5 papers
Machine learning-based optimization workflow of the homogeneity of spunbond nonwovens with human validation
Viny Saajan Victor, Andre Schmeißer, Heike Leitte +1
In the last ten years, the average annual growth rate of nonwoven production was 4%. In 2020 and 2021, nonwoven production has increased even further due to the huge demand for non…
Machine Learning Based Optimization Workflow for Tuning Numerical Settings of Differential Equation Solvers for Boundary Value Problems
Viny Saajan Victor, Manuel Ettmüller, Andre Schmeißer +2
Several numerical differential equation solvers have been employed effectively over the years as an alternative to analytical solvers to quickly and conveniently solve differential…
Machine Learning Optimized Approach for Parameter Selection in MESHFREE Simulations
Paulami Banerjee, Mohan Padmanabha, Chaitanya Sanghavi +2
Meshfree simulation methods are emerging as compelling alternatives to conventional mesh-based approaches, particularly in the fields of Computational Fluid Dynamics (CFD) and cont…
Analysis of the fiber laydown quality in spunbond processes with simulation experiments evaluated by blocked neural networks
Simone Gramsch, Alex Sarishvili, Andre Schmeißer
We present a simulation framework for spunbond processes and use a design of experiments to investigate the cause-and-effect-relations of process and material parameters onto the f…
Three-dimensional simulation of nonwoven fabrics using a greedy approximation of the distribution of fiber directions
Simone Gramsch, Max Kontak, Volker Michel
An elementary algorithm is used to simulate the industrial production of a fiber of a 3-dimensional nonwoven fabric. The algorithm simulates the fiber as a polyline where the direc…