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At least 253 records · Page 14

Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. These modeling efforts make extensive of MOOSE (Multiphysics Object-Oriented Simulation Environment), a general-purpose open source finite element framework developed at INL. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Updated SAM Model for the Molten Salt Reactor Experiment (MSRE)

The development of reference standard problems based on prototypical reactor designs is of particular importance to verify the adequacy of computer codes and evaluation models for specific reactor types. To support the multiphysics coupled simulation of molten-salt-fueled reactor (MSR) using SAM and Griffin computer codes for safety and licensing analysis, much efforts have been put into enhancing code capabilities and developing reference models for the MSR primary loop in SAM. In this work, a previously developed Molten Salt Reactor Experiment (MSRE) primary loop model was updated to include a two-dimensional (2-D) core region and external core components in one-dimension (1-D) or zero-dimension (0-D). To ensure accurate feedback calculation in multi-physics simulations, the delayed neutron precursor tracking model and solid graphite model were added in the SAM model. In addition, the 2-D and 1-D domains are tightly coupled using the recently developed single-solve approach in SAM. The updated model has been tested under both steady-state and transient scenarios to demonstrate its potential for the multi-physics simulation of MSRE with coupled SAM and Griffin.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Summary of Methodology for Mitigating Risks Associated with Licensing and Qualifying AM Nuclear Materials

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program focuses on accelerating the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Laser powder bed fusion (LPBF) is one of the most popular additive manufacturing (AM) processes for fabricating components with intrinsically complex geometries. LPBF was extensively explored for nuclear applications under the previous Transformational Challenge Reactor program. Additionally, Oak Ridge National Laboratory developed and licensed the Peregrine software and larger digital platform that couples machine learning and in situ data collection during AM to detect anomalies and any evolved defects. The digital platform will be critical to (1) the qualification of AM components for nuclear applications that link location-specific data to macroscopic properties and (2) predict final component performance. Current in situ process monitoring tools are valuable for observing the formation of stochastic flaws, but additional data are needed to predict the resulting microstructures and associated material performance. Rapid cooling rates and large thermal gradients have caused large heterogeneities in the microstructure, which cause anisotropy in mechanical performance. The AMMT program is evaluating the best approaches for addressing these heterogeneities and their effect on component performance using a combination of multiscale modeling, enhanced in situ process monitoring, and high throughput experimental testing. This report summarizes strategies for mitigating the risks associated with qualifying AM components, including developing new sensing capabilities for in situ process monitoring and characterizing melt pool solidification and residual stresses to inform multiscale modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications

There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.

Telecommunication↗

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Space Operations Learning Center

The Space Operations Learning Center (SOLC) is a tool that provides an online learning environment where students can learn science, technology, engineering, and mathematics (STEM) through a series of training modules. SOLC is also an effective media for NASA to showcase its contributions to the general public. SOLC is a Web-based environment with a learning platform for students to understand STEM through interactive modules in various engineering topics. SOLC is unique in its approach to develop learning materials to teach schoolaged students the basic concepts of space operations. SOLC utilizes the latest Web and software technologies to present this educational content in a fun and engaging way for all grade levels. SOLC uses animations, streaming video, cartoon characters, audio narration, interactive games and more to deliver educational concepts. The Web portal organizes all of these training modules in an easily accessible way for visitors worldwide. SOLC provides multiple training modules on various topics. At the time of this reporting, seven modules have been developed: Space Communication, Flight Dynamics, Information Processing, Mission Operations, Kids Zone 1, Kids Zone 2, and Save The Forest. For the first four modules, each contains three components: Flight Training, Flight License, and Fly It! Kids Zone 1 and 2 include a number of educational videos and games designed specifically for grades K-6. Save The Forest is a space operations mission with four simulations and activities to complete, optimized for new touch screen technology. The Kids Zone 1 module has recently been ported to Facebook to attract wider audience.

Lui, Ben↗

Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development

Global expansion of hydropower resources has increased in recent years to meet growing energy demands and fill worldwide gaps in electricity supply. However, hydropower induces significant environmental impacts on river ecosystems - impacts that are addressed through environmental impact assessment (EIA) processes. The need for effective EIA processes is increasing as environmental regulations are either stressed in developing countries undertaking rapid expansion of hydropower capacity or time- and resource-intensive in developed countries. Part of the challenge in implementing EIAs lies in reaching a consensus among stakeholders regarding the most important environmental factors as the focus of impact studies. To help address this gap, we developed a weight-of-evidence approach (and toolkit) as a preliminary and coarse assessment of the most relevant impacts of hydropower on primary components of the river ecosystem, as identified using river function indicators. Through a science-based questionnaire and predictive model, users identify which environmental indicators may be impacted during hydropower development as well as those indicators that have the highest levels of uncertainty and require further investigation. Furthermore, an assessment tool visualizes inter-dependent indicator relationships, which help formulate hypotheses about causal relationships explored through environmental studies. We apply these tools to four existing hydropower projects and one hypothetical new hydropower project of varying sizes and environmental contexts. We observed consistencies between the output of our tools and the Federal Energy Regulatory Commission licensing process (inclusive of EIAs) but also important differences arising from holistic scientific evaluations (our toolkit) versus regulatory policies. The tools presented herein are aimed at increasing the efficiency of the EIA processes that engender environmental studies without loss of rigor or transparency of rationale necessary for understanding, considering, and mitigating the environmental consequences of hydropower.

