A5018254186- Advanced Multi-Objective Optimization Algorithms
- Probabilistic and Robust Engineering Design
- Metal Forming Simulation Techniques
- Manufacturing Process and Optimization
- Metallurgy and Material Forming
- Structural Health Monitoring Techniques
- Fatigue and fracture mechanics
- Optimal Experimental Design Methods
- Gear and Bearing Dynamics Analysis
Technical University of Munich
2022-2024
Abstract Multi-fidelity optimization schemes enriching expensive high-fidelity functions with cheap-to-evaluate low-fidelity have gained popularity in recent years. In the present work, an scheme based on a hierarchical kriging is proposed for large-scale and highly non-linear crashworthiness problems. After comparison to other multi-fidelity techniques infill criterion called variable-fidelity expected improvement applied evaluated. This complemented by two innovative techniques, new...
Abstract In the early-stage development of sheet metal parts, key design properties new structures must be specified. As these decisions are made under significant uncertainty regarding drawing configuration changes, they sometimes result in parts that, at a later stage, will not drawable. result, there is need to increase certainty experience-driven decisions. Complementing this process with global sensitivity analysis (GSA) can provide insight into impact various changes configurations on...
Abstract New structural sheet metal parts are developed in an iterative, time-consuming manner. To improve the reproducibility and speed up iterative drawability assessment, we propose a novel low-dimensional multi-fidelity inspired machine learning architecture. The approach utilizes results of low-fidelity high-fidelity finite element deep drawing simulation schemes. It hereby relies not only on parameters, but also additional features to generalization ability applicability assessment...
Abstract Multi-fidelity optimization, which complements an expensive high-fidelity function with cheaper low-fidelity functions, has been successfully applied in many fields of structural optimization. In the present work, exemplary cross-die deep-drawing optimization problem is investigated to compare different objective functions and assess performance a multi-fidelity efficient global technique. To that end, hierarchical kriging combined infill criterion called variable-fidelity expected...
Abstract A brief review of methods in design experiments and criteria to determine space-filling properties a set samples is given. Subsequently, the so-called curse dimensionality sampling reviewed used as motivation for proposal an adaptation strata creation process Latin hypercube based on idea nested same-sized hypervolumes. The proposed approach places closer space boundaries, where higher dimensions majority volume located. same introduced Monte Carlo considering affordable number...