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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 163 records · Page 9

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NASA NTRS1982

Advanced flight control system study

A fly by wire flight control system architecture designed for high reliability includes spare sensor and computer elements to permit safe dispatch with failed elements, thereby reducing unscheduled maintenance. A methodology capable of demonstrating that the architecture does achieve the predicted performance characteristics consists of a hierarchy of activities ranging from analytical calculations of system reliability and formal methods of software verification to iron bird testing followed by flight evaluation. Interfacing this architecture to the Lockheed S-3A aircraft for flight test is discussed. This testbed vehicle can be expanded to support flight experiments in advanced aerodynamics, electromechanical actuators, secondary power systems, flight management, new displays, and air traffic control concepts.

Hartmann, G. L.↗

NASA NTRS1985

A software technology evaluation program

A set of quantitative approaches is presented for evaluating software development methods and tools. The basic idea is to generate a set of goals which are refined into quantifiable questions which specify metrics to be collected on the software development and maintenance process and product. These metrics can be used to characterize, evaluate, predict, and motivate. They can be used in an active as well as passive way by learning form analyzing the data and improving the methods and tools based upon what is learned from that analysis. Several examples were given representing each of the different approaches to evaluation. The cost of the approaches varied inversely with the level of confidence in the interpretation of the results.

Novaes-Card, David N.↗

NASA NTRS2003

Effects of Impact Damage in Midplane Asymmetric Sandwich Composites

Several structural sandwich composites arc in service on military and commercial aerospace vehicles, however, these components have been limited to secondary structures partly because the impact damage and damage tolerance of these composites have not been extensively characterized. To improve durability, safety, and life cycle performance of PMCs while reducing maintenance costs, combined analysis, and test methods that provide a means of predicting critical engineering properties after impact damage of the structure, must be developed. A key enabling technology here is the establishment of the correlation between the impact test results conducted in the laboratory and the mechanics-based phenomenological solutions. This research was undertaken to investigate the compression and flexural properties following low velocity impact of a nomex/phenolic honeycomb core, fiberglass/epoxy facesheet, midplane asymmetric sandwich composite. One facesheet (thin side) was composed of two plies of the fiberglass/epoxy (0/90), while the other facesheet (thick side) was composed of four plies (0/90/0/90) of fiberglass/epoxy. Due to the differences in facesheet thickness, impact damage was separately induced on the thick side as well as the thin side. The compression and flexural strength properties for each damage arrangement were compared using different levels of impact energy ranging from 0 to 452 Joules. In all cases, higher impact energy resulted in decreased compression and flexural strength. Impact on the thin side showed slightly more retention of compression strength at low impact levels, whereas higher residual compressive strength was observed from impact on the thick side at higher impact levels. Different facesheet thicknesses or midplane asymmetry, played an important role in the flexural strength, however, low velocity impact on the both the thick and thin fiberglass/epoxy facesheet side showed an almost linear loss of flexural strength to saturation.

Meador, Michael↗

NASA NTRS1995

Reliability and Maintainability model (RAM) user and maintenance manual

This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided.

Ebeling, Charles E.↗

NASA NTRS1972

Apollo quality through predictive testing.

Discussion of testing performed during the Apollo program and its relationship to the engineering, qualification, manufacturing, maintenance, and training aspects of the program. Illustrative examples of Apollo experience are used to highlight the discussion.

White, G. C., Jr.↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

NASA NTRS1979

Performance considerations in long-term spaceflight

Maintenance of skilled performance during extended space flight is of critical importance to both the health and safety of crew members and to the overall success of mission goals. An examination of long term effects and performance requirements is therefore a factor of immense importance to the planning of future missions. Factors that were investigated include: definition of performance categories to be investigated; methods for assessing and predicting performance levels; in-flight factors which can affect performance; and factors pertinent to the maintenance of skilled performance.

Akins, F. R.↗

DOE OSTI2026

Resilience Measurement Framework For Post-deployment Artificial Intelligence (ai) Integrated Systems

Resilience is largely defined as the ability to adapt or recover from adverse conditions, stresses, attacks, or compromises on systems that use or are enabled by digital resources. In Artificial Intelligence Management and Research for Advanced Networked Testbed Hub (AMARANTH), resilience is measured in the amount of time it took from the beginning of a testing period for the model to reach predictions outside of the original 95% confidence interval or using the Kullback-Leibler (KL) divergence theorem, the Population Stability Index (PSI), and traditional methods such as root mean squared error (RMSE) threshold. Artificial Intelligence (AI) model drift is of significant concern when deploying AI-integrated systems into critical and/or secure environments. Drift can impact resilience of the AI-integrated system post-deployment and requires consistent maintenance and upkeep to ensure the model is accurate and precise. To quantify model drift and predict the point when a model's drift becomes unacceptable, we describe using Kullback-Leibler (KL) divergence, Population Stability Index (PSI) and/or confidence interval width estimations to determine the point of failure and time to failure of a model post-deployment. Through simple code functions, the KL-divergence, PSI, confidence interval, and root mean squared (RMSE) point of failures can be used to derive when a model needs to be maintained as well as the impact of adversarial action through statistical means.

