Global ETD Search

1	Accuracy and Computational Stability of Tensorally-Correct Subgrid Stress and Scalar Flux Representations in Autonomic Closure of LES January 2020 (has links) abstract: Autonomic closure is a recently-proposed subgrid closure methodology for large eddy simulation (LES) that replaces the prescribed subgrid models used in traditional LES closure with highly generalized representations of subgrid terms and solution of a local system identification problem that allows the simulation itself to determine the local relation between each subgrid term and the resolved variables at every point and time. The present study demonstrates, for the first time, practical LES based on fully dynamic implementation of autonomic closure for the subgrid stress and the subgrid scalar flux. It leverages the inherent computational efficiency of tensorally-correct generalized representations in terms of parametric quantities, and uses the fundamental representation theory of Smith (1971) to develop complete and minimal tensorally-correct representations for the subgrid stress and scalar flux. It then assesses the accuracy of these representations via a priori tests, and compares with the corresponding accuracy from nonparametric representations and from traditional prescribed subgrid models. It then assesses the computational stability of autonomic closure with these tensorally-correct parametric representations, via forward simulations with a high-order pseudo-spectral code, including the extent to which any added stabilization is needed to ensure computational stability, and compares with the added stabilization needed in traditional closure with prescribed subgrid models. Further, it conducts a posteriori tests based on forward simulations of turbulent conserved scalar mixing with the same pseudo-spectral code, in which velocity and scalar statistics from autonomic closure with these representations are compared with corresponding statistics from traditional closure using prescribed models, and with corresponding statistics of filtered fields from direct numerical simulation (DNS). These comparisons show substantially greater accuracy from autonomic closure than from traditional closure. This study demonstrates that fully dynamic autonomic closure is a practical approach for LES that requires accuracy even at the smallest resolved scales. / Dissertation/Thesis / Doctoral Dissertation Aerospace Engineering 2020 Fluid mechanics Computational physics Combustion Computational Fluid Dynamics Fluid Sciences Large Eddy Simulation Machine Learning Turbulence
2	A fundamental approximation in MATLAB of the efficiency of an automotive differential in transmitting rotational kinetic energy Vaughn, James Roy 30 July 2012 (has links) The VCOST budgeting tool uses a drive cycle simulator to improve fuel economy predictions for vehicle fleets. This drive cycle simulator needs to predict the efficiency of various components of the vehicle's powertrain including any differentials. Existing differential efficiency models either lack accuracy over the operating conditions considered or require too great an investment. A fundamental model for differential efficiency is a cost-effective solution for predicting the odd behaviors unique to a differential. The differential efficiency model itself combines the torque balance equation and the Navier-Stokes equations with models for gear pair, bearing, and seal efficiencies under a set of appropriate assumptions. Comparison of the model with existing data has shown that observable trends in differential efficiency are reproducible in some cases to within 10% of the accepted efficiency value over a range of torques and speeds that represents the operating conditions of the differential. Though the model is generally an improvement over existing curve fits, the potential exists for further improvement to the accuracy of the model. When the model performs correctly, it represents an immense savings over collecting data with comparable accuracy. / text Differential Automotive Automobile Final drive Gear Windage Bearing Seal VCOST Fuel economy Efficiency Powertrain Drivetrain Power train Drive train Model MATLAB Light-duty Heavy-duty Dual differential Tandem axle Tag axle Lubricant ATF Automatic transmission fluid Society of Automotive Engineers Walther Sutherland Wheel drive Transaxle Thermal/fluid sciences TFS TxDOT Texas Department of Transportation

Search results

Accuracy and Computational Stability of Tensorally-Correct Subgrid Stress and Scalar Flux Representations in Autonomic Closure of LES

A fundamental approximation in MATLAB of the efficiency of an automotive differential in transmitting rotational kinetic energy