Search NASA⌕ Search

SEARCH · Search NASA

Results for “Plant Water Management”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Prairie State Generating Company Site: Storage Field Development Plan

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, operational plans, and costs associated with the proposed Prairie State Energy Campus - Carbon Capture and Storage (PSEC-CCS) project in Washington County, Illinois, near Marissa. The proposed storage complex, known as the St. Peter-Everton Storage Complex, comprises the St. Peter Sandstone and Everton sandstone reservoirs, with the Maquoketa Shale serving as the primary confining unit and the Knox Group as lower confining unit. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Pennsylvanian section.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Crop diversification improves water-use efficiency and regional water sustainability

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s improvements to WUE, with direct implications for climate adaptation. More broadly, our framework offers a tool to evaluate other sustainable practices and guide policy and farm-scale decision-making.

climate-resilient agriculture↗
DOE OSTI2023

West Valley Demonstration Project (WVDP) (Annual Site Environmental Report (ASER), Calendar Year 2022)

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2022. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2022 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Operational and Performance Monitoring of East Tennessee Technology Park Ponds—2023 Results

Performance and operational monitoring are regulatory requirements associated with a non–time-critical removal action for three surface water bodies at the East Tennessee Technology Park (ETTP) in Oak Ridge, Tennessee: the K-1007-P1 Pond, the K-901-A Pond, and the K-720 Slough. This progress report summarizes the monitoring activities and results from fiscal year (FY) 2023. The goal of ecological enhancement of the K-1007-P1 and K-901-A Ponds is to reduce risk from polychlorinated biphenyl (PCB) contamination in fish to humans and wildlife. Lowering PCB concentrations in the water column and in the food that fish eat is expected to decrease PCB bioaccumulation in fish. Performance monitoring of the K-1007-P1 Pond focuses on annual PCB trends in water, clams, and fish. PCBs in fish also are sampled annually at the K-720 Slough. Operational monitoring ensures that ecological enhancement measures—including water quality, plant community, fish community, and wildlife actions—have been implemented as intended. Monitoring provides the information necessary to determine whether modifications are needed to attain the design end state (i.e., a heavily vegetated, clearwater pond dominated by sunfish with significantly diminished or at least downwardly trending PCB levels in fish). In FY 2023, fish removal efforts and vegetation planting primarily focused on the K-901-A Pond. These actions were implemented to help push the systems toward the desired end state. Descriptions of the various monitoring activities and preliminary 2023 results are provided in the following sections. An update on fish and plant management actions in FY 2023 is also included in this report. A summary of the more detailed information in this report will be presented as required in the upcoming Remediation Effectiveness Report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Operational and Performance Monitoring of East Tennessee Technology Park Ponds—2025 Results

Performance and operational monitoring are regulatory requirements associated with a non–time-critical removal action for three surface water bodies at the East Tennessee Technology Park (ETTP) in Oak Ridge, Tennessee (Figure 1): the K-1007-P1 Pond, the K-901-A Pond, and the K-720 Slough. This progress report summarizes the monitoring activities and results from FY 2025. The goal of ecological enhancement of the K-1007-P1 and K-901-A Ponds is to reduce risk from polychlorinated biphenyl (PCB) contamination in fish to humans and wildlife. Lowering PCB concentrations in the water column and in the food that fish eat is expected to decrease PCB bioaccumulation in fish. Performance monitoring of the K-1007-P1 Pond focuses on annual PCB trends in water, clams, and fish. PCBs in fish also are sampled annually at the K-720 Slough. Operational monitoring ensures that ecological enhancement measures—including water quality, plant community, fish community, and wildlife actions—have been implemented as intended. Monitoring provides the information necessary to determine whether modifications are needed to attain the design end state (i.e., a heavily vegetated, clearwater pond dominated by sunfish with significantly diminished or at least downwardly trending PCB levels in fish). In FY 2025, fish removal efforts and vegetation planting primarily focused on the K-901-A Pond. These actions were implemented to help push the systems toward the desired end state. Descriptions of the various monitoring activities and preliminary 2025 results are provided in the following sections. An update on fish and plant management actions in FY 2025 is also included in this report. A summary of the more detailed information in this report will be presented as required in the upcoming Remediation Effectiveness Report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Regionalized Life-Cycle Water Impacts of Microalgal-Based Biofuels in the United States

