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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Failure prediction and estimation of failure parameters

Machine-learning methods and apparatus are disclosed to determine frictional state or other parameters in an earthquake zone or other failing medium, using acoustic emission, seismic waves, or other detectable indicators of microscopic processes. Predictions of future failures are demonstrated in different regimes. A classifier is trained using time series of acoustic emission data along with historic data of frictional state or failure events. In disclosed examples, random forests and gradient boost trees are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to testing or live data in order to assess a frictional state, assess seismic hazard, or make predictions regarding a future failure event. The technology has been developed in a double direct shear apparatus, but can be widely applied to seismic faults, other terrestrial failures, or failures in man-made structures. Variations are disclosed.

Johnson, Paul Allan↗
DOE OSTI2022

Gas generation and intramolecular isotope study in laboratory pyrolysis of the Springfield coal from the Illinois Basin

Position-specific (PS) isotopes of propane have been proposed as a potential geochemical tool to decipher various geological processes (e.g., thermal cracking, biodegradation, H exchange) in natural reservoirs. The limited studies have been conducted on the PS isotopes of propane from the pyrolysis gases from marine shales, and natural gases sourced from lacustrine and marine kerogens, but little is known on gases produced from the humic kerogen. Here, this study investigated the PS δ 13 C of propane in the closed-system pyrolysis of the Springfield coal, Illinois Basin, Indiana, at 310 to 470 °C (Easy %Ro: 0.76 to 3.07). The C kinetic isotope effect (KIE) of CH 4 produced in both this study and previous low-temperature pyrolysis of the same coal indicates the cleavage of C—O bonds is the main generation pathway at the early kerogen cracking stage, followed by the breakdown of alkyl groups. At the wet-gas cracking stage, C 3 H 8 production from thermally stable compounds has a significant influence on the bulk and position-specific C KIE in the pyrolysis of marine Woodford kerogen and Springfield coal. According to the PS δ 13 C of propane, the central site is likely more enriched in 13 C and the δ 13 C of the terminal site is relatively heterogeneous within the propyl group attached to different functional groups of the gas-prone kerogen. Our findings based on the pyrolysis experiments and natural gas samples indicate thermal cracking and biodegradation appear to alter the δ 13 C cen values more significantly than the δ 13 C ter values of propane. The larger magnitude of ΔC c-t in the kMC simulations (Peterson et al., 2018) compared with those from the marine shale and coal possibly implies the non-random distributions of 13 C of propane precursors in the kerogens. As a new dimension of intramolecular isotopic information of propane, the PS δ 13 C values can contribute to fingerprinting the gas origins and identifying the various geological processes (e.g., kerogen cracking, wet-gas cracking, microbial activities) in sedimentary basins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Influence of rapid heating and cooling combined with deformation at ultrahigh strain rates on the microstructure evolution of pure titanium shaped charge liner

Highlights: • A slug prepared from pure titanium SCL was recovered after detonation deformation at an ultrahigh strain rate over 10{sup 5} s{sup −1}. • The α → β → α phase transformation occurred in Ti SCL during the ultrahigh-strain -rate deformation. • The microstructures of the recovered slug included lamellar α grains, equiaxed α grains, and jagged α grains. - Abstract: A slug prepared from pure titanium shaped charge liners was recovered after detonation deformation at an ultrahigh strain rate over 10{sup 5} s{sup −1} and high strain over 500%. Optical microscopy, electron backscattered diffraction (EBSD), and transmission electron microscopy (TEM) were employed to investigate the microstructure of the Ti shaped charged liner before and after the detonation deformation. The microstructures of the recovered slug include lamellar α grains, equiaxed α grains within localized shear bands, and jagged α grains. EBSD results indicated that the grain orientation distribution is random and no texture was observed in the slug. TEM observation revealed that the α → β → α phase transformation occurred owing to the rapid heating and cooling combined with deformation at ultrahigh strain rates in the Ti shaped charge liner. No melting phenomenon was observed during the deformation process. The deformation process consisted of the explosive detonation stage combined with rapid heating and the subsequent penetration stage combined with rapid cooling. In the explosive detonation stage, the α → β phase transformation instantaneously occurred via a martensitic mechanism. In the penetration stage, the high-temperature slug in β state was cooled rapidly and showed different deformation behaviors in three different areas.

