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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 1,063 records · Page 59

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NASA NTRS2004

Environment of Space Interactions with Space Systems

The primary product of this research project was a computer program named SAVANT. This program uses the Displacement Damage Dose (DDD) method of calculating radiation damage to solar cells. This calculation method was developed at the Naval Research Laboratory, and uses fundamental physical properties of the solar cell materials to predict radiation damage to the solar cells. This means that fewer experimental measurements are required to characterize the radiation damage to the cells, which results in a substantial cost savings to qualify solar cells for orbital missions. In addition, the DDD method makes it easier to characterize cells that are already being used, but have not been fully tested using the older technique of characterizing radiation damage. The computer program combines an orbit generator with NASA's AP-8 and AE-8 models of trapped protons and electrons. This allows the user to specify an orbit, and the program will calculate how the spacecraft moves during the mission, and the radiation environment that it encounters. With the spectrum of the particles, the program calculates how they would slow down while traversing the coverglass, and provides a slowed-down spectrum.

Source record↗

NASA NTRS1997

Interpretation of Trace Gas Data Using Inverse Methods and Global Chemical Transport Models

This is a theoretical research project aimed at: (1) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (2) utilization of inverse methods to determine these source/sink strengths which use the NCAR/Boulder CCM2-T42 3-D model and a global 3-D Model for Atmospheric Transport and Chemistry (MATCH) which is based on analyzed observed wind fields (developed in collaboration by MIT and NCAR/Boulder), (3) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and, (4) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3-D models. Important goals include determination of regional source strengths of methane, nitrous oxide, and other climatically and chemically important biogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements and hydrohalocarbons used as alternatives to the restricted halocarbons.

Prinn, Ronald G.↗

NASA NTRS2004

Unsteady Aerodynamic Response of a Linear Cascade of Airfoils in Separated Flow

The overall objective of this research program was to investigate methods to modify the leading edge separation region, which could lead to an improvement in aeroelastic stability of advanced airfoil designs. The airfoil section used is representative of current low aspect ratio fan blade tip sections. The experimental potion of this study investigated separated zone boundary layer from removal through suction slots. Suction applied to a cavity in the vicinity of the separation onset point was found to be the most effective location. The computational study looked into the influence of front camber on flutter stability. To assess the influence of the change in airfoil shape on stability the work-per-cycle was evaluated for torsion mode oscillations. It was shown that the front camberline shape can be an important factor for stabilizing the predicted work-per-cycle and reducing the predicted extent of the separation zone. In addition, data analysis procedures are discussed for reducing data acquired in experiments that involve periodic unsteady data. This work was conducted in support of experiments being conducted in the NASA Glenn Research Center Transonic Flutter Cascade. The spectral block averaging method is presented. This method is shown to be able to account for variations in airfoil oscillation frequency that can occur in experiments that force oscillate the airfoils to simulate flutter.

Capece, Vincent R.↗

DOE OSTI2023

malbacR: A Package for Standardized Implementation of Batch Correction Methods for Omics Data

Mass spectrometry is a powerful tool for identifying and analyzing small molecules, such as metabolites and lipids, in com-plex biological samples. Liquid chromatography and gas chromatography mass spectrometry studies quite commonly in-volve large numbers of samples, which can require significant time for sample preparation and analyses. To accommodate such studies, the samples are commonly split into batches. Inevitably, variations in sample handling, temperature fluctua-tion, imprecise timing, column degradation and other factors result in systematic errors or biases of the measured abundances between the batches. Numerous methods are available via R packages to assist with batch correction for small molecule om-ics data; however, since these methods were developed by different research teams, the algorithms are available in separate R packages, each with different data input and output formats. We introduce the malbacR package which consolidates eleven common batch effect correction methods for small molecule omics data into one place so users can easily implement and compare: pareto scaling, power scaling, range scaling, ComBat, EigenMS, NOMIS, RUV-random, QC-RLSC, WaveI-CA2.0, TIGER, and SERRF. The malbacR package standardizes data input and output formats across these batch correction methods. The package works in conjunction with the pmartR package, allowing users to seamlessly include batch effect cor-rection in a pmartR workflow without needing any additional data manipulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Metal (Cu,Al)/CNT Composite Wires for Energy Efficient Motors

