Advanced numerical optimization methods in the rapid product development process of diesel engines |

Advanced numerical optimization methods in the rapid product development process of diesel engines

Amos Giovannini (BMW)

BMW leveraged modeFRONTIER to optimize the fatigue life of a diesel engine crankcase and gasket. The objectives were to maximize safety factors at the inter-cylinder walls, while maximizing the minimum bead pressure during the low temperature phases of combustion.

Challenge - BMW’s traditional optimization techniques tended to “over optimize,” producing solutions that performed well at the design point, but showed different results due to off-design characteristics. To address this issue, the team needed to take into account the uncertainty of certain input parameters since they couldn’t always be precisely determined under real manufacturing and operating conditions. Moreover, a product designed for one specific environmental scenario was not especially suited in other environments; thus the team needed a way to come up with designs which had lower variability of performance.

BMW Diesel Engine Development - Robust Design Optimization FE (Crankcase)

Solution -  modeFRONTIER’s robust design algorithms helped address the multi-objective design optimization challenge by allowing one variable and three constants to be defined as stochastic. In that way, the platform automatically created a set of sample designs during the optimization with a user-specified distribution and variance for each stochastic variable, centered at the initial value point. modeFRONTIER’s workflow editor, together with several direct integration nodes, helped the team create an automated pipeline connecting the different solvers required to solve the optimization challenge, including Paramesh to modify the geometry, Abaqus for the thermo-structural computations, and Femfat, to compute the safety factors.

Results - By using the RSM approach to run a virtual, robust, optimization with thousands of computations, in addition to running ABAQUS to validate the virtual results, BMW was able to improve the Fatigue Safety Factor by 15%, a solution which also constrained the variation of the measured output to less than 1%.