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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
NASA NTRS1992

Numerical solution of a three-dimensional cubic cavity flow by using the Boltzmann equation

A three-dimensional cubic cavity flow has been analyzed for diatomic gases by using the Boltzmann equation with the Bhatnagar-Gross-Krook (B-G-K) model. The method of discrete ordinate was applied, and the diffuse reflection boundary condition was assumed. The results, which show a consistent trend toward the Navier-Stokes solution as the Knudson number is reduced, give us confidence to apply the method to a three-dimensional geometry for practical predictions of rarefied-flow characteristics. The CPU time and the main memory required for a three-dimensional geometry using this method seem reasonable.

Hwang, Danny P.↗
NASA NTRS2002

Micromechanics Based Design/Analysis Codes for Advanced Composites

Advanced high temperature Ceramic Matrix Composites (CMC) hold an enormous potential for use in aero and space related applications specifically for propulsion system components. Consequently, this has led to a multitude of research activities pertaining to fabrication, testing and modeling of these materials. The efforts directed at the development of ceramic matrix composites have focused primarily on improving the properties of the constituents as individual phases. It has, however, become increasingly clear that for CMC to be successfully employed in high temperature applications, research and development efforts should also focus on optimizing the synergistic performance of the constituent phases within the as-produced microstructure of the complex shaped CMC part. Despite their attractive features, the introduction of these materials in a wide spectrum of applications has been excruciatingly slow. The reasons are the high costs associated with the manufacturing and a complete experimental testing and characterization of these materials. Often designers/analysts do not have a consistent set of necessary properties and design allowables to be able to confidently design and analyze structural components made from these composites. Furthermore, the anisotropy of these materials accentuates the burden both on the test engineers and the designers by requiring a vastly increased amount of data/characterization compared to conventional materials.

Mital, Subodh K.↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won’t happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures.

Jones, Harry W.↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won't happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures

Jones, Harry W.↗
NASA NTRS2020

Burning Embers: Towards More Transparent and Robust Climate-change Risk Assessments

The Intergovernmental Panel on Climate Change (IPCC) reports provide policy-relevant insights about climate impacts, vulnerabilities and adaptation through a process of peer-reviewed literature assessments underpinned by expert judgement. An iconic output from these assessments is the burning embers diagram, first used in the Third Assessment Report to visualize reasons for concern, which aggregate climate-change-related impacts and risks to various systems and sectors. These burning embers use colour transitions to show changes in the assessed level of risk to humans and ecosystems as a function of global mean temperature. In this Review, we outline the history and evolution of the burning embers and associated reasons for concern framework, focusing on the methodological approaches and advances. While the assessment framework and figure design have been broadly retained over time, refinements in methodology have occurred, including the consideration of different risks, use of confidence statements, more formalized protocols and standardized metrics. Comparison across reports reveals that the risk level at a given temperature has generally increased with each assessment cycle, reflecting accumulating scientific evidence. For future assessments, an explicit, transparent and systematic process of expert elicitation is needed to enhance comparability, quality and credibility of burning embers.

burning embers diagram↗
DOE OSTI2022

PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks

We propose a novel prediction interval (PI) method for uncertainty quantification, which addresses three major issues with the state-of-the-art PI methods. First, existing PI methods require retraining of neural networks (NNs) for every given confidence level and suffer from the crossing issue in calculating multiple PIs. Second, they usually rely on customized loss functions with extra sensitive hyperparameters for which fine tuning is required to achieve a well-calibrated PI. Third, they usually underestimate uncertainties of out-of-distribution (OOD) samples leading to over-confident PIs. Our PI3NN method calculates PIs from linear combinations of three NNs, each of which is independently trained using the standard mean squared error loss. The coefficients of the linear combinations are computed using root-finding algorithms to ensure tight PIs for a given confidence level. We theoretically prove that PI3NN can calculate PIs for a series of confidence levels without retraining NNs and it completely avoids the crossing issue. Additionally, PI3NN does not introduce any unusual hyperparameters resulting in a stable performance. Furthermore, we address OOD identification challenge by introducing an initialization scheme which provides reasonably larger PIs of the OOD samples than those of the in-distribution samples. Benchmark and real-world experiments show that our method outperforms several state-of-the-art approaches with respect to predictive uncertainty quality, robustness, and OOD samples identification.

