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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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At least 361 records · Page 20

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Comfort and Safety Metrics to Evaluate Customer Centric Resilience Enhancement Strategies

As the coincident events of extreme weather and major power outages continue to rise there is an increased need to implement resilience solutions. Many of these solutions are customer-centric, requiring the flexibility of demand, and many of the standard economic evaluations of these solutions do not include the benefits of resilience that are not easily quantified and monetized. Indoor air temperature has a large impact on the comfort and safety of building occupants during an extreme weather event. This work proposes metrics that can be used to compare the performance of resilience solutions in the context of comfort and safety.

Cost benefit analysis, Demand Side Management, Pow↗

Energy and Momentum in Mechanical Impact Testing

The ASTM G86 method is used to determine the ignition sensitivity of materials to mechanical impact in oxygen. It has long been known that different systems built to the standard produce different results. Given the current push towards direct comparison of numerical results from different systems rather than just material rankings, it is desirable to normalize the systems to some performance-based metric. Normalization is complicated by the fact that the energy and momentum of a particular impact scale differently with plummet mass and drop height, and therefore adjusting the mass and height to account for system differences would result in a different impact. The standard uses dent blocks to assess impacts. However, it was unknown if the differences in momentum could be identified during dent block impacts. To determine this, dent blocks were impacted with constant energy and different momentums, using instrumented and non-instrumented plummets. The dent blocks showed statistically significant differences in the penetration function when subjected to impacts with the same energy but different momentum. Further, the instrumented plummet showed drastic differences in the power delivery with different momentums. System configuration was also shown to have an effect on the response of the penetration function to different momentums.

Energy↗

Energy and Momentum in Mechanical Impact Testing

The ASTM G86 method is used to determine the ignition sensitivity of materials to mechanical impact in oxygen. It has long been known that different systems built to the standard produce different results. Given the current push towards direct comparison of numerical results from different systems rather than just material rankings, it is desirable to normalize the systems to some performance-based metric. Normalization is complicated by the fact that the energy and momentum of a particular impact scale differently with plummet mass and drop height, and therefore adjusting the mass and height to account for system differences would result in a different impact. The standard uses dent blocks to assess impacts. However, it was unknown if the differences in momentum could be identified during dent block impacts. To determine this, dent blocks were impacted with constant energy and different momentums, using instrumented and non-instrumented plummets. The dent blocks showed statistically significant differences in the penetration function when subjected to impacts with the same energy but different momentum. Further, the instrumented plummet showed drastic differences in the power delivery with different momentums. System configuration was also shown to have an effect on the response of the penetration function to different momentums.

Energy↗

Cambium 2022 Scenario Descriptions and Documentation

The National Renewable Energy Laboratory’s (NREL’s) Cambium data sets are annually released sets of simulated hourly emission, cost, and operational data for a range of modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision making. The 2022 Cambium data set is the third annual release. The data sets are a companion product to NREL’s Standard Scenarios, which are likewise released annually and are a set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, but covering more scenarios with less temporal granularity. In this documentation, we describe Cambium 2022’s scenarios (Section 3), define the metrics (Section 5), and document the Cambium-specific methods for calculating those metrics (Section 6).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Acidic Oxygen Evolution Reaction Activity–Stability Relationships in Ru-Based Pyrochlores