This report summarizes the main results of research project on Metal/CNT nanocomposites conducted at University of Central Florida (UCF). It should be noted that the project was budgeted for three years, but the budget period 3 was unfortunately not funded and conducted in COVID19 pandemic years due to many reasons. The demonstration plan on the small motors was also removed according to the discussion with the DOE program manager. All research activities were focused on the (Cu,Al)/CNT material development and wire extrusion. Existing methods to fabricate Metal/CNTs were usually suffering from agglomeration of CNTs due to their density and stiffness differences. A new method is studied by the UCF research team, where CNTs are surface treated firstly, then coated with pure metals (i.e., Al, Cu, and Nickle). The metal encapsulation on CNT is expected to significantly improve the interfacial bonding between CNTs and the intimated metal matrices. The coated CNT powders were used to make sample materials through sintering, then a customized wire extrusion process was employed to fabricate wires. Measurement of material property improvements in mechanical strength, thermal conductivity, and electrical conductivity were conducted on both cylinder samples and extruded wires. In addition to the sintering process, casting on metal coated CNT powder was also investigated. The best results we achieved are summarized as follows. (1) The measured thermal conductivity of Al/CNT composite made with Ni-encapsulated CNTs and pure Al powders is about 85% better than that of pure aluminum fabricated. The measured electrical conductivity of fabricated Al/CNT is about 14-20% better than that of pure aluminum. (2) The measured electrical conductivity of Cu/CNT is about 14.5% better than that of pure copper fabricated. (3) The mechanical strengths of both Cu/CNT and Al/CNT (with about 1% wt. CNTs) are 70% better than pure metals although losing some material ductility. (4) Two-stage wire extrusion at high temperatures were designed and successfully conducted to fabricate wires of Metal/CNTs.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Trajectory optimization for the National Aerospace Plane

The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.

Lu, Ping↗

NASA NTRS1996

Evaluating Sleep Disturbance: A Review of Methods

There are three general approaches to evaluating sleep disturbance in regards to noise: subjective, behavioral, and physiological. Subjective methods range from standardized questionnaires and scales to self-report measures designed for specific research questions. There are two behavioral methods that provide useful sleep disturbance data. One behavioral method is actigraphy, a motion detector that provides an empirical estimate of sleep quantity and quality. An actigraph, worn on the non-dominant wrist, provides a 24-hr estimate of the rest/activity cycle. The other method involves a behavioral response, either to a specific probe or stimuli or subject initiated (e.g., indicating wakefulness). The classic, gold standard for evaluating sleep disturbance is continuous physiological monitoring of brain, eye, and muscle activity. This allows detailed distinctions of the states and stages of sleep, awakenings, and sleep continuity. Physiological delta can be obtained in controlled laboratory settings and in natural environments. Current ambulatory physiological recording equipment allows evaluation in home and work settings. These approaches will be described and the relative strengths and limitations of each method will be discussed.

Smith, Roy M.↗

NASA NTRS1947

Development and Construction of an Interferometer for Optical Measurements of Density Fields

A method of interference is described in the present report which promises profitable application in aeronautical research. The physical foundation of the method and a simple method of adjustment are briefly discussed. The special technical construction of the instrument is described which guarantees its use also in the case of vibrations of the surrounding space and permits the investigation of unsteady phenomena. It is found that the interference method will make the small differences in density in the flow field around the body even at low speeds. (40 m/sec) optically measurable.

Zobel, Th.↗

NASA NTRS2005

Exploring Diverse Data Sets and Developing New Theories and Ideas With Project Integration Architecture

The development of new ideas is the essence of scientific research. This is frequently done by developing models of physical processes and comparing model predictions with results from experiments. With models becoming ever more complex and data acquisition systems becoming more powerful, the researcher is burdened with wading through data ranging in volume up to a level of many terabytes and beyond. These data often come from multiple, heterogeneous sources and usually the methods for searching through it are at or near the manual level. In addition, current documentation methods are generally limited to researchers pen-and-paper style notebooks. Researchers may want to form constraint-based queries on a body of existing knowledge that is, itself, distributed over many different machines and environments and from the results of such queries then spawn additional queries, simulations, and data analyses in order to discover new insights into the problem being investigated. Currently, researchers are restricted to working within the boundaries of tools that are inefficient at probing current and legacy data to extend the knowledge of the problem at hand and reveal innovative and efficient solutions. A framework called the Project Integration Architecture is discussed that can address these desired functionalities.

Benyo, Theresa L.↗

NASA NTRS2016

Improving and Expanding NASA Software Cost Estimation Methods

Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm.