36 MATERIALS SCIENCE↗
NASA NTRS2022

Simulating the Diffusion of Hydrogen in Amorphous Silicates: A ‘Jumping’ Migration Process and its Implications for Solar Wind Implanted Lunar Volatiles

We use molecular dynamics (MD) simulations to better explain the movement of atomic hydrogen in amorphous silica and quantify the planetary science implications of these findings. Previous MD simulations had a large range of predicted values and did not agree well with experiment. Our simulations sample atomic motion for a longer duration and consider a wider range of temperatures than previous simulations. In contrast to constant atomic motion, the hydrogen atoms were shown to undergo random intermittent jumps from one oxygen atom to another, the number of which increase with temperature. Predicted diffusion coefficients had a better agreement to experimental values than previous MD simulations, suggesting the importance of longer simulation durations for better statistics. The low activation energy and jumps observed at lunar temperatures do not support the theory of diurnal variations in OH content for an undamaged amorphous silica surface. Instead, we conclude that energetic solar wind impacts can induce two competing atomic hydrogen motion processes in the exposed surface: A prompt effect that induces jumps in the temperature spike volume, but also a long term effect of damage in the structure that traps atomic hydrogen. We then use SDTrimSP to quantify the damage created during exposure and MD to demonstrate the H retention and trapping near these defects. Damage was shown to be dependent on impact energy, with defects easily retaining implanted hydrogen. MD results like those presented herein on unweathered surfaces are therefore most relevant to magnetic anomalies. As a result, we demonstrate the importance of lunar volatile models to account for the damage state of the substrate when modelling hydrogen diffusion, retention, and subsequent OH/water production.

Liam S. Morrissey↗
NASA NTRS1987

Real-time hierarchically distributed processing network interaction simulation

The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

Zimmerman, W. F.↗
NASA NTRS2019

Improved Processing Techniques for Inclusion-Free Steel for Bearing and Mechanical Component Applications

High hardness, high carbide powder metallurgy tools steels such as M62 enable the operation of ball bearings at extremely high load and stress levels. Operation under such conditions increases the potential for rolling contact fatigue failure attributed to ceramic particle inclusions. To address this challenge, industry has sought steel made from ever increasing levels of cleanliness but the results have been uneven owing to the random nature of the occurrence of material flaws. One common approach is to rely upon careful ingot inspections prior to bearing manufacture. By selecting the cleanest portion of an ingot, it is expected that bearings relatively free from material flaws will result. This approach is not always successful because detrimental flaws that exist deep within an ingot can pass inspection undetected potentially causing subsequent failure. Recent efforts to commercialize an intermetallic material, 60NiTi, for rolling element bearings demonstrates a pathway to produce bearing steel that is free from unwanted ceramic particle inclusions. In this paper, the process used to make bearing grade ceramic-free NiTi alloys is described and applied to steelmaking. At its core, the NiTi process differs from steel making in one key aspect. NiTi alloys are made from elementally pure starting materials that are melted, blended and processed in equipment absolutely free from exposure to oxygen and ceramics ensuring a ceramic particle-free product. In contrast, the predominant method to make bearing steel is to employ a successive series of purification steps to reduce contamination levels below required thresholds. This paper describes the processes developed and applied to high carbide tool steel, M62. The resulting material and microstructures are evaluated and compared to M62 prepared by conventional powder metallurgy techniques. It is hoped that the application of materials manufacturing techniques used for fracture sensitive ceramics and intermetallic materials like NiTi can provide a pathway to Ultra-Clean, Ceramic-Inclusion free steels for rolling element bearings and other failure critical applications.

Steel↗
DOE OSTI2025

Graph-based design of irregular metamaterials

In the field of metamaterial research, random structures offer a novel and less conventional approach compared to traditional periodic designs. Designing random metamaterials is challenging when it comes to ensuring intercon- nectivity, which is essential for manufacturability. This study introduces an innovative framework for generating random metamaterials using graph al- gorithms, ensuring connectivity and adaptability across various base shapes, including cylinders, triangles, pyramids, and cubes. By employing graph algorithms, our framework enhances the intuitiveness and efficiency of de- sign representation and manipulation, streamlining the design process. The framework generates families of designs that exhibit a wide range of prop- erty magnitudes that can be adjusted intuitively by modifying the input parameters. The rapid design process allows many designs to be generated, offering the user a multitude of solutions around the target property range. The designs can be effectively implemented in various fields and subjected to diverse analytical studies, including static, dynamic, and eigenfrequency assessments. We illustrate computational results for two key properties (stiff- ness and acoustic impedance), showcasing the method’s effectiveness through examples ranging from rod-based to cube-based designs. Here, the framework not only advances metamaterial research but also creates new opportunities for innovation in fields requiring customized material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Towards a fully automated algorithm driven platform for biosystems design

