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Integrating Simulation Tools for an Efficient Optimization Process

Simulation-driven design optimization is an iterative and multi-phase process, often requiring seamless cooperation of a set of different Computer Aided Design (CAD) and Computer Aided Engineering (CAE) tools. It consists of multiple steps that remain conceptually similar from problem to problem, but geometry needs to be prepared and meshed, simulation needs to be performed and new designs need to be generated. The methods used in literature vary greatly depending on the type of the problem and physical phenomena simulated, however forming and managing a tool chain of relevant CAE-CAD resources requires expertise on all pieces of software involved in each phase. 

A system that facilitates interoperability between different tools in a distributed environment allows the users to adapt the tool chain in a straightforward manner according to the optimization problem at hand. In addition to that, if the execution of the process relies on ad-hoc solutions chosen to apply only to a single optimization problem, the effort placed in integrating these tools is lost when engaging in a new optimization project requiring a slightly different set of software or execution with a different set of parameters. Thus it is reasonable to suggest the use of an integrated software platform where the main workflow of the process remains static, yet the parts performing each individual task can be changed or tuned according to the requirements posed by the problem.

One challenge for integrating these tools is that the interfaces (inputs, outputs, file formats and parameters) of the programs vary between applications and each phase of the process requires its own amount of computational power. Thus it would be reasonable for example to perform the simulation and objective function computation using a more powerful computer.

Also using several types of meshers for different types of problems would be useful as it would be preparing a full optimization pipeline for each optimization problem. These are all demanding task which require expertise with a variety of applications, often belonging to more than one discipline. Therefore the use of a powerful integration platform can drammatically facilitate engineers work within the design process, especially when tackling multi-disciplinary sources.

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