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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI1994

Nuclear Safety [Vol. 35, No. 1, January-June 1994]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. THE CHERNOBYL ACCIDENT: 1 Chernobyl Accident Management Actions, A. R Sich; GENERAL SAFETY CONSIDERATIONS: 25 The IAEA-ASSET Approach to Avoiding Accidents is to Recognize the Precursors to Prevent Incidents, F. Reisch; ACCIDENT ANALYSIS: 36 A Review of the Available Information on the Triggering Stage of a Steam Explosion, D. F. Fletcher; 58 Analysis and Modeling of Flow-Blockage-Induced Steam Explosion Events in the High-Flux Isotope Reactor, R. P. Taleyarkhan, V. Georgevich, C. W. Nestor, U. Gat, B. L. Lepard, D. H. Cook, J. Freels, S. J. Chang, C. Luttrell, R. C. Gwaltney, and J. Kirkpatrick; 74 An Analysis of Disassembling the Radial Reflector of a Thermionic Space Nuclear Reactor Power System, M. S. El-Genk and D. V. Paramonov; CONTROL AND INSTRUMENTATION: 86 Standards for High-Integrity Software, D. R. Wallace, D. R. Kuhn, L M. Ippolito, and L. Beltracchi; DESIGN FEATURES: 98 Adoption of New Design Features for the Next Generation Nuclear Power Reactors, L. S. Tong; 114 Review of Nuclear Piping Seismic Design Requirements, G. C. Slagis and S. E. Moore; ENVIRONMENTAL EFFECTS: 128 PC-Based Probabilistic Safety Assessment Study for a Geological Waste Repository Placed in a Bedded Salt Formation, S. A. Khan; OPERATING EXPERIENCES: 142 Managing Aging in Nuclear Power Plants: Insights from NRC’s Maintenance Team Inspection Reports, A. Fresco and M. Subudhi; 150 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 153 Selected Safety-Related Events, Compiled by G. A. Murphy; RECENT DEVELOPMENTS: 158 Reports, Standards, and Safety Guides, D. S. Queener; 168 Proposed Rule Changes as of Dec. 31, 1993; ANNOUNCEMENTS: 177 Symposium on Radioactive and Mixed Waste—Risk as a Basis for Waste Classification; 177 1995 Incineration Conference 178 Ninth Power Plant Dynamics Control and Testing Symposium; 174 The Authors

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1989

Probabilistic modeling for simulation of aerodynamic uncertainties in propulsion systems

The numerical simulation of the probabilistic aerothermodynamic response of propulsion system components to randomness in their environment was explored. The reusable rocket engine turbopumps were selected as an example because of the severe cryogenic environment in which they operate. The thermal and combustion instabilities, coupled with the engine thrust requirements from start up to shut down, lead to randomness in the flow variables and uncertainties in the aerodynamic loading. The probabilistic modeling of the turbopumps aerodynamic response was accomplished using the panel method coupled with fast probability integration methods. The aerodynamic response in the form of probabilistic rotor blades and splitter loading were predicted and the results presented for specified flow coefficient and rotor preswirl variance. Possible future applications of the aerothermodynamic probabilistic modeling in engine transient simulation, condition monitoring and engine life prediction are briefly discussed.

Hamed, Awatef↗
NASA NTRS1990

Probabilistic modeling for simulation of aerodynamic uncertainties in propulsion systems

The numerical simulation of the probabilistic aerothermodynamic response of propulsion system components to randomness in their environment was explored. The reusable rocket engine turbopumps were selected as an example because of the severe cryogenic environment in which they operate. The thermal and combustion instabilities, coupled with the engine thrust requirements from start up to shut down, lead to randomness in the flow variables and uncertainties in the aerosynamic loading. The probabilistic modeling of the turbopumps' aerodynamic response was accomplished using the panel method coupled with fast probability integration methods. The aerodynamic response in the form of probabilistic rotor blades and splitter loading were predicted and the results presented for specified flow coefficient and rotor preswirl variance. Possible future applications of the aerothermodynamic probabilistic modeling in engine transient simulation, condition monitoring, and engine life prediction are briefly discussed.

Hamed, A.↗
NASA NTRS2014

Goal Based Testing: A Risk Informed Process

A process for life demonstration testing is developed, which can reduce the number of resources required by conventional sampling theory while still maintaining the same degree of rigor and confidence level. This process incorporates state-of-the-art probabilistic thinking and is consistent with existing NASA guidance documentation. This view of life testing changes the paradigm of testing a system for many hours to show confidence that a system will last for the required number of years to one that focuses efforts and resources on exploring how the system can fail at end-of-life and building confidence that the failure mechanisms are understood and well mitigated.

Everline, Chester↗
NASA NTRS2004

Modelling and Analysis of a Regenerative Fuel Cell Propulsion System for a High Altitude Long Endurance UAV

In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked

Simpson, Mike B.↗
DOE OSTI2025

Radioisotope Identification with List-Mode Gamma-Ray Data

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with spectra containing similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and qualitative distribution analysis. Additionally, we propose a probabilistic classification model that can utilize spectral data, temporal data, or both to determine if the incorporation of temporal information improves radioisotope identification. Our findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated to develop more robust and optimal methods for utilizing this temporal information in applications requiring radioisotope identification.

