Load spectrum is a decisive factor that is used to analyze fatigue, reliability, and durability of components. In this article, the typical load spectrum of proving ground is collected through load measurement equipment. Load-spectrum preprocessing, including spikes filter, signal denoising, and low-amplitude load elimination, are completed. According to parts correlation of automotive transmission systems, the load transmission route is established. The Monte Carlo sampling is applied to analyze interference of random factors in the process of load transfer route. Load spectrum of key parts of the automobile is determined and thus rain flow counting analysis is scheduled. A non-parametric method is used to complete load-spectrum extrapolation. Eventually, one-dimensional and two-dimensional programming load spectrums are built. The technical basis for fatigue life prediction and references for other similar researches are provided in this article.
Introduction:The drift-diffusion model of charge transport neglects non-local effects and does not always give results of adequate accuracy for submiciron device modeling. More general transport models have computational resource requirements that are typically one to six orders of magnitude greater. There is consequently interest in developing "augmented drift-diffusion" transport models which retain most of the efficiency of drift-diffusion but improve its accuracy [l-61. Recent results [6] suggest that the use of augmented drift-diffusion models in general purpose device simulators is both desirable and achievable. For various reasons (including one dimensional assumptions, problems with built-in fields, and neglect of undershoot) none of the existing formulations is satisfactory for this purpose. This paper presents a new formulation of augmented drift-diffusion transport that is suitable for inclusion in general purpose device simulators.
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