Liu, Siyan↗
DOE OSTI2025

Dynamic Charging Rendezvous and Motion Planning for a Multi-AGV Team Including a Mobile Charging Host

Teams of automated battery-powered electric vehicles have the potential to execute complex mission tasks in off-road environments for agriculture, military, and other applications. Limited onboard energy reserves hinder their adoption in large-scale resource-constrained environments, where recharging is a necessity. It may be infeasible to install a network of static charging stations in off-road environments. For this reason, dedicated mobile host vehicles with charging capabilities are proposed as a means to increase range and capabilities of the multivehicle team. Here, in this study, we consider an ad hoc planning framework, where results from a high-confidence trajectory planner are leveraged to plan charging rendezvous between a host and other worker vehicles in a receding horizon fashion to provide high confidence that energy reserves will not be prematurely exhausted. The core problem is posed so as to minimize the impact of recharging on the mission in terms of task delays, overall energy utilization, and costs of fast charging. Through extensive Monte Carlo simulations of an off-road mission, we show a decrease in task delays without substantial increases in energy needs by updating the charging rendezvous plan during the mission. However, if updates are made too often, model mismatch may cause unnecessary cycling and mission failure.

Energy constraints↗
NASA NTRS1994

A rose by any other name: Certification seen as process rather than content

Green (1990) believes that the two main factors safeguarding flying from human error are both related to certification and regulation. First is the increasingly proceduralized nature of flying whereby as much as possible is reduced to a rule-based activity. Second is the emphasis placed upon training and competency checking of aircrew in simulators and in the air, both generally and for all particular types of aircraft flown. This leaves, believes Green, other human factors that are relatively unaddressed as yet and which can give rise to human reliability problems. These include: hardware factors and especially pilot/co-pilot relationships; and system factors including fatigue and cost/safety trade-offs. He also, importantly, identifies problems with the integration of the 'electronic crew member' following increased automation. Human reliability failures with artificial intelligence and automation, due to over-reliance on the system fail-safe mechanisms, or to operator under- confidence in the integrity or self-regulating capacity of the system, or to out-of-loop effects, are widely accepted as being due to deficiencies in plant design, planning, management and maintenance more than to 'operator error' - Reason's (1990) latent error or organization pathogens argument. Reliability failures in complex systems are well enough documented to give cause for concern and at least promote a debate on the merits of a full certification program. The purpose of this short paper is to seek out and explore what is valuable in certification, at the least to show that the benefits outweigh the disadvantages and at best to identify positive outcomes perhaps not obtainable in other ways. On both sides of the debate on certification there is general agreement on the need for a better human factors perspective and effort in complex aviation systems design. What is at issue is how this is to be promoted. It is incumbent upon opponents of certification to say how else such promotion be enabled. This is an exploratory and philosophical review, not a focused and specific one, and it will draw upon much that is not firmly in the domain of complex aviation systems.

Wilson, John R.↗
NASA NTRS2002

Active Control Analysis for Aeroelastic Instabilities in Turbomachines

Turbomachines onboard aircraft operate in a highly complex and harsh environment. The unsteady flowfield inherent to turbomachines leads to several problems associated with safety, stability, performance and noise. In-flight surge or flutter incidents could be catastrophic and impact the safety and reliability of the aircraft. High-Cycle-Fatigue (HCF), on the other hand, can significantly impact safety, readiness and maintenance costs. To avoid or minimize these problems generally a more conservative design method must be initiated which results in thicker blades and a loss of performance. Actively controlled turbomachines have the potential to reduce or even eliminate the instabilities by impacting the unsteady aerodynamic characteristics. By modifying the unsteady aerodynamics, active control may significantly improve the safety and performance especially at off-design conditions, reduce noise, and increase the range of operation of the turbomachine. Active control can also help improve reliability for mission critical applications such as the Mars Flyer. In recent years, HCF has become one of the major issues concerning the cost of operation for current turbomachines. HCF alone accounts for roughly 30% of maintenance cost for the United States Air-Force. Other instabilities (flutter, surge, rotating-stall, etc.) are generally identified during the design and testing phase. Usually a redesign overcomes these problems, often reducing performance and range of operation, and resulting in an increase in the development cost and time. Despite a redesign, the engines do not have the capabilities or means to cope with in-flight unforeseen vibration, stall, flutter or surge related instabilities. This could require the entire fleet worldwide to be stood down for expensive modifications. These problems can be largely overcome by incorporating active control within the turbomachine and its design. Active control can help in maintaining the integrity of the system in unforeseen events and provide for more aggressive designs to reduce the weight and improve efficiency of the turbomachine. Another area where active control can be useful is in controlling and suppressing rotating stall and surge in compressors, thereby increasing its operating range. Although some of these benefits will be offset by the added cost and weight penalty of the control system, the potential benefits in safety, reliability, performance, and noise characteristics are significant enough to warrant research in the area of active control of turbomachines. There is renewed interest within industry to understand unsteady aerodynamic behavior. This improved understanding not only leads to better design of turbomachines, which avoid instabilities but also which helps in understanding the controllability of the instabilities. The proliferation of micro-electro-mechanical-system (MEMS) devices has made available new tools to designers for employing feedback controls at reasonable costs. MEMS have also made the control devices small and unobtrusive enough to be implemented within the turbomachine without significant obstruction to the flow path. This has made active-control very attractive especially for systems requiring extreme confidence.

