Academic literature on the topic 'Field Crash Reports'

Many years before Charles Elton collected the detailed data on fur returns to The Hudson’s Bay Trading Company, or described the regular fluctuations in small mammal numbers, scientists and naturalists had observed and were proposing explanations for the cause of periodic crashes in numbers of red grouse known as “grouse disease.” MacDonald (1883) claimed “that it was more than eighty years since the alarm of grouse disease was sounded in this country,” implying that naturalists were starting to examine the phenomenon nearly 200 years ago. In 1873, The House of Commons established a Select Committee to consider the game laws of the United Kingdom and, since this had followed a year of particularly severe population collapse in red grouse numbers, they took exhaustive evidence on a wide range of possible causes of “grouse disease.” An examination of the letters in The Times and The Field shows that the debate over the cause of the population crashes was contentious and as heated as many of the recent debates over the causes of population cycles. Scientific studies were initiated by Cobbold (1873) who examined grouse killed during a population crash, published a pamphlet that described the presence of large numbers of “strongle worms,” and advocated the theory that the cause of grouse disease was wholly due to the presence of nematode worms. In 1905, the Board of Agriculture appointed a Committee of Inquiry on Grouse Disease to investigate the life history of the parasite and the causes of “grouse disease.” The extensive survey and detailed analysis was quite remarkable for the time, and was presented in a two-volume publication (Lovat 1911). The Committee surveyed grouse populations, undertook experiments and, after nearly 2000 dissections, came to the conclusion that “the strongyle worm, and the strongyle worm alone, is the immediate causa causans of adult ‘Grouse Disease.’“ The Principal Field Officer was E. A. Wilson, a gifted artist and scientist who was later appointed as the Scientific Director to Captain Scott’s Antarctic expedition on the Terra Nova. Unfortunately, Wilson never saw the production of the final report as he died with Scott during their return from the South Pole.

Motor vehicle fatalities and injuries remain a leading public health problem worldwide. In 2009, the World Health Organization reported more than 1.2 million people die each year worldwide as a result of motor vehicle crash [1]. Researchers are using a wide array of tools to mitigate the societal tool of this epidemic, and finite element (FE) computer models are one method gaining interest in the biomechanics field. Full body FE models are used to examine the potential for occupant injury in vehicle crash. Such models are often built to represent an average (50 th percentile) male occupant [2]

Utilization of magnesium alloys within the field of vehicle design offers substantial opportunity for mass reduction. This has resulted in a wide range of automotive applications. More recently, the scope of application has been extended to include components that are considered crash critical. However, the magnesium die casting process is widely reported as producing parts that exhibit large local variation in part properties. Hence, this introduces the technical challenge of how to design effectively based upon these constraints. In order to better understand this phenomenon, two large size

Syntactic foams are a class of particulate composites made with hollow microspheres dispersed uniformly in a matrix. By the inclusion of hollow spheres in the matrix, the bulk mechanical properties are improved by limiting the bending of cell edges and localization of inelastic deformation, which is the cause of failure in the case of low-density foams. For the general class of cellular materials, several analytical and experimental methods are available in the literature to characterize the material. In the case of syntactic foams, relatively few methods exist for the computation of effective

We view the most important question in evaluation of a computer model to be: Does the computer model provide predictions that are accurate enough for the intended use of the model? The purpose of this presentation is to discuss a systematic six-step model validation process intended to help answer that question. This will be done by presenting a Bayesian statistical strategy for developing error bounds on model predictions with the interpretation that there is a specified confidence (e.g. 80%) that the corresponding true process value will lie within the range of these error bounds. Although s

Right-turn lane (RTL) crashes are among the most key contributors to intersection crashes in the US. Different right turn lanes based on their design, traffic volume, and location have varying levels of crash risk. Therefore, engineers and researchers have been looking for alternative ways to improve the safety and operations for right-turn traffic. This study investigates the traffic safety performance of the RTL in Indiana state based on multi-sources, including official crash reports, official database, and field study. To understand the RTL crashes' influencing factors, we introduce a rand