While algal biofuels have the potential to reduce the national reliance on fossil fuels, high water consumption associated with algal biomass cultivation represents a major concern potentially compromising the sustainable commercialization of this technology. This study focuses on quantifying the water footprint (WF) and water scarcity footprint (WSF) of renewable diesel derived from algal biomass and provides insights into where algal cultivation is less water-intensive than traditional ethanol and biodiesel feedstocks. Results are generated with an engineering process model developed to predict the life-cycle water consumption, considering green, blue, and gray water, of algae facilities across the United States at a high spatiotemporal resolution. The total WFs for Florida and Arizona are determined to be 13.1 and 17.6 m 3 GJ –1 , respectively. The blue WF in Arizona is shown to be 8.5 times larger than in Florida, while the green WF is 4.5 times smaller, but when combined into a total WF, there is just a 26% difference between the two locations. The analysis reveals that the total life-cycle WFs of algal renewable diesel are smaller than the optimal WFs of corn ethanol and soybean biodiesel. Algal systems benefit from higher growth rates and offer the opportunity to manage wastewater streams, therefore generating smaller green and gray WFs than those of conventional biofuels. Here, the WSF analysis identifies the Gulf Coast as the most suitable region for algal cultivation, with cultivation in the western US shown to exacerbate local water stress levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hybrid Energy Systems: Opportunities for Coordinated Research

This chapter presents a baseline assessment of DOE’s current portfolio related to hybrid systems that produce electricity as their only output (Track 1), within the context of the key challenges facing these systems. Of particular importance is that this chapter is focused on understanding what makes a hybrid different from two standalone technologies, both in terms of the research being performed and the challenges that ongoing and planned research will seek to overcome. The purpose of summarizing and describing current research areas is to identify opportunities DOE could consider supporting in the near term. DOE encompasses several offices, each of which has unique objectives and is financially constrained. Additionally, the emergence of low-cost hybrid resources presents an array of new opportunities for the electricity sector, including better managing and allocating risk, improving operating performance, reducing system costs, and enhancing reliability and resilience. Realizing these opportunities will require overcoming barriers to the deployment of hybrids through targeted R&D which multiple DOE offices can invest in and benefit from.

42 ENGINEERING↗
DOE OSTI2023

Synthetic Calcium Carbonate Production by Carbon Dioxide (CO 2 ) Mineralization of Industrial Waste Brines