54 ENVIRONMENTAL SCIENCES↗

Preliminary Analysis of Postclosure DPC Criticality Consequences

One of the objectives of the United States (U.S.) Department of Energy's (DOE) Office of Nuclear Energy's Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the U.S. has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act 1982). Any repository licensed to dispose the SNF must meet requirements regarding the longterm performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently being used to store and transport SNF but were not designed for permanent geologic disposal. A two-phase study has been initiated to begin examining the potential consequences, with respect to longterm repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. Phase I, a scoping phase, consisted of developing an approach intended to be a starting point for the development of the modeling tools and techniques that may eventually be required either to exclude criticality from or to include criticality in a performance assessment (PA) as appropriate; Phase I is documented in Price et al. (2019). The Phase I approach guided the analyses and simulations done in Phase II to further the development of these modeling tools and techniques as well as the overall knowledge base. The purpose of this report is to document the results of the analyses conducted during Phase II. The remainder of Section 1 presents the background, objective, and scope of this report, as well as the relevant key assumptions used in the Phase II analyses and simulations. Subsequent sections discuss the analyses that were conducted (Section 2), the results of those analyses (Section 3), and the summary and conclusions (Section 4). This report fulfills the Spent Fuel and Waste Science and Technology Campaign deliverable M2SF-20SN010305061.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Plasma Ignition and Combustion Stabilization Technology to Improve Flexible Operation, Reliability and Economics of an Existing Coal-Fired Boiler

GE Steam Power, Inc. (GE) proposed to improve reliability, flexibility, and economics of an existing coal-fired power plant by applying a new advanced technology developed by GE, a plasma-assisted pulverized fuel firing system. The objective of this program is to demonstrate the achievement of lower load by improved flame stabilization and therefore lower operating costs in a full-scale field installation at coal-fired electric utility. GE’s Plasma Ignition and Combustion Stabilization System is designed to operate continuously to support low load operation. With the plasma on, the flame will be attached and stable, removing the firing system as a limitation to low load operation. In addition, GE’s exclusively from ABENZ company licensed AC based technology has a 90+% system efficiency compared to all other systems at which are DC and operate with ~75% efficiency. Plant operating costs are lowered by eliminating use of expensive support fuel as well as the ability to operate at lower loads. The utilities’ ability to better match the demand curve will result in significant savings. Maintenance is lower for an AC system than a DC system as it operates at lower current. This eliminates the need for a demineralized cooling water system and provides longer electrode life which translates into both material and labor savings. It is the objective of GE to not only demonstrate the additional low load achievable with a plasma system after best achievable tuning, sensor and software approach has been exhausted, but also the increased stability of the flame at all loads with plasma assistance as well as cost savings at all low loads using plasma instead of oil. Upon successful completion of this project, GE will have sufficient field experience to rapidly deploy the Plasma Technology. The project objectives were achieved through the implementation of plasma ignitor technology at PacifiCorp Hunter Station Unit 3. A plasma ignitor system was retrofitted on ten wall-fired burners, Mill 3-4 combustion system. The Plasma Ignitors installed at Hunter proved that this GE technology is a direct and complete replacement for the original oil ignitors. The Hunter Unit 3 burner management system allows the plasma system to be used in all applications that originally required oil to be burned. This includes any time the Mill 3-4 is started or stopped for any reason including boiler starts, load changes, and low load support.

01 COAL, LIGNITE, AND PEAT↗

New Outboard Motor Firing on All Pistons

Seven years ago, NASA was in the planning stages of producing an aluminum alloy with higher strength and resistance at elevated temperatures for aerospace applications. At that time, a major automobile manufacturer happened to approach NASA for solutions to lowering engine emissions and the costs associated with developing aluminum engine pistons. The Space Agency realized the answers to the manufacturer's problems could lie within the proposed alloy. Jonathan Lee, a structural materials engineer at Marshall Space Flight Center s Materials, Processes, and Manufacturing Department, and PoShou Chen, a scientist with Huntsville, Alabama-based Morgan Research Corporation, partook in the development project as the inventors. The resulting NASA High-Strength Aluminum Alloy, or "MSFC-398," was capable of casting metal components at both high volume and low cost, making it extremely attractive for commercial application, not just in automotives, but in a variety of other industries, as well. NASA patented the technology and introduced it for public licensing in 2001.

Source record↗

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗

Optimization of Dry Storage Canister Cutting Operations - 20534

A recent project investigated the optimal cutting method for the opening of a welded dry storage/shielded canister (DSC) or dual purpose canister (DPC) containing Used Nuclear Fuel (UNF). Due to the lack of a disposal path for UNF in the U.S., the majority of UNF is currently moved into welded DSCs and DPCs designed by Orano TN, NAC, and Holtec. As the DSCs/DPCs were neither designed nor licensed for disposal and may not be able to be emplaced in a geologic repository due to physical emplacement constraints, near-term thermal limitations, or long-term criticality issues, the UNF in these existing DSCs/DPCs may need to be repackaged into transportation, aging, and disposal canisters (TADs), generic standard TADs (STADs), transportation casks, new cask/canister systems, and/or cask/canister/package systems suitable for disposal. These DSCs/DPCs may also be opened to simply remove the UNF in preparation for recycling, re-storage, or placement into a waste package suitable for disposal. Regardless of need, the DSCs/DPCs would require to be cut open by a potentially large scale operation. This project examined the multiple means for cutting welded metal systems and considered several factors to determine an optimal approach. Issues arose around some of the cutting approaches when applied to systems with 2 or 3 lids and with pre-cutting gas testing required. The resulting preferences in cutting methods with an optimized application for the opening of DSCs/DPCs are presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