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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Computational Assessment of Inlet Backflow Effects on Rotating Detonation Engine Performance and Operability

The performance impact of flow reversal at the inlet of an airbreathing rotating detonation engine (RDE) is investigated using 2 and 3-dimensional computational fluid dynamic (CFD) simulations. Flow reversal, or backflow, occurs in RDE inlets in the high-pressure region directly behind the rotating detonation front. This is also where most of the engine thrust or pressure gain is produced. The amount of backflow relative to throughflow depends on the inlet design. For the present work, a simple annular ‘slit’ design is used. The simulations are idealized in several ways, including that fuel and air are premixed, but prevented from reacting when within the inlet region. The results indicate that even with idealizations, the impact of inlet backflow on pressure gain can be substantial. The simulations also reveal an intriguing instability that develops in certain configurations. The mass flow rate into the RDE begins to oscillate at a regular frequency that is substantially less than the detonation rotational frequency. This is accompanied by oscillations in the detonation height. The oscillation amplitude grows over time until the detonation ultimately fails. Both the performance and instability results emphasize the need for carefully designed RDE inlets that provide low loss when flow is in the forward direction, but high resistance when the flow is reversed. Development of such high-diodicity inlets is critical to achieving pressure gain in airbreathing RDE’s.

Detonation↗
NASA NTRSDate not supplied

Computational Assessment of Inlet Backflow Effects on Rotating Detonation Engine Performance and Operability

The performance impact of flow reversal at the inlet of an airbreathing rotating detonation engine (RDE) is investigated using 2 and 3-dimensional computational fluid dynamic (CFD) simulations. Flow reversal, or backflow, occurs in RDE inlets in the high-pressure region directly behind the rotating detonation front. This is also where most of the engine thrust or pressure gain is produced. The amount of backflow relative to throughflow depends on the inlet design. For the present work, a simple annular ‘slit’ design is used. The simulations are idealized in several ways, including that fuel and air are premixed, but prevented from reacting when within the inlet region. The results indicate that even with idealizations, the impact of inlet backflow on pressure gain can be substantial. The simulations also reveal an intriguing instability that develops in certain configurations. The mass flow rate into the RDE begins to oscillate at a regular frequency that is substantially less than the detonation rotational frequency. This is accompanied by oscillations in the detonation height. The oscillation amplitude grows over time until the detonation ultimately fails. Both the performance and instability results emphasize the need for carefully designed RDE inlets that provide low loss when flow is in the forward direction, but high resistance when the flow is reversed. Development of such high-diodicity inlets is critical to achieving pressure gain in airbreathing RDE’s.

detonation↗
DOE OSTI2025

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

Traditional hazards analysis (HA) methods, originally developed to address physical and operational risks, often fall short when it comes to identifying and mitigating cyber threats. These cyber threats pose unique and evolving risks to critical infrastructure and industrial control systems (ICS). This report explores the integration of Cyber-Informed Engineering (CIE) principles into existing HA methods to enhance their ability to address cyber-induced risks. CIE provides organizations with a practical, cost-effective approach to closing the gap between traditional HA methods and the need for cyber risk mitigation. By leveraging existing safety processes and controls, CIE allows users to examine and mitigate cyber vulnerabilities without overhauling existing HA methods. This report identifies areas where HA and CIE naturally align and where their approaches diverge. It emphasizes how CIE principles can be used to adapt HA methods, broadening their scope to include cyber risks and enabling the mitigation of cyber- induced impacts alongside traditional hazards and failure scenarios. This report examines how CIE can be applied across various HA methods—such as Hazard and Operability Studies (HAZOP), Probabilistic Risk Assessment (PRA), Failure Modes and Effects Analysis (FMEA), Systems-Theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), and Layers of Protection Analysis (LOPA). It provides strategies for integrating CIE to strengthen the identification, assessment, and mitigation of cyber-induced risks. The findings offer a structured entry point for organizations to embed CIE concepts into hazards and safety analyses, as well as broader engineering processes, ultimately supporting the design and operation of a more resilient infrastructure.

