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Improving Real-Time Methane Monitoring In Longwall Coal Mines Through System Response Characterization Of A Multi-Nodal Methane Detection Network, Brian Philip Cappellini
Improving Real-Time Methane Monitoring In Longwall Coal Mines Through System Response Characterization Of A Multi-Nodal Methane Detection Network, Brian Philip Cappellini
Graduate Theses, Dissertations, and Problem Reports
Machine automation and atmospheric monitoring are used by many industries to improve safety and productivity in the workplace. The underground Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development. The MWS aims to improve safety and productivity by introducing 10 compact sampling units designed to be easily integrated within the current roof support equipment of the mine. Each unit contains an array of sensors used to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. All MWS units report information back to a remote central processing hub (CPH) which collects nodal …
Updates And Improvements To The Satellite Drag Coefficient Response Surface Modeling Toolkit, Phillip Logan Sheridan
Updates And Improvements To The Satellite Drag Coefficient Response Surface Modeling Toolkit, Phillip Logan Sheridan
Graduate Theses, Dissertations, and Problem Reports
For satellites in Low Earth Orbit, the drag coefficient is a major area of uncertainty. Researchers at the Los Alamos National Laboratory have created a Response Surface Modeling (RSM) toolkit to provide the community with a resource for simulating and modeling satellite drag coefficients in Free Molecular Flow. The toolkit combines the high fidelity of numerical simulation techniques with the speed of regression modeling. Specifically, it uses a training sample of drag coefficients simulated with the Test Particle Monte Carlo method with the robust Gaussian Process Regression approach. The RSM toolkit is the prime process to become a toolkit of …