Keith, Theo G., Jr.↗
NASA NTRS2002

Probabilistic Analysis and Density Parameter Estimation Within Nessus

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Godines, Cody R.↗
NASA NTRS2008

Safety Critical Mechanisms

Spaceflight mechanisms have a reputation for being difficult to develop and operate successfully. This reputation is well earned. Many circumstances conspire to make this so: the environments in which the mechanisms are used are extremely severe, there is usually limited or no maintenance opportunity available during operation due to this environment, the environments are difficult to replicate accurately on the ground, the expense of the mechanism development makes it impractical to build and test many units for long periods of time before use, mechanisms tend to be highly specialized and not prone to interchangeability or off-the-shelf use, they can generate and store a lot of energy, and the nature of mechanisms themselves, as a combination of structures, electronics, etc. designed to accomplish specific dynamic performance, makes them very complex and subject to many unpredictable interactions of many types. In addition to their complexities, mechanism are often counted upon to provide critical vehicle functions that can result in catastrophic events should the functions not be performed. It is for this reason that mechanisms are frequently subjected to special scrutiny in safety processes. However, a failure tolerant approach, along with good design and development practices and detailed design reviews, can be developed to allow such notoriously troublesome mechanisms to be utilized confidently in safety-critical applications.

Robertson, Brandan↗
NASA NTRS1994

The Local Supercluster as a test of cosmological models

The Local Supercluster kinematic properties (the Local Group infall toward the Virgo Cluster and galaxy density distribution about the Virgo Cluster) in various cosmological models are examined utilizing large-scale N-body (PM) simulations 500(exp 3) cells, 250(exp 3) particles, and box size of 400 h(exp -1) Mpc) and are compared to observations. Five models are investigated: (1) the standard, Cosmic Background Explorer Satellite (COBE)-normalized cold dark matter (CDM) model with omega = 1, h = 0.5, and sigma(sub 8) = 1.05; (2) the standard Hot Dark Matter (HDM) model with omega = 1, h = 0.75, and sigma(sub 8) = 1; (3) the tilted CDM model with omega = 1, h = 0.5, n = 0.7, and sigma(sub 8) = 0.5; (4) a CDM + lambda model with omega = 0.3, lambda = 0.7, h = 2/3, and sigma(sub 8) = 2/3; (5) the PBI model with omega = 0.2, h = 0.8, x = 0.1, m = -0.5, and sigma(sub 8) = 0.9. Comparison of the five models with the presently available observational measurements v(sub LG) = 85 - 305 km/s (with mean of 250 km/s), delta(n(sub g))/(n(sub g)-bar) = 1.40 + or - 0.35) suggests that an open universe with omega approximately 0.5 (with or without lambda) and sigma(sub 8) approximately 0.8 is preferred, with omega = 0.3-1.0 (with or without lambda) and sigma(sub 8) = 0.7-1.0 being the acceptable range. At variance with some previous claims based on either direct N-body or spherical nonlinear approaches, we find that a flat model with sigma(sub 8) approximately 0.7-1.0 seems to be reasonably consistent with observations. However, if one favors the low limit of v(sub LG) = 85 km/s, then an omega approximately 0.2-0.3 universe seems to provide a better fit, and flat (omega = 1) models are ruled out at approximately 95% confidence level. On the other hand, if the high limit of v(sub LG) = 350 km/s is closer to the truth, then it appears that omega approximately 0.7-0.8 is more consistent. This test is insensitive to the shape of the power spectrum, but rather sensitive to the normalization of the perturbation amplitude on the relevant scale (e.g., sigma(sub 8)) and omega. We find that neither linear nor nonlinear relations (with spherical symmetry) are good approximations for the relation between radial peculiar velocity and density perturbation, i.e., nonspherical effects and gravitational tidal field are important. The derived omega using either of the two relations is underestimated. In some cases, this error is as large as a factor of 2-4.