42 ENGINEERING↗
DOE OSTI2026

Demonstration of Electrolyzer Operation at a Nuclear Plant to Allow for Dynamic Participation in an Organized Electricity Market and In-House Hydrogen Supply

This document details the execution of Cooperative Agreement DE-EE0008849, “demonstration of electrolyzer operation at a nuclear plant to allow for dynamic participation in an organized electricity market and in-house hydrogen supply” during the performance period of 10/1/2019 – 9/30/2024. The project was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE). Constellation Energy Generation, LLC (formerly Exelon Generation Company, LLC) is the prime recipient of the award. Other members of the project team are INL, NREL, ANL and Nel Hydrogen. The main project objective was to demonstrate an end-to-end integrated grid-scale carbon-free H 2 production, storage and utilization pilot plant at a nuclear generating facility. The project also aimed to evaluate market opportunities and regulatory requirements related to the participation of integrated hydrogen production and nuclear plant facilities in organized power markets, by demonstrating dynamic control and operation of the electrolyzer and assessing the economics of dynamic participation combined with the revenue streams from hydrogen production. On March 7th , 2023 Constellation started hydrogen production at it’s Nine Mile Point Nuclear Plant in Oswego, New York. The PEM electrolyzer operating at Nine Mile Point uses 1.25 megawatt of nuclear electricity to produce 560 kilograms of clean hydrogen per day, more than enough to meet the plant’s operational hydrogen use. It will also help set the stage for possible large-scale deployments at other clean energy centers in Constellation’s fleet that would couple clean hydrogen production with storage and other on-site uses. Employing the lessons learned from the 1.25 MW demonstration-scale, nuclear-powered clean hydrogen production facility at Nine Mile Point, Constellation was a major participant in the MachH2 hydrogen hub recently selected for up to $\$$1 billion by the Department of Energy (DOE) as part of the bipartisan Infrastructure Investment and Jobs Act. Constellation will use a portion of the hub funding to build the world’s largest nuclear-powered clean hydrogen production facility at its LaSalle Clean Energy Center in Illinois. The project was featured in a number of news articles and press releases and received 2 awards. At the 2023 DOE HFTO’s Annual Merit Review meeting, the P.I. Dr. Uuganbayar Otgonbaatar and project manager Robert Beaumont were recognized for “outstanding achievements in the development and demonstration of a first-of-a-kind clean hydrogen production facility, powered by carbon-free nuclear energy, at the Nine Mile Point Nuclear Station in Oswego, New York.” The project was also awarded 2023 Nuclear Energy Institute’s Top Innovative Practice award.

08 HYDROGEN↗
DOE OSTI2025

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

Traditional hazards analysis (HA) methods, originally developed to address physical and operational risks, often fall short when it comes to identifying and mitigating cyber threats. These cyber threats pose unique and evolving risks to critical infrastructure and industrial control systems (ICS). This report explores the integration of Cyber-Informed Engineering (CIE) principles into existing HA methods to enhance their ability to address cyber-induced risks. CIE provides organizations with a practical, cost-effective approach to closing the gap between traditional HA methods and the need for cyber risk mitigation. By leveraging existing safety processes and controls, CIE allows users to examine and mitigate cyber vulnerabilities without overhauling existing HA methods. This report identifies areas where HA and CIE naturally align and where their approaches diverge. It emphasizes how CIE principles can be used to adapt HA methods, broadening their scope to include cyber risks and enabling the mitigation of cyber- induced impacts alongside traditional hazards and failure scenarios. This report examines how CIE can be applied across various HA methods—such as Hazard and Operability Studies (HAZOP), Probabilistic Risk Assessment (PRA), Failure Modes and Effects Analysis (FMEA), Systems-Theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), and Layers of Protection Analysis (LOPA). It provides strategies for integrating CIE to strengthen the identification, assessment, and mitigation of cyber-induced risks. The findings offer a structured entry point for organizations to embed CIE concepts into hazards and safety analyses, as well as broader engineering processes, ultimately supporting the design and operation of a more resilient infrastructure.

42 - ENGINEERING↗
NASA NTRS1991

Technology needs for high-speed rotorcraft

A study to determine the technology development required for high-speed rotorcraft development was conducted. The study begins with an initial assessment of six concepts capable of flight at, or greater than 450 knots with helicopter-like hover efficiency (disk loading less than 50 pfs). These concepts were sized and evaluated based on measures of effectiveness and operational considerations. Additionally, an initial assessment of the impact of technology advances on the vehicles attributes was made. From these initial concepts a tilt wing and rotor/wing concepts were selected for further evaluation. A more detailed examination of conversion and technology trade studies were conducted on these two vehicles, each sized for a different mission.

