Optimization & Robust Design
Engineer High-Performance Products and Robust Designs with ANSYS CFD
Product development teams face many challenges when engineering a new design. They must answer critical questions, such as: “Will this product provide the best performance possible?” and “What do we need to do to keep the final product from failing?"
To beat the competition, a product must be high quality and high performance. To ensure brand integrity, the product must function as deigned, each and every time it is used. The most successful companies develop best practices to eliminate high product return — and worse: product recall costs.
Computational fluid dynamics (CFD) solutions from ANSYS enable engineers to develop product designs that are both robust and high performance. ANSYS tools enable you to couple CFD simulation with optimization techniques — finding the optimal design — as well as robust design techniques, including design of experiments and six sigma analysis.
ANSYS DesignXplorer leverages the power of ANSYS Workbench for parametric analyses. The intuitive Workbench platform makes it easy to create and manage parameters across a wide range of ANSYS products; it also has a persistent setup and performs automatic updates. ANSYS DesignXplorer takes harnesses these strengths and enables you to explore, understand and optimize your design. The best practice here is driving innovative product development via simulation.
ANSYS CFD software offers shape optimization capabilities that can automatically adjust the geometric parameters of a specific design until you meet specified optimization goals for that design. Examples include optimized aerodynamics of a car or aircraft wing and flow rate in nozzles and ducts.
ANSYS Fluent offers groundbreaking adjoint solver technology, which provides insight into how to modify geometry to achieve design goals. It allows you to modify the mesh from within to see the effect of the recommended change. It provides information in a single simulation — data that is difficult and expensive to gather using other methods — by computing the derivative of engineering quantities with respect to the system inputs. The discrete adjoint solver is available for examining downforce (for Formula One car racing applications), decreasing drag (for automobiles), and reducing total pressure drop (for ducts and pipes). The adjoint solver performs robustly and with excellent scalability on large meshes of more than 10 million cells.