Domain-Informed Assessment of Nuclear Reactor Operations.
Abstract not provided.
Reichardt, Thomas A.↗
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Production of Xenon-135 from isotopically enriched Xenon-134 and Xenon-136 Targets
Atmospheric radioxenon analyses conducted under the Comprehensive Test Ban Treaty Organization (CTBTO) necessitates the collection and analysis of air samples to quantify 135Xe, an indicator for nuclear explosions and reactor operations. Analytical instrument calibration for these analyses requires high quality, monoisotopic reference standards that are typically short lived, and therefore must be produced and shipped promptly to monitoring stations worldwide. This work describes the preparation of 135Xe by neutron capture (n, ?) on monoisotopic 134Xe, neutron irradiation (n,2n) on monoisotopic 136Xe, and high energy photon irradiation (?, n) on monoisotopic 136Xe. The targets are prepared by electromagnetic isotope separation of natural xenon. Results from each process are compared for 135Xe yield and purity.
07 ISOTOPE AND RADIATION SOURCES↗
Multi-Sensor Data Acquisition System for Process Monitoring
Idaho National Laboratory is building a new nuclear fuel cycle test bed. This fuel cycle test bed named “Beartooth” will give researchers the opportunity to study the nuclear fuel cycle process. The process operations include the use of centrifugal contactors and process flow for the purification of special nuclear material recovery in used fuel. This new research facility has the need to use non-traditional measurement sensors to determine the state-of-health of the solvent extraction process. These non-traditional sensors can also enhance nuclear nonproliferation supervision and other activities. The non-traditional sensors include accelerometers, acoustic, current, flow, colorimetric, temperature, pH and conductivity. The challenge behind deploying all these sensors, is the need for fast and reliable data collection. The data acquisition system (DAQ) needs to be capable of recording up to 12 accelerometers and/or acoustic microphones simultaneously at rates up to 12.8 kSamples/second/channel. This requires the need for a strong architecture and data collection solution. This summary identifies the system architecture, DAQ, and sensors needed to support non-traditional measurements in a solvent extraction process.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Use of Machine Learning for Signature Development in a Multi-Sensor Environment for Safeguard Applications of Solvent Extraction Processes
Idaho National Laboratory is constructing the Special Nuclear Material test bed (Beartooth) for research and development pertaining to nuclear fuel processing operations using centrifugal contactors. Beartooth will enable give researchers the opportunity to study the dissolution, separation, and conversion of special nuclear materials (e.g., plutonium, enriched uranium, and thorium). As a lead-in to Beartooth, this project constructed a test bed to study the process and equipment behavior with real time series data collection using a variety of non-traditional sensors, in order to identify process failures and label them as either accidental or purposeful, thus enhancing nuclear nonproliferation stewardship. The measurement sources in this test bed include vibration, acoustic, current, flow, colorimetric, and thermal data. These measurements vary in terms of magnitude, frequency, and location. This information will be combined and used within data-driven machine-learning methods to detect operation condition changes that are either intentional (i.e., changes in operating set points) or malicious (i.e., flow diversion) in nature. This presentation covers the data processing and signature development activities necessary for utilizing this heterogeneous dataset to classify process anomalies.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Conceptual Design and Analysis of a Power Generator with Integrated Thermal Energy Storage and CO2 Capture
This presentation was delivered at the 2022 American Institute of Chemical Engineers (AIChE) annual meeting.
Susarla, Naresh↗
Leak Detection and Sensor Importance Within a Solvent Extraction Process Abstract
In anticipation of the Special Nuclear Material test bed (Beartooth), Idaho National Laboratory has developed a smaller, multi-sensor system for analyzing the solvent extraction process. These systems will allow for research into nuclear fuel processing operations. The multi-sensor system consists of a row of centrifugal contactors and allows for measurement sources that are not traditionally used in the solvent extraction process to be explored including temperature, vibration, acoustics, pH, color, flow, and motor current. Currently, the solvent extraction process is very labor intensive and requires vigilant operators to identify the occurrence of leaks, which can be common during startup or after any change to the system. This study aims to locate leaks using non-traditional measurement sources then to identify which signals were of greatest importance in making this classification using Local Interpretable Model-agnostic Explanations. These results can be used to help solvent extraction process operators detect leaks and to inform future test beds designers to which sensors contain relevant, actionable information in this scenario.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Data Challenges in Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process
Idaho National Laboratory (INL) is maintaining and gaining knowledge into the nuclear fuel cycle by building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying solvent extraction processes that use centrifugal contactors. As part of INL’s mission, the goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multisensory data can support the development of safeguards by design, provide operator process awareness, and discover process anomalies. This poster will highlight some of the data collection and analytics challenges for the multi-sensor system as well as the mitigation strategies to build a robust system. Additionally, some preliminary data from the first testing campaign will be shown to help illustrate the data needs of the system.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Preliminary Results of a Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process
Idaho National Laboratory is building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying the solvent extraction process and the use of centrifugal contactors. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, color, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data supports the development of safeguards by design, provides operator process awareness, and aids in the discovery of process anomalies. This paper highlights some of the preliminary results from initial data collection campaigns and shares some of the lessons learned.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Multi-period GDP Optimization in IDAES: Simultaneous Design and Operation of an Integrated Fossil and Thermal Energy Storage System.
