recently, it has been widely
accepted that excessive exposure to sound can cause major health issues, leading
to the definition of noise pollution as a term. Although most of the noise found
in modern cities is emitted ...
Substructuring-Based Parametric Model Order Reduction Strategies for Efficient Structural Dynamic Simulation of Mechanical System Assemblies KU Leuven
With the continuous advancement of mechanical system assemblies, including vehicles, aircraft and machines, the emphasis on lightweight design for ecological and economic considerations and the utilization of multi-material combinations have become increasingly prevalent. Joints play an important role in ensuring the performance of these structures, effectively connecting the lightweight and multi-material components. Moreover, the pursuit of ...
Experimental model based estimation of inputs and parameters for vibro-acoustic system-level predictions KU Leuven
Dynamic Modeling of Macro-Fiber Composite Transducers Integrated into Composite Structures KU Leuven
Composite structures have been already widely applied in engineering. Laminated composites using isotropic or anisotropic layers provide numerous options for designing lightweight structural components, that have high static stiffness and excellent impact resistance for automotive and aerospace products. However, lightweight structures can be susceptible to external disturbances due to mass reduction and light damping in many cases. As a ...