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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probabilistic Assessment of High-Renewables Power Systems: Current Work and Future Directions

In a future with higher penetrations of variable and energy-limited resources, the dominant sources of resource adequacy risk begin to shift from (assumed) independent thermal unit outages to spatially- and temporally-correlated weather-driven phenomena. Traditional resource adequacy assessment and planning methods can be ill-suited to such scenarios. This presentation will highlight aspects of NREL's work in adapting and developing new probabilistic methods and tools in anticipation of the needs of the power system planning exercises of tomorrow.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Derivation of Capabilities and Resources for Treating Medical Conditions in Deep Space

BACKGROUND: Medical care in spaceflight requires the adaptation of terrestrial standards to the constraints of the space environment. However, there is often conflict between the ideal resources required for treatment and diagnosis of a medical condition, and the constraints on their mass, volume, data needs, etc. This optimization of trades between medical risk and resources will be a significant challenge for deep space medical system design. METHODS: A team of physicians with a broad range of expertise reviewed the 120 medical conditions on the condition list for NASA’s Informing Mission Planning via analysis of Complex Tradespaces Medical Database (IMPACT-MD). Each team member was assigned a subset of conditions based on their experience and training. The assigned physician generated a proposed list of capabilities, definitions, and resources required to treat each condition based on terrestrial practice guidelines, medical literature, and subject matter expertise. Additional specialists were consulted for conditions where expertise was not present within the main group. The proposed list was then reviewed by the broader team and modified as needed to achieve consensus. Each capability and resource was then assigned parameters to define quantity required per medical event, necessity, training level required, and primacy order of any alternative resources. These capabilities and resources were placed into condition specific tables and delivered to a team of engineers who added mass and volume data for each specific resource and converted the table into a database for use as input to a computational model to simulate spaceflight (IMPACT) DISCUSSION: This process ensures that a minimum of three subject matter experts review and agree upon the scope of practice, medical diagnostic tools, and treatment modalities that would be necessary to address emergent and non-emergent conditions that may arise during spaceflight to inform requirements during the vehicle design phase. The method is scalable to any design reference mission and permits modification of the existing database as information, conditions or experience are added. By including specialists, generalists, and those with subject matter expertise in the spaceflight environment on the team, we ensure that the included capabilities represent a realistic and actionable foundation for planning deep space missions.

D R Levin↗
DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗
NASA NTRSDate not supplied

Baseline Medical System Translation for the Impact Medical Database

NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model (IMM). This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). Whereas IMM focuses on the resources and risks associated with International Space Station (ISS) and Low Earth Orbit (LEO) missions, IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. One of the services offered by IMM is a series of generic or baseline medical systems associated with typical mission types or DRMs (Design Reference Missions), such that requestors may prioritize questions pertaining to the mission itself over the medical supplies indicated by the model outputs for that DRM. In a mission focused request, the appropriate baseline medical system is used in place of a prepared or optimized medical kit. In preparation, an effort was undertaken to create baseline systems of medical resources within IMPACT suitable for typical DRMs. Using an existing baseline medical system within IMM’s Integrated Medical Evidence Database (iMED) as a starting point, the resources found within the medical kit were compared to and substituted for equivalent resources available within the IMPACT MD (Medical Database). In consultation with clinicians with knowledge of IMPACT’s MD, each resource was matched as closely as possible to a similarly purposed resource in IMPACT, seeking to preserve the treatment capabilities and procedures offered by the IMM medical system while reconciling the differences in modeled resources and medical conditions between the models. To demonstrate the efficacy of this work, a prototype ISS medical system in IMPACT was translated from the baseline used in the IMM. The appropriate medical system was then run through its associated medical model to compare and validate the resultant risks and risk mitigation provided by each baseline ISS medical kit.

S Schwartz↗
DOE OSTI2020

An Improved Risk Priority Measure for the Management of Project Risk

Monte Carlo-based project risk models are essential tools in project risk management, particularly for large, complex projects in which it is difficult to glean intuitively the importance of individual risks to the overall project. Conventional correlation-based methods for measuring the importance of contributing risks in such models are argued here to be both statistically flawed and unintuitive in the importance metrics they produce. Drawing on and adapting methods more traditionally associated with engineering risk models, Risk Reduction Worth (RRW) is introduced as an importance measure. RRW is shown to be statistically robust and provide an easily interpretable, quantitative measure of the importance of a risk to the overall performance of a project; specifically, measuring the extent to which removal of a risk would improve confidence in project outcomes. To ensure practicality of the method, an approach is described in which RRWs can be produced for all contributing risks based on a single Monte Carlo sample. This is demonstrated through application to a large, complex project risk model from which intuitive risk importance insights provide a robust, transparent basis for the allocation of risk management resources.