Ru-based oxygen evolution reaction (OER) catalysts show significant promise for efficient water electrolysis, but rapid degradation poses a major challenge for commercial applications. In this work, we explore several Ru-based pyrochlores (A 2 Ru 2 O 7 , A = Y, Nd, Gd, Bi) as OER catalysts and demonstrate improved activity and stability of catalytic Ru sites relative to RuO 2 . Furthermore, we combine complementary experimental and theoretical analysis to understand how the A-site element impacts activity and stability under acidic OER conditions. Among the A 2 Ru 2 O 7 studied herein, we find that a longer Ru–O bond and a weaker interaction of the Ru 4d and O 2p orbitals compared with RuO 2 results in enhanced initial activity. We observe that the OER activity of the catalysts changes over time and is accompanied by both A-site and Ru dissolution at different relative rates depending on the identity of the A-site. Pourbaix diagrams constructed using density functional theory (DFT) calculations reveal a driving force for this experimentally observed dissolution, indicating that all compositions studied herein are thermodynamically unstable in acidic OER conditions. Theoretical activity predictions show consistent trends between A-site cation leaching and OER activity. These trends coupled with Bader charge analysis suggest that dissolution exposes highly oxidized Ru sites that exhibit enhanced activity. Overall, using the stability number (molO2 evolved/molRu dissolved) as a comparative metric, the A 2 Ru 2 O 7 materials studied in this work show substantially greater stability than a standard RuO2 and commensurate stability to some Ir mixed metal oxides. Finally, the insights described herein provide a pathway to enhanced Ru catalyst activity and durability, ultimately improving the efficiency of water electrolyzers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Impacts to baleen whales are of particular concern in the context of offshore wind development because of their conservation status, the overlap of their habitat with current and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The scope of this report is to assess the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions in conjunction with offshore wind foundation installation. This work considers the performance of various sensing technologies that can be used to observe the presence of baleen whales near offshore construction activities. The scope of work includes: 1. Technology Performance Metrics – Identify metrics that can be used to assess technology performance. 2. Technology Evaluation – Synthesize the past performance of technologies with respect to the performance metrics based on available literature. 3. Technology Characterization Framework – Describe a potential framework to characterize technology performance with a standardized approach. 4. Technology Research and Development Needs – Identify future needs and opportunities for research, development, and deployment to improve technologies.

17 WIND ENERGY↗

AI-Driven Crack Detection for Remanufacturing Cylinder Heads Using Deep Learning and Engineering-Informed Data Augmentation

Detecting cracks in cylinder heads traditionally relies on manual inspection, which is time-consuming and susceptible to human error. As an alternative, automated object detection utilizing computer vision and machine learning models has been explored. However, these methods often face challenges due to a lack of sufficiently annotated training data, limited image diversity, and the inherently small size of cracks. Addressing these constraints, this paper introduces a novel automated crack-detection method that enhances data availability through a synthetic data generation technique. Unlike general data augmentation practices, our method involves copying cracks from one location to another, guided by both random and informed engineering decisions about likely crack formations due to cyclic thermomechanical loads. The innovative aspect of our approach lies in the integration of domain-specific engineering knowledge into the synthetic generation process, which substantially improves detection accuracy. We evaluate our method’s effectiveness using two metrics: the F2 score, which emphasizes recall to prioritize detecting all potential cracks, and mean average precision (MAP), a standard measure in object detection. Experimental results demonstrate that, without engineering insights, our method increases the F2 score from 0.40 to 0.65, while maintaining a stable MAP. Incorporating detailed engineering knowledge further enhances the F2 score to 0.70 and improves MAP to 0.57, representing increases of 63% and 43%, respectively. These results confirm that our approach not only mitigates the limitations of traditional data augmentation but also significantly advances the reliability and precision of crack detection in industrial settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Artificial Neural Network Modeling for Airline Disruption Management

Since the 1970s, most airlines have incorporated computerized support for managing disruptions during flight schedule execution. However, existing platforms for airline disruption management (ADM) employ monolithic system design methods that rely on the creation of specific rules and requirements through explicit optimization routines, before a system that meets the specifications is designed. Thus, current platforms for ADM are unable to readily accommodate additional system complexities resulting from the introduction of new capabilities, such as the introduction of unmanned aerial systems (UAS), operations and infrastructure, to the system. To this end, we use historical data on airline scheduling and operations recovery to develop a system of artificial neural networks (ANNs), which describe a predictive transfer function model (PTFM) for promptly estimating the recovery impact of disruption resolutions at separate phases of flight schedule execution during ADM. Furthermore, we provide a modular approach for assessing and executing the PTFM by employing a parallel ensemble method to develop generative routines that amalgamate the system of ANNs. Our modular approach ensures that current industry standards for tardiness in flight schedule execution during ADM are satisfied, while accurately estimating appropriate time-based performance metrics for the separate phases of flight schedule execution.

Kolawole Ogunsina↗

Performance Metrics to Evaluate Utility Resilience Investments

In 2019, Sandia National Laboratories (Sandia) contracted Synapse Energy Economics (Synapse) to research the integration of community and electric grid resilience investment planning as part of the Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis (BCA), performance metrics, microgrids, and regulatory mechanisms. This report focuses on BCA. BCA is an approach that electric utilities, electric utility regulators, and communities can use to evaluate the costs and benefits of a wide range of grid resilience investments in a comprehensive and consistent way. While BCA is regularly applied to some types of grid investments, application of BCA to grid resilience investments is in the early stages of development. Though resilience is increasingly cited in connection with grid investment proposals and plans, the resilience- related costs and benefits of grid resilience investments are typically not fully identified, infrequently quantified, and almost never monetized. Without complete assessments of costs and benefits, regulators can be hesitant to approve some types of grid resilience investments. This report provides the first application of the framework developed in the 2020 National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources (NSPM for DERs) to grid resilience investments. We provide guidance on next steps for implementation to enable grid resilience investments to receive due consideration. We suggest developing BCA principles and standards for jurisdiction-specific BCA tests. We also recommend identifying the resilience impacts of the investments and quantification of these impacts by establishing utility performance metrics for resilience. Proactive integration of grid resilience investments into existing regulatory processes and practices can increase the capacity of jurisdictions to respond to and recover from the consequences of extreme events. 1 National Energy Screening Project. 2020. National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DCS: A Case Study of Identification of Knowledge and Disposition Gaps Using Principles of Continuous Risk Management

The Human Research Program (HRP) is formulated around the program architecture of Evidence-Risk-Gap-Task-Deliverable. Review of accumulated evidence forms the basis for identification of high priority risks to human health and performance in space exploration. Gaps in knowledge or disposition are identified for each risk, and a portfolio of research tasks is developed to fill them. Deliverables from the tasks inform the evidence base with the ultimate goal of defining the level of risk and reducing it to an acceptable level. A comprehensive framework for gap identification, focus, and metrics has been developed based on principles of continuous risk management and clinical care. Research towards knowledge gaps improves understanding of the likelihood, consequence or timeframe of the risk. Disposition gaps include development of standards or requirements for risk acceptance, development of countermeasures or technology to mitigate the risk, and yearly technology assessment related to watching developments related to the risk. Standard concepts from clinical care: prevention, diagnosis, treatment, monitoring, rehabilitation, and surveillance, can be used to focus gaps dealing with risk mitigation. The research plan for the new HRP Risk of Decompression Sickness (DCS) used the framework to identify one disposition gap related to establishment of a DCS standard for acceptable risk, two knowledge gaps related to DCS phenomenon and mission attributes, and three mitigation gaps focused on prediction, prevention, and new technology watch. These gaps were organized in this manner primarily based on target for closure and ease of organizing interim metrics so that gap status could be quantified. Additional considerations for the knowledge gaps were that one was highly design reference mission specific and the other gap was focused on DCS phenomenon.

Norcross, Jason↗

Reliability Analysis and Standardization of Spacecraft Command Generation Processes

center dot In order to reduce commanding errors that are caused by humans, we create an approach and corresponding artifacts for standardizing the command generation process and conducting risk management during the design and assurance of such processes. center dot The literature review conducted during the standardization process revealed that very few atomic level human activities are associated with even a broad set of missions. center dot Applicable human reliability metrics for performing these atomic level tasks are available. center dot The process for building a "Periodic Table" of Command and Control Functions as well as Probabilistic Risk Assessment (PRA) models is demonstrated. center dot The PRA models are executed using data from human reliability data banks. center dot The Periodic Table is related to the PRA models via Fault Links.

human errors.↗

Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model

Contact Graph Routing (CGR) for Delay/Disruption Tolerant Networking (DTN) space-based networks makes use of the predictable nature of node contacts to make real-time routing decisions given unpredictable traffic patterns. The contact graph will have been disseminated to all nodes before the start of route computation. CGR was designed for space-based networking environments where future contact plans are known or are independently computable (e.g., using known orbital dynamics). For each data item (known as a bundle in DTN), a node independently performs route selection by examining possible paths to the destination. Route computation could conceivably run thousands of times a second, so computational load is important. This work refers to the simulation software model of Enhanced Contact Graph Routing (ECGR) for DTN Bundle Protocol in JPL's MACHETE simulation tool. The simulation model was used for performance analysis of CGR and led to several performance enhancements. The simulation model was used to demonstrate the improvements of ECGR over CGR as well as other routing methods in space network scenarios. ECGR moved to using earliest arrival time because it is a global monotonically increasing metric that guarantees the safety properties needed for the solution's correctness since route re-computation occurs at each node to accommodate unpredicted changes (e.g., traffic pattern, link quality). Furthermore, using earliest arrival time enabled the use of the standard Dijkstra algorithm for path selection. The Dijkstra algorithm for path selection has a well-known inexpensive computational cost. These enhancements have been integrated into the open source CGR implementation. The ECGR model is also useful for route metric experimentation and comparisons with other DTN routing protocols particularly when combined with MACHETE's space networking models and Delay Tolerant Link State Routing (DTLSR) model.