List-mode data↗
NASA NTRS2015

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Leser, Patrick E.↗
NASA NTRS2010

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Rash, James L.↗
NASA NTRS2017

Medical Optimization Network for Space Telemedicine Resources

INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. NASA recognizes the need to improve capabilities for autonomous care on such missions. As the medical system is developed, it is important to have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources was developed for this reason, and is now a system to gauge the relative importance of medical resources in addressing medical conditions. METHODS: A list of medical conditions of potential concern for an exploration mission was referenced from the Integrated Medical Model, a probabilistic model designed to quantify in-flight medical risk. The diagnostic and treatment modalities required to address best and worst-case scenarios of each medical condition, at the terrestrial standard of care, were entered into a database. This list included tangible assets (e.g. medications) and intangible assets (e.g. clinical skills to perform a procedure). A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program ranked each of the items listed according to its criticality. Data was then obtained from the IMM for the probability of occurrence of the medical conditions, including a breakdown of best case and worst case, during a Mars reference mission. The probability of occurrence information and criticality for each resource were taken into account during analytics performed using Tableau software. RESULTS: A database and weighting system to evaluate all the diagnostic and treatment modalities was created by combining the probability of condition occurrence data with the criticalities assigned by the physician team. DISCUSSION: Exploration Medical Capabilities research at NASA is focused on providing a medical system to support crew medical needs in the context of a Mars mission. MONSTR is a novel approach to performing a quantitative risk analysis that will assess the relative value of individual resources needed for the diagnosis and treatment of various medical conditions. It will provide the operational and research communities at NASA with information to support informed decisions regarding areas of research investment, future crew training, and medical supplies manifested as part of the exploration medical system.

Shah, R. V.↗
NASA NTRSDate not supplied

Sensorimotor Application of Proposed Methods to Combine the Effects of Multiple Countermeasures for PRisM

Risk associated with human systems is challenging to quantify but is critical for the mission planning and decision making required to enable future Lunar and Martian missions. To address this gap, the Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) project is developing an integrated computational model for CHP mission risk. Much like how MEDPRAT is designed to allow medical resource trades informed by medical risk, CHP-PRA will enable analogous trades in human system risks across multiple CHP functions and capabilities. Human performance is one component of the risk intended to be captured by CHP-PRA through the Performance Risk Model (PRisM). The sensorimotor risk area provides a good frame of reference for investigating the structure of a performance model because most tasks that astronauts are expected to perform require input from the sensory system and/or movement/motor control. Additionally, sensorimotor countermeasures are an area of particular concern for NASA’s Human Research Program because of the increased sensorimotor risk associated with surface operations in Lunar and Martian missions. Thus, a tool that can quickly compare risk reductions of potential countermeasures would be beneficial in guiding research and development of effective countermeasures. In this proof of concept, we present a systematic way to combine multiple performance data sets for humans subjected to different countermeasures such that we can predict the countermeasure(s) that optimize astronaut performance on relevant tasks. PRisM assumes that both the tests that are used to measure countermeasure effectiveness (input data) and the tasks we use to represent astronaut performance, can be broken down and represented as a function/vector of the human systems required to perform that test/task. Through mathematical combination, test data are used to predict performance on astronaut tasks that use similar systems. We propose that when combining countermeasures evaluated using the same test, that only one value should be used to represent their combined effectiveness. We start our analysis with the assumption that two countermeasures together will perform better than each countermeasure individually. Our initial implementation of this framework compares various space motion sickness countermeasures and the most up to date analysis will be demonstrated at the IWS.

Caroline R Austin↗
DOE OSTI2024

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Management of SSME hardware life utilization

Statistical and probabilistic reliability methodologies were developed for the determination of hardware life limits for the Space Shuttle Main Engine (SSME). Both methodologies require that a mathematical reliability model of the engine (system) performance be developed as a function of the reliabilities of the components and parts. The system reliability model should be developed from the Failute Modes and Effects Analysis/Critical Items List. The statistical reliability methodology establishes hardware life limits directly from the failure distributions of the components and parts obtained from statistically-designed testing. The probabilistic reliability methodology establishes hardware life limits from a decision analysis methodology which incorporates the component/part reliabilities obtained from a probabilistic structural analysis, a calibrated maintenance program, inspection techniques, and fabrication procedures. Probilistic structural analysis is recommended as a tool to prioritize upgrading of the components and parts. The Weibull probability distribution is presently being investigated by NASA/MSFC to characterize the failure distribution of the SSME hardware from a limited data base of failures.

