Simulating and Optimising Thermochemical Energy Storage Reactors with Firedrake

Kurzfassung

Thermochemical energy storage (TCES), where thermal energy is stored in a reversible chemical reaction in a porous powder bed, is a promising technology for large-scale and long-term heat storage. It has been under long-standing investigation for prospective applications, such as the capture of excess heat from industrial processes or storing energy in concentrated solar power plants to offset their unpredictable energy generation. As heat transport from a heat source to the reactive material is a limiting factor in current reactor designs, fin structures are incorporated to enhance heat transfer. The geometry of these heat transfer structures has a major influence on the performance characteristics of the reactor, such as capacity and power delivery. In this talk we show how we are using Firedrake for the simulation and optimization of TCES reactors. First, we give a short introduction into problem setting and the reactor model, which is implemented with a finite volume discretization with an immersed interface. Then we show, how to use firedrake.adjoint for sensitivity analysis and topology optimization. Finally, we show how the optimization can be sped up by using firedrakes pyTorch interface to construct a fast surrogate model, which is then used for optimization.