Large Nuclear Detector Array Interconnection by Direct-Write Laser Chemical Vapor Deposition (CVD)
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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Testing of fiber optic based sensors for advanced reactors in the Texas A&M University TRIGA reactor
An Optical Fiber Based Gamma Thermometer has been developed and tested at the Texas A&M University reactor as well as the Ohio State Research Reactor. This sensor technology provides temperature measurement of a thermal mass undergoing gamma heating, from which the gamma flux along the length of the sensor may be calculated. The gamma flux data from an array of OFBGTs could allow the determination of local power density within a nuclear reactor core in three dimensions. The design of the sensor makes use of optical fiber as a truly distributed temperature sensor with a spatial resolution less than 1mm and temperature accuracy of ±1°C. The testing program showed that the system provided the expected temperature data for each location. Overall, this sensor technology shows promise for current Light Water Reactors as well as advanced nuclear reactors by providing an unparalleled level of precision in reactor power measurement.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
On-Line Monitoring of Gas-Phase Molecular Iodine Using Raman and Fluorescence Spectroscopy Paired with Chemometric Analysis
Molten salt reactors (MSRs) have the potential to safely support green energy goals. However, licensing and deployment of these systems will be aided through development of new technology. This includes on-line monitoring tools for real-time compositional analysis. Of particular interest is quantifying iodine within reactor off-gas streams to support design and operational control of reactor off-gas treatment systems. Here we discuss the development of advanced Raman spectroscopy systems for the on-line analysis of I 2(g) within the gas phase. Signal response is explored with two Raman instruments utilizing a 532 nm and a 671 nm excitation source, as a function of I 2(g) pressure and temperature. Furthermore, the applicability of chemometric modeling for advanced analysis of data is explored. Raman spectroscopy paired with chemometric analysis is demonstrated to be a powerful route to analyzing I 2(g) composition within the gas phase, which lays the foundation for applications within molten salt reactor off-gas analysis and other significant chemical processes producing iodine species.
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Application of On-Line Monitoring and Real-Time Characterization of Low Level Waste Samples from Hanford Tanks - 20380
Waste and treatment stream characterization is an essential part of safe, efficient, and cost-effective processing of Hanford materials. The demand for materials characterization, including chemical, radionuclide, and physical attributes during waste management, transfer, and staging operations in the Hanford tank farms, is expected to significantly increase as the U.S. Department of Energy Office of River Protection (ORP) progresses toward Hanford waste treatment and immobilization. The application of on-line monitoring can greatly improve operation time frames and reduce costs by providing real-time data and supporting the reduction of necessary grab sample collection. Recently, our team applied Raman online monitoring and chemometric modeling to the supernate of Hanford tank 241-AP-105, and demonstrated the quantitative measurement of nine analytes within this waste. Application of this method has been expanded to additional Hanford tank wastes, AW-102 and AP-107. The performance of the process monitoring instruments and the accuracy of the chemometric models will be assessed. On-line monitoring results will be compared to anion results determined from the current standard, ion-chromatographic and inductively coupled plasma mass spectrometry methods. Comparisons of both determined values and uncertainties of results will be presented. Results will be shared with personnel working on flowsheet interfaces for the Direct-Feed Low Activity Waste mission at Hanford. (authors)
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An unstructured mesh based neutronics optimization workflow
We have developed a fully automated workflow to optimize the neutronics performance of the Second Target Station (STS) at the Oak Ridge National Laboratory’s Spallation Neutron Source. The optimization workflow starts with the parametrized solid CAD engineering models and converts them into the unstructured mesh (UM) models for the neutronics calculations with MCNP6.2. Calculations are executed and their results are loaded into the Dakota optimization toolkit. Dakota analyzes the results and proposes new geometry parameters for the next design iteration. The cycle repeats until the optimal parameters are found. The automated CAD to MCNP conversion, the use of high-fidelity UM models, and the use of modern optimizer are the key elements that advance the entire optimization workflow in comparison with the original workflow. The original workflow was based on a simplified constructive solid geometry (CSG) modeling with MCNPX, mcnp_pstudy tool, and an in-house optimizer. Herein to demonstrate the new workflow, we present a case of neutronics optimization of the moderator–reflector assembly (MRA). Apart from the MRA, the workflow can optimize other major STS components, such as the spallation target, neutron beamlines, radiation shielding, and various accelerator components. Importantly, the new workflow opens the door to the advanced multi-physics multi-parameter optimization and has the potential for use in other nuclear physics and accelerator applications.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Unsupervised Learning for Improved Gamma-Ray Spectrometry in Pixelated Cadmium Zinc Telluride (CZT) Detectors
Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The Population of H ii Regions in NGC 7020
The galaxy NGC 7020 displays an exotic hexagonal ringlike central structure with conspicuous ansae located at two opposite vertices and a tenuous external ring populated by H ii regions. Inside and around the hexagonal structure, Hα emission is also present at the inner disk. To characterize the population of the H ii regions, as well as their ionizing clusters, we imaged NGC 7020 with narrowband Hα and nearby continuum filters attached to GMOS-S installed on the Gemini South telescope. We found 202 H ii regions or complexes of H ii regions evenly distributed between the outer ring and the central disk The nucleus and ansae also present Hα emission. The equivalent width of the Hα line (W {sub Hα}) is systematically greater at the regions of the outer ring relative to those of the inner disk. We discuss the influence of the metallicity gradient of the disk and the upper limit of the masses of the initial mass function on W {sub Hα}, and we conclude that the data are still consistent with the occurrence of a younger burst of H ii region formation in the outer ring. The central regions present more massive clusters, M ≥ 10{sup 6} M {sub ⊙}, than those of the outer ring (M ≤ 10{sup 6} M {sub ⊙}). Three clusters within 5″ of the nucleus present masses higher than 10{sup 8} M {sub ⊙}. The presence of diffuse Hα emission in the inner 5″ suggests gas flows in the nuclear region.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Challenges and Practical Solutions for Conducting Structural MARSSIM Surveys in Elevated Radon Environments - 20413
The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) [1] provides comprehensive guidance for the development and implementation of radiological surveys conducted to demonstrate compliance with a dose- or risk-based cleanup goal during final status survey. The MARSSIM methodology follows an integrated strategy combining direct measurements and sampling to assess uniform residual contamination, and scanning surveys to identify localized areas of elevated activity. Building surveys assessing residual surface contamination present unique challenges from reliance on field measurements that may be subject to less than ideal environmental conditions. Additionally, limited characterization and excessive conservatism incorporated into the conceptual site model may result in derived concentration guideline levels (DCGL) and, as a consequence of relatively inefficient field instrumentation, corresponding attributable count rates generally comparable to background. The presence of elevated ambient radon concentrations and associated progeny deposition both exacerbate these intrinsic survey challenges and introduce a series of technical, logistic, and administrative obstacles that can wreak havoc on the statistical legitimacy of each component of the MARSSIM process. Short-lived radon progeny including polonium-218, lead-214, bismuth-214, and polonium-214 produce excessive alpha and beta radiation that may decrease instrument sensitivity through an increase in background count rates, and, at worst, may result in incorrect survey unit failure through the simulation of residual surface activity. Aside from the obvious solution of exhaustive radon mitigation, the primary objectives are to distinguish between radon progeny deposition and actual surface activity, and collect sufficient defensible data. The following is a technical discussion of the consequences of performing building MARSSIM surveys in the presence of elevated ambient radon atmospheres, conceptual examples, and an overview of practical strategies to minimize the effects of radon interference while collecting sufficient defensible data to complete the survey. (authors)
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Online Lead/Water Heat Exchanger Sensor/System Feasibility-PNNL (Final Report)
On-line structural health corrosion monitoring in advanced lead fast reactor heat exchangers and molten salt reactor heat exchangers is desirable for detecting tube degradation prior to leaks that may allow mixing of heat exchanger fluids or release of radiological contamination beyond the design containment boundary. This program, On-Line Lead/Water Heat Exchanger Sensor/System Feasibility – PNNL 76092, demonstrates feasibility for an ultrasonic torsional wave mode sensor attached to the outside of a long (30.5-m) heat exchanger tube in the stagnant flow area where the tube joins a heat exchanger plenum and where it is possible to protect a sensor and cable from high-force flows. The sensor must be cable connected to a monitoring instrument near the heat exchanger. The sensor and cable management approach for periodic in-service inspection will be impractical to implement on existing heat exchangers; rather permanently mounted sensors must be installed in conjunction with heat exchanger fabrication. Previous work has shown low-temperature lead zirconate titanate (PZT) piezoceramic sensors are able to detect anomalies of interest in 3.0-m long tubes. These sensors have hereby been extended to a 30.5-m long tube more representative of commercial power heat exchanger designs. The program will continue to investigate higher temperature piezoelectric ceramics and long-term performance of high temperature adhesives and sealants and mechanical pressure coupling for 350-500 °C lead reactor environments and higher temperature (700 °C) molten salt environments.
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Can We Use Machine Learning to Control Nuclear Power Plants?