Risk↗
DOE OSTI2021

Risk Management for Distributed Energy Resources

The National Institute of Standards and Technology will be hosting on Tuesday, February 2 and Wednesday, February 3, 2021, the second workshop in a new series focusing on the Open Security Controls Assessment Language. NREL extended the scope of the DERCF to include the NIST Risk Management Framework (RMF), addressing the challenges faced by federal energy managers when complying with the NIST RMF for DER systems. The NIST RMF is a cyclical process designed to incorporate principles of security and risk management into an organization’s system policies and procedures. The DER-RM will be downloadable application that runs locally and documents all the major requirements for achieving Authority to Operate the DER.

cybersecurity↗
NASA NTRSDate not supplied

Crowd Sourcing Medical Data Collection Using Medical Students

OBJECTIVE We undertook an upgrade of the Evidence Library database of NASA HRP’s Integrated Medical Model, assessing 120 medical conditions which integrate with a novel probabilistic risk assessment (IMPACT) tool of medical risk and resource utilization for long duration exploration human spaceflight. This data collection process included a selection of these conditions crowd sourced over one year via three 4-week medical student electives at the University of Colorado School of Medicine (IDPT 8059 Space Medicine: Human Spaceflight Factors & Medical Risk Assessment). Students undertook a rapid systematic review of each medical condition, under close preceptors with backgrounds in clinical medicine, library science, epidemiology, biostatistics, and evidence-based medicine. As part of the elective, students also received instruction in core space medicine concepts, evidence based medicine and problem based learning sessions as a flight surgeon supporting a simulated Mars mission. METHODS The list of 120 medical conditions includes both common, terrestrial illness/injury (epistaxis, diverticulitis) as well as spaceflight-specific ones (space adaptation conditions, EVA-related injuries). A rapid systematic review process was developed that would allow students to find the data for determining disease incidence/prevalence, return to definitive care (often a surrogate such as hospitalization rates), loss of crew life, and treatment duration. Each data point required a tailored, specialized search process using different databases and corresponding specialized search filters. Databases were selected on their ability to provide high quality literature in an efficient manner and prioritized by their ability to provide graded evidence via a set rubrics specific to human spaceflight. Students were responsible for performing all literature searches and identifying the highest quality available evidence for each data point. Completed student data sheets underwent initial review by faculty preceptors followed by a secondary editing review by the ExMC Clinical Science Team. RESULTS Over the course of three electives, approximately 105 medical conditions were researched by students using spreadsheets with pre-crafted search strategies. Overall, this process was successful in allowing students to perform the preponderance of work to update incidence, treatment duration, return to definitive care, and loss of crew life data points. Students were successful in running searches, identifying the necessary data points within the literature, and determining the types of terrestrial data that most aligns with the astronaut population for successful completion of their tasks. Limitations included variable student experience with search methodologies [PubMed], differing values of evidence grading [best practice evidence based medicine vs. relevant to spaceflight], and students’ unfamiliarity with spaceflight specific conditions. CONCLUSION Finding the relevant literature for medical conditions in spaceflight within terrestrial databases in a systematic method is time consuming and not intuitive. However, the stepwise process that balanced sensitivity with specificity allowed for students to be highly successful in a short amount of time. Additionally, as the process was refined over the course of three electives, preceptors were better able to anticipate where students were likely to encounter barriers, which allowed the course to be adjusted to account for certain data points needing more time for completion. This replicable process may be an efficient way to accomplish rapid systematic reviews for a large volume of data in a short amount of time.

J Lemery↗
DOE OSTI2026

Cybersecurity Risk Profiles for Distributed Energy Resource Management Systems

Managing the digitalization of increasingly diversity energy resources is a complex challenge for energy systems planners and managers. As the penetration of solar photovoltaics (PV) and other distributed renewable energy resources (DERs) expands, distributed energy resource management systems (DERMS) will play an increasingly important role in managing, monitoring, and controlling DERs as electric systems before more distributed, interconnected, and networked. However, the cybersecurity implications of DERMS deployments are not well understood today. A lack of understanding around the cybersecurity implications of DERMS deployments and variability in the security posture of DERMS vendors, owners, and operators could introduce new security risks to evolving electric power systems. This paper describes cybersecurity attack scenarios on DERMS, identifies related cybersecurity standards and guidelines, reviews the security features of state-of-the-art DERMS solutions, and offers cybersecurity guidance for DERMS vendors, owners, and operators to protect DERMS' unique capabilities. Standardizing cybersecurity requirements for DERMS could help improve the security of DERMS integrations and improve innovations that are more secure by design. The cybersecurity guidance found in this paper is intended to offer a unified approach and lay the foundation for future standardization of DERMS cybersecurity to reduce risk to the solar industry and other renewable energy stakeholders when integrating these technologies with electric power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Gulf of Mexico Risk Analysis Database (GoMRAD)

The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.

BOEM,Bathymetry,Gulf Of Mexico,Machine Learning,Me↗
DOE OSTI2020

Distributed Energy Resources Cybersecurity Framework: Applying the NIST Risk Management Process

In an effort to strengthen the cybersecurity posture for federal agencies and reduce the time and complexities of following the Risk Management Framework (RMF) six-step process, the National Renewable Energy Laboratory has dedicated research into expanding the existing Distributed Energy Resources Cybersecurity Framework to provide functionality that aids in the RMF steps. Users will have the opportunity to learn, document, and review the framework, saving time and resources. Existing functionality within the web application will continue to be available with added features for usability.