The global scale of CO 2 emission has crossed 36 B tons, and the United State represents 14% of the total emissions. In light of the high cost associated with current CO 2 capture processes ($60-to-150 per ton of CO 2 ), carbon capture and utilization (CCU), wherein CO 2 is converted to beneficial products, provides a pragmatic path to overcome the economic barrier for CO 2 emissions control. In particular, CO 2 mineralization offers an attractive route as it produces high-value mineral carbonates that sequester CO 2 in a stable form. For instance, fine precipitated calcium carbonate, a valuable product with unit price in the range of $230-280/t and a global market projected to reach 99 M tons in 2020, can be produced by capturing CO 2 within aqueous Ca 2+ solution. However, two critical challenges need to be overcome—(i) the need for costly processes such as electrolysis or addition of alkali hydroxides to maintain alkalinity during mineralization, and (ii) the geographic availability of Ca-rich solutions (or brines) which often renders efficient integration with power plants impractical. To simultaneously address these challenges, this project developed two novel routes to enable carbonate production based on efficient CO 2 mineralization. In one variation, the project developed a new alkaline carbonation process to capture CO 2 and produce calcite precipitates from coal ashes. Herein, coal ash is carbonated first in a sodium carbonate solution. The carbonation reaction produces sodium hydroxide and raises the solution pH. This high-pH hydroxide solution is then used for CO 2 capture, which converts the sodium hydroxide solution back to sodium carbonate to repeat the carbonation cycle. The carbonated ash residue is refined with a CO 2 pressure swing step to produce high-purity precipitated calcium carbonate. In another variation, Ca-rich produced water brine serves as the Ca-source to mineralize CO 2 . An H + /Na + ion-exchange cycle was designed to provision alkalinity during mineralization and regenerate the ion-exchange reagent in brines with high salinity. Ca-depleted brines can then be treated within a centralized water treatment facility. Both variations beneficially utilize reject streams—such as coal ashes and brines from oil and gas extraction or CO 2 storage operations—that are available at substantial quantities in the vicinity of coal power plants within the U.S. In addition to technology development, this project included techno-economic and life-cycle analysis to identify technically and economically appropriate solutions for power plants in different geographic locations. Taken together, the project provides a unique route to integrate CO 2 emissions control and waste handling/treatment for coal power plants, while producing a high-value product to offset the economic burden associated with waste management. The developed processes utilize post-desulfurization flue gas from coal-fired power plants as is. The CO 2 conversion reactions are performed in alkaline brines at ambient pressure from the flue gas, thereby minimizing the energy burden. By beneficiation of industrial waste streams with low energy input, the processes offers significant technical advantages in energy and CO 2 footprint over the current paradigm of precipitated calcium carbonate production, which involves calcination of limestone at processing temperatures in excess of 800 °C. Overall, this project developed viable CO 2 mineralization processes while strategically maximizing the economic benefit.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Assessment of EPRI’s Tan Delta Approach to Manage Cables in Submerged Environments: Statistical Review of EPRI Data

Research conducted by the Electric Power Research Institute (EPRI) and other research institutions have concluded that water-trees are one of the leading degradation mechanisms that contribute to the loss of dielectric insulation strength in medium-voltage cable insulating materials in wet or submerged environments. The electrochemical reactions are caused by the combined effect of water presence and relatively high electrical stress. Records of cable failures provided by the licensees in response to Generic Letter (GL) 2007-01 (NRC 2007) have called into question the reliability of medium voltage cables in wetted or submerged environments. EPRI’s dissipation factor or Tan Delta testing guidelines and acceptance criteria have been adopted by most nuclear power plant operators as the primary tool for condition monitoring of medium voltage cables in wet or submerged environments. EPRI has been collecting member data since late 2009 to analyze and provide feedback to members, validate the EPRI-developed acceptance criteria guidelines, support analysis of test results, recommend appropriate actions for the "action required" category, and gather candidate cables for EPRI-sponsored forensic research on causes for insulation degradation. EPRI has collected data from 37 nuclear sites, which represent 44 operating units. The test results have been organized by insulation type, such as cross-linked polyethylene (XLPE); butyl rubber; black, pink, and brown ethylene-propylene rubber (EPR); and compact insulation (black and pink EPR)1. The data have been analyzed, and follow-up information was obtained from members for “action required” test results. EPRI has also performed correlations between Tan Delta tests and the information gathered under the EPRI forensic research on medium-voltage cables. In addition, EPRI has developed guidance by cable insulation type on how to systematically analyze Tan Delta test results. The analysis described here reviewed the two primary EPRI reports (EPRI 3002000557 and EPRI 3002005321) as well as two precedent EPRI reports (EPRI 1028262 and EPRI 1021070) that were cited in the primary reports. The principal results and conclusions from the project analyses are provided.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Advances in Resin Management Using 3R-Scan - 20154

