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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

High Power Flex-Propellant Arcjet Performance

A MW-class electrothermal arcjet based on a water-cooled, wall-stabilized, constricted arc discharge configuration was subjected to extensive performance testing using hydrogen and simulated ammonia propellants with the deliberate aim of advancing technology readiness level for potential space propulsion applications. The breadboard design incorporates alternating conductor/insulator wafers to form a discharge barrel enclosure with a 2.5-cm internal bore diameter and an overall length of approximately 1 meter. Swirling propellant flow is introduced into the barrel, and a DC arc discharge mode is established between a backplate tungsten cathode button and a downstream ringanode/ spin-coil assembly. The arc-heated propellant then enters a short mixing plenum and is accelerated through a converging-diverging graphite nozzle. This innovative design configuration differs substantially from conventional arcjet thrusters, in which the throat functions as constrictor and the expansion nozzle serves as the anode, and permits the attainment of an equilibrium sonic throat (EST) condition. During the test program, applied electrical input power was varied between 0.5-1 MW with hydrogen and simulated ammonia flow rates in the range of 4-12 g/s and 15-35 g/s, respectively. The ranges of investigated specific input energy therefore fell between 50-250 MJ/kg for hydrogen and 10-60 MJ/kg for ammonia. In both cases, observed arc efficiencies were between 40-60 percent as determined via a simple heat balance method based on electrical input power and coolant water calorimeter measurements. These experimental results were found to be in excellent agreement with theoretical chemical equilibrium predictions, thereby validating the EST assumption and enabling the utilization of standard TDK nozzle expansion analyses to reliably infer baseline thruster performance characteristics. Inferred specific impulse performance accounting for recombination kinetics during the expansion process implied nearly frozen flow in the nozzle and yielded performance ranges of 800-1100 sec for hydrogen and 400-600 sec for ammonia. Inferred thrust-to-power ratios were in the range of 30-10 lbf/MWe for hydrogen and 60-20 lbf/MWe for ammonia. Successful completion of this test series represents a fundamental milestone in the progression of high power arcjet technology, and it is hoped that the results may serve as a reliable touchstone for the future development of MW-class regeneratively-cooled flex-propellant plasma rockets.

Litchford, Ron J.↗
DOE OSTI2021

mystic : software for autonomous discovery and design under uncertainty

Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.

42 ENGINEERING↗
DOE OSTI2022

Application of Margin-Based Methods to Assess System Health

Health management of complex systems such as nuclear power plants is an essential task to guarantee system reliability. This task can be greatly enhanced by constantly monitoring asset status and performances and process such data (through anomaly detection, diagnostic, and prognostic computational algorithms) to identify asset degradation trends and faulty states. While such information and data are typically available for many of the assets, they are not propagated from the asset to the system level in order to identify the most critical assets and prioritize maintenance and surveillance activities. The main reason is driven by the fact that current reliability modeling techniques are inadequate to process such information/data. This is due to the nature of these techniques which are based on the concept of failure rate/probability that do not serve an operational context where quantitative asset health information is available. Simply stated, current reliability techniques serve a run-to-failure operational setting and not a predictive maintenance one where the goal is to perform maintenance and surveillance activities only when they are needed based on asset health. The risk informed asset management (RIAM) project is focusing on the development of a different kind of reliability modeling techniques designed to adequately serve a predictive operational setting. Such reliability techniques move aways from a failure rate/probability to a margin-based mindset where margin is here used as a metric to quantify asset health based only on current and past operational experience of the asset under consideration. In addition, margin-based reliability techniques are able to propagate asset health information from the component to system level and provide importance measure to each asset. This report summarizes a recent activity performed in collaboration with plant modernization pathway designed to integrate monitoring data into margin-based reliability models. Such activity focuses on a specific system of an existing nuclear power plant where large amount of historic monitoring data is used to monitor asset and system health.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The power reliability event simulator tool (PRESTO): A novel approach to distribution system reliability analysis and applications

The growing interest in onsite solar photovoltaic and energy storage systems is partially motivated by customer concerns regarding grid reliability. However, accurately assessing the effectiveness of PVESS in mitigating these interruptions requires a comprehensive understanding of location-specific outage patterns and the ability to simulate realistic scenarios. To address the gap, we introduce the Power Reliability Event Simulation TOol (PRESTO), the first publicly available tool that simulates location-specific power interruptions at the county level. PRESTO allows for a more realistic assessment of system reliability by considering the unpredictability and location-specific patterns of power interruptions. We applied PRESTO in a case study of a single-family home across three U.S. counties, examining the performance of a solar photovoltaic system with 10kWh of battery storage during short-duration power interruptions. Our findings show that this system reliably met 93% of energy demand for essential non-heating and cooling loads, fully serving these loads in 84% of events, despite the constraints of daily time-of-use bill management which limits the battery's state-of-charge reserve. However, when heating and cooling loads were included, system performance decreased significantly, with only 70% of demand met and full service in 43% of events. These results highlight the challenges of using solar photovoltaic and energy storage systems for short-duration outages, emphasizing the need to consider factors like battery size and grid charging strategies to improve reliability. Our study demonstrates the practical applications of PRESTO, providing valuable insights into potential mitigation strategies including grid charging and optimizing battery size.

