The automotive industry has been increasingly challenged to invest heavily in innovative powertrain technologies. These advancements can result in a complex array of tunable control parameters to optimize engine performance over a range of operating conditions. Hence, the calibration process of a modern passenger car diesel engine consumes significant time, effort and resources, making it a bottleneck during the development process. Advanced modeling tools, such as CFD, are often used with the goal of streamlining portions of the calibration process. The usefulness of CFD simulations tools for in-cylinder engine combustion is often compromised by the computational overhead of detailed chemical kinetics and uncertainty in the combustion chamber wall temperatures. Specifically, traditional diesel engine CFD simulations consist of partial geometry sector mesh computations utilizing reduced order kinetics mechanisms, fixed spatially uniform wall temperature boundary conditions, and a prescribed solid body swirl velocity field prior to spray injection in lieu of computing air induction with valve motion. The proposed research seeks to leverage recent advancements in CFD to improve the accuracy CFD computations and accelerate engine calibration. First, higher order kinetics will be solved using a GPU based chemical kinetics solver (leveraged in past ALCC awards CMB119 and CMB124). Next, full in-cylinder 3D spray, flow and combustion simulations will be undertaken considering conjugate heat transfer to predict temporally and spatially varying wall temperature boundary conditions. The results will be analyzed to compare differences in combustion and emissions (NOx, CO, UBHC, Smoke) with actual engine measurements.
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