The most important factor underlying optimal waste management is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For over 35 years since the publishing of 10CFR61, waste characterization has relied on sampling the final waste product after formation. In the days following 10CFR61, the cost of final disposal was marginal with only a small impact on the overall costs. Constraints were added by provisions of the Low Level Waste Policy Act of 1985 leading to increasingly limited access to those disposal sites that remained available. In addition, Nuclear Regulatory Commission (NRC) pressure promoting waste volume reduction led to disposal costs inevitably rising. Despite this, characterization practices in monitoring of waste generation for activity content still center on the same dated processes. This results in a disposal classification on the basis of endpoint sampling without consideration of the homogeneity of the waste mixture. It can also disregard consideration of the representativeness of the single or small sample base. As a minimum effort, a formalized sampling program of a fixed grouping of waste streams can be implemented that could account for more than 95% of all of the activity carried in solid waste products. The sample results for each radionuclide could then be trended as time passes to develop reasonable scaling factors for difficult to measure radionuclides. This process, identified in NRC guidance, has been rigorously followed by a relatively small number of facilities. The trended scaling factors serve to improve accuracy by identifying anomalous results that could otherwise go undetected. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality. This paper discusses viable options for developing the basis for characterization through process monitoring of the accumulation of activity at the point of generation. Special focus is on resin bed tracking and how process knowledge of these streams can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in this paper include the merger of the fission product release computer program, 3R-STAT, with the radwaste sample analysis computer program, SCAN4 to create 3R-SCAN, the importance of individual waste stream influences on the overall source term, and the use of historic sample data to develop scaling factors using an automated process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Northern Hemisphere Snow Drought in Earth System Model Simulations and ERA5‐Land Data in 1980–2014

Abstract Low snow levels over the past few decades and predictions of a low‐to‐no snow future have spurred research into snow droughts, which pose a threat to water security and management. Systematic data‐model comparisons of snow drought have been lacking, hindering our understanding of the drivers of snow drought in the past. To address this gap, we analyzed snow drought events using standardized snow water equivalent index derived from monthly results of four numerical experiments using the E3SM Land Model (ELM) and ERA5‐Land data during the period of 1980–2014. Additionally, we compared snow drought duration calculated from models with those from the ERA5‐Land data during selected El Niño‐Southern Oscillation (ENSO) years. The numerical experiments were conducted with ELM driven by two prescribed atmospheric forcings, and with the coupled land‐atmosphere configuration of E3SM with and without plant hydraulics scheme feedback. Analysis reveals that 20%–30% of snow droughts occur due to factors other than above‐normal temperature and low snowfall, such as low soil moisture, warm soil temperature, and low relative humidity, etc., especially in high latitudes (50° North). Furthermore, our study highlights the exacerbating effect of ENSO events on snow drought conditions in various regions, despite some discrepancies between model and ERA5‐Land results. We also identified limitations of the coupled land‐atmosphere models in our current configuration in capturing the spatial patterns of snow droughts. This study underscores the challenge of predicting and mitigating snow drought and the need for a comprehensive understanding of the factors contributing to snow drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Toward Enhancing Wastewater Treatment with Resource Recovery in Integrated Assessment and Computable General Equilibrium Models

Sustainable water management is essential to increasing water availability and decreasing water pollution. The wastewater sector is expanding globally and beginning to incorporate technologies that recover nutrients from wastewater. Nutrient recovery increases energy consumption but may reduce the demand for nutrients from virgin sources. We estimate the increase in annual global energy consumption (1,100 million GJ) and greenhouse gas emissions (84 million t CO2e) for wastewater treatment in the year 2030 compared to today’s levels to meet sustainable development goals. To capture these trends, integrated assessment and computable general equilibrium models that address the energy-water nexus must evolve. We reviewed 16 of these models to assess how well they capture wastewater treatment plant energy consumption and GHG emissions. Only three models include biogas production from the wastewater organic content. Four explicitly represent energy demand for wastewater treatment, and eight include explicit representation of wastewater treatment plant greenhouse gas emissions. Of those eight models, six models quantify methane emissions from treatment, five include representation of emissions of nitrous oxide, and two include representation of emissions of carbon dioxide. Our review concludes with proposals to improve these models to better capture the energy-water nexus associated with the evolving wastewater treatment sector.