14 SOLAR ENERGY↗
NASA NTRS1995

Preliminary Studies of a Pulsed Detonation Rocket Engine

In the new era of space exploration, there is a strong need for more efficient, cheaper and more reliable propulsion devices. With dramatic increase in specific impulse, the overall mass of fuel to be lifted into orbit is decreased, and this leads, in turn, to much lower mass requirements at lift-off, higher payload ratios and lower launch costs. The Pulsed Detonation engine (PDE) has received much attention lately due to its unique combination of simplicity, light-weight and efficiency. Current investigations focus principally on its use as a low speed, airbreathing engine, although other applications have also been proposed. Its use as a rocket propulsion device was first proposed in 1988 by the present authors. The superior efficiency of the Pulsed Detonation Rocket Engine (PDRE) is due to the near constant volume combustion process of a detonation wave. Our preliminary estimates suggest that the PDRE is theoretically capable of achieving specific impulses as high as 720 sec, a dramatic improvement over the current 480 sec of conventional rocket engines, making it competitive with nuclear thermal rockets. In addition to this remarkable efficiency, the PDRE may eliminate the need for high pressure cryogenic turbopumps, a principal source of failures. The heat transfer rates are also much lower, eliminating the need for nozzle cooling. Overall, the engine is more reliable and has a much lower weight. This paper will describe in detail the operation of the PDRE and calculate its performance, through numerical simulations. Engineering issues will be addressed and discussed, and the impact on mission profiles will also be presented. Finally, the performance of the PDRE using in-situ resources, such as CO and O2 from the martian atmosphere, will also be computed.

Cambier, Jean-Luc↗
NASA NTRS2018

2.5/3D Daisy Chain Reliability Evaluation

The objective of this task is to evaluate thermal cycle behavior of advanced 2.5/3D electronics — commercial-off the-shelf (COTS) —packages of different configurations assembled onto printed circuit boards (PCBs). Three key approaches were considered for evaluation. The first approach focused on the through-mold via (TMV™) technology at assembly level. The second approach focused on evaluation of 2.5D (also known as, System in Package (SiP)) in fine pitch ball grid array (FPGA). The third approach focused on evaluation of through-silicone-via (TSV) technologies. This report presents the test results for TMV™ and SiP packaging technologies and reliability, and it also provides lessons learned on quality assurance methods. Specifically, the report presents the test matrix for various 3D TMV™ packaging assembly configurations and reliability characterizations performed under two accelerated thermal cycling (ATC) and accelerated thermal shock cycling (ATSC) conditions. The ATC and ATSC were performed in the range of –55°C to 125°C and –100°C to 100°C, respectively. The report also includes assembly of a SiP— a 60-mm fine-pitch ball-grid array (FPGA) interposer with an IC at the center and six chip-scale package (CSP) daisy chains at the periphery—with package assembly characterizations. After assembly, the daisy chains were subjected to ATCs in the range of –40°C to 125°C for reliability evaluation. Finally, for both TMV™ and SiP packaging configurations, characterizations results by X-ray, optical imaging, and daisy-chain resistance evaluations were also presented.

Ghaffarian, Reza↗
NASA NTRS1978

Characterization of large 2219 aluminum alloy hand forgings for the space shuttle solid rocket booster

The mechanical properties, including fracture toughness, and stress corrosion properties of four types of 2219-T852 aluminum alloy hand forgings are presented. Weight of the forgings varied between 450 and 3500 lb at the time of heat treatment and dimensions exceeded the maximum covered in existing specifications. The forgings were destructively tested to develop reliable mechanical property data to replace estimates employed in the design of the Space Shuttle Solid Rocket Booster (SRB) and to establish minimum guaranteed properties for structural refinement and for entry into specification revisions. The report summarizes data required from the forgers and from the SRB Structures contractor.

