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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Experimental Investigation of Gas/Slag/Matte/Tridymite Equilibria in the Cu-Fe-O-S-Si System in Controlled Gas Atmospheres: Experimental Results at 1473 K (1200 °C) and P(SO{sub 2}) = 0.25 atm

Experimental studies were undertaken to determine the gas/slag/matte/tridymite equilibria in the Cu-Fe-O-S-Si system at 1473 K (1200 °C), P(SO{sub 2}) = 0.25 atm, and a range of P(O{sub 2})’s. The experimental methodology involved high-temperature equilibration using a substrate support technique in controlled gas atmospheres (CO/CO{sub 2}/SO{sub 2}/Ar), rapid quenching of equilibrium phases, followed by direct measurement of the chemical compositions of the phases with Electron Probe X-ray Microanalysis (EPMA). The experimental data for slag and matte were presented as a function of copper concentration in matte (matte grade). The data provided are essential for the evaluation of the effect of oxygen potential under controlled atmosphere on the matte grade, liquidus composition of slag and chemically dissolved copper in slag. The new data provide important accurate and reliable quantitative foundation for improvement of the thermodynamic databases for copper-containing systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Frequency and site selection criteria for MST radars, part 5.1A

The majority of mesosphere-stratosphere-troposphere (MST) and ST radars are located in or near mountainous terrain. When measuring horizontal velocities, the terrain is a small factor, but when measuring vertical velocities, the meteorological noise induced by rough terrain can severely limit the usefulness of the observations. When the variance of the vertical velocity is too large, it is not possible to suitably filter the data to detect the small synoptic-scale signal with reasonable statistical confidence. The variance of vertical velocity at all tropospheric levels is directly related to the low level wind speed during flow over rough terrain. It is suggested that the synoptic-scale vertical velocity can be measured by ST radars where the terrain is smooth. The large-scale vertical velocity cannot always be reliably determined from MST radar data when the underlying terrain is rough. The vertical velocity is potentially on of future radar site selections, taking into account the desired meteorological applications of the data and engineering design factors. If the synoptic-scale vertical velocity is a desired variable, the radar should not be located near mountains.

Nastrom, G. D.↗
NASA NTRS2003

Generalized Symbolic Execution for Model Checking and Testing

Modern software systems, which often are concurrent and manipulate complex data structures must be extremely reliable. We present a novel framework based on symbolic execution, for automated checking of such systems. We provide a two-fold generalization of traditional symbolic execution based approaches: one, we define a program instrumentation, which enables standard model checkers to perform symbolic execution; two, we give a novel symbolic execution algorithm that handles dynamically allocated structures (e.g., lists and trees), method preconditions (e.g., acyclicity of lists), data (e.g., integers and strings) and concurrency. The program instrumentation enables a model checker to automatically explore program heap configurations (using a systematic treatment of aliasing) and manipulate logical formulae on program data values (using a decision procedure). We illustrate two applications of our framework: checking correctness of multi-threaded programs that take inputs from unbounded domains with complex structure and generation of non-isomorphic test inputs that satisfy a testing criterion. Our implementation for Java uses the Java PathFinder model checker.

Khurshid, Sarfraz↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2023

Chemical Blast Standard (1 kg)

Chemical explosions create blast waves with large overpressure disturbances. It is important to develop a standard blast model based on data to accurately predict acoustic blast-wave amplitudes near detonations and invert for explosion energy from distant observations of blast-wave signals. However, open data from large, controlled chemical explosions with reliable ground truth can be challenging to find. The lack of access to such data could limit the number of contributions to related research and potentially stifle the rate of discoveries or validation of existing models. Here, to address these data scarcity problem, we have curated and compiled a standardized set of 817 blast-wave waveforms from 19 distinct high-explosive events. The blast-wave waveforms are standardized to a 1 kg trinitrotoluene explosion using scaling laws and corrections for location effects. A brief overview of the dataset is presented along with explosion feature models as well as recommendations for extracting explosion features. The resulting dataset is distributed to an open repository in both Seismic Analysis Code and pandas DataFrame formats containing the waveforms, the scaled distances, and the sample rates.

58 GEOSCIENCES↗
NASA NTRS1973

Redundancy management of inertial systems.