Rutherford, John↗
NASA NTRS1979

Assessment of airframe noise

A component method of airframe noise prediction is used to predict levels of operational and proposed aircraft airframe noise to assess the contribution of airframe noise to community noise levels. This is done after first evaluating the prediction method using newly acquired detailed measurements from full-scale aircraft and models. In the course of the evaluation, modeling techniques of airframe noise sources are examined with attention to scaling. Finally, when used to predict approach airframe EPNLs, the levels fell about 10 EPNdB below current noise regulations and about 5 EPNdB below proposed noise regulations.

Block, P. J. W.↗
DOE OSTI2020

Applicability of Public Dose Limits to Individuals on the Nevada National Security Site

Historically all persons working on the Nevada National Security Site (NNSS) were considered subject to worker dose limits when calculations of potential dose from the air pathway were conducted to demonstrate compliance with Title 42 United States Code (USC) Chapter 85, “The Clean Air Act,” and Title 40 Code of Federal Regulations (CFR) Part 61, Subpart H, “National Emission Standards for Hazardous Air Pollutants (NESHAP).” Calculations were also conducted for the all-pathways potential dose to demonstrate compliance with U.S. Department of Energy (DOE) Order DOE O 458.1 Chg. 3, “Radiation Protection of the Public and the Environment.” The need to evaluate environmental air sampling locations and past regulator questions about the existence of persons potentially subject to public dose limits being on the NNSS drove this assessment (letter from EPA [U.S. Environmental Protection Agency] Region 9 to DOE/Nevada Operations Office, dated September 3, 1999). This assessment also supports determining those persons subject to public dose limits from the all pathways perspective. A person that is a member of the public is subject to public dose limits.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Discrete-Event Model of WIPP Operations

The Waste Isolation Pilot Plant (WIPP) is the critical component of the Department of Energy's (DOE) Transuranic Radioactive Waste (TRU) disposition infrastructure. Quantifying the operations ofWIPP with a discrete-event model demonstrates the capability to assess efficiency, identity bottlenecks, and improve future operations. Such a model has been developed with the simulation software ExtendSim. This report outlines the structure of that model, summarizes the model's successful reproduction of the annual amount of emplaced waste, and demonstrates that WIPP is successfully receiving and emplacing waste at a rate consistent with the rate at which the waste arrives. The model serves as a first step toward future production enhancements at WIPP. Those enhancements will rely on close collaboration with the Carlsbad Field Office (CBFO), accurate interpretation and incorporation of the model results, and effective planning with other DOE Environmental Management (DOE-EM) entities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2017

Evolution of a Simulation Testbed into an Operational Tool

This paper describes the evolution over a 20-year period of the Future ATM (Air Traffic Management) Concepts Evaluation Tool (FACET) from a National Airspace System (NAS) based simulation testbed into an operational tool. FACET was developed as a testbed for assessing futuristic ATM concepts, e.g., automated conflict detection and resolution. NAS Constraint Evaluation and Notification Tool (NASCENT) is an application, within FACET, for alerting airspace users of inefficiencies in flight operations and advising time- and fuel-saving reroutes.It is currently in use at American Airlines Integrated Operations Center in Fort Worth, TX. The concepts assessed,research conducted, and the operational capability developed, along with the NASA support and achievements are presented in this paper.

Sheth, Kapil↗
DOE OSTI2023

LANSCE Facility Longevity Assessment

This LANSCE Facility Longevity Assessment examined 34 total systems critical to the operation of the LANSCE accelerator complex. These systems are primarily owned, operated, and maintained by AOT Division. Based on the criteria used in this assessment, there are 12 AOT Division systems that are potential high risk as related to longterm LANSCE operations. These systems may also impact the success of LAMP. Also summarized in this report are the facility activities planned over the next decade. These include general facility maintenance and infrastructure upgrades, as well as planned electrical system upgrades. The LANSCE Facility Operations (LFO) Division is responsible for this activity scope and budget planning. Most of the planned activities are general in nature and should have little impact on accelerator operations or LAMP activities as currently envisioned. However, close coordination with between AOT, LFO, and LAMP would be prudent. A next step should be to develop an actionable plan to address the high-risk systems. Potential criteria for developing such a plan could include: (1) Evaluating the global impact of the system (operations, program, safety, etc.), (2) Ranking by impact (ranked now by risk), (3) Estimating cost to implement the corrective actions (Is there already a plan or not?), and (4) Estimating the time required for corrective actions. An alternative could include integration of the assessment data into both the Asset Management System and the Maintenance Analytics Risk Register.

