Two-Dimensional Motion of Vehicles Damaged due to Collision

This paper deals with two-dimensional motion analysis of vehicles damaged due to collision. Various parts of vehicles are damaged due to collision in general. The effects of the damage in vehicle body and wheels on the vehicle motions are investigated. The center of gravity of the vehicle and the polar moment of inertia are changed by the deformation of vehicle body. Furthermore, the geometrical relations of wheels like wheelbase, treads and steering angles may be changed by damage of the wheels. Thus the vehicle loses symmetry with respect to the vehicle axis. The four-wheel vehicle model is extended to take into account the vehicle damage due to collision. The motions of damaged vehicles are compared with those of undamaged vehicles. It is found that vehicle damages have a significant influence on vehicle motion after impact.     

A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

REGULATION OF PRODUCTION OF PARATHYROID HORMONE－RELATED PEPTIDE （PTHrP） AND EXPRESSION OF ITS mRNA IN A HUMANLIVER－DERIVED CE

ＲＥＧＵＬＡＴＩＯＮＯＦＰＲＯＤＵＣＴＩＯＮＯＦＰＡＲＡＴＨＹＲＯＩＤＨＯＲＭＯＮＥ－ＲＥＬＡＴＥＤＰＥＰＴＩＤＥ（ＰＴＨｒＰ）ＡＮＤＥＸＰＲＥＳＳＩＯＮＯＦＩＴＳｍＲＮＡＩＮＡＨＵＭＡＮＬＩＶＥＲ－ＤＥＲＩＶＥＤＣＥＬＬＬＩＮＥＬｉＨｕｓｏｎｇ；Ｐ...     

Time-series model for vehicle speeds

This paper presents a time-series model for the spot speeds of vehicles on a road section. Based on time-series analysis techniques, the model incorporates information on the extent of existing dependency between the speeds of successive vehicles. The model for the data is chosen while relying heavily on the data, and thus emphasis is given to their special characteristics. The advantages of using the model are examined with regard to the relative speed of two successive vehicles along a road section. The results are compared with those obtained by using a model of independent observations; fewer errors are obtained with the time-series model. Therefore, it is concluded that the sequence of speed observations contains valuable information which should be incorporated into speed models.     

Further evidence on the temporal stability of disaggregate travel demand models

Current evidence on the transferability of disaggregate travel demand models is inconclusive. Adding to this body of research, the present analysis focuses upon the temporal characteristics of work trip behavior in the San Francisco Bay Area. Using before and after data sets associated with the BART Impact Travel Study, multinomial logit models of work trip modal choice are estimated. The results indicate that the general form and the coefficient estimates of a pre BART model are transferable in time. Moreover, when updated to reflect BART's presence, the model's predictive success and its implied elasticity measures are generally accurate, relative to those implied by reestimating the entire model on post BART data. Finally, as economic theory would predict, elasticity measures of the service related variables were found to increase over time.     

Model-based analysis of the mechanical subsystem of an air brake system

Most commercial vehicles such as buses and trucks use an air brake system, often equipped with an S-cam drum brake, to reduce their speed and/or to stop. With a drum brake system, the clearance between the brake shoe/pad and the brake drum may increase because of various reasons such as wearing of the brake shoe and/or brake drum and drum expansion caused by high heat generation during the braking process. Hence, to ensure proper functioning of the brake system, it is essential that the clearance between the brake shoe and the brake drum is monitored. In this paper, we present a mathematical model for the mechanical subsystem of the air brake system that can be used to monitor this clearance. This mathematical model correlates the push rod stroke transients and the brake chamber pressure transients. A kinematic analysis and a dynamic analysis of the mechanical subsystem of the air brake system were performed, and the results are corroborated with experimental data.     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.