Parametric-adjoint Approach for the Effcient Optimization of Flow-Exposed Geometries VI International Conference on Computational Methods in Marine Engineering MARINE 2015 F. Salvatore, R. Broglia and R. Muscari (Eds) PARAMETRIC-ADJOINT APPROACH FOR THE EFFICIENT OPTIMIZATION OF FLOW-EXPOSED GEOMETRIES MATTIA BRENNER * , STEFAN HARRIES * , JÖRN KRÖGER † AND THOMAS RUNG † * FRIENDSHIP SYSTEMS AG Benzstr. 2, 14482 Potsdam, Germany e-mail: brenner@friendship-systems.com, www.caeses.com † Inst. Fluid Dynamics and Ship Theory (M8) Hamburg University of Technology (TUHH) Am Schwarzenberg-Campus 4, 21073 Hamburg, Germany e-mail: joern.kroeger@tuhh.de, www.tuhh.de Key words: Hull Form Optimization, Adjoint RANS CFD, Parametric Modelling Abstract. Today, the optimization of ship hulls and appendages, including energy-saving devices, is typically undertaken by means of coupling parametric modelling (variable geometry) and Computational Fluid Dynamics (CFD). A relatively new approach is based on parameter-free solutions, solving the adjoint RANS equations for selected objective functions (like drag and lift). Combining parametric and parameter-free solutions is an emerging technique that helps to effectively optimize shapes without leaving the CAD domain of the model, making it easier to integrate in the overall design process. On the basis of the Computer Aided Engineering (CAE) software CAESES, a parametric- adjoint approach will be presented. The approach is built on concatenating so-called “design velocities” and “adjoint shape sensitivities”. Design velocities yield regions of influence from a pure geometric point of view within a given parametric model. Meanwhile, adjoint shape sensitivities show where and how changes of the surface affect the objective. Overlaying the surface distributions of both the design velocities and the adjoint shape sensitivities result in so-called “parametric sensitivities.” These help to understand the importance of all parameters within the chosen model. This approach will be demonstrated on a practical hull form optimization example. 1 INTRODUCTION Using parametric modelling in the design process allows for an efficient variation of the geometry, see [1], [2]. The total number of shape-defining parameters for a typical parametric model of a flow-exposed geometry like a ship hull in the CAE platform CAESES is usually within the range of 20 to 50. This means that for complex free-form geometries the number of degrees of freedom is still so large that when using a direct optimization approach, taking into account all parameters, a high number of function evaluations, i.e. CFD computations, would be necessary to identify trends with respect to the necessary geometry modifications leading 230