Slides for the INL AI/ML Symposium 11.0 focused on AI/ML in instrumentation, control, and automation. This presentation was on how we can use AI/ML for control of nuclear power plants. A recording of the presentation and other INL AI/ML symposiums can be found at https://inl.gov/artificial-intelligence/.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Low Cost Data Acquisition Synchronization for Nuclear Physics Applications. Phase II - Final Report
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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Neutrino-detector design for safeguarding small modular reactors
Nuclear reactors have long been a favored source for antineutrino measurements for estimates of power and burnup. With appropriate detector parameters and background rejection, an estimate of the reactor power can be derived from the measured antineutrino event rate. Antineutrino detectors are potentially attractive as a safeguards technology that can monitor reactor operations and thermal power from a distance. Advanced reactors have diverse features that may present challenges for current safeguards methods. By comparison, neutrino detectors offer complementary features, including a remote, continuous, unattended, and near-real-time monitoring capability, that may make them useful for safeguarding certain classes of advanced reactors. This study investigates the minimum depth and size of an antineutrino detector for a small modular reactor to meet safeguards needs for advanced reactors. Furthermore, extrapolating performance from several prior reactor antineutrino experiments, this study uses an analytical approach to develop a possible design for a remote antineutrino-based monitoring device.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The Simons Observatory Microwave SQUID Multiplexing Detector Module Design
Advances in cosmic microwave background (CMB) science depend on increasing the number of sensitive detectors observing the sky. New instruments deploy large arrays of superconducting transition-edge sensor (TES) bolometers tiled densely into ever larger focal planes. High multiplexing factors reduce the thermal loading on the cryogenic receivers and simplify their design. We present the design of focal-plane modules with an order of magnitude higher multiplexing factor than has previously been achieved with TES bolometers. We focus on the novel cold readout component, which employs microwave SQUID multiplexing (μmux). Simons Observatory will use 49 modules containing 70,000 bolometers to make exquisitely sensitive measurements of the CMB. We validate the focal-plane module design, presenting measurements of the readout component with and without a prototype detector array of 1728 polarization-sensitive bolometers coupled to feedhorns. The readout component achieves a 95% yield and a 910 multiplexing factor. The median white noise of each readout channel is 65 . This impacts the projected SO mapping speed by <8%, which is less than is assumed in the sensitivity projections. The results validate the full functionality of the module. We discuss the measured performance in the context of SO science requirements, which are exceeded.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
RheoSurfR – Neutron Reflectivity-Rheology Sample Environment for Studying Soft Matter, Biology and Materials Processing at Air-Liquid and Liquid-Liquid Interfaces
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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Characterization of Intrinsic Fiber Optic Temperature Sensors by In-core and Furnace Testing
Increased research and development in nuclear technology has raised the demand for novel sensors and instrumentation to meet data objectives, and survive in different conditions and environments, beyond conventional light water reactor (LWR) environments. Expediting the deployment of advanced nuclear technologies by developing, demonstrating, and qualifying advanced reactor fuel forms necessitates a deeper understanding of how irradiation affects fuels and materials' performance. To achieve a more comprehensive understanding of fuels and materials performance, researchers require more specialized experiments and measurements. The demand for innovative sensors to support nuclear fuel development arises from the complexity of materials' behavior under irradiation and the challenges of deploying instrumentation in Material Test Reactors (MTRs) for irradiation tests. Additionally, measurements of material properties require integrated measurement systems to characterize thermal properties, mechanical properties, chemistry, and microstructure [1]. Among the potential measurement techniques, optical fiber-based sensors have been identified as potential sensors to measure different physical phenomena such as temperature, strain, pressure, and fluid level. Optical fiber sensors have the capability to provide multi-sensing and multiplexing instrumentation, allowing the measurement of different physical parameters within a single sensor configuration, and transmitting data collected at multiple locations through a single fiber. They offer immunity to electromagnetic interference, electrical passivity, compatibility with various sensing methodologies, and cost-effectiveness. Beyond their widespread use in telecommunications, silica fiber-based instruments are utilized in industrial applications, even at temperatures reaching 300?400°C, such as distributed temperature sensing in oil and gas recovery. The Department of Energy (DOE) is interested in using fiber optics to support fuel cycle development [2]. Fiber optics are an excellent candidate for harsh environment sensing, including sensing at very high temperatures (1900oC for sapphire optical fibers). Distributed fiber optic sensing has been deployed in other harsh environments like coal gasification plants [3]. Distributed strain sensing, which operates similarly to distributed temperature sensing, has been deployed to monitor underground mines and fibers have been imbedded in soil to monitor sink-hole development [4][5]. The application of fiber optic sensors to advanced reactor development is a promising area of research.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Assessment of Flow-Enhanced Electrochemical Sensor Testing and Deployments
The goal of our activities in FY24 was to enable advanced materials accountancy for molten salt reactors (MSRs) through the development and optimization of robust flow-enhanced electrochemical sensors (FEES) using a safeguards-focused sensor testing platform called the modular flow instrumentation testbed (MFIT). Flow-enhanced electrochemical sensors are a type of electroanalytical sensor that have been developed at Argonne National Laboratory to be installed directly into MSR flow conduits to make measurements of the salt composition. These sensors represent a significant improvement in capabilities compared to earlier electroanalytical sensors that instead can only be operated in quiescent conditions. Previous work has focused on testing of the FEES in flowing conditions provided by the MFIT to assess the accuracy and precision of the sensor measurements. This year, the FEES technical readiness was increased by (1) demonstrating the use of optimized sensor techniques to achieve measurements in very high-concentration MSR-relevant salts, (2) leveraging new multimodal sensors and automation approaches to reduce measurement uncertainties, and (3) fabricating and deploying sensors to industrial partners to improve their ability to make measurements in challenging environments. Additionally, we also ran the sensors during complex system operations involving combined flow and purification activities to demonstrate safeguards-relevant measurements during online processing for MSRs.
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An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures
This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.
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