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The following paper presents an innovative approach to determining vehicle precrash velocity when hitting an immovable obstacle facing forward. Precrash velocity is necessary in order to perform a crash reconstruction. It is needed for the time-space analysis of the events, as well as to assess crash mitigation and to evaluate drivers' technique and tactics. For this task, the authors are using Gaussian Process Regression (GPR). Such an approach offers a number of advantages over the currently used methods that prove to be outdated when considering modern vehicles. The mathematical model was trained on a database shared by the National Highway Traffic Safety Administration. This database covers a large number of crash tests of different kind, however authors focus on frontal collisions of the subcompact car class. Due to low accuracy of linear methods used up till now, Authors developed an innovative approach to determine the EES parameter utilizing Gaussian process regression. The newly developed method is an effective and accurate way to determine the vehicle's velocity and shows promising results, as is demonstrated in this paper. [ABSTRACT FROM AUTHOR]

This paper introduces another approach to pre-crash velocity determination by the means of genetic algorithm model adjustment (GAMA). This innovative method is based on the standard genetic algorithm approach applied to the problem of determining the dependency of predicted variable on given parameters. The experiment is performed on a database obtained from NHTSA (National Highway Traffic Safety Administration), which contains potent number of data samples regarding frontal vehicle crash tests: i.e. vehicle mass, deformation zone and deformation coefficients C1-C6. Various classes of possible functions are considered and the model for determining the pre-crash speed based on the given parameters is obtained. [ABSTRACT FROM AUTHOR]

Serious damage to the inner rim of the rear twin wheel in one dump truck was noted during the operation of the fleet performing transport tasks. It was a drive wheel, and its damage occurred while driving with a load exceeding the permissible value. The examination of selected fragments of the damaged rim surface was conducted visually as well as using a digital microscope with a portable head. The measurements of the Vickers hardness and microscopic observations of the material structure of the sample cut along the thickness of the rim disk were carried out. The drive torque loading of the twin wheels of the tipper-truck rear axle, under their mating with different kinds of road roughness and under various vertical loads of the wheels was calculated. An analysis of stress distributions in the rim modelled using the Finite Element Method was also conducted for several possible scenarios of wheel loading. The damage to the rim was caused by simultaneous action of several factors, such as overloading the car, poor condition of the tires, loading the drive wheel by a part of the vehicle weight and the driving torque, and hitting a wheel on a cavity in a dirt road, causing a temporary relief of one of the tires on a twin wheel. [ABSTRACT FROM AUTHOR]