Hihn, Jairus↗

DOE OSTI2020

Parallel-in-Time Multigrid Methods for Hyperbolic Problems, with a Focus on the Shallow Water Equations

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations, which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic problems of programmatic interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic problems on future architectures. The difficulty lies in the fact that hyperbolic problems are well-known to be difficult for parallel-in-time methods, with the most common parallel-in-time method, Parareal, diverging in many cases. Here, the chosen methodology for scalably solving these hyperbolic space-time equations is multigrid-reductionin-time (MGRIT), because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. To further research in this area, this project will explore a model hyperbolic problem (the shallow water equations) in the context of recent advances (e.g., by Wingate and Haut) in constructing improved coarse time-grid time-propagators by using the slow asymptotic structure of the equations. In particular, we will investigate if such coarse time-propagators offer significant advantages in an MGRIT setting, and explore any broader insights gained into parallel-in-time for hyperbolic problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.

Rutz, Jonathan J.↗

DOE OSTI2023

ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study

Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.

critical clearing time↗

DOE OSTI2023

The Legendre Polynomial Axial Expansion Method

This work presents a new formulation of the axial expansion transport method explicitly using Legendre polynomials for arbitrarily high-order expansions. This new formulation also features an alternative method of axial leakage calculation to allow for nonextruded flat source region meshes. This alternative axial leakage is introduced alongside a balance equation requirement to ensure that neutron balance is preserved in the coarse mesh for a given axial leakage formulation, which allows for effective coarse mesh finite difference acceleration. A matrix exponential table method is derived to allow for fast computations of arbitrarily high-order matrix exponentials for this work and precludes the need for further research into matrix exponential calculations for this method. Numerical results are presented that demonstrate the stability of the axial expansion method in systems with voidlike regions, showcase the speedup from matrix exponential tables, and investigate the axial convergence of the method in terms of both expansion order and mesh size.

Herring, Nicholas↗

NASA NTRS1979

NASA-Langley Research Center's participation in a round-robin comparison between some current crack-propagation prediction methods

A round-robin study was conducted which evaluated and compared different methods currently in practice for predicting crack growth in surface-cracked specimens. This report describes the prediction methods used by the Fracture Mechanics Engineering Section, at NASA-Langley Research Center, and presents a comparison between predicted crack growth and crack growth observed in laboratory experiments. For tests at higher stress levels, the correlation between predicted and experimentally determined crack growth was generally quite good. For tests at lower stress levels, the predicted number of cycles to reach a given crack length was consistently higher than the experimentally determined number of cycles. This consistent overestimation of the number of cycles could have resulted from a lack of definition of crack-growth data at low values of the stress intensity range. Generally, the predicted critical flaw sizes were smaller than the experimentally determined critical flaw sizes. This underestimation probably resulted from using plane-strain fracture toughness values to predict failure rather than the more appropriate values based on maximum load.

Hudson, C. M.↗

DOE OSTI2025

Vision Foundation Models in Remote Sensing: A survey

Artificial intelligence (AI) technologies have profoundly transformed the field of remote sensing (RS), revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, RS research has been significantly enhanced by the advent of foundation models (FMs)—large-scale pretrained AI models capable of performing a wide array of tasks with unprecedented accuracy and efficiency. This article provides a comprehensive survey of FMs in the RS domain. We categorize these models based on their architectures, pretraining datasets, and methodologies. Through detailed performance comparisons, we highlight emerging trends and the significant advancements achieved by those FMs. Additionally, we discuss technical challenges, practical implications, and future research directions, addressing the need for high-quality data, computational resources, and improved model generalization. Our research also finds that pretraining methods, particularly self-supervised learning (SSL) techniques like contrastive learning (CL) and masked autoencoders (MAEs), remarkably enhance the performance and robustness of FMs. This survey aims to serve as a resource for researchers and practitioners by providing a panorama of advances and promising pathways for the continued development and application of FMs in RS.

data models↗

DOE OSTI2022

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Benchmark probabilistic solar forecasts: Characteristics and recommendations

We illustrate and compare commonly used benchmark, or reference, methods for probabilistic solar forecasting that researchers use to measure the performance of their proposed techniques. A thorough review of the literature indicates wide variation in the benchmarks implemented in probabilistic solar forecast studies. To promote consistent and sensible methodological comparisons, we implement and compare ten variants from six common benchmark classes at two temporal scales: intra-hourly forecasts and hourly resolution forecasts. Using open-source Surface Radiation Budget Network (SURFRAD) data from 2018, these benchmark methods are compared using proper probabilistic metrics and common diagnostic tools. Practical implementation issues, such as the impact of missing data and applicability for operational forecasting, are also discussed. Furthermore, we make recommendations for practitioners on the appropriate selection of benchmark methods to properly showcase state-of-the-art improvements in forecast reliability and sharpness. All code and open-source data are available on Github for reproducibility and for other researchers to apply the same benchmark methods to their own data.

14 SOLAR ENERGY↗