Abstract not provided.
Rawlings, Edna↗
Acoustic Monitoring of Pyroprocessing Equipment
This paper provides an introduction to using acoustic monitoring to advance detection techniques for pyroprocessing in support of nuclear safeguards and non-proliferation. The usage of free air acoustic monitoring has been previously demonstrated at Idaho National Laboratory (INL) facilities such as the Advanced Test Reactor and the National Security Test Range. However, the proposed work revolves around a new deployment environment, the Fuel Conditioning Facility, that brings forward several questions regarding the performance of the technology in non-free air media. The confinement of the pyroprocessing equipment to a heavily shielded hot cell, the atmosphere of the hot cell containing argon gas, and the radiation dose inside the hot cell are all new environments for acoustic monitoring. To our knowledge, acoustic measurements have not been completed in such an environment before. This offers a new opportunity to study not only the acoustic signatures of the equipment inside of the hot cell, but also the propagation of the signals through the hot cell and at distances away from their origination. The objective of this paper is to explain the planned instruments to monitor the Fuel Conditioning Facility in order to evaluate acoustic signals emitted from equipment during various stages of operation. Identifying these signals can potentially enable the identification of specific pieces of equipment used in pyroprocessing and produce information of their operational status. If successful, this type of monitoring could offer a new method to aid in safeguards and proliferation detection of pyroprocessing activities.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Development of a Multi-Sensor Data Science System Used for Signature Development on Solvent Extraction Processes in support of safeguards- an overview
A new nuclear fuel cycle test bed is being built at Idaho National Laboratory to support the purification of special nuclear material recovered from used fuel. The test bed provides an opportunity to research process flow and the application of computational tools in solvent extraction processes. A deeper understanding of process and equipment behavior coupled with real time data collection can indicate whether a process failure is accidental or purposeful. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data can support the development of safeguards by design and security by design measures for such a facility. Additionally, it can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. This overview encompasses the current research and testing of sensors to develop a spectrum of process signatures. To be followed by planned experiments aimed to characterize said signatures and study potential feature extraction techniques to identify a fault in the system (i.e. flow diversion).
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Multiperiod Conceptual Design of Integrated Energy Systems with Market Interaction Surrogate Models
The presentation highlights the market analysis capabilities, both price-taker analysis and the novel market surrogate models approach, applied to optimal design of electricity and hydrogen co-production systems. The research findings were presented at the 2023 AIChE Annual Meeting.
Chen, Xinhe↗
A New Approach to Monitoring Solvent Extraction Processes for the Nuclear Industry
As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is building the Beartooth testbed. Beartooth will include a cascade of centrifugal contactors, glove box lines, solidification, and dissolution equipment to aid in the progression of novel separation techniques and provide hands-on opportunities to early-career separation scientists. Beartooth will incorporate novel monitoring techniques using sensors and machine learning algorithms to inform a process operator of separation conditions. This research is examining monitoring technologies not typically used in nuclear separation processes such as acoustic microphones, accelerometers, infrared cameras, red-green-blue color sensors, among others. These sensors are being examined for their functionality within a separation process and their ability to detect applicable signals. Machine learning methods are being developed to determine their utility in detecting faults and alerting operators of expected and unexpected events. These methods have the potential to impact Safeguards by Design efforts and real-time decision making. This overview will detail preliminary results from acoustic, vibration, and color sensors.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Photonuclear Production of Radioxenon for Air Samples
Radioxenon plays an important role in ensuring compliance with the Comprehensive Nuclear-Test-Ban Treaty due to its ability to be transported through the atmosphere, as well as the fact that the half-lives of its isotopes provide a window long enough to be detected but not long enough that it could become background radiation. This allows it to be correlated with specific events that indicate the testing of nuclear weapons. Idaho National Laboratory supports this mission by providing spiked air samples for monitoring stations to enable instrument calibration and ensure measurement accuracy. We tested a photonuclear method of producing one of the main isotopes of radioxenon, Xe-135. We also tested the separation of Xe-135 from the parent isotope Xe-136 using the method of kinematic recoil. Aluminum coils were placed in quartz ampoules filled with enriched Xe-136 and were irradiated by a bremsstrahlung beam with an endpoint energy of 21 MeV. The results showed that we were not only successful in producing Xe-135 but also that the Xe-135 was deposited into the coil allowing it to be removed from the Xe-136 gas. The coil and the Xe-135 can then be chemically separated. At the time of counting the coil, it was calculated that there was about 18 Bq of activity from Xe-135 remaining in the coil. Future work includes determining the optimal material and geometry of the catcher to maximize the amount of Xe-135 captured.