Brennecke, M. W.↗
NASA NTRS1990

Probabilistic fatigue methodology for six nines reliability

Fleet readiness and flight safety strongly depend on the degree of reliability that can be designed into rotorcraft flight critical components. The current U.S. Army fatigue life specification for new rotorcraft is the so-called six nines reliability, or a probability of failure of one in a million. The progress of a round robin which was established by the American Helicopter Society (AHS) Subcommittee for Fatigue and Damage Tolerance is reviewed to investigate reliability-based fatigue methodology. The participants in this cooperative effort are in the U.S. Army Aviation Systems Command (AVSCOM) and the rotorcraft industry. One phase of the joint activity examined fatigue reliability under uniquely defined conditions for which only one answer was correct. The other phases were set up to learn how the different industry methods in defining fatigue strength affected the mean fatigue life and reliability calculations. Hence, constant amplitude and spectrum fatigue test data were provided so that each participant could perform their standard fatigue life analysis. As a result of this round robin, the probabilistic logic which includes both fatigue strength and spectrum loading variability in developing a consistant reliability analysis was established. In this first study, the reliability analysis was limited to the linear cumulative damage approach. However, it is expected that superior fatigue life prediction methods will ultimately be developed through this open AHS forum. To that end, these preliminary results were useful in identifying some topics for additional study.

Everett, R. A., Jr.↗
NASA NTRS2019

Inclusion of Radiation Environment Variability for Reliability Estimates for SiC Power MOSFETs

Variability of the solar energetic particle environment is investigated for single-event-burnout reliability of silicon-carbide power metal-oxide-semiconductor field effect transistors. A probabilistic assessment of failure evaluates the benefits of de-rating voltage, shielding, and mission length. The Prediction of Solar particle Yields for Characterizing Integrating Circuits code is used to calculate a cumulative density function for the fluence of the environment. The lethal ion method is then used to determine what proportion of the environment will cause single-event-burnout. The operating voltage determines the lowest linear-energy-transfer particle that will cause single-event-burnout and that should be included in the environment distribution. The shielding and mission length also determine the final environment distribution of the mission fluence. Through calculating the reliability for different operating voltages, shielding, and mission length for a specific device, it is shown that shielding thickness and operating voltage have a large effect on reliability and can be traded off during the design.

Heavy ion↗
NASA NTRS1983

The Hierarchical Specification and Mechanical Verification of the SIFT Design

The formal specification and proof methodology employed to demonstrate that the SIFT computer system meets its requirements are described. The hierarchy of design specifications is shown, from very abstract descriptions of system function down to the implementation. The most abstract design specifications are simple and easy to understand, almost all details of the realization were abstracted out, and are used to ensure that the system functions reliably and as intended. A succession of lower level specifications refines these specifications into more detailed, and more complex, views of the system design, culminating in the Pascal implementation. The section describes the rigorous mechanical proof that the abstract specifications are satisfied by the actual implementation.

Source record↗
NASA NTRS1992

Reliability of a Shuttle reaction timer

Reaction, movement, and task times refer to the times needed to initially respond to a stimulus, make the specific movement, and complete the entire task. This study evaluated the reliability of a simple reaction timer designed to mimic a Space Shuttle task (turning on an overhead switch).

Hays, Russell D.↗
NASA NTRS2005

A Reliability Model to Assess Reliability of Shuttle Derived Launch Vehicle and Next Generation Vehicles

One important thrust in NASA s space exploration vision is to improve the safety and reliability of future launch vehicles. A quantitative reliability model is an essential technical tool to evaluate launch vehicle reliability and to enhance launch vehicle configuration down selection and detailed designs. A quantitative reliability model that supports NASA's thrust has been developed and implemented in an MS Excel spreadsheet. The model addresses key reliability parameters, and provides for sensitivity analysis of various vehicle designs. This paper presents the specific elements of the model and examples of selected sensitivity analysis results. Reliability input parameters in the model include the following: 1. Main propulsion element failure probability; 2. Propulsion element catastrophic failure fraction (Cf). This is defined as the ratio of probability of uncontained failures over sum of probability of uncontained failures and contained failures); 3. Engine-out design vs. no-engine-out design; 4. Engine with redlines vs. no redlines; 5. Different levels of health management system implementation; 6. Launch Escape System (LES) reliability; and 7. Power level correlation with reliability. The sensitivity results will illustrate the impact of each of the above parameters on several reliability metrics: Loss of Mission (LOM), LOV (Loss of Vehicle) and Loss of Crew (LOC).

Huang, Zhao↗
NASA NTRS1992

Uncertainties in obtaining high reliability from stress-strength models

There has been a recent interest in determining high statistical reliability in risk assessment of aircraft components. The potential consequences are identified of incorrectly assuming a particular statistical distribution for stress or strength data used in obtaining the high reliability values. The computation of the reliability is defined as the probability of the strength being greater than the stress over the range of stress values. This method is often referred to as the stress-strength model. A sensitivity analysis was performed involving a comparison of reliability results in order to evaluate the effects of assuming specific statistical distributions. Both known population distributions, and those that differed slightly from the known, were considered. Results showed substantial differences in reliability estimates even for almost nondetectable differences in the assumed distributions. These differences represent a potential problem in using the stress-strength model for high reliability computations, since in practice it is impossible to ever know the exact (population) distribution. An alternative reliability computation procedure is examined involving determination of a lower bound on the reliability values using extreme value distributions. This procedure reduces the possibility of obtaining nonconservative reliability estimates. Results indicated the method can provide conservative bounds when computing high reliability. An alternative reliability computation procedure is examined involving determination of a lower bound on the reliability values using extreme value distributions. This procedure reduces the possibility of obtaining nonconservative reliability estimates. Results indicated the method can provide conservative bounds when computing high reliability.