Pauschke, J. M.↗
NASA NTRS2011

Estimating Controller Intervention Probabilities for Optimized Profile Descent Arrivals

Simulations of arrival traffic at Dallas/Fort-Worth and Denver airports were conducted to evaluate incorporating scheduling and separation constraints into advisories that define continuous descent approaches. The goal was to reduce the number of controller interventions required to ensure flights maintain minimum separation distances of 5 nmi horizontally and 1000 ft vertically. It was shown that simply incorporating arrival meter fix crossing-time constraints into the advisory generation could eliminate over half of the all predicted separation violations and more than 80% of the predicted violations between two arrival flights. Predicted separation violations between arrivals and non-arrivals were 32% of all predicted separation violations at Denver and 41% at Dallas/Fort-Worth. A probabilistic analysis of meter fix crossing-time errors is included which shows that some controller interventions will still be required even when the predicted crossing-times of the advisories are set to add a 1 or 2 nmi buffer above the minimum in-trail separation of 5 nmi. The 2 nmi buffer was shown to increase average flight delays by up to 30 sec when compared to the 1 nmi buffer, but it only resulted in a maximum decrease in average arrival throughput of one flight per hour.

continous descent arrivals↗
NASA NTRSDate not supplied

Gateway Program Safety and Mission Assurance Integration - the Future of Safe Deep Space Human Exploration

As a foundational element of the National Aeronautics and Space Administration (NASA) Artemis Campaign, the Gateway is an incrementally built cislunar spacecraft that will serve as a platform for deep space human exploration, science, and technology demonstration. The Gateway will be a unifying catalyst for international partners around the world to establish sustained deep space scientific investigations, lunar surface access, and missions to Mars. As human exploration moves farther away from Earth, spacecraft designs must prioritize and optimize mass and volume allocations, while minimizing human and spacecraft risk. To accomplish this objective, the Gateway Program Safety and Mission Assurance functions develop, implement, and ensure compliance with requirements, in concert with the accurate characterization and transparent communication of residual hazard risks, for integrated safety, reliability and maintainability and quality assurance. Safety and Mission Assurance was a key contributor during Gateway program pre-formulation and formulation activities where safety and reliability analysis was embedded in the Gateway Systems Engineering and Integration team. During these early program stages, a preliminary Gateway Integrated Hazard Analysis and Preliminary Gateway Probabilistic Risk Assessment assisted in Gateway architectural and operational definition as part of a risk-informed design process. As the deep space architecture has matured, the integrated Safety and Mission Assurance analyses have matured, new safety review processes have been developed, and requirements have been refined to ensure compliance with integrated safety and mission assurance objectives. The Gateway Program is currently concluding the preliminary design review informed milestone, where the primary objectives included: - Ensured completeness and consistency of the preliminary design, including the meeting of all requirements within appropriate margins and acceptable risk posture. - Identification of any major issues moving forward to the Critical Design phase. At this milestone, Safety and Mission Assurance provided numerous products, including Gateway Top Risks and Risk Mitigation Plans, updated integrated hazard analyses, updated probabilistic risk assessment, Crew Survival Analysis Report, and updated Safety and Mission Assurance Requirements and Plans. These products provide a many-faceted perspective on the inherent risk and available mitigations involved in flying the current proposed vehicle design and anticipated stack configurations. In addition, Safety and Mission Assurance identified top technical, process and workforce concerns to be addressed as the program progresses toward the critical design phase. This paper will detail the evolution of the Gateway Program Safety and Mission Assurance integration functions, provide its current status and lessons learned for future human spaceflight programs. Throughout this paper the key tenets of the Gateway Program Safety and Mission Assurance will be discussed: - Application of a risk-informed approach to identify and mitigate areas of highest risk. - Leverage of valuable processes and lessons learned from earlier spaceflight programs. - Development of Safety and Mission Assurance products to inform design risk trades. - Utilization of common Safety and Mission Assurance practices to identify safety risks for multiple perspectives: top-down, bottom-up, and across lines of integration. - Approval of safety hazards at the appropriate level of authority, keeping most deliberation closest to design expertise and elevating risks of greatest concern for program-level consideration. - Championing of Safety and Mission Assurance processes and forums to foster a pervasive safety culture that is transparent, inclusive, and collaborative between all partners. These tenets have allowed the Gateway Safety and Mission Assurance function to play a key role in optimized vehicle design evolution, and early identification and mitigation of Gateway program and Artemis mission risk.

Helen Vaccaro↗
NASA NTRS2008

Strategic Analysis Overview

NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.

Cirillo, William M.↗
NASA NTRSDate not supplied

CFD2030 Grand Challenge: CFD-in-the-Loop Monte Carlo Simulation for Space Vehicle Design

Space vehicle design and certification differs widely from aircraft design relying more on probabilistic approaches than deterministic. Monte Carlo simulation plays an important role in the probabilistic design of space vehicles to ensure robust and reliable operation. Today, Monte Carlo flight simulation requires 1000’s of trajectory simulations that use databases to provide aerosciences models. These databases can be extremely expensive and time consuming to develop. Replacing these databases with unsteady computational fluid dynamics directly in the simulation loop has potential to significantly reduce the time required to analyze space vehicle concepts, improve simulation accuracy, and reduce the cost of space vehicle development. The CFD Vision 2030 Study outlined gaps and roadblocks to meeting the vision described in the study. The geometric, physical, and computational challenges associated with CFD-in-the-loop Monte Carlo simulation for space vehicle design are substantial and serve as an excellent grand challenge to advance the CFD 2030 vision.

CFD2030↗
NASA NTRS2000

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