07 ISOTOPE AND RADIATION SOURCES↗
Use of Sensors and Machine Learning for Signal Discovery in a Solvent Extraction Process – 23280
Reprocessing is an important step in the nuclear fuel cycle where usable nuclear materials are extracted from spent fuel for recycling. The extraction of materials for reuse simultaneously reduces not only the volume of nuclear waste, but its decay time to radioactivity levels similar to that of the originating uranium ore. As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is designing and constructing a solvent extraction testbed named Beartooth. Beartooth will allow researchers to refine extraction processes, test innovative extraction processes, and give early career scientists opportunities to gain skills in performing separations chemistry that uses centrifugal contactors. In addition, the Beartooth testbed is being uniquely designed to enable novel technologies including machine learning capabilities for the characterization of chemical process operations in near real-time. To aid in the design of Beartooth, a team of researchers are installing a variety of atypical sensors into a system of contactors for signal discovery. The team will implement machine learning methods on sensor data to determine signal features with the goal of providing a process operator with a deeper understanding of the chemical process and equipment usage. This work will summarize sensors utilized and preliminary results from an infrared camera.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Isotope Production Education and Research via a Systematic Study of Photo-nuclear Reaction Yields and Excitation Functions
A new collaboration between the New Mexico Institute of Mining and Technology, Idaho State University, and Idaho National Laboratory builds the domestic workforce in isotope production and related science and technologies by conducting research and education programs related to photo-nuclear reactions. Workforce development was identified by the Department of Energy’s Office of Science in the Reaching a New Energy Sciences Workforce (RENEW) program that seeks to engage underrepresented university students in isotope production activities. This collaboration includes coursework development, student training, and isotope production research utilizing photo-nuclear reactions at electron linear accelerators. Bremsstrahlung-weighted excitation functions and cross-sections will be measured and the use of nanomaterials to exploit kinematic recoil reactions will be investigated. Students will be hosted at the Idaho National Laboratory where mentors will provide opportunities to explore careers in nuclear science and technology. This presentation regards the ongoing progress of the research and education objectives of the collaboration that was performed under the Office of Science Isotopes Program under award number D000-22-2765.
07 ISOTOPE AND RADIATION SOURCES↗
Novel Photonuclear Methods to Produce an Argon-37 Standard
The mission of this research is to explore novel photonuclear-based pathways into the production of 37Ar. Above-background detection levels of 37Ar uniquely indicates the occurrence of an underground nuclear explosion, produced from fission neutrons interacting in the surrounding environment through the 40Ca(n,a)37Ar reaction. The half-life of 35 days allows on-site inspectors (OSI) adequate time following the nuclear event to detect 37Ar and verify compliance or defiance of non-proliferation treaties such as the Comprehensive Nuclear-Test-Ban Treaty (CTBT). An 37Ar standard would give OSI the ability to calibrate their detectors and measure detector efficiency allowing for the quantification of detected activity, give OSI authentic samples to test detectors in field exercises, and improve models predicting diffusion pathways of 37Ar through the underground environment.
43 PARTICLE ACCELERATORS↗
Persistent Acoustic Sensing for Monitoring A Reactor Facility - Oral Presentation
Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios (MINOS) project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at a large research reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operation. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper will present recent research advances in this area including studies to explore the transferability of learned parameters from one smartphone to another, the detectability of events from multiple sensors at different locations simultaneously, and the feasibility of porting analytical tools directly to the smartphones to allow edge computing with optimized configurations.
42 ENGINEERING↗