Neal, Donald M.↗
NASA NTRS1972

The ATS F&G systems reliability program.

Assurance of reliability, quality, and proper testing requires a large coordinating effort and a means for connecting the various areas involved. All parts used on the spacecraft are required to meet strict specifications and consequently must be approved by the systems reliability manager. The parts program has access to a computer data bank into which all information concerning nonstandard parts approval requests has been stored. Through the data bank, the system collects and distributes timely information concerning quality and reliability to all departments that may be concerned.

Doyle, H.↗
NASA NTRSDate not supplied

A Methodology for Reliability Assessments of Arbitrary Satellite Constellations

The commercial success of small satellite development and multi-satellite missions has led to constellation missions being proposed in every sector of the market. This paradigm shift has the potential to enable more capable and cost-effective space science missions. However, these novel approaches to space missions have outstripped existing policy and analysis methods for assessing the reliability of multi-satellite missions. Mission designers and decisionmakers need new methods and standards for modeling how the reliability of constituent spacecraft elements affect the aggregate reliability of constellations across a wide range of concepts and application-specific requirements. The Space Mission Analysis Branch at NASA’s Langley Research Center has developed a methodology for simulating the on-orbit reliability of arbitrary spacecraft constellations. In this paper, the authors describe the methodology and provides examples of how it can be used to evaluate specific constellation designs. To demonstrate the flexibility of the approach, several different constellation configurations are considered, including both homogenous and heterogenous designs. Next, the authors demonstrate the ability to perform broad parameter sweeps to develop greater insight into the intrinsic reliability trends associated with constellation concepts. Finally, the authors provide tables and novel data graphics which enable decisionmakers to quickly discern the relationships between constellation sizes, topologies, replenishment strategies, and overall constellation reliability.

satellite↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
DOE OSTI2025

Delamination-informed lifecycle decisions: A dielectric and machine learning framework for composite sorting and recycling

Composite materials are widely used in aerospace, marine, and automotive sectors due to their high strength-to-weight ratio and durability. However, their long-term reliability can be compromised by damage accumulation. Specifically, delamination initiation serves as a precursor to structural failure, which is often difficult to detect during damage inspection. Identifying and sorting delamination initiation in samples not only increases operational safety while providing critical information for end-of-life decisions, which influences both the service life extension value and the efficiency of fiber extraction during recycling. This research addresses two challenges: (1) developing a nondestructive, ex-situ framework to sort composite materials based on damage severity, particularly delamination, and (2) understanding how damage in composites influences resin removal during pyrolysis. Both experimental work and finite element analysis were performed to predict critical stress levels that are associated with delamination onset. Based on these results, three loading levels 50 %, 75 %, and 90 % of maximum stress, were selected for controlled experiments, generating composite samples with varying extents of damage for machine learning model training. Microscopic imaging of these samples confirmed the damage progression from matrix cracking to delamination, validating the computational predictions. We explored supervised machine learning using dielectric measurements to classify damage states. Preliminary results show an artificial neural network can identify early delamination which is a potential precursor to failure, with 94.44 % accuracy on our dataset. A parallel investigation into the effect of damage severity on pyrolysis recycling showed that heavily delaminated samples required significantly less energy for comparable matrix removal than undamaged samples.

dielectric variables↗
DOE OSTI2021

A review of functions, attributes, properties and measurements for the quality control of proton exchange membrane fuel cell components

Quality control (QC) is an essential part of fuel cell technology industrialization, providing means to reduce cost of components, enhancing the reliability of the final product, and offering specification guidance for new entrants in the supply chain. The membrane electrode assembly (MEA), including membrane, catalyst layer (CL), and gas diffusion layer (GDL), as well as bipolar plate (BP), are key components of a proton exchange membrane (PEM) fuel cell, and the attributes of each component strongly correlate with the cell performance and longevity. To ensure the quality of the fuel cell, it is of great importance to characterize the properties with respect to the standardization of component/sub-component specifications. In collaboration with the fuel cell industry, this work aims at establishing compendiums of attributes, or so-called books of attributes, of key fuel cell components for the QC of PEM fuel cells through reviewing, identifying, categorizing, and prioritizing the main attributes/properties that determine their functionalities. The books of attributes for the major PEM fuel cell components include catalyst coated membrane (CCM) as a sub-assembly, GDL, and BP. To address the full spectrum of fuel cell components, gaskets and sub-gaskets are also included.

25 ENERGY STORAGE↗