This paper presents an efficient optimization process, where the parameters defining the features in a feature-based CAD model are used as design variables. The process exploits adjoint methods for the computation of gradients, and as such the computational cost is essentially independent of the number of design variables, making it ideal for optimization in large design spaces. The novelty of this paper lies in linking the adjoint surface sensitivity information with geometric sensitivity values, referred to as design velocities, computed for CAD models created in commercial CAD systems (e.g. CATIA V5 or Siemens NX). This process computes gradients based on the CAD feature parameters, which are used by the optimization algorithm, which in turn updates the values of the same parameters in the CAD model. In this paper, the design velocity and resulting gradient calculations are validated against analytical and finite-difference results. The proposed approach is demonstrated to be compatible with different commercial CAD packages and computational fluid dynamics solvers.

The gas-liquid interface dips during the draining of a liquid through a discharge port of a vessel or a tank. The dip develops into a gas-core vortex which subsequently enters the discharge port. This entry can be either gradual or sudden, depending on the intensification of the rotational flow currents during the draining process. The extension of the gas-core into the drain port reduces the flow area and consequently the flow rate. In liquid propellant rocket motors, this phenomenon can have adverse effect on the performance as well as lead to under utilisation of the propellant. In this paper, the authors have tried to find the reason why such an air-core vortex develops in the first place, and the factors that influence its intensification over time, as reported in literature. These investigations have been carried out through simulations done using the commercial ANSYS Fluent code to validate the findings from the CFD results. The simulations are carried out using the volume of fluid (VOF) method, which obtains the volume fraction of each of the fluid throughout the domain and thereby captures the gas-liquid interface motion. Thereafter, the air-core vortex height predictions are validated with results reported in the literature.

This paper presents an approach which increases the flexibility of a computer-aided design (CAD) model by automatically refining its parameterization and adding new CAD features to the model’s feature tree. It aims to overcome the limitations imposed by the choice of parameters used during the initial model creation, which constrains how the model shape can change during design optimisation. Parametric effectiveness compares the maximum performance improvement that can be achieved using a parameterisation strategy to the maximum performance improvement that can be obtained where the model is unconstrained in how it moves. As such, it provides a measure of how good a parameterisation strategy is and allows different strategies to be compared. The change in parametric effectiveness due to inserting multiple different CAD features can be calculated using a single adjoint analysis; therefore, the computational cost is essentially independent of the number of parameterisation strategies being analysed. The described approach can be used to automatically add new features to the model and subsequently allows the use of the newly added parameters, along with the existing parameters to be used for optimization, providing the opportunity for a better performing product. The developed approach is applied on CAD models created in CATIA V5 for 2D and 3D finite element and computational fluid dynamic problems.

This paper presents an optimisation framework based on an open-source CAD system and CFD solver. In this work, the high-fidelity flow solutions and surface sensitivities are obtained using the primal and discrete adjoint formulations of $S{U}^2$. This paper shows the direct use of CAD models for optimisation by developing a CAD system application programming interface and creating a link between the CAD-MESH-CFD analysis. A methodology to obtain geometric sensitivities is introduced, enabling the calculation of accurate gradients with respect to CAD variables and the deformation of the analysis mesh during the optimisation process. This methodology guarantees that the new surface mesh lies exactly on the CAD geometry. The optimisation framework is applied to a rectangular wing and a three section high-lift aerofoil configuration derived from the NASA CRM-HL configuration. Both geometries are created using FreeCAD. The performance objectives are to decrease the drag while constraining the lift to be above a desired value. The twist distribution of the wing was parameterised within the CAD system, allowing the minimisation of the induced drag by obtaining a nearly elliptical lift distribution. For the high-lift configuration, the position and rotation of the flap and slat were parameterised with respect to the original section; the final optimised positions yield a drag reduction of approximately 16.5%. These results show that the CAD parameterisation can be reliably used to obtain efficient optimums while operating directly on the CAD geometries.