Abstract

SimScale GmbH and Datadvance have developed a scalable cloud integrated workflow for multi-objective optimisation studies. This paper presents a case study of a quasi-static, axisymmetric thermal-structural problem in the form of a low pressure rotating turbine disk model. The purpose is to optimise the physical characteristics and geometry of the rotating disk which has 11 variable geometric dimensions and multiple constraints, whilst minimising the overall mass and keeping within structural and stress limits. An Application Programming Interface (API) is used to connect the geometric optimisation tool to SimScale’s multiphysics cloud simulation engine. pSeven Enterprise is used to build and run the optimization workflow. Each time a particular geometry and simulation parameters are sent to the API, SimScale will simulate the model and return outputs for that instance including temperature distribution, radial displacements and stresses. Data is then fed into the pSeven surrogate optimisation model. As the workflow is scalable, many hundreds of geometric scenarios can be modelled. The physics outputs for each scenario are tracked using a pareto front to converge on the local minima (the optimised solution) where the mass and radial displacement are the two key parameters. In one case, after 400 iterations, a 20% reduction in overall mass of the disk was achieved. SimScale simulated all 400 iterations on the cloud, in parallel, without the need for any local hardware, thus the speedup in simulation and analysis time is exponential compared to current approaches. The new workflow makes the procedure time and cost efficient and accessible via only a web browser, meaning, for the first time this kind of speed and power is available without the need for costly and complex hardware. pSeven Enterprise allows going beyond the solution of optimization problems in the cloud. A workflow-powered web application can be built and published to AppsHub gallery within pSeven.