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Optimization and Uncertainty Analysis of a Diesel Engine Operating Point Using CFD

SmartUQ and Convergence Science

This study optimizes a diesel engine operating point using an analytical model constructed by sequential design of experiments (DOEs) and then compares the results to a genetic algorithm (GA). Additionally, the analytical model quantifies the uncertainty of the diesel engine operating point.

The DOE method found an optimum with 0.401% improvement in merit and 0.429% improvement in gISFC over the baseline case. The GA method found a slightly better optimum with 0.454% improvement in merit and gISFC, but the DOE method would take a week to run where the GA method would take about two months.

Additionally, the DOE method provided added value in understanding the uncertainty surrounding the optimum point.

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