During the summer of 1983, a series of pool fire tests was conducted in which the test item was a 1.4 m diameter, 6 . 9 m long, mild steel calorimeter with a mass of approximately 10,000 kg. of these tests was to study the thermal response of a large test item in a specified fire configuration, to define thermal boundary conditions, and to assess the repeatability of the fire environment. The calorimeter was used to simulate a nuclear waste transportation cask in both a geometric and thermal sense.The purpose INTRODUCTION
In support of the Cassini Mission Final Safety Analysis Report (FSAR), Sandia National Laboratories (SNL) was requested by Lockheed Martin Corporation (LMC) to investigate for various scenarios, the distribution of aerosol and particulate mass in a stabilized buoyant plume created as a result of a fireball explosion. The information obtained from these calculations is to provide background information for the radiological consequence analysis of the FSAR. Specifically, the information is used to investigate the mass distribution within the "cap and stem" portions of the initial fireball plume, a modeling feature included in the SATRAP module in the LMC SPARRC code. The investigation includes variation of the plume energy and the application of several meteorological conditions for a total of seven sensitivity case studies. For each of the case studies, the calculations were performed for two configurations of particle mass in the plume (total mass and plutonium mass).ii This page intentionally left blank.iii
This paper describes the application of directed genetic programming to explore the functional form of non-linear restoring forces that arise due to micro-slip friction. Data are obtained from an experiment to investigate the friction forces in a simple shear interface subjected to a vibration environment. A candidate functional form is proposed to model this friction, and a genetic search is then performed which seeks optimal parameters for the function. The resulting parameters provide the best fit of the proposed functional to the experimental data.
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