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Service loading histories have the same general character for an individual route and the magnitudes vary from driver to driver. Both the magnitude and character of the loading history change from route to route and a linear scaling of one loading history does not characterize the variability of usage over a wide range of operating conditions. In this paper a technique for measuring and extrapolating cumulative exceedance diagrams to quantify the distribution of service loading in a vehicle is described. Monte Carlo simulations are coupled with the local stress strain approach for fatigue to obtain distributions of service loading. Fatigue life estimates based on the original loading histories are compared to those obtained from statistical descriptions of exceedance diagrams.

The purpose this paper is to delineate why there exists a trade-off between biomechanical realism and algorithmic efficiency for human motion simulation models, and to illustrate how empirical human movement data and findings can be integrated with novel modeling techniques to overcome such a realism-efficiency tradeoff. We first review three major classes of biomechanical models for human motion simulation. The review of these models is woven together by a common fundamental problem of redundancy—kinematic and/or muscle redundancy. We describe how this problem is resolved in each class of models, and unveil how the trade-off arises, that is, how the computational demand associated with solving the problem is amplified as a model evolves from small scale to large scale, or from less realism to more realism.

The ability to categorize, compare and segregate the roll dynamical behavior of various vehicles from one another is a subject of considerable research interest. A number of comparison paradigms have been developed (static stability index, roll couple methods, etc.), but all suffer from lack of robustness: results developed on the basis of a particular comparison metric are often not able to be generalized across vehicle lines and types, etc., or they simply do not segregate vehicles at all. In addition, most models do not describe vehicle dynamics in sufficient detail, and some contain no dynamics at all (e.g., static stability index = t/2h). In the present work, static stability index, a two-degree-of-freedom roll model and a three-degree-of-freedom roll and handling model were used to locate eigenvalues for a sample of 43 vehicles consisting of (1) passenger cars, (2) light trucks, (3) sport/utility vehicles and (4) minivans.

A multicomponent fuel film vaporization model using continuous thermodynamics is developed for multidimensional spray and wall film modeling. The vaporization rate is evaluated using the turbulent boundary-layer assumption and a quasi-steady approximation. Third-order polynomials are used to model the fuel composition profiles and the temperature within the liquid phase in order to predict accurate surface properties that are important for evaluating the mass and moment vaporization rates and heat flux. By this approach, the governing equations for the film are reduced to a set of ordinary differential equations and thus offer a significant reduction in computational cost while maintaining adequate accuracy compared to solving the governing equations for the film directly.

This paper examines the feasibility of modifying an existing semi-trailer air suspension system to function as an anti-rollover system in addition to its normal suspension operation. The semi-trailer model used is a dynamic, two-dimensional system. The anti-rollover system controller is formulated using projective control theory. All other factors being equal, simulations show that use of the modified suspension system decreases the weight shift when the semi-trailer undergoes lateral acceleration. By decreasing weight shift, the modified suspension system decreases the possibility of rollover.

An efficient multi-component fuel droplet vaporization model has been developed in this work using discrete approach. The precise modeling of droplet vaporization process is divided into two parts: vapor-phase and liquid-phase sub-models. Temporal evolution of flow inside the droplet is considered to describe the transient behavior introduced by the slow diffusion process. In order to account for the internal circulation motion, surface regression and finite diffusion without actually resolving the spatial governing equations within the liquid phase, a set of ordinary differential equations is applied to describe the evolution of the non-uniform distributions of universal diffusional variables, i.e. temperature and species mass fraction. The differences between the droplet surface and bulk mean states are modeled by constructing a quasi-1D frame; the effect of the internal circulations is taken into consideration by using the effective diffusivity rather than physical diffusivity.

A numerical investigation of air-fuel mixing in gasoline direct-injection (GDI) engines is presented in this paper. The primary goal of this study is to demonstrate the importance of fuel representation. In the past studies, fuel has been usually modeled as a single component substance. However, most fuels are mixtures of hydrocarbons with diverse boiling points, resulting in mixture vaporization behavior substantially different from single-component behavior. This study presents a newly developed multicomponent vaporization model, which takes into account important mechanisms such as preferential vaporization, internal circulation, surface regression, and non-ideal behavior in high-pressure environments. A sheet spray atomization model was also used to calculate the disintegration of the liquid sheet and the breakup of the subsequent droplets. The results of a single-component fuel representation and a multicomponent fuel representation were compared.