Tobias Kattmann(AG Scientific Computing, Prof. Nico Gauger)
hosted by PhD Program in CS @ TU KL
"Efficient Adjoint-Based Design Capability for Unsteady Conjugate Heat Transfer Problems"
Shape optimization using gradients computed via the adjoint method has become a common feature and also, practically, a requirement among the major CFD and multi-physics solvers. Accurate sensitivities are widespread available for single-zone steady-state problems, with unsteady or multi-physics adjoint solvers being less common. Yet, gradient availability is a desirable feature for all primal simulation capabilities. Many practical flows of industrial interest are unsteady in nature, and for the simulation of heating/cooling devices the coupling between a fluid and solid domain is essential to accurately capture the system's behavior. Combining these two general observations of the demand for sensitivities and unsteady conjugate heat transfer applications, is the objective of the present work.
Bio: This talk presents the development and application of a computationally efficient unsteady discrete adjoint solver for conjugate heat transfer in the open-source solver SU2.
|Time:||Monday, 30.01.2023, 17:00|