Subprojects

T2 Simulate

Physics-based Process Evaluation and Decision Support for Structural Process Improvement

T2 builds validated simulations of the process that supply data sensors cannot measure and test changes before they are built.

Illustration. A hot laminate of four tape plies is formed while grippers hold its ends; lines and dots show fibres along and across the section. The fibres barely stretch, so the plies slide against each other on the walls, where the marker lines through the stack become stepped. Colour shows temperature, which drops where the laminate touches the tools. Runs differ in their settings, such as the gripper forces (arrows). Where one gripper holds back more, it draws in less and the laminate slides towards it, so each run ends in a different part. Every run is added to the simulation data from which M2 learns.

Work packages

Results of the first funding phase, by work package.

  1. T2.1 Development of a high-fidelity process simulation CAE chain

    A hexahedral solid-shell element predicts thickness changes in forming simulation. It was extended to rate-dependent material behaviour and applied to stamp forming of thermoplastic tapes. Interpolation methods for fibre orientation tensors reduce information loss along the CAE chain, and the SimEnvironment generates simulation data automatically for the M subprojects.

    Pipeline diagram. Process parameters from a project partner pass through a Python interface into the simulation environment, which runs scripted preprocessing, the Abaqus solver and an automated evaluation, and returns the simulation results.
    Data generation pipeline for stamp-forming simulations with the SimEnvironment, shown under its former name, GymEnvironment. Figure: KI-FOR 5339.

    Publications

  2. T2.2 Development of low-fidelity simulation models

    Physics-informed models of the thermal behaviour can partly be trained without simulation data. Fast Python simulations of static problems and nonlinear solid mechanics, simplified forming models and dedicated datasets, including one for a simplified double-dome benchmark, support the development of learned surrogates.

    Publications

  3. T2.3 Validity assessment towards CAE chain enhancement

    A study of the material parameters of the solid-shell element shows which of them drive the global forming behaviour, and underlines the relevance of rate-dependent modelling. A covariance-based validation framework assesses whether a model reproduces the relevant system dynamics. Its numerical studies show when isothermal models suffice and when thermomechanical models are needed, and the simulation data are openly available.

    Publications

  4. T2.4 Process evaluation and decision support for modification

    With T1, a study showed that the gripper positions clearly influence contour, curvature and thickness distribution of the formed part. With T1, M1 and M3, T2 provided the high-fidelity simulation basis for the Bayesian optimisation of gripper configurations.

    Publications

About the subproject

When data-driven improvement runs out, the process may still be immature. Validated simulations then show why, and suggest structural changes that T1 can build.

Principal investigators
Researchers
  • Johannes Mitsch
  • Tobias Würth
Host institute
Institute of Vehicle System Technology (FAST), KIT
People in T2

Publications 15