Advanced Full- and Reduced-Order Simulations as Digital Tools in Production Engineering
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Beschreibung
One of the central questions in production engineering is how to manufacture new products from raw material as effectively, efficiently, and economically as possible. In this context, simulation-based methods can play an important role as digital tools, especially with regard to ongoing transformations in the course of the Fourth Industrial Revolution. This work considers approaches for the simulation of heat conduction and flow problems, as they appear in various manufacturing processes. In combination with optimization and uncertainty quantification (UQ) strategies, the main objective is to increase the insight, the performance, and the reliability for relevant processes.
Providing useful tools for this purpose is the focus of this work, realized through the following two contributions. First, the application of a novel method to handle the computational mesh in specific deforming domain problems is presented. These problems are characterized by large relative translational motion, including object entry and exit. Second, the potential of Model Order Reduction (MOR) to enable the original computational models for many-query scenarios is investigated. The rationale here is to provide models suitable for the integration in optimization or UQ approaches. This topic is studied for shape parametric heat conduction problems and for the flow of plastics melt, which is modeled by the non-linear Stokes equations using a shear-thinning viscosity model. Also, the respective flow on deforming domains is considered.
The simulation of a packaging process based on the aforementioned mesh update method illustrates the potential gain of insight for complex flows in such an application. In addition, three different test cases in the context of plastics extrusion are used to demonstrate the capability of the developed models to contribute to an enhanced performance and reliability of the process through optimization and UQ, respectively.
Autor*in
Fabian Key
Themen in »Advanced Full- and Reduced-Order Simulations as Digital Tools in Production Engineering«
Production Engineering Simulation Model Order Reduction