The paper reviews developments in failure detection and isolation techniques applicable to gimballed and strapdown systems. It examines basic redundancy management goals of improved reliability, performance and logistic costs, and explores mechanizations available for both input and output data handling. The meaning of redundant system reliability in terms of available coverage, system MTBF, and mission time is presented and the practical hardware performance limitations of failure detection and isolation techniques are explored. Simulation results are presented illustrating implementation coverages attainable considering IMU performance models and mission detection threshold requirements. The implications of a complete GN&C redundancy management method on inertial techniques are also explored.

Mckern, R. A.↗
NASA NTRS1983

Performance interface document for users of Tracking and Data Relay Satellite System (TDRSS) electromechanically steered antenna systems (EMSAS)

Satellites that use the NASA Tracking and Data Relay Satellite System (TDRSS) require antennas that are crucial for performing and achieving reliable TDRSS link performance at the desired data rate. Technical guidelines are presented to assist the prospective TDRSS medium-and high-data rate user in selecting and procuring a viable, steerable high-gain antenna system. Topics addressed include the antenna gain/transmitter power/data rate relationship; Earth power flux-density limitations; electromechanical requirements dictated by the small beam widths, desired angular coverage, and minimal torque disturbance to the spacecraft; weight and moment considerations; mechanical, electrical and thermal interfaces; design lifetime failure modes; and handling and storage. Proven designs are cited and space-qualified assemblies and components are identified.

Hockensmith, R.↗
NASA NTRS2008

Performance of MEMS Silicon Oscillator, ASFLM1, under Wide Operating Temperature Range

Over the last few years, MEMS (Micro-Electro-Mechanical Systems) resonator-based oscillators began to be offered as commercial-off-the-shelf (COTS) parts by a few companies [1-2]. These quartz-free, miniature silicon devices could compete with the traditional crystal oscillators in providing the timing (clock function) for many digital and analog electronic circuits. They provide stable output frequency, offer great tolerance to shock and vibration, and are immune to electro-static discharge [1-2]. In addition, they are encapsulated in compact lead-free packages, cover a wide frequency range (1 MHz to 125 MHz), and are specified, depending on the grade, for extended temperature operation from -40 C to +85 C. The small size of the MEMS oscillators along with their reliability and thermal stability make them candidates for use in space exploration missions. Limited data, however, exist on the performance and reliability of these devices under operation in applications where extreme temperatures or thermal cycling swings, which are typical of space missions, are encountered. This report presents the results of the work obtained on the evaluation of an ABRACON Corporation MEMS silicon oscillator chip, type ASFLM1, under extreme temperatures.

Patterson, Richard L.↗
NASA NTRS2011

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.↗
NASA NTRSDate not supplied

Application of a Bayesian Framework for Plasticity Model Selection

Interpretable Machine Learning (IML) has performed well when tasked with deriving constitutive material models. However, IML has been shown to prefer models that overfit noise in data, which tends to lead to bloat and a decrease in interpretability. Due to these issues, the ability of IML to reliably derive models that fit the data and are both interpretable and generalizable is limited. A method developed recently has shown promise to improve upon traditional IML by using a Bayesian fitness definition for the evolution of free-form models with non-deterministic parameters. This framework was developed for genetic-programming-based symbolic regression(GPSR) and involves model parameter estimation using Sequential Monte Carlo sampling (SMC).The method has demonstrated a reduction in bloat when dealing with noisy data in comparison to conventional GPSR. The results of this framework applied to stress-strain data for copper show models that more effectively predict the experimental data better than was previously shown with GPSR.

plasticity↗
NASA NTRS1990

Empirically based analysis of failures in software systems

An empirical analysis of software-system failures is used to study several specific issues in software testing, reliability analysis, and reuse. Failure data from a large software manufacturer and a NASA production environment were collected and analyzed. The systems ranged in size from 30,000 to over 100,000 lines. The results show that (1) the first 15 percent of the test cases detected 67 percent of the high-severity failures and 50 percent of all failures; (2) multiple fault-detection and testing phases may result in a significant increase in reliability or none at all; (3) composite measures of system reliability did not adequately reflect reliability at the function or component level; (4) developers were biased toward portions of systems that would be heavily tested; (5) fault-proneness of reused or modified components was 74 percent less than that of newly developed components; and (6) systems with more reused software had lower component development effort, but not lower component fault-proneness.

