Engineering topics

Sen, Satyabrata

Publications and source records attributed to Sen, Satyabrata.

3 records

DOE OSTI2020

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗

DOE OSTI2020

Automated Vehicle Detection in a Nuclear Facility Using Low-Frequency Acoustic Sensors

This article presents an analysis of the method of construction and results for a classifier intended to identify vehicles using low-frequency acoustic data collected by a dis-tributed sensor network. This data is collected as part of a venture intended to explore data analytics and multisensor fusion techniques for the monitoring of activities at a test bed nuclear facility located at Oak Ridge National Laboratory in Oak Ridge, Tennessee. We describe the associated target signature and design a classifier based on a multilayer perceptron, followed by an analysis of its results. We discuss how overall accuracy is not the only consideration in constructing this classifier, and how for this application, it is actually desirable to operate at a lower level of accuracy in exchange for a reduction in the false alarm rate, as well as how this relates to the actual deployment of the classifier in practical use.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2020

Detecting Low-level Radiation Sources Using Border Monitoring Gamma Sensors

We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"x2" NaI Gamma sensors deployed on the periphery of 42m x 42m outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.

Sen, Satyabrata↗