Design Optimization Through Simulation

Exa’s technology and products are catalyzing a disruptive change in how manufacturers design, engineer, and optimize their products. PowerFLOW simulation-driven design makes predictive information available earlier in the design process, permitting deeper exploration of the design space. Rapid iterations between simulation and design provide essential insight into how new concepts can improve the design.



The goal of engineering is produce an “optimal” product design that balances the competing constraints and requirements, performs as well as possible, and is aesthetically compelling. What is meant by “optimization” depends on where you are in the design process. In the early stages of design (concept development), it is extremely useful to use “optimization” techniques to characterize the design space — that is, to understand how the product is likely to perform across a wide range of varying design parameters, and which of the design parameters have the most impact or sensitivity on the design. Gaining this understanding gives engineers and designers the freedom to explore the design space and develop creative solutions. Later in the product development process, when the design concepts are fixed and the details of the design are being developed, it is useful to use optimization techniques to find a more optimal solution than can be found using conventional design/test iteration loops. Note that it is not necessary to find the absolute optimal solution in order to gain value — rather, to find a better solution than you would have otherwise.

Comparison of alternative designs (note differences in wake structure produced by subtle changes in geometry)



One of the biggest barriers to using  optimization with 3D simulation tools has been that typically, a large number of simulations is required — making it time prohibitive. Design of Experiments (DoE) is often thought of as being the same as optimization. DoE is a useful technique, but is simply a starting point in determining the initial set of design parameters to test. The real process and value in optimization/characterization lies in deciding what to do next. Many optimization/characterization projects assume that the design parameters are independent, and seek to find an optimal value for each parameter independent of the others. However, there are interactions between the key design parameters in almost every design. Typical methods fail to provide an understanding of these relationships, and therefore fail to guide engineers to the overall best solution. In addition, with traditional fluid simulation tools, it is very difficult to perform multi-disciplinary design studies across aerodynamics, aeroacoustics, and thermal management because the simulation tools and input meshes must be fine-tuned for each type of analysis, and cannot be combined.

Graphic above: response surface



Exa has developed significant expertise in, and proprietary methods for, performing design characterization and optimization using adaptive response surfaces. The major benefit of the approach is to enable design characterization and optimization to occur with significantly fewer simulation runs than traditional approaches. This makes the Exa approach faster and cheaper. Exa’s expert team works with customers to carefully design optimization projects so true understanding of the design behavior is gained.


One of the advantages of the Exa optimization solution is mesh morphing with PowerCLAY. After the optimization algorithm determines which design parameter values to set for the next simulation run, new design geometry that corresponds to these new values must be prepared. The traditional process requires waiting for a designer to provide updated geometry — a process that could take days, which defeats the idea of rapid iterations driven by the optimization algorithm. However,  PowerCLAY enables you to directly morph the mesh model used for simulation in real time. Using patented lattice transformations, you apply parameterized morphing features that correspond to the design parameters, and can be parametrically varied to any value. Thus, the optimization algorithm can rapidly drive generation of the next design model.


You can automate the entire optimization process such that the optimization engine drives the generation of updated designs, simulations are set up and run, and post processing is executed automatically to determine the next run to be performed.


A major advantage to PowerFLOW is the ability to carry out multi-disciplinary design studies and optimization using a single digital model, enabling engineering teams to efficiently collaborate early in the design process. With PowerFLOW, aerodynamic, thermal, aeroacoustic, and climate control simulations can use the same fully detailed geometry model and the same fluid solver, providing rapid design trade-offs. Exa’s proprietary DIGITAL PHYSICS provides a single solver for all applications — without any tuning needed.


Morph surfaces in real time using Exa's suite of software products.

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