Simulation and Optimization
Today’s product and manufacturing engineers face challenges their predecessors could barely imagine. Globalization, increased regulation, sustainability, embedded computer systems, fewer engineering resources, and other issues force development teams to do everything possible to make optimal use of their time and resources. Modeling and simulation are already important, but today’s leading engineering groups are taking their use of computer tools to the next level with engineering optimization technology.
Many times engineers need to go beyond the simulation and validation of existing design by helping teams identify new and more optimal design possibilities. This approach combines the best of existing engineering analysis with a computational approach to optimization, allowing many possible solutions to be tested in less time than it would take to do with manual methods.
Optimization Approaches
A typical optimization task is weight reduction while maintaining necessary stiffness. Early on topology optimization can lead to a design proposal that combines these requirements. This leads to a shorter overall design process, as the back-and-forth between design and prototype can be reduced. In this example, the addition of numerical optimization reduces the need for physical prototypes, saving money and helping the product reach the marketplace faster.
Initial topology design is only one area in which optimization helps engineers push the design envelope. Consider these other elements:
Sizing: Applying an optimal relation between weight, stiffness, and dynamic behavior usually won’t work if the size is wrong. Use tomometry analysis to seek the perfect relationships to gain material savings. Sizing allows complex variables, such as vehicle bodies, to reach optimal design parameters when the size is fixed or can only be modified slightly.
Shape optimization: In later design stages, small local changes in the original design can reap big savings without compromising original design intent. Local stress and strain peaks can be identified and reduced, increasing durability and lengthening maintenance cycles.
Bead optimization: Shell structured benefit from bead optimization, used to create more efficient bead pattern layouts with increased stiffness and reduced noise. Many engineers rely on intuition or limited testing to design bead layout; optimizing bead layout will provide a better final design in less time.
Fluid-based Optimization
Our Fluid-based optimization solution uses a non-parametric approach to topology optimization. The principle idea is to remove areas from the initial design that impact flow loss or interference. Existing CFD models are used, allowing for the most complete shape flexibility leading to innovative designs.
In a fluid-based optimization, the initial design does not represent the existing design but the “design space,” a representation of the maximum available space the user can offer. There are no limitations on the shape of the design space as long as a high-quality mesh is used.
Fluid analysis operates as a coupled simulation; the CFD solver and the optimizer exchange data for every CFD iteration. This means only one single coupled run is needed for a complete topology optimization, saving time. The finished design is a 3D surface mesh that is generally reconstructed in CAD. This allows for an interpretation of the optimization, and guarantees downstream designers follow necessary constraints to maximize use of the optimal design.
It is also possible to Fluid optimization in an non-sequential method with a CAD tool and a CFD solver to help discover a more optimal shapes where the fluids pass.
A holistic approach to design optimization
Adaptive can help you optimize fluid design by integrating the best of the CAE algorithmic solvers with the power of a computational approach to design optimization. Creating optimal designs early in the product development process leads to shorter time-to-market and reduces unnecessary overhead from a more manual, iterative process. Calculations and optimizations also get closer to the original design intent sooner, creating a stronger integrated development process.