42 ENGINEERING↗
DOE OSTI2024

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗
DOE OSTI1994

Nuclear Safety [Vol. 35, No. 2, July-December 1994]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 179 Consideration of Postaccident Consequences in the Determination of Safety Objectives for Future Nuclear Power Plants in France, D. Queniart, A. Sugier, and J. Lochard; ACCIDENT ANALYSIS: 187 Nuclear Safety Research: The Phebus FP Severe Accident Experimental Program, P. von der Hardt, A. V. Jones, C. Lecomte, and A. Tattegrain; 205 Containment Performance Analysis of the Advanced Neutron Source Reactor at the Oak Ridge National Laboratory, S. H. Kim, R. P. Taleyarkhan, and V. Georgevich; 213 Assessment of Fission Product Deposits in the Reactor Coolant System: The DEVAP Program, G. Le Marois and M. Megnin; 222 Erratum to “A Review of the Available Information on the Triggering Stage of a Steam Explosion," Vol. 35, No. 1, CONTROL AND INSTRUMENTATION: 223 Effects of Normal Aging on Calibration and Response Time of Nuclear Plant Resistance Temperature Detectors and Pressure Sensors, H. M. Hashemian; DESIGN FEATURES: 235 Defense in Depth Against the Hydrogen Risk—A European Research Program, F. Fineschi; ENVIRONMENTAL EFFECTS: 246 Technical Note: A Preliminary Analysis of the Risks to Hong Kong Resulting from Potential Accidents of Daya Bay Nuclear Power Plant, Z. Shi and X. Wei; OPERATING EXPERIENCES: 253 Reactor Shutdown Experience, Compiled by J. W. Cletcher; SPECIAL SECTION ON TMI-2 VESSEL INVESTIGATION PROJECT: 256 Three Mile Island—New Findings 15 Years After the Accident A. M. Rubin and E. Beckjord; 269 Relocation of Molten Material to the TMI-2 Lower Head, J. R. Wolf, D. W. Akers, and L. A. Neimark; 280 Insight Into the TMI-2 Core Material Relocation Through Examination of Instrument Tube Nozzles, L. A. Neimark; 288 Physical and Radiochemical Examinations of Debris from the TMI-2 Lower Head, D. W. Akers and B. K. Schuetz; 301 Results of Metallographic Examinations and Mechanical Tests of Pressure Vessel Samples from the TMI-2 Lower Head, D. R. Diercks and G. E. Korth; 313 Margin-to-Failure Calculations for the TMI-2 Vessel, J. Rempe, L. Stickler, S. Chavez, G. Thinnes, R. Witt, and M. Corradini; U.S. NUCLEAR REGULATORY COMMISSION INFORMATION AND ANALYSES: 328 1993 Accident Sequence Precursor (ASP) Program Results, L. N. Vanden Heuvel, J. W. Cletcher, D. A. Copinger, J. W. Minarick, B. W. Dolan, and P. D. O’Reilley; RECENT DEVELOPMENTS: 339 Reports, Standards, and Safety Guides, D. S. Queener; 345 Proposed Rule Changes as of June 30, 1994; ANNOUNCEMENTS: 234 Thirty-First Annual Meeting of the National Council on Radiation Protection and Measurements; 356 1995 International Incineration Conference; 358 Fifth International Controls and Instrumentation Conference; 359 ANS International Topical Meeting on Safety of Operating Reactors; 359 Fifth International Conference on Nuclear Criticality Safety; 360 International Conference on Probabilistic Safety Assessment Methodology and Applications; 351 The Authors; 357 Reviewers of Nuclear Safety, Vol. 35.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

The environmental footprint of data centers in the United States

Much of the world's data are stored, managed, and distributed by data centers. Data centers require a tremendous amount of energy to operate, accounting for around 1.8% of electricity use in the United States. Large amounts of water are also required to operate data centers, both directly for liquid cooling and indirectly to produce electricity. For the first time, we calculate spatially-detailed carbon and water footprints of data centers operating within the United States, which is home to around one-quarter of all data center servers globally. Our bottom-up approach reveals one-fifth of data center servers direct water footprint comes from moderately to highly water stressed watersheds, while nearly half of servers are fully or partially powered by power plants located within water stressed regions. Approximately 0.5% of total US greenhouse gas emissions are attributed to data centers. We investigate tradeoffs and synergies between data center's water and energy utilization by strategically locating data centers in areas of the country that will minimize one or more environmental footprints. Our study quantifies the environmental implications behind our data creation and storage and shows a path to decrease the environmental footprint of our increasing digital footprint.

54 ENVIRONMENTAL SCIENCES↗