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DSI3D-RCS: Theory manual

Description: The DSI3D-RCS code is designed to numerically evaluate radar cross sections on complex objects by solving Maxwell`s curl equations in the time-domain and in three space dimensions. The code has been designed to run on the new parallel processing computers as well as on conventional serial computers. The DSI3D-RCS code is unique for the following reasons: Allows the use of unstructured non-orthogonal grids, allows a variety of cell or element types, reduces to be the Finite Difference Time Domain (FDTD) method when orthogonal grids are used, preserves charge or divergence locally (and globally), is conditionally stable, is non-dissipative, is accurate for non-orthogonal grids. This method is derived using a Discrete Surface Integration (DSI) technique. As formulated, the DSI technique can be used with essentially arbitrary unstructured grids composed of convex polyhedral cells. This implementation of the DSI algorithm allows the use of unstructured grids that are composed of combinations of non-orthogonal hexahedrons, tetrahedrons, triangular prisms and pyramids. This algorithm reduces to the conventional FDTD method when applied on a structured orthogonal hexahedral grid.
Date: March 16, 1995
Creator: Madsen, N.; Steich, D.; Cook, G. & Eme, B.
Partner: UNT Libraries Government Documents Department

DSI3D-RCS test case manual

Description: The DSI3D-RCS code is designed to numerically evaluate radar cross sections on complex objects by solving Maxwell`s curl equations in the time-domain and in three space dimensions. The code has been designed to run on the new parallel processing computers as well as on conventional serial computers. The DSI3D-RCS code has been used to solve the following problems: (1) wedge cylinder--thin flat metal plate; (2) wedge cylinder with plate extension--thin flat metal plate; (3) plate with half cylinder extension--thin flat metal plate; (4) rectangular plate (business card)--thin flat metal plate; (5) wedge cylinder with gap--thin flat metal plate; (6) NASA Almond; (7) wavelength circular cavity. In order to generate each of the angle sweeps, it was necessary to run DSI3D once for each data point on the graphs. This is because these are backscatter calculations, and the incident pulse comes from a different direction as the angle {phi} is changed.
Date: August 1, 1995
Creator: Madsen, N.; Steich, D.; Cook, G. & Eme, B.
Partner: UNT Libraries Government Documents Department

Integration of AMS and ERDS Measurement Data into NARAC Dispersion Models FY05 Technology Integration Project Final Report

Description: Staff from Lawrence Livermore National Laboratory (LLNL), Bechtel Nevada Remote Sensing Laboratory (RSL), and Sandia National Laboratory (SNL) completed the proposed work for the Technology Integration Project titled Integration of AMS and ERDS Measurement Data into NARAC Dispersion Models. The objectives of this project were to develop software to convert Aerial Measurement Survey (AMS) and Emergency Response Data System (ERDS) field measurement data into a standard electronic format for transmission to the National Atmospheric Release Advisory Center (NARAC), and to streamline aspects of the NARAC operational atmospheric dispersion modeling system to quickly process these data for use in generating consequence calculations based on refined, field measurement-based estimates of the source strength. Although NARAC continues to develop and maintain a state-of-the-art atmospheric dispersion modeling system, model predictions are constrained by the availability of information to properly characterize the source term. During an actual atmospheric release, very little may be known initially about the source material properties, amount, or release time and location. Downwind measurements often provide the best information about the scope and nature of the release. The timely integration of field measurement data with model calculations is an obvious approach toward improving the model consequence predictions. By optimizing these predictions a more accurate representation of the consequences may be provided to (a) predict contamination levels which may be below the detectable limit of sensors, but which may still pose a significant hazard, (b) determine contamination is areas where measurements have not yet been made, and (c) prioritize the locations of future measurement surveys. By automating and streamlining much of the related field measurement data processing, these optimized predictions may be provided within a significantly reduced period, and with a reduction in potential errors. The associated operational shortfalls were resolved by completing the following major tasks under this technology integration project: ...
Date: September 20, 2005
Creator: Foster, K.; Arnold, E.; Bonner, D.; Eme, B.; Fischer, K.; Gash, J. et al.
Partner: UNT Libraries Government Documents Department

Advances in National Capabilities for Consequence Assessment Modeling of Airborne Hazards

Description: This paper describes ongoing advancement of airborne hazard modeling capabilities in support of multiple agencies through the National Atmospheric Release Advisory Center (NARAC) and the Interagency Atmospheric Modeling and Atmospheric Assessment Center (IMAAC). A suite of software tools developed by Lawrence Livermore National Laboratory (LLNL) and collaborating organizations includes simple stand-alone, local-scale plume modeling tools for end user's computers, Web- and Internet-based software to access advanced 3-D flow and atmospheric dispersion modeling tools and expert analysis from the national center at LLNL, and state-of-the-science high-resolution urban models and event reconstruction capabilities.
Date: November 26, 2007
Creator: Nasstrom, J; Sugiyama, G; Foster, K; Larsen, S; Kosovic, B; Eme, B et al.
Partner: UNT Libraries Government Documents Department