Engineering topics

Joshi, Tenzing H. Y.

Publications and source records attributed to Joshi, Tenzing H. Y..

3 records

DOE OSTI2024

Surrogate Distributed Radiological Sources—Part II: Aerial Measurement Campaign

In this second part of a multipaper series, we present results from outdoor aerial measurements of surrogate distributed gamma-ray sources. Here we detail the design, manufacture, and testing of 300 individual ~7 mCi Cu-64 sealed sources at the Washington State University (WSU) research reactor and their deployment in various source patterns (each comprising up to 100 point sources) during the aerial measurement campaign. We show the results of two such measurements, in which approximate source shapes and qualitative source intensities can be seen from the count rate versus position plots, even without performing reconstructions. We also detail our efforts in ground-truthing the deployed sources and comparing measured gamma-ray data to model predictions. In particular, we compare measured versus expected count data using the Poisson deviance formalism of Part I to evaluate whether the fielded surrogate point-source arrays “look like” their truly continuous distributed source analogs. More generally, we find that the point-source array technique provides high source placement accuracy, relative ease of quantifying the true source configuration, scalability to source dimensions of ≲100 m, ease of reconfiguration and removal, and relatively low dose to personnel. Finally, we consider potential improvements and generalizations of the point-source array technique for future measurement campaigns.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Correlations Between Panoramic Imagery and Gamma-Ray Background in an Urban Area

When searching for radiological sources in an urban area, a vehicle-borne detector system will often measure complex, varying backgrounds primarily from natural gamma-ray sources. Much work has been focused on developing spectral algorithms that retain sensitivity and minimize the false-positive rate even in the presence of such spectral and temporal variability. However, information about the environment surrounding the detector system might also provide useful clues about the expected background, which if incorporated into an algorithm, could improve performance. Recent work has focused on extensive measuring and modeling of urban areas with the goal of understanding how these complex backgrounds arise. This work presents an analysis of panoramic video images and gamma-ray background data collected in Oakland, California, by the radiological multisensor analysis platform (RadMAP) vehicle. Features were extracted from the panoramic images by semantically labeling the images and then convolving the labeled regions with the detector response. A linear model was used to relate the image-derived features to gamma-ray spectral features obtained using nonnegative matrix factorization (NMF) under different regularizations. Here we find some gamma-ray background features correlate strongly with image-derived features that measure the response-adjusted solid angle subtended by sky and buildings, and we discuss the implications for the development of future, contextually aware detection algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Gamma-Ray Point-Source Localization and Sparse Image Reconstruction using Poisson Likelihood

Gamma-ray imaging trys to reconstruct the spatial and intensity distribution of gamma-emitting radionuclides from a set of measurements. Wholly, this problem is solved by discretizing the spatial dimensions and employing the maximum likelihood expectation maximization (ML-EM) algorithm, with or without some form of regularization. While the generality of this formulation enables use in a wide variety of scenarios, it is susceptible to overfitting, limited by the discretization of spatial coordinates, and can be computationally expensive. We present a novel approach to 3D gamma-ray image reconstruction for scenarios where sparsity may be assumed, for example radiological source search. In this work we first formulate a point-source localization (PSL) approach as an optimization problem where both position and source intensity are continuous variables. We then extend and generalize this formulation to an iterative algorithm called additive point-source localization (APSL) for sparse parametric image reconstruction. A set of simulated source search scenarios using a single non-directional detector are considered, finding improved image accuracy and computational efficiency with APSL over traditional grid-based methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