Selby, Richard W.↗
NASA NTRS1996

Attitude and Trajectory Estimation Using Earth Magnetic Field Data

The magnetometer has long been a reliable, inexpensive sensor used in spacecraft momentum management and attitude estimation. Recent studies show an increased accuracy potential for magnetometer-only attitude estimation systems. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computer and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both the spacecraft trajectory and attitude errors. Therefore, these errors can be used to estimate both trajectory and attitude. Traditionally, satellite attitude and trajectory have been estimated with completely separate system, using different measurement data. Recently, trajectory estimation for low earth orbit satellites was successfully demonstrated in ground software using only magnetometer data. This work proposes a single augmented extended Kalman Filter to simultaneously and autonomously estimate both spacecraft trajectory and attitude with data from a magnetometer and either dynamically determined rates or gyro-measured body rates.

Deutschmann, Julie↗
DOE OSTI2024

Complete and Correct Transfer of Information (CACTI)

Many distributed systems, file transfer mechanisms, and message passing systems offer reliability mechanisms such as acknowledgements, retries, and durability. While these tools may be “good enough” for their typical use cases, they may not offer sufficient coverage for the wide range of faults that impact data transfers and communication. A gap in the reliability measures may lead to some small amount of data loss. Some high-consequence systems cannot tolerate the loss or corruption of even a single record. We present seven principles that will counter a wide range of faults and protect against data loss and corruption. These principles bring together lessons learned from a wide range of technologies and can inform appropriate system design and application usage. These principles will help readers reason on how prevent data loss in a multi-hop pipeline and how to properly use tools that may have a deficiency in reliability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Effects of Reactive Power on Photovoltaic Inverter Reliability and Lifetime

This paper performs research on predicting Photovoltaic (PV) inverters reliability and lifetime based on thermal cycling. Thermal cycling is considered the most important stressors in an inverter system. In order to achieve this, a detailed electro-thermal model of the PV inverter will be developed along with their controllers capable of providing voltage support through reactive power. An in-house inverter was built, and a PV inverter model was developed to match the physical inverter. The PV inverter electrothermal model was validated for different ambient temperatures to match the in-house inverter hardware. The in-house inverter was placed inside a thermal chamber to emulate different ambient temperatures and their losses and temperature rises within the system were measured. After the validation of the model, a reduced order model of the inverter will be implemented to translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The junction temperature data will be used to identify the reliability indices and hence predict the useful lifetime of the inverter system. Along with the model to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The key observation in this paper shows that lifetime of the inverter decreases as the operating power factor moves away from unity.

14 SOLAR ENERGY↗
DOE OSTI2020

Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2011

NASA Accident Precursor Analysis Handbook, Version 1.0

Catastrophic accidents are usually preceded by precursory events that, although observable, are not recognized as harbingers of a tragedy until after the fact. In the nuclear industry, the Three Mile Island accident was preceded by at least two events portending the potential for severe consequences from an underappreciated causal mechanism. Anomalies whose failure mechanisms were integral to the losses of Space Transportation Systems (STS) Challenger and Columbia had been occurring within the STS fleet prior to those accidents. Both the Rogers Commission Report and the Columbia Accident Investigation Board report found that processes in place at the time did not respond to the prior anomalies in a way that shed light on their true risk implications. This includes the concern that, in the words of the NASA Aerospace Safety Advisory Panel (ASAP), "no process addresses the need to update a hazard analysis when anomalies occur" At a broader level, the ASAP noted in 2007 that NASA "could better gauge the likelihood of losses by developing leading indicators, rather than continue to depend on lagging indicators". These observations suggest a need to revalidate prior assumptions and conclusions of existing safety (and reliability) analyses, as well as to consider the potential for previously unrecognized accident scenarios, when unexpected or otherwise undesired behaviors of the system are observed. This need is also discussed in NASA's system safety handbook, which advocates a view of safety assurance as driving a program to take steps that are necessary to establish and maintain a valid and credible argument for the safety of its missions. It is the premise of this handbook that making cases for safety more experience-based allows NASA to be better informed about the safety performance of its systems, and will ultimately help it to manage safety in a more effective manner. The APA process described in this handbook provides a systematic means of analyzing candidate accident precursors by evaluating anomaly occurrences for their system safety implications and, through both analytical and deliberative methods used to project to other circumstances, identifying those that portend more serious consequences to come if effective corrective action is not taken. APA builds upon existing safety analysis processes currently in practice within NASA, leveraging their results to provide an improved understanding of overall system risk. As such, APA represents an important dimension of safety evaluation; as operational experience is acquired, precursor information is generated such that it can be fed back into system safety analyses to risk-inform safety improvements. Importantly, APA utilizes anomaly data to predict risk whereas standard reliability and PRA approaches utilize failure data which often is limited and rare.

Groen, Frank↗