Cen, Renyue↗
NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗
DOE OSTI2021

Analyses of transcriptomes and the first complete genome of Leucocalocybe mongolica provide new insights into phylogenetic relationships and conservation

In this study, we report a de novo assembly of the first high-quality genome for a wild mushroom species Leucocalocybe mongolica (LM). We performed high-throughput transcriptome sequencing to analyze the genetic basis for the life history of LM. Our results show that the genome size of LM is 46.0 Mb, including 26 contigs with a contig N50 size of 3.6 Mb. In total, we predicted 11,599 protein-coding genes, of which 65.7% (7630) could be aligned with high confidence to annotated homologous genes in other species. We performed phylogenetic analyses using genes form 3269 single-copy gene families and showed support for distinguishing LM from the genus Tricholoma (L.) P.Kumm., in which it is sometimes circumscribed. We believe that one reason for limited wild occurrences of LM may be the loss of key metabolic genes, especially carbohydrate-active enzymes (CAZymes), based on comparisons with other closely related species. The results of our transcriptome analyses between vegetative (mycelia) and reproductive (fruiting bodies) organs indicated that changes in gene expression among some key CAZyme genes may help to determine the switch from asexual to sexual reproduction. Taken together, our genomic and transcriptome data for LM comprise a valuable resource for both understanding the evolutionary and life history of this species.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Space Station Freedom cupola definition

Following the realization that adequate Space Station Freedom viewing could not be achieved without breaking the plane of the modules, a conceptual design phase for the development of a cupola progressed from the idea of a small, bubble-type canopy to a much larger, two crewmember cupola. The evolving cupola conceptual designs were each evaluated against the requirements for providing a large field-of-view, a complete proximity control workstation with flexible and relocatable restraints, and sufficient volume for two, 95th percentile crewmembers to operate while still maintaining reasonable weight and size restrictions. As the SS Freedom program Preliminary Design Review draws closer, the cupola development phase shifts toward evaluation of viewing and operational capability. The appropriate balance of viewing, structures and operations must be achieved before the program can place confidence in a cupola design providing SS Freedom with a direct viewing workstation capable of supporting the great variety of tasks projected for the life of the station.

Weaver, Laurie A.↗
NASA NTRS1979

Nationwide forestry applications program. Ten-Ecosystem Study (TES) site 8, Grays Harbor County, Washington

The author has identified the following significant results. Level 2 forest features (softwood, hardwood, clear-cut, and water) can be classified with an overall accuracy of 71.6 percent plus or minus 6.7 percent at the 90 percent confidence level for the particular data and conditions existing at the time of the study. Signatures derived from training fields taken from only 10 percent of the site are not sufficient to adequately classify the site. The level 3 softwood age group classification appears reasonable, although no statistical evaluation was performed.

Prill, J. C.↗
NASA NTRS1994

Diagnosing anomalies of spacecraft for space maintenance and servicing

Very often servicing of satellites is necessary to replace components which are responsible for anomalous behavior of satellite operations due to adverse interactions with the natural space environment. A major difficulty with this diagnosis is that those responsible for diagnosing these anomalies do not have the tools to assess the role of the space environment causing the anomaly. To address this issue, we have under development a new rule-based, expert system for diagnosing spacecraft anomalies. The knowledge base consists of over two-hundred rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Lauriente, Michael↗
NASA NTRS1993

An Intelligent computer-aided tutoring system for diagnosing anomalies of spacecraft in operation

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Rolincik, Mark↗