Yockey, Patience [Idaho National Laboratory (INL),↗

DOE OSTI2024

Eco-evolutionary strategies for relieving carbon limitation under salt stress differ across microbial clades

With the continuous expansion of saline soils under climate change, understanding the eco-evolutionary tradeoff between the microbial mitigation of carbon limitation and the maintenance of functional traits in saline soils represents a significant knowledge gap in predicting future soil health and ecological function. Through shotgun metagenomic sequencing of coastal soils along a salinity gradient, we show contrasting eco-evolutionary directions of soil bacteria and archaea that manifest in changes to genome size and the functional potential of the soil microbiome. In salt environments with high carbon requirements, bacteria exhibit reduced genome sizes associated with a depletion of metabolic genes, while archaea display larger genomes and enrichment of salt-resistance, metabolic, and carbon-acquisition genes. This suggests that bacteria conserve energy through genome streamlining when facing salt stress, while archaea invest in carbon-acquisition pathways to broaden their resource usage. These findings suggest divergent directions in eco-evolutionary adaptations to soil saline stress amongst microbial clades and serve as a foundation for understanding the response of soil microbiomes to escalating climate change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

JT8D and JT9D jet engine performance improvement program. Task 1: Feasibility analysis

JT8D and JT9D component performance improvement concepts which have a high probability of incorporation into production engines were identified and ranked. An evaluation method based on airline payback period was developed for the purpose of identifying the most promising concepts. The method used available test data and analytical models along with conceptual/preliminary designs to predict the performance improvements, weight, installation characteristics, cost for new production and retrofit, maintenance cost, and qualitative characteristics of candidate concepts. These results were used to arrive at the concept payback period, which is the time required for an airline to recover the investment cost of concept implementation.

Gaffin, W. O.↗

NASA NTRS2002

Convective Systems during the South China Sea Monsoon Onset and Post-Onset Simulated by a Cloud Resolving Model Using SCSMEX Data

South China Sea Monsoon Experiment (SCSMEX, 1998), one of several major TRMM field experiments, has successfully obtained a wealth of information and observational data on the summer monsoon onset and evolution in the South China Sea region. The primary goal of the experiment is to provide a better understanding of the key physical processes for the onset and maintenance of the monsoon over Southeast Asia and southern China leading to improved predictions. In this paper, our objective is to investigate the major physical and microphysical processes involved in the convective systems that developed during the onset and post-onset of the South China Sea monsoon - for both the similarities and differences between these two phases. There are two episodes simulated in this study, one of the onset period (May 18-26, 1998) and one of the post-onset period (June 2-11, 1998). The focus of this paper is to study four major aspects between these two different episodes. First, characteristics of rainfall such as rainfall amount and occurrence in the convective and stratiform regions are investigated, as well as the propagation of convective systems. The numerical precipitation fields are also validated against both the TRMM Microwave Imager (TMI) soundings and Precipitation Radar (PR) observations. Second, the domain-averaged heat and moisture budgets are analyzed to comprehend the essential roles played by physical processes such as the large-scale forcing and latent heat flux. Third, the microphysical processes associated with warm rain or ice are also closely examined during these two episodes. Finally, vertical distributions of Q1 and Q2 budgets are presented to perform a detailed discussion on the energy and moisture cascade in the vertical direction.

Shie, C.-L.↗

NASA NTRS1977

Industrial Productivity

NASTRAN is an offshoot of the computer-design technique used in construction of airplanes and spacecraft. [n this technique engineers create a mathematical model of the aeronautical or space vehicle and "fly" it on the ground by means of computer simulation. The technique enables them to study performance and structural behavior of a number of different designs before settling on the final configuration and proceeding with construction. From this base of aerospace experience, NASA-Goddard developed the NASTRAN general purpose computer program, which offers an exceptionally wide range of analytic capability with regard to structures. NASTRAN has been applied to autos, trucks, railroad cars, ships, nuclear power reactors, steam turbines, bridges, and office buildings. NASA-Langley provides program maintenance services regarded as vital by many NASTRAN users. NASTRAN is essentially a predictive tool. It takes an electronic look at a computerire$.dedgn and reports how the structure will react under a great many different conditions. It can, for example, note areas where high stress levels will occur-potential failure points that need strengthening. Conversely, it can identify over-designed areas where weight and material might be saved safely. NASTRAN can tell how pipes stand up under strong fluid flow, how metals are affected by high temperatures, how a building will fare in an earthquake or how powerful winds will cause a bridge to oscillate. NASTRAN analysis is quick and inexpensive. It minimizes trial-and-error in the design process and makes possible better, safe, lighter structures affording large-scale savings in development time and materials. Some examples of the broad utility NASTRAN is finding among industrial firms are shown on these pages.

