Is this project an undergraduate, graduate, or faculty project?

Undergraduate

group

Daytona Beach

Poster Session; 5-minute Oral Presentation; 10-minute Oral Presentation

Authors' Class Standing

Emma Galligan, Senior Grant Johnson, Senior DeAndre Lesley, Senior

Lead Presenter's Name

Emma Galligan

Faculty Mentor Name

Mihhail Berezovski

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Abstract

The Disruptive Technologies Group in the National Security Directorate of Pacific Northwest National Laboratory teamed up with students at Embry-Riddle Aeronautical University on a research project that aims to develop quantitative methods for characterizing features in radiation transport simulation data and comparing features across different computational approaches. Understanding how radiation particles are transported throughout a system and interact with shielding is extremely computationally expensive. Reduced order models (ROMs) can be used to significantly increase the speed of these calculations. This project focuses on analysis of the simulated radiation transport for Cobalt-60, Cesium-137, and Technetium-99. A ROM may be developed from several formalisms and then analyzing the feature vectors of each. The methods considered here include principal component analysis (PCA), non-negative matrix factorization (NNMF), and CP tensor decomposition (CPT). By comparing the signal from fitted Lorentzian profiles to spectral features, we evaluate whether each ROM is capable of accurately displaying the radiation signal traces in the data.

Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, or Ignite Grants) from the Office of Undergraduate Research?

No

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PNNL - Using Matrix and Tensor Factorization for Analyzing Radiation Transport Data

The Disruptive Technologies Group in the National Security Directorate of Pacific Northwest National Laboratory teamed up with students at Embry-Riddle Aeronautical University on a research project that aims to develop quantitative methods for characterizing features in radiation transport simulation data and comparing features across different computational approaches. Understanding how radiation particles are transported throughout a system and interact with shielding is extremely computationally expensive. Reduced order models (ROMs) can be used to significantly increase the speed of these calculations. This project focuses on analysis of the simulated radiation transport for Cobalt-60, Cesium-137, and Technetium-99. A ROM may be developed from several formalisms and then analyzing the feature vectors of each. The methods considered here include principal component analysis (PCA), non-negative matrix factorization (NNMF), and CP tensor decomposition (CPT). By comparing the signal from fitted Lorentzian profiles to spectral features, we evaluate whether each ROM is capable of accurately displaying the radiation signal traces in the data.

 

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