Demo, N.

Ivagnes*, A.

Rozza, G.

Scipedia

Non-intrusive Reduced Order Modeling to Accelerate Designand Optimization ProcessesAnna IvagnesMathematics Area, mathLab, SISSAvia Bonomea 265, I-34136 Trieste, Italyanna.ivagnes@sissa.itNicola DemoFAST Computingvia Mazzini, 20, I-34121 Trieste, Italynicola.demo@fastcomputing.netGianluigi RozzaMathematics Area, mathLab, SISSAvia Bonomea 265, I-34136 Trieste, Italygianluigi.rozza@sissa.itReduced order modeling (ROM) provides a consolidated approach to reduce the often highcomputational cost of simulation-based design and optimization problems. Proper orthog-onal decomposition (POD) is a reduction technique that can be used for solving parametricPDEs in an efficient and fast way by combining a limited set of pre-computed numericalsolutions. Its employment with nonlinear physics phenomena and complex geometries mayrequire however further numerical treatments in order to keep the desired accuracy. Insuch a contribution, we will present several examples of applications where a POD-basedframework has been adopted to reduce the computational burden of hull and propeller op-timization. We will discuss the adopted deformation techniques, with a deep focus on theirintegration within the ROM pipeline. We will then present the non-intrusive POD frame-works, so-called since it is a family of methods that rely only on the data, allowing largeremployment. The last part of the contribution is dedicated to the optimization strategy,where a genetic algorithm has been applied to explore the non-convex solution manifold ofthe reduced model.

Non-intrusive Reduced Order Modeling to Accelerate Design and Optimization Processes

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Non-intrusive Reduced Order Modeling to Accelerate Design and Optimization Processes

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