14 SOLAR ENERGY↗
DOE OSTI2025

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗
DOE OSTI2023

International Cybersecurity: Capabilities and Overview [Slides]

Innovations in clean energy technology are beginning to transform electric grids around the world. It is more important than ever to understand and improve the resiliency and security of the grid against natural and human disruptions as our energy systems become more distributed, intelligent, and interconnected. Through its advanced cybersecurity technical assistance portfolio, experts at the National Renewable Energy Laboratory (NREL) work with international governments to support secure and resilient deployment of renewable energy assets and address grid interconnection challenges. Cybersecurity technical assistance is tailored to the needs of our international partners.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗
NASA NTRS2008

DARPA/USAF/USN J-UCAS X-45A System Demonstration Program: A Review of Flight Test Site Processes and Personnel

The Joint Unmanned Combat Air Systems (J-UCAS) program is a collaborative effort between the Defense Advanced Research Project Agency (DARPA), the US Air Force (USAF) and the US Navy (USN). Together they have reviewed X-45A flight test site processes and personnel as part of a system demonstration program for the UCAV-ATD Flight Test Program. The goal was to provide a disciplined controlled process for system integration and testing and demonstration flight tests. NASA's Dryden Flight Research Center (DFRC) acted as the project manager during this effort and was tasked with the responsibilities of range and ground safety, the provision of flight test support and infrastructure and the monitoring of technical and engineering tasks. DFRC also contributed their engineering knowledge through their contributions in the areas of autonomous ground taxi control development, structural dynamics testing and analysis and the provision of other flight test support including telemetry data, tracking radars, and communications and control support equipment. The Air Force Flight Test Center acted at the Deputy Project Manager in this effort and was responsible for the provision of system safety support and airfield management and air traffic control services, among other supporting roles. The T-33 served as a J-UCAS surrogate aircraft and demonstrated flight characteristics similar to that of the the X-45A. The surrogate served as a significant risk reduction resource providing mission planning verification, range safety mission assessment and team training, among other contributions.

Cosentino, Gary B.↗
NASA NTRS2010

NASA Applied Sciences Program

Goal 1: Enhance Applications Research Advance the use of NASA Earth science in policy making, resource management and planning, and disaster response. Key Actions: Identify priority needs, conduct applied research to generate innovative applications, and support projects that demonstrate uses of NASA Earth science. Goal 2: Increase Collaboration Establish a flexible program structure to meet diverse partner needs and applications objectives. Key Actions: Pursue partnerships to leverage resources and risks and extend the program s reach and impact. Goal 3:Accelerate Applications Ensure that NASA s flight missions plan for and support applications goals in conjunction with their science goals, starting with mission planning and extending through the mission life cycle. Key Actions: Enable identification of applications early in satellite mission lifecycle and facilitate effective ways to integrate end-user needs into satellite mission planning

Irwin, Daniel↗
DOE OSTI2022

Market-Integrated Optimization of Wind-Battery-Hydrogen Hybrids for Peaking Capacity via Storage

As Integrated Energy Systems (IES) combine multiple energy and storage technologies to provide potentially more value and less risk via resource diversification, complementary overbuild, increased flexibility, and revenue-stacking, IES value is dependent on electricity market dispatch and grid interactions should play an important role in IES design and operation. This study hybridizes and retrofits wind and combustion turbine plants to study the impacts of replacing gas generation capacity with wind, battery, PEM electrolysis, hydrogen tanks and hydrogen turbines. The optimized design is co-simulated in a production cost model with different bidding strategies in order to compare performance and highlight the importance of grid-interactions. We analyze the revenue and dispatch changes as well as the price and cost implications of wind-battery-hydrogen IESs.

electrolysis↗
DOE OSTI2025

DEVELOPMENT AND APPLICATION OF RISK ANALYSIS TOOLKIT FOR PLANT RESOURCE OPTIMIZATION

This paper presents the development of methods and tools that are being designed to optimize plant operations (e.g., maintenance/replacement schedules and optimal maintenance postures for plant components) in a manner that is more cost effective than current approaches and makes better use of available component health and cost data. These methods include both data- and model-based optimization methods. Model-based optimization methods directly include reliability and cost models to determine an optimal plant operational strategy. We consider gradient-based and evolutionary (based on genetic algorithms) optimization methods. The second class of methods target more specific use cases (e.g., project schedule optimization) and are not based on reliability models directly, but they require specific component reliability and cost data. This class of methods is based on variants of the knapsack problem with an aim to determine an optimal project schedule that maximizes the overall NPV. This paper also presents multi-objective methods designed to identify an optimal maintenance posture based on a Pareto frontier analysis. Rather than dictating the “right” tradeoff (i.e., identify the absolute best posture), we show how it is possible to perform a trade space exploration approach (i.e., identify value and costs of several postures and let the analysis account for desired value and cost metrics). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space. For all these methods we present detailed applicative examples that show their validity from a decision-making perspective.

97 - MATHEMATICS AND COMPUTING↗