Source record↗

NASA NTRS1977

Modular control subsystems for use in solar heating systems for multi-family dwellings

Progress in the development of solar heating modular control subsystems is reported. Circuit design, circuit drawings, and printed circuit board layout are discussed along with maintenance manuals, installation instructions, and verification and acceptance tests. Calculations made to determine the predicted performance of the differential thermostat are given including details and results of tests for the offset temperature, and boil and freeze protect points.

Source record↗

NASA NTRS1993

Reliability Prediction

RELAV, a NASA-developed computer program, enables Systems Control Technology, Inc. (SCT) to predict performance of aircraft subsystems. RELAV provides a system level evaluation of a technology. Systems, the mechanism of a landing gear for example, are first described as a set of components performing a specific function. RELAV analyzes the total system and the individual subsystem probabilities to predict success probability, and reliability. This information is then translated into operational support and maintenance requirements. SCT provides research and development services in support of government contracts.

Source record↗

NASA NTRS2014

A Testbed for Implementing Prognostic Methodologies on Cryogenic Propellant Loading Systems

Prognostics technologies determine the health state of a system and predict its remaining useful life. With this information, operators are able to make maintenance-related decisions, thus effectively streamlining operational and mission-level activities. Experimentation on testbeds representative of critical systems is very useful for the maturation of prognostics technology; precise emulation of actual fault conditions on such a testbed further validates these technologies. In this paper we present the development of a pneumatic valve testbed, initial experimental results and progress towards the maturation and validation of component-level prognostic methods in the context of cryogenic refueling operations. The pneumatic valve testbed allows for the injection of time-varying leaks with specified damage progression profiles in order to emulate common valve faults. The pneumatic valve testbed also contains a battery used to power some pneumatic components, enabling the study of the effects of battery degradation on the operation of the valves.

Prognositcs↗

NASA NTRS2020

Securing the legacy of TESS through the care and maintenance of TESS planet ephemerides

Much of the science from the exoplanets detected by the TESS mission relies on precisely predicted transit times that are needed for many follow-up characterization studies. We investigate the severity of ephemeris deterioration for simulated TESS planets and find that the ephemerides of 81% of those will have expired (i.e. mid-transit time uncertainties greater than 30 minutes, impeding the efficient scheduling of follow-up observations) one year after their TESS observations. This rapid deterioration is driven primarily by the relatively short time baseline of TESS observations. In particular, of the simulated planets that would be recommended as potential James Webb Space Telescope targets by Kempton et al. (2018), 80% will have 1 mid-transit time uncertainties greater than 30 minutes by the earliest time JWST would observe them. The recently-approved extension to the TESS mission means that the ephemerides of most (though not all) primary mission planets will eventually be rescued, but the benefits of these new observations can only be reaped two years after the primary mission observations. Moreover, even with the advent of the TESS mission extension, the ephemerides of most primary mission TESS planets (as well as those newly discovered during the extended mission) will again have expired by the time future facilities such as the ELTs, Ariel and the possible LUVOIR/OST missions come online. We identify categories of TESS planets for which the ephemeris deterioration is most severe, and provide strategies for maintaining their ephemerides fresh through additional follow- up transit observations. We find that the longer the baseline between the TESS and the follow-up observations, the longer the ephemerides stay fresh, and that 51% of simulated primary mission TESS planets will require space-based observations to refresh their ephemerides.

Surveys↗

NASA NTRSDate not supplied

Assimilation of Soil Moisture Observations Over Land Improves Analysis and Prediction of Tropical Cyclone Idai

Soil moisture conditions can impact the circulation and structure of a tropical cyclone (TC) when part or all of the circulation is over land. Dry land surface conditions may lead to faster dissipation of a TC over land, whereas very wet conditions may lead to a prolonged maintenance of its intensity. While this relationship is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tbs significantly improves modeled land surface states. Here we evaluate: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP Tb observations. We find that in the analysis with SMAP assimilation, the TC has a better-defined, more aligned vertical structure over land relative to the control run; moreover, the analyzed TC size, as measured by the wind speed radius, better matches the observed TC size. We further find significant reductions in the forecast intensity error and the forecast along-track error, measured against observations. The largest error reductions occur at lead times of 36 to 72 hours, suggesting that the land with its longer memory gains in importance as a source of predictability at this timescale. An investigation of the underlying mechanisms leading to the skill improvements from SMAP data assimilation revealed that the assimilation of SMAP leads to wetter soil moisture conditions and an increased latent heat flux in the SMAP analysis, which results in a TC with higher column-integrated total moisture content and total energy compared to the control analysis.

Jana Kolassa↗