Segui, John S.↗

Current Performance Characteristics of NASA Langley Research Center's Cockpit Motion Base and Standardized Test Procedure for Future Performance Characterization

This report documents the updated performance characteristics of NASA Langley Research Center's (LaRC) Cockpit Motion Base (CMB) after recent revisions that were made to its inner-loop, feedback control law. The modifications to the control law will be briefly described. The performance of the CMF will be presented. A short graphical comparison to the previous control law can be found in the appendix of this report. The revised controller will be shown to yield reduced parasitic accelerations with respect to the previous controller. Metrics based on the AGARD Advisory Report No. 144 are used to assess the overall system performance due to its recent control algorithm modification. This report also documents the standardized simulator test procedure which can be used in the future to evaluate potential updates to the control law.

Cowen, Brandon↗

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Australian Solar Energy Forecasting System (ASEFS) (CRADA CRD-14-541 Final Report)

This project forms a part of the broader project with the same name which is funded by ASI under the US-Australia Solar Energy Collaboration (Broader Project). The Broader Project involves a number of other participants, being the University of New South Wales, the University of South Australia, the Australian Energy Market Operator Limited and the Commonwealth of Australia acting through the Bureau of Meteorology (Other Participants). NREL and CSIRO will each work with the Other Participants in the performance of this CRADA. However, for the avoidance of doubt, this CRADA does not cover the whole of the Broader Project and only relates to the work described in this Joint Work Statement, which is to be carried out by NREL. In the course of this project, NREL may be provided with materials belonging to CSIRO or the Other Participants, which it may use solely for the purpose of performing the project described in this Joint Work Statement. Similarly, CSIRO may provide NREL project materials to Other Participants pursuant to Article IX or XV of the CRADA, for the purpose of performing research forming part of the Broader Project in collaboration with CSIRO.

14 SOLAR ENERGY↗

Large-scale Hydrogen Storage Risk Assessment

This project investigated risks involved in deploying a large-scale hydrogen storage system at the Port of Seattle (hereafter, the Port) for its on-terminal and maritime applications in an urban industrial setting. Alongside, the project attempted to address some of the barriers to risk assessment such as need for an exact system design for a systematic investigation, direct access to surrounding communities to gauge their perceptions, and an integrated software required to undertake a full-fledged risk assessment. These barriers were overcome using illustrative reference station designs, engaging with community-facing agencies through Port support, and pooling national laboratory capabilities available for risk assessments. The project identified relevant public safety risk metrics, compared various hydrogen carriers, engaged with community-facing agencies, and explored potential gaps in existing safety codes and standards. The primary impacts of this project include the development of risk assessment guidance for ports and utilities, informing them of the trade-offs in the choice of hydrogen carriers, and the ability to increase public capacity for dialog and engagement. This paves the way toward decarbonization of the Port activities, bringing about awareness around jobs in the market for risk assessments, and the need to ramp up community engagement long before any hydrogen system deployment is undertaken.

08 HYDROGEN↗

The Current State of Light-Duty Electric Vehicle Supply Equipment Costs: An Assessment of Contemporary Understanding

This study uses a hybrid meta-analysis and literature-review approach to understand the current state of knowledge regarding the costs of electric vehicle supply equipment (EVSE). We present a novel way to consider, categorize, and label measures of cost and show cost measure estimates from a sample of 13 recent studies. We find that in general, there is too much variation and too few commonly represented EVSE cost measures to reasonably provide aggregate figures for these measures. We propose a convention for presenting EVSE cost measures that includes the application (commercial or residential), the power level (Level 1, Level 2, DCFC [with further distinction based on rated power capacity]), and the type of cost measure (hardware, installation, operation, and total cost). We contend that providing researchers with standard cost measures will help to advance our knowledge of EVSE costs by ensuring that future work will use common metrics. Establishing common metrics will enable conventional meta-analyses that will make assessments of EVSE costs even more accessible. Additionally, common metrics will make tracking costs more reliable as the technology continues to evolve and become more ubiquitous.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