43 PARTICLE ACCELERATORS↗
NASA NTRS1977

Orbiter/payload proximity operations: Lateral approach technique

The lateral approach is presented for proximity operations associated with the retrieval of free flying payloads. An out of plane final approach emphasizing onboard software support is recommended for all except the latter segment of the final approach in which manual control is considered mandatory. An overall assessment of various candidate proximity operations techniques are made.

Bell, J. A.↗
NASA NTRS2015

Credibility Assessment of Deterministic Computational Models and Simulations for Space Biomedical Research and Operations

Human missions beyond low earth orbit to destinations, such as to Mars and asteroids will expose astronauts to novel operational conditions that may pose health risks that are currently not well understood and perhaps unanticipated. In addition, there are limited clinical and research data to inform development and implementation of health risk countermeasures for these missions. Consequently, NASA's Digital Astronaut Project (DAP) is working to develop and implement computational models and simulations (M&S) to help predict and assess spaceflight health and performance risks, and enhance countermeasure development. In order to effectively accomplish these goals, the DAP evaluates its models and simulations via a rigorous verification, validation and credibility assessment process to ensure that the computational tools are sufficiently reliable to both inform research intended to mitigate potential risk as well as guide countermeasure development. In doing so, DAP works closely with end-users, such as space life science researchers, to establish appropriate M&S credibility thresholds. We will present and demonstrate the process the DAP uses to vet computational M&S for space biomedical analysis using real M&S examples. We will also provide recommendations on how the larger space biomedical community can employ these concepts to enhance the credibility of their M&S codes.

Mulugeta, Lealem↗
NASA NTRS2004

Common Operating Picture: UAV Security Study

This initial communication security study is a top-level assessment of basic security issues related to the operation of Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). Security considerations will include information relating to the use of International Civil Aviation Organization (ICAO) Aeronautical Telecommunications Network (ATN) protocols and applications identifying their maturity, as well as the use of IPV4 and a version of mobile IPV6. The purpose of this assessment is to provide an initial analysis of the security implications of introducing UAVs into the NAS.

Source record↗
DOE OSTI2020

Sandia National Laboratories Annual Site Environmental Report, 2019: New Mexico

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the United States Department of Energy (DOE) National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. DOE and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2019. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting, and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Droughts in Wind and Solar Power: Assessing Climate Model Simulations for a Net‐Zero Energy Future

Abstract Understanding and predicting “droughts” in wind and solar power availability can help the electric grid operator planning and operation toward deep renewable penetration. We assess climate models' ability to simulate these droughts at different horizontal resolutions, ∼100 and ∼25 km, over Western North America and Texas. We find that these power droughts are associated with the high/low pressure systems. The simulated wind and solar power variabilities and their corresponding droughts during historical periods are more sensitive to the model bias than to the model resolution. Future climate simulations reveal varied future change of these droughts across different regions. Although model resolution does not affect the simulation of historical droughts, it does impact the simulated future changes. This suggests that regional response to future warming can vary considerably in high‐ and low‐resolution models. These insights have important implications for adapting power system planning and operations to the changing climate.

Liu, Xue [Department of Oceanography Texas A&amp,M↗
NASA NTRSDate not supplied

Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response

Aerial wildfire operations are high risk and account for a large number of firefighter deaths. Increasing intensity of wildfires is driving a surge in aerial operations, while simultaneously there is growing interest in improving system safety and performance. In this work, wildfire aviation mishaps documented using the SAFECOM system are analyzed using a previously developed framework for hazard extraction and analysis of trends (HEAT). Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard are calculated, including frequency, rate, and severity. We examine whether these metrics change over time, and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on rate of occurrence and average severity. Results identify jumper operations hazards as high-risk, in addition to bucket drop failures, cargo let down failures, and severe weather as medium risk.

machine learning↗
NASA NTRSDate not supplied

Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response

Aerial wildfire operations are high risk and account for a large number of firefighter deaths. Increasing intensity of wildfires is driving a surge in aerial operations, while simultaneously there is growing interest in improving system safety and performance. In this work, wildfire aviation mishaps documented using the SAFECOM system are analyzed using a previously developed framework for hazard extraction and analysis of trends (HEAT). Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard are calculated, including frequency, rate, and severity. We examine whether these metrics change over time, and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on rate of occurrence and average severity. Results identify jumper operations hazards as high-risk, in addition to bucket drop failures, cargo let down failures, and severe weather as medium risk.

machine learning↗