SKM 2023 – wissenschaftliches Programm
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CPP: Fachverband Chemische Physik und Polymerphysik
CPP 2: Modeling and Simulation of Soft Matter I
CPP 2.7: Vortrag
Montag, 27. März 2023, 11:30–11:45, MER 02
Differentiable simulation for Solar Power Plants and beyond — •Stefan Kesselheim1, Max Pargmann2, and Jan Ebert1 — 1Forschungszentrum Jülich — 2German Aerospace Center (DLR)
In Solar Power Plants, temperatures sufficient for chemical processes or the generation of electrical power are created by reflecting sunlight with thousands of mirrors ("heliostats") to a surface ("the receiver"). In operation, the temperature distribution on the receiver is critical for the performance and must be optimized. The heliostats are never perfectly flat as due to budget constraints, the construction is not optimal. We have devised a method to infer the heliostat surface from the reflection of the sun. The technique is based on an implementation of a simulation in PyTorch, where the automatic differentiation engine is used to optimize the surface. The surface is modeled as by a Non-Uniform Rational B-Spline (NURBS) and the NURBS parameters are subject to optimization. Furthermore we employ a regularization technique to mitigate the appearing challenge of ambiguous solutions. Our approach makes efficient use of GPUs based on PyTorch's linear algebra engine. We believe our approach poses an interesting example of a fruitful interaction of techniques originating from Machine Learning and simulation, that can serve as an exciting example how to integrate simulation and experimental data, for example in biomolecular simulation.