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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Freestream turbulence effects on the development of a rotor wake

The effect of freestream turbulence on the development of a three-dimensional wake of a compressor rotor blade was studied experimentally. The turbulence level at the inlet of a rotor was varied systematically using grids upstream of the rotor. The rotor wake was measured with inlet turbulence intensities of 0.5, 3, and 5%. The experimental results indicate that the maxium change in the mean velocity defect is 4% over the range of inlet turbulence levels employed, while the turbulence structure in the wake is altered more substantially. The freestream turbulence effect was also analyzed, numerically, using the modified Reynolds stress closure model. The comparison between numerical prediction and experimental data shows that the freestream turbulence effect can be represented successfully with the turbulence closure model employed in this paper.

Hah, C.↗
NASA NTRS1982

Recent sidewall boundary-layer investigations with suction in the Langley 0.3-m Transonic Cryogenic Tunnel

An experimental and theoretical study of the Langley 0.3-m Transonic Cryogenic Tunnel (TCT) sidewall boundary-layer with and without suction, has been made. Without suction, the boundary-layer displacement thickness at a station ahead of the model varied from about 1.6 mm to 1.3 mm over a Reynolds number range of 20 million to 200 million per m at Mach numbers from 0.30 to 0.76. Measured velocity profiles were correlated using the defect law of Hama. The boundary-layer displacement thickness decreased when suction was applied; however, after suction of about 2 percent of test section mass flow, the change in the thickness was small. A comparison of the measured suction effectiveness with finite difference and integral methods of boundary-layer calculation showed that both methods predicted the right trend over the range of suction velocities (up to a suction to free-stream velocity ratio of -0.02).

Murthy, A. V.↗
NASA NTRS1981

A comprehensive analysis of the performance characteristics of the Mount Laguna solar photovoltaic installation

This paper represents the first comprehensive survey of the Mount Laguna Photovoltaic Installation. The novel techniques used for performing the field tests have been effective in locating and characterizing defective modules. A comparative analysis on the two types of modules used in the array indicates that they have significantly different failure rates, different distributions in degradational space and very different failure modes. A life cycle model is presented to explain a multimodal distribution observed for one module type. A statistical model is constructed and it is shown to be in good agreement with the field data.

Shumka, A.↗
NASA NTRS1993

The Marshall Automated Weld System (MAWS)

A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer-controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.

Russell, Carolyn K.↗
NASA NTRS1993

The Marshall Automated Weld System (MAWS)

A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.

Russell, Carolyn K.↗
NASA NTRS1995

Software dependability in the Tandem GUARDIAN system

Based on extensive field failure data for Tandem's GUARDIAN operating system this paper discusses evaluation of the dependability of operational software. Software faults considered are major defects that result in processor failures and invoke backup processes to take over. The paper categorizes the underlying causes of software failures and evaluates the effectiveness of the process pair technique in tolerating software faults. A model to describe the impact of software faults on the reliability of an overall system is proposed. The model is used to evaluate the significance of key factors that determine software dependability and to identify areas for improvement. An analysis of the data shows that about 77% of processor failures that are initially considered due to software are confirmed as software problems. The analysis shows that the use of process pairs to provide checkpointing and restart (originally intended for tolerating hardware faults) allows the system to tolerate about 75% of reported software faults that result in processor failures. The loose coupling between processors, which results in the backup execution (the processor state and the sequence of events) being different from the original execution, is a major reason for the measured software fault tolerance. Over two-thirds (72%) of measured software failures are recurrences of previously reported faults. Modeling, based on the data, shows that, in addition to reducing the number of software faults, software dependability can be enhanced by reducing the recurrence rate.

Lee, Inhwan↗
NASA NTRS2001

Development of sensory systems in zebrafish (Danio rerio)

Zebrafish possess all of the classic sensory modalities: taste, tactile, smell, balance, vision, and hearing. For each sensory system, this article provides a brief overview of the system in the adult zebrafish followed by a more detailed overview of the development of the system. By far the majority of studies performed in each of the sensory systems of the zebrafish have involved some aspect of molecular biology or genetics. Although molecular biology and genetics are not major foci of the paper, brief discussions of some of the mutant strains of zebrafish that have developmental defects in each specific sensory system are included. The development of the sensory systems is only a small sampling of the work being done using zebrafish and provides a mere glimpse of the potential of this model for the study of vertebrate development, physiology, and human disease.

Non-NASA Center↗
NASA NTRS2005

Low Conductivity Thermal Barrier Coatings

Thermal barrier coatings will be more aggressively designed to protect gas turbine engine hot-section components in order to meet future engine higher fuel efficiency and lower emission goals. In this presentation, thermal barrier coating development considerations and requirements will be discussed. An experimental approach is established to monitor in real time the thermal conductivity of the coating systems subjected to high-heat-flux, steady-state and cyclic temperature gradients. Advanced low conductivity thermal barrier coatings have also been developed using a multi-component defect clustering approach, and shown to have improved thermal stability. The durability and erosion resistance of low conductivity thermal barrier coatings have been improved utilizing advanced coating architecture design, composition optimization, in conjunction with more sophisticated modeling and design tools.

