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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

HiRel - Reliability/availability integrated workstation tool

The HiRel software tool is described and demonstrated by application to the mission avionics subsystem of the Advanced System Integration Demonstrations (ASID) system that utilizes the PAVE PILLAR approach. HiRel marks another accomplishment toward the goal of producing a totally integrated computer-aided design (CAD) workstation design capability. Since a reliability engineer generally represents a reliability model graphically before it can be solved, the use of a graphical input description language increases productivity and decreases the incidence of error. The graphical postprocessor module HARPO makes it possible for reliability engineers to quickly analyze huge amounts of reliability/availability data to observe trends due to exploratory design changes. The addition of several powerful HARP modeling engines provides the user with a reliability/availability modeling capability for a wide range of system applications all integrated under a common interactive graphical input-output capability.

Bavuso, Salvatore J.↗
NASA NTRS1999

Modeling and Simulation Reliable Spacecraft On-Board Computing

The proposed project will investigate modeling and simulation-driven testing and fault tolerance schemes for Spacecraft On-Board Computing, thereby achieving reliable spacecraft telecommunication. A spacecraft communication system has inherent capabilities of providing multipoint and broadcast transmission, connectivity between any two distant nodes within a wide-area coverage, quick network configuration /reconfiguration, rapid allocation of space segment capacity, and distance-insensitive cost. To realize the capabilities above mentioned, both the size and cost of the ground-station terminals have to be reduced by using reliable, high-throughput, fast and cost-effective on-board computing system which has been known to be a critical contributor to the overall performance of space mission deployment. Controlled vulnerability of mission data (measured in sensitivity), improved performance (measured in throughput and delay) and fault tolerance (measured in reliability) are some of the most important features of these systems. The system should be thoroughly tested and diagnosed before employing a fault tolerance into the system. Testing and fault tolerance strategies should be driven by accurate performance models (i.e. throughput, delay, reliability and sensitivity) to find an optimal solution in terms of reliability and cost. The modeling and simulation tools will be integrated with a system architecture module, a testing module and a module for fault tolerance all of which interacting through a centered graphical user interface.

Park, Nohpill↗
NASA NTRS1981

Tropospheric chemistry - A global perspective

Processes that affect the concentration of tropospheric OH are considered, taking into account linkages between the chemistry of OH and the chemistry of H, HO2, and H2O2. A review is presented of observational data of special relevance to OH, notably the distributions of CO, CH4, O3, H2O, HNO3, NO, and NO2. Most of the results presented in connection with the description of the model were obtained by solving time-dependent continuity equations. Rates for photolytic processes were allowed to vary diurnally with insolation. It is found that a well-calibrated and reliable model for OH places important constraints on global budgets for a variety of gases including CH4, H2, and CH3Cl in addition to CO. Accurate measurements of species such as CH3CCl3 can provide valuable checks on global models that must integrate over a variety of atmospheric conditions. However, emission rates for the relevant gases must be adequately quantified.

Logan, J. A.↗
NASA NTRS2011

The Use of Crow-AMSAA Plots to Assess Mishap Trends

Crow-AMSAA (CA) plots are used to model reliability growth. Use of CA plots has expanded into other areas, such as tracking events of interest to management, maintenance problems, and safety mishaps. Safety mishaps can often be successfully modeled using a Poisson probability distribution. CA plots show a Poisson process in log-log space. If the safety mishaps are a stable homogenous Poisson process, a linear fit to the points in a CA plot will have a slope of one. Slopes of greater than one indicate a nonhomogenous Poisson process, with increasing occurrence. Slopes of less than one indicate a nonhomogenous Poisson process, with decreasing occurrence. Changes in slope, known as "cusps," indicate a change in process, which could be an improvement or a degradation. After presenting the CA conceptual framework, examples are given of trending slips, trips and falls, and ergonomic incidents at NASA (from Agency-level data). Crow-AMSAA plotting is a robust tool for trending safety mishaps that can provide insight into safety performance over time.

Dawson, Jeffrey W.↗
NASA NTRS1983

The reliability analysis of a separated, dual fail operational redundant strapdown IMU

A methodology for quantitatively analyzing the reliability of redundant avionics systems, in general, and the dual, separated Redundant Strapdown Inertial Measurement Unit (RSDIMU), in particular, is presented. The RSDIMU is described and a candidate failure detection and isolation system presented. A Markov reliability model is employed. The operational states of the system are defined and the single-step state transition diagrams discussed. Graphical results, showing the impact of major system parameters on the reliability of the RSDIMU system, are presented and discussed.

Motyka, P.↗
NASA NTRS1992

Automatic Generation Of Countdown-Simulating Software

ANPS computer program assists programmers attempting to model prelaunch countdown sequence. Designed to write simulation programs for problems concerning prelaunch activities of space vehicles and operation of ground support equipment and has potential for use in developing network-reliability models for systems and subsystems of equipment. Aids user in defining problem and then automatically writes appropriate simulation program in GPSS/PC code. Written in Turbo Prolog Version 2.0.

Schroer, Bernard J.↗
NASA NTRS1996

Reliability and Maintainability Model (RAM): User and Maintenance Manual: Improved Supportability Analysis - Part 2

This report documents the procedures for utilizing and maintaining the Reliability & Maintainability Model (RAM) developed by the University of Dayton for the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). The purpose of the grant is to provide support to NASA in establishing operational and support parameters and costs of proposed space systems. As part of this research objective, the model described here was developed. This Manual updates and supersedes the 1995 RAM User and Maintenance Manual. Changes and enhancements from the 1995 version of the model are primarily a result of the addition of more recent aircraft and shuttle R&M data.

Ebeling, Charles E.↗
NASA NTRS1978

The origin and relative abundances of C, N and the noble gases on the terrestrial planets and in meteorites

Relative concentrations of noble gases and C and N are evaluated for the terrestrial planets. Comparisons between amounts of volatile materials in carbonaceous chondrites and on Earth and Mars are presented as support for the accretion model of planetary formation. However, attention is given to the large differences in the C/noble gas ratios on various bodies in the solar system, e.g. the Sun, Venus, Earth, Mars, stressing that the data are too incomplete to provide a reliable model for the sources of volatile and noble elements on the terrestrial planets.

Bogard, D. D.↗
NASA NTRS1989

Reliability and performance evaluation of systems containing embedded rule-based expert systems

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Beaton, Robert M.↗
NASA NTRS1985

Space-flight simulations of calcium metabolism using a mathematical model of calcium regulation

The results of a series of simulation studies of calcium matabolic changes which have been recorded during human exposure to bed rest and space flight are presented. Space flight and bed rest data demonstrate losses of total body calcium during exposure to hypogravic environments. These losses are evidenced by higher than normal rates of urine calcium excretion and by negative calcium balances. In addition, intestinal absorption rates and bone mineral content are assumed to decrease. The bed rest and space flight simulations were executed on a mathematical model of the calcium metabolic system. The purpose of the simulations is to theoretically test hypotheses and predict system responses which are occurring during given experimental stresses. In this case, hypogravity occurs through the comparison of simulation and experimental data and through the analysis of model structure and system responses. The model reliably simulates the responses of selected bed rest and space flight parameters. When experimental data are available, the simulated skeletal responses and regulatory factors involved in the responses agree with space flight data collected on rodents. In addition, areas within the model that need improvement are identified.

Brand, S. N.↗
DOE OSTI2025

Comparing Classical and Machine Learning Force Fields for Modeling Deformation of Metal–Organic Frameworks Relevant for Direct Air Capture

Deformation of metal–organic frameworks (MOFs) induced by adsorbate molecules can affect adsorption properties such as capacity and selectivity, but most computational studies of MOFs assume framework rigidity to simplify calculations. Although flexible force fields (FFs) for MOFs have been parametrized for specific materials, the generality of FFs for reliably modeling adsorbate-induced deformation to accuracy nearing that of density functional theory (DFT) has not been established. This work confirms using DFT calculations that adsorbate-induced deformation can affect CO 2 and H 2 O adsorption energies in a considerable fraction of MOFs promising for direct air capture (DAC). We then benchmark the efficacy of several general-purpose FFs in describing adsorbate-induced deformation for DAC against DFT. Our results show that current classical FFs are insufficient for describing MOF deformation, especially in cases of interest for DAC where strong interactions exist between adsorbed molecules and MOF frameworks. Some emerging machine learning force fields (MLFFs) we tested, particularly CHGNet, MACE-MP-0, and Equiformer V2, appear to be more promising than the classical FF for emulating the deformation behavior described by DFT. The best performing FF (CHGNet), however, fails to achieve the accuracy required for practical predictions with a mean absolute adsorption energy error of 0.124 eV.

adsorption↗
NASA NTRS1982

Modeling of human operator dynamics in simple manual control utilizing time series analysis

Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

Agarwal, G. C.↗
NASA NTRS2022

Useful Life of Tantalum Capacitors

Currently, the major reliability characteristic of tantalum capacitors is the failure rate, which is a constant used to characterize random failures of electronic components. However, contemporary MnO2 and polymer tantalum capacitors have both infant mortality (IM) and wear-out (WO) failures. This requires assessments of the useful life of the parts that is limited by the time of inception of WO failures that can be determined using an adequate reliability model and results of highly accelerated life testing (HALT). In this presentation, a modified time dependent dielectric breakdown (TDDB) model is used to describe both IM and WO failures during HALT. Specifics of physical processes resulting in degradation and failures in polymer and MnO2 tantalum capacitors are discussed, and the increase of IM failures with the level of stress is explained. The model justifies exponential dependence of the acceleration factors on voltage and predicts higher values of the voltage acceleration constant for IM compared to WO failures.

tantalum capacitors↗
DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
NASA NTRS2022

Remote sensing-based vegetation and soil moisture constraints reduce irrigation estimation uncertainty

Understanding the human water footprint and its impact on the hydrological cycle is essential to inform water management under climate change. Despite efforts in estimating irrigation water withdrawals in earth system models, uncertainties and discrepancies exist within and across modeling systems conditioned by model structure, irrigation parameterization, and the choice of input datasets. Achieving model reliability could be much more challenging for data-sparse regions, given limited access to ground truth for parameterization and validation. Here, we demonstrate the potential of utilizing remotely sensed vegetation and soil moisture observations in constraining irrigation estimation in the Noah-MP land surface model. Results indicate that the two constraints together can effectively reduce model sensitivity to the choice of irrigation parameterization by 7%–43%. It also improves the characterization of the spatial patterns of irrigation and its impact on evapotranspiration and surface soil moisture by correcting for vegetation conditions and irrigation timing. This study highlights the importance of utilizing remotely sensed soil moisture and vegetation measurements in detecting irrigation signals and correcting for vegetation growth. Integrating the two remote sensing datasets into the model provides an effective and less feature engineered approach to constraining the uncertainty of irrigation modeling. Such strategies can be potentially transferred to other modeling systems and applied to regions across the globe.

Wanshu Nie↗
NASA NTRS1991

System reliability approaches for advanced propulsion system structures

This paper identifies significant issues that pertain to the estimation and use of system reliability in the design of advanced propulsion system structures. Linkages between the reliabilities of individual components and their effect on system design issues such as performance, cost, availability, and certification are examined. The need for system reliability computation to address the continuum nature of propulsion system structures and synergistic progressive damage modes has been highlighted. Available system reliability models are observed to apply only to discrete systems. Therefore a sequential structural reanalysis procedure is formulated to rigorously compute the conditional dependencies between various failure modes. The method is developed in a manner that supports both top-down and bottom-up analyses in system reliability.

Cruse, T. A.↗
NASA NTRS1993

Discrete range clustering using Monte Carlo methods

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Chatterji, G. B.↗