On-Road Versus Simulator Data in Driver Model Development Driver Performance Model Experience

Author(s):  
Alvah C. Bittner ◽  
Ozgur Simsek ◽  
William H. Levison ◽  
John L. Campbell
Author(s):  
Michael Gorelik ◽  
Jacob Obayomi ◽  
Jack Slovisky ◽  
Dan Frias ◽  
Howie Swanson ◽  
...  

While turbine engine Original Equipment Manufacturers (OEMs) accumulated significant experience in the application of probabilistic methods (PM) and uncertainty quantification (UQ) methods to specific technical disciplines and engine components, experience with system-level PM applications has been limited. To demonstrate the feasibility and benefits of an integrated PM-based system, a numerical case study has been developed around the Honeywell turbine engine application. The case study uses experimental observations of engine performance such as horsepower and fuel flow from a population of engines. Due to manufacturing variability, there are unit-to-unit and supplier-to-supplier variations in compressor blade geometry. Blade inspection data are available for the characterization of these geometric variations, and CFD analysis can be linked to the engine performance model, so that the effect of blade geometry variation on system-level performance characteristics can be quantified. Other elements of the case study included the use of engine performance and blade geometry data to perform Bayesian updating of the model inputs, such as efficiency adders and turbine tip clearances. A probabilistic engine performance model was developed, system-level sensitivity analysis performed, and the predicted distribution of engine performance metrics was calibrated against the observed distributions. This paper describes the model development approach and key simulation results. The benefits of using PM and UQ methods in the system-level framework are discussed. This case study was developed under Defense Advanced Research Projects Agency (DARPA) funding which is gratefully acknowledged.


Author(s):  
Chaoqin Zhai ◽  
David H. Archer ◽  
John C. Fischer

This paper presents the development of an equation based model to simulate the combined heat and mass transfer in the desiccant wheels. The performance model is one dimensional in the axial direction. It applies a lumped formulation in the thickness direction of the desiccant and the substrate. The boundary conditions of this problem represent the inlet outside/process and building exhaust/regeneration air conditions as well as the adiabatic condition of the two ends of the desiccant composite. The solutions of this model are iterated until the wheel reaches periodic steady state operation. The modeling results are obtained as the changes of the outside/process and building exhaust/regeneration air conditions along the wheel depth and the wheel rotation. This performance model relates the wheel’s design parameters, such as the wheel dimension, the channel size and the desiccant properties, and the wheel’s operating variables, such as the rotary speed and the regeneration air flowrate, to its operating performance. The impact of some practical issues, such as wheel purge, residual water in the desiccant and the wheel supporting structure, on the wheel performance has also been investigated.


1970 ◽  
Vol 9 (3) ◽  
pp. 326-337 ◽  
Author(s):  
A. Boltax ◽  
P. Murray ◽  
A. Biancheria

2016 ◽  
Vol 123 ◽  
pp. 192-204 ◽  
Author(s):  
Junjing Yang ◽  
Mattheos Santamouris ◽  
Siew Eang Lee ◽  
Chirag Deb

2011 ◽  
Vol 84 (4) ◽  
pp. 493-506
Author(s):  
Irene S. Yurovska ◽  
Michael D. Morris ◽  
Theo Al

Abstract Racing tires and motorcycle tires present individual segments of the tire market. For instance, while the average life of car and truck tires is 50 000 miles, the average life of race tires is 100 miles. Because tires play a critical role in a race, technical demands to assure safety and performance are growing. Similarly, tires have a large influence on safety, handling/grip, and performance of the rapidly growing world fleet of motorcycles, due to the fact of only two wheels being in contact with the ground. Thus, the common feature of both market segments is that the typical tire compromise of wear, rolling resistance, and traction is strongly weighted toward traction. Most of the recent efforts of rubber scientists have been directed toward lowering rolling resistance of the tread compounds, which left a certain void in the science of compounding for racing and motorcycle treads. Particularly, the industrial assortment of polymers and fillers used for motorcycle treads is commonly different from that used for car or truck treads, but it is not known how the filler properties affect the hysteresis–stiffness compromise. The objective of this study is to evaluate the effects of the carbon black characteristics on the important properties of a typical racing and motorcycle tire tread compound. More than 50 individual carbon blacks were mixed in a SBR formulation. The acquired data were statistically analyzed, and a linear multiple regression model was developed to relate rubber properties (responses), such as static modulus, complex dynamic modulus, hysteresis, and viscosity to the key carbon black characteristics (variables) of surface area, structure, aggregate size distribution, and surface activity. Prediction profiles created from the model demonstrate rubber performance limits for the range of carbon blacks tested, and indicate the niches to provide required combinations of the rubber properties.


Author(s):  
William H. Levison ◽  
Ozgur Simsek ◽  
Alvah C. Bittner ◽  
Steven J. Hunn

The Interactive Highway Safety Design Model (IHSDM) is a high-priority research area for FHWA. IHSDM is a software system for evaluating the safety of alternative highway designs in a computer-aided design environment. The initial phase of this research program is to develop IHSDM for use in the design of two-lane rural highways. IHSDM includes a driver-vehicle module that simulates the moment-to-moment actions of a single driver-vehicle unit. Reviewed are the computational approaches that have guided the implementation of the driver performance model (DPM) that along with a vehicle model and other components constitute the driver-vehicle module. Five major computational functions of DPM are reviewed: perception, speed decision, path decision, speed control, and path control. Comparison of model results with data from a driving simulator demonstrates the ability of DPM to account for the horizontal curve deflection angle on the speed profile.


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