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Transformer Analysis with ANSYS Maxwell and COMSOL

Rodriguez, Angel E.; Tran, Coty; Niederhaus, John H.J.

This is an extension of work described by Rodriguez et al. (2021). It continues analyses of a generic transformer design by Wes Greenwood. In this report, we summarize that work and add comparable results using the ANSYS Maxwell software (henceforward, “ANSYS”), and with COMSOL . We found the ANSYS and COMSOL calculations of inductance agreed well with previous results for simplified coils in air, and with a ferromagnetic core. We then describe the ANSYS and COMSOL approach and show results for a full transformer model based on magnetic field analyses. Finally, we present electrostatic analyses of E field enhancement, once again resolving individual wires. The purpose is to assess the electrostatic fields in order to locate where electric breakdown is likely to originate. We found the maximum enhancement between the secondary and either the primary or the tertiary at the end of the windings with a large potential difference.

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TYPE SAND Report YEAR 2023
DOIOSTI

Notional Chemical Facility PathTrace Modeling Study

Orr, Austin T.; Parks, Mancel J.

This SAND report provides system effectiveness analysis results for notional chemical facilities. Two facilities were analyzed in total, evaluating the effectiveness of the unique security systems in place at each location. Each analysis looked at a range of threat and response capabilities, specific target configurations, and task times to acquire target material in both theft and release scenarios. This report details results for both facilities.

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TYPE SAND Report YEAR 2023
DOIOSTI

Notes on Regression Analysis for Radar Parameter Estimation

Doerry, Armin W.; Bickel, Douglas L.

A fundamental task of radar, beyond merely detecting a target, is to estimate some parameters associated with it. For example, this might include range, direction, velocity, etc. In any case, multiple measurements, often noisy, need to be processed to yield a ‘best estimate’ of the parameter. A common mathematical method for doing so is called “Regression” analysis. The goal is to minimize the expected squared error in the estimate. Even when alternate algorithms are considered, the least squared-error regression analysis is the benchmark against which alternatives are compared.

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TYPE SAND Report YEAR 2023
DOIOSTI
Results 3726–3750 of 99,299
Results 3726–3750 of 99,299