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publications

Evaluating 3D Gamma-ray Imaging Techniques for Distributed Sources at the Fukushima Daiichi Nuclear Power Station

Published in 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2020

Polaris-Lamp,a commercially available detector that has been integrated with contextual sensors, was hand-carried in a parking lot containing vehicles used during remediation efforts following the March 2011 Fukushima Daiichi Nuclear Power Station accident.

Recommended citation: K. Knecht et. al., "Evaluating 3D Gamma-ray Imaging Techniques for Distributed Sources at the Fukushima Daiichi Nuclear Power Station," in Proc. NSS/MIC, 2020, pp. 1-5. https://ieeexplore.ieee.org/abstract/document/9507840/

Polaris-LAMP: Multi-modal 3D Image Reconstruction with a Commercial Gamma-ray Imager

Published in IEEE Transactions on Nuclear Science, 2021

The Polaris-LAMP multi-modal 3D gamma-ray imager is a radiation mapping and imaging platform which uses a commercial-off-the-shelf detector integrated with a contextual sensor localization and mapping platform.

Recommended citation: J. Hecla and K. Knecht et. al.. "Polaris-LAMP: Multi-modal 3D Image Reconstruction with a Commercial Gamma-ray Imager" IEEE Trans. Nucl. Sci., vol. 68, no. 10, pp. 2539-2549, Oct. 2021, doi: 10.1109/TNS.2021.3110162. https://ieeexplore.ieee.org/abstract/document/9528363/

3D Compton Imaging of Distributed Sources around the Chernobyl Nuclear Power Plant

Published in 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2021

Here, we present results employing Compton image reconstruction in combination with SDF of data that were collected over series of 20-50 minute dynamic measurements around Pripyat, a nearby town which has been abandoned since the accident in 1986 and in some locations within ChNPP.

Recommended citation: K. Knecht et. al., "3D Compton Imaging of Distributed Sources around the Chernobyl Nuclear Power Plant," in Proc. NSS/MIC, 2021, pp. 1-4. https://ieeexplore.ieee.org/abstract/document/9507840/

From the Field

Published in Berkeley Science Review Spring 2022, 2022

Late in the night on April 26, 1986, Chornobyl Nuclear Power Plant Unit 4 was scheduled for routine safety testing. Preparations for testing left the reactor in an unstable condition, resulting in a meltdown followed by explosions that destroyed the reactor building and released radioactive material for many days after.

Recommended citation: K. Knecht, "From the Field," in Proc. NSS/MIC, 2022.

Scene-Informed Optimization of Measurement Locations for Radiological Assessment

Published in 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2022

Recommended citation: K. Knecht et. al., "Scene-Informed Optimization of Measurement Locations for Radiological Assessment," in Proc. NSS/MIC, 2022.

Scene-Informed Optimal Measurement Positions for Quantitative Safeguards Measurement

Published in 2023 INMM & ESARDA Joint Annual Meeting, 2023

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gammaray imaging through scene data fusion (SDF). While developed for free-moving measurements, SDF also has applications in cases that require multiple static measurements to generate quantitative 3D images, where the scene information can improve results. The scene information captured by these devices can be leveraged to determine optimal measurement positions for quantification measurements, such as in safeguards applications, where limited time is provided to quantify nuclear material present. In this work the scene information obtained from contextual sensors is used to construct a 3D voxel grid.

Recommended citation: K. Knecht et. al., "Scene-Informed Optimal Measurement Positions for Quantitative Safeguards Measurement," in Proc. INNM & ESARDA Joint Annual Meeting, 2023. https://resources.inmm.org/annual-meeting-proceedings/scene-informed-optimal-measurement-positions-quantitative-safeguards

Enhanced use of contextual data for quantitative Compton Imaging

Published in 2023 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2023

In this work the scene information obtained from contextual sensors is used to construct a 3D voxel grid. A 3D object of interest within this grid is selected by an operator either manually or automatically through an object detection machine learning framework. A number of potential measurement positions and orientations (poses) around this object of interest are identified, and the sensitivity to each of the object voxels from each of these poses is computed.

Recommended citation: K. Knecht et. al., "Enhanced use of contextual data for quantitative Compton Imaging," in Proc. NSS/MIC, 2023.

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015