Automatic adjoint-based design optimization for laminar combustion applications

We present an open-source and flexible framework for automatic adjoint-based design optimization for laminar combustion devices. The framework allows for multi-objective optimization of various key performance indicators like heat transfer and pollutant emissions. Geometry and mesh deformation is performed based on surface sensitivities computed from the discrete adjoint solution of the reactive Navier Stokes equations, and algorithmic differentiation is used for the gradient calculations. The flow solution is obtained from the preconditioned variable-density Navier–Stokes equations in the low Mach number limit, and combustion is modeled using a flamelet approach for laminar premixed conditions. Reaction chemistry, thermodynamics, and mass transport are parameterized with a progress variable and the total enthalpy. To increase the accuracy of pollutant emissions, additional transport equations for CO and NOx are solved. The framework is built on the foundation of several open-source applications to calculate CFD and adjoint solutions, obtain geometrical sensitivities, and perform free form deformations. To ensure high mesh quality, an automatic re-meshing procedure has been applied by coupling an external mesh generator in the optimization workflow. The optimization framework is demonstrated by simultaneously minimizing CO and NOx emissions as well as the outlet temperature of a steady, laminar, premixed methane–air flame in a simplified 2D model of a burner and heat exchanger with strong flue gas cooling. The optimized geometries and the impact of the objective weight factors on the pollutant emissions, thermal efficiency, and the shape change are investigated. •Extension of discrete adjoint method to combustion problems using FGM.•Implementation of automatic design optimization workflow in open-source code SU2.•Validation of CFD solution with detailed chemistry.•Optimization of canonical burner-heat exchanger configuration for different objectives.