A5042884989- Probabilistic and Robust Engineering Design
- Structural Health Monitoring Techniques
- Elasticity and Material Modeling
- Model Reduction and Neural Networks
- Fatigue and fracture mechanics
- Asphalt Pavement Performance Evaluation
- Civil and Structural Engineering Research
- Enhanced Oil Recovery Techniques
- Computational Geometry and Mesh Generation
- Advanced Numerical Methods in Computational Mathematics
- Injection Molding Process and Properties
- Geotechnical Engineering and Analysis
- Rheology and Fluid Dynamics Studies
- Advanced Multi-Objective Optimization Algorithms
- Additive Manufacturing and 3D Printing Technologies
- Manufacturing Process and Optimization
- Advanced Mathematical Modeling in Engineering
- Composite Material Mechanics
- Advanced Numerical Analysis Techniques
University of Siegen
2018-2022
Folkwang University of the Arts
2019-2022
In this contribution, several case studies with data uncertainties are presented which have been performed in individual projects as part of the DFG (German Research Foundation) Priority Programme SPP 1886 “Polymorphic uncertainty modelling for numerical design structures.” all models derived from engineering problems describing concepts handling and incorporating measurement data, either model input parameters or system response. The first study deals polymorphic uncertain based on computer...
Abstract In a data‐driven finite element analysis the experimental data are directly employed as an input for computational analysis, thus evading any state of matter modeling. The essential physical principles, such balance laws and continuity, remain unchanged, do all numerical schemes used in their discretization. addition, uncertainties fluctuations experimentally measured enter simulation. Here is applied to diffusion which common problem with multiple applications like particle...
Abstract The presence of voids or cavities inside a material plays an important role in several applications. Recently, their investigation has gained attention to understand the effect such inhomogeneities on 3D‐printed structures. Such structures could be already weakened due procedure additive manufacturing. Voids can visualized by computed tomography but practically micrograph obtained planar cut through is simpler and cheaper. This requires, however, reconstruction three‐dimensional...
Abstract In the classical Euler‐Bernoulli cantilever beam theory deflection w depends on different parameters. On one hand we have material and geometric parameters, like Young's Modulus E , second moment of area I length L . other there are loading types point loads F distributed loads, or varying loads. All these parameters usually modeled in a deterministic way. this contribution analyze distribution maximum max depending uncertain To end model input as random variables ( X ) fields i )....
This paper presents a model-free data-driven strategy for linear and non-linear finite element computations of open-cell foam. Employing sets material data, the problem is formulated as minimization distance function subjected to physical constraints from kinematics balance laws mechanical problem. The data foam are deduced here representative microscopic volumes. These volume elements capture stochastic characteristics microstructure properties polyurethane material. Their computation...
Abstract Recently Kirchdoerfer and Ortiz proposed a new computing paradigm, called data‐driven [1]. It is approach to overcome uncertainties in the modeling process of material law. The aim this work compare solutions method with classical finite element an analytic solution. A simple elastic problem considered all methods are presented.
Abstract In data driven modeling the constitutive model is replaced by a set and therefore yields model‐free computation. this context also can be input for noisy material describe uncertainty. This contribution presents juxtaposition of different finite element trechniques to uncertainties, namely stochastic method method.
Abstract This contribution explores the ability to conduct polymorphic uncertainty computations within data‐driven finite element framework. The constitutive equation is replaced by data sets that determine material behavior, and a fuzzy load used for approach. To many simulations with discretized variables increase numerical efficiency, cost reduced multi‐level method.