Zhu, Dong-Ming↗
NASA NTRS2006

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the good material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide the details of the analytic model; an overview of the PCA process; as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

Cramer, K. Elliott↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase-field modeling for restructuring in the dark zone of high burnup UO 2

This report summarizes the mesoscale modeling work performed in fiscal year 2024 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to capture the microstructural evolution and restructuring observed in the dark regions of high burnup UO 2 nuclear fuel. This is the first attempt to realistically simulate the restructuring behavior observed in different region of a high burnup fuel. We employ a grand-potential based phase-field model to concurrently evaluate the formation of subgrains and growth of fission bubbles within the fuel. A energy-based subgrain formation criteria is introduced to simulate the restructuring process. Effect of different initial conditions and different modeling parameters are studies systematically to capture how each of these parameters influence the characteristics of the restructured fuel. It is observed that the subgrain formation begins around existing fission gas bubbles and then proceeds towards triple junctions, grain boundaries and grain interiors. It is demonstrated that restructuring is influenced by a combination of initial dislocation densities, subgrain formation rate, and temperature. Rate of restructuring increases with increase in fuel temperature. A restructuring bias is observed within the microstructure due to variation in defect accumulation among different grains. Furthermore, bubble sizes and distribution does not have a significant effect on rate of restructuring. The predicted microstructures resembles the characteristics of the restructured regions as observed in experiments. Finally, a correlation is presented that demonstrates the evolution of the restructuring volume fraction as a function of local effective burnup. This work provides a first of its kind restructuring model for darkzone that can be used by BISON for performance prediction of high burnup UO 2 fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Inferring relative dose-dependent color center populations in proton irradiated thoria single crystals using optical spectroscopy

In this work, we have utilized photoluminescence spectroscopy and optical ellipsometry to characterize the dose-dependence of the photoluminescence emission intensity and changes in optical absorption of thoria single crystals subject to irradiation with energetic protons at room- and elevated-temperatures. The photoluminescence peaks and the optical absorption bands are attributed to creation of new electronic states emerging from defects resulting from displacement damage. These bands are most likely associated with electrons trapped at the oxygen vacancy sites similar to color centers formed in other irradiated oxides and halides. Our experimental observations are supported by a standard density functional theory calculation of the electronic structure in pristine and oxygen vacancy-bearing thoria crystals. The dose-dependence of the intensity of the photoluminescence peaks is used to parameterize a rate theory model that estimates the concentration of color centers in the irradiated crystals. This parameterization provides optimized migration barrier parameters for oxygen interstitials and vacancies that simultaneously capture the optical response of the crystals irradiated at room- and elevated-temperature. These optical spectroscopy techniques offer a promising pathway to characterize the population of color centers formed at the sites of oxygen anion vacancies, particularly in irradiated nuclear fuels, where atomic-level defects cannot be readily imaged using electron microscopy. When combined with other direct and indirect characterization tools, our approach can provide new insight into defect formation and accumulation in energy materials over single atomic to extended length scales.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Vertebrate development in the environment of space: models, mechanisms, and use of the medaka

With the advent of space travel, it is of immediate interest and importance to study the effects of exposure to various aspects of the altered environment of space, including microgravity, on Earth-based life forms. Initial studies of space travel have focused primarily on the short-term effects of radiation and microgravity on adult organisms. However, with the potential for increased lengths of time in space, it is critical to now address the effects of space on all phases of an organism's life cycle, from embryogenesis to post-natal development to reproduction. It is already possible for certain species to undergo multiple generations within the confines of the Mir Space Station. The possibility now exists for scientists to consider the consequences of even potentially subtle defects in development through multiple phases of an organism's life cycle, or even through multiple generations. In this discussion, we highlight a few of the salient observations on the effects of the space environment on vertebrate development and reproductive function. We discuss some of the many unanswered questions, in particular, in the context of the choice of appropriate models in which to address these questions, as well as an assessment of the availability of hardware already existing or under development which would be useful in addressing these questions.

Flight Experiment↗
DOE OSTI2018

Ion Implantation in Narrow-Gap Cd{sub x}Hg{sub 1–x}Te Solid Solutions

The results of experimental studies of processes of the radiation defect formation under ion implantation of narrow-gap Cd{sub x}Hg{sub 1-x}Te solid solutions (MCT) are presented. The processes of formation of structural damages of the crystal and their effect on the electrophysical properties of ion-implanted bulk crystals and ptype heteroepitaxial structures grown by liquid-phase and molecular-beam epitaxy are considered. The results on the spatial distribution of implanted boron atoms and radiation donor centers in these materials are presented as a function of the mass, dose, and energy of ions being implanted and the implantation temperature. The processes and models of the formation of n{sup +}–n{sup -}–p-structures during boron ion implantation in p-type MCT and their experimental proof are considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Defect-mediated selective hydrogenation of nitroarenes on nanostructured WS 2

Transition metal dichalcogenides (TMDs) are well known catalysts as both bulk and nanoscale materials. Two-dimensional (2-D) TMDs, which contain single- and few-layer nanosheets, are increasingly studied as catalytic materials because of their unique thickness-dependent properties and high surface areas. Here, colloidal 2H-WS 2 nanostructures are used as a model 2-D TMD system to understand how high catalytic activity and selectivity can be achieved for useful organic transformations. Free-standing, colloidal 2H-WS 2 nanostructures containing few-layer nanosheets are shown to catalyze the selective hydrogenation of a broad scope of substituted nitroarenes to their corresponding aniline derivatives in the presence of other reducible functional groups. Microscopic and computational studies reveal the important roles of sulfur vacancy-rich basal planes and tungsten-terminated edges, which are more abundant in nanostructured 2-D materials than in their bulk counterparts, in enabling the functional group selectivity. At tungsten-terminated edges and on regions of the basal planes having high concentrations of sulfur vacancies, vertical adsorption of the nitroarene is favored, thus facilitating hydrogen transfer exclusively to the nitro group due to geometric effects. At lower sulfur vacancy concentrations on the basal planes, parallel adsorption of the nitroarene is favored, and the nitro group is selectively hydrogenated due to a lower kinetic barrier. These mechanistic insights reveal how the various defect structures and configurations on 2-D TMD nanostructures facilitate functional group selectivity through distinct mechanisms that depend upon the adsorption geometry, which may have important implications for the design of new and enhanced 2-D catalytic materials across a potentially broad scope of reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