Large-scale data acquisition and analysis are often required in the successful implementation of the design, build, test, and learn (DBTL) cycle in biosystems design. However, it has long been hindered by experimental cost, variability, biases, and missed insights from traditional analysis methods. Here, we report the application of an integrated robotic system coupled with machine learning algorithms to fully automate the DBTL process for biosystems design. As proof of concept, we have demonstrated its capacity by optimizing the lycopene biosynthetic pathway. This fully-automated robotic platform, BioAutomata, evaluates less than 1% of possible variants while outperforming random screening by 77%. A paired predictive model and Bayesian algorithm select experiments which are performed by Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB). BioAutomata excels with black-box optimization problems, where experiments are expensive and noisy and the success of the experiment is not dependent on extensive prior knowledge of biological mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Operator Relaxation and the Optimal Depth of Classical Shadows

Classical shadows are a powerful method for learning many properties of quantum states in a sample-efficient manner, by making use of randomized measurements. Here we study the sample complexity of learning the expectation value of Pauli operators via “shallow shadows,” a recently proposed version of classical shadows in which the randomization step is effected by a local unitary circuit of variable depth t. Here we show that the shadow norm (the quantity controlling the sample complexity) is expressed in terms of properties of the Heisenberg time evolution of operators under the randomizing (“twirling”) circuit—namely the evolution of the weight distribution characterizing the number of sites on which an operator acts nontrivially. For spatially contiguous Pauli operators of weight k, this entails a competition between two processes: operator spreading (whereby the support of an operator grows over time, increasing its weight) and operator relaxation (whereby the bulk of the operator develops an equilibrium density of identity operators, decreasing its weight). From this simple picture we derive (i) an upper bound on the shadow norm which, for depth t~log⁡(k), guarantees an exponential gain in sample complexity over the t=0 protocol in any spatial dimension, and (ii) quantitative results in one dimension within a mean-field approximation, including a universal subleading correction to the optimal depth, found to be in excellent agreement with infinite matrix product state numerical simulations. Our Letter connects fundamental ideas in quantum many-body dynamics to applications in quantum information science, and paves the way to highly optimized protocols for learning different properties of quantum states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Estimating physics models and quantifying their uncertainty using optimization with a Bayesian objective function

This paper reports a verification study for a method that fits functions to sets of data from several experiments simultaneously. The method finds a maximum a posteriori probability (MAP) estimate of a function subject to constraints (e. g., convexity in the study), uncertainty about the estimate, and a quantitative characterization of how data from each experiment constrains that uncertainty. While the present work focuses on a model of the Equation Of State (EOS) of gasses produced by detonating a high explosive, the method can be applied to a wide range of physics processes with either parametric or semi-parametric models. As a verification exercise, a reference EOS is used and artificial experimental data sets are created using numerical integration of ordinary differential equations and pseudo-random noise. The method yields an estimate of the EOS that is close to the reference, and identifies how each experiment most constrains the result.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Tailoring Surface Roughness Using Additive Manufacturing to Improve Internal Cooling

Abstract Surface roughness present on internal cooling channels produced with additive manufacturing has been previously shown to augment heat transfer and pressure loss to levels similar to traditionally cast turbulators. Given the ability of the surface roughness to improve the cooling performance of small cooling channels, the question arises on whether there is an optimal combination of random roughness features to maximize internal cooling performance. To investigate this question, test coupons with different surface roughness morphologies and magnitudes were manufactured by manipulating the parameters in the laser powder bed fusion additive manufacturing process. The coupons were tested to characterize the friction factor and Nusselt number of the cooling channels over a range of Reynolds numbers. Results showed that certain roughness combinations outperformed others, increasing the internal cooling performance of the channels. Additionally, manipulation of the performance using the process parameters allowed for reductions in build time, which could be useful for controlling component cost.

Engineering↗
DOE OSTI2024

FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems

Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs in stochastic diffusion-based graph problems such as influence maximization. These applications heavily rely on BPTs to implement a Monte-Carlo sampling step for their approximations. Given the large sampling complexity, stochasticity of the diffusion process, and the inherent irregularity in real-world graph topologies, efficiently parallelizing these BPTs remains significantly challenging. In this paper, we present a new algorithm to fuse massive number of concurrently executing BPTs with random starts on the input graph. Our algorithm is designed to fuse BPTs by combining separate traversals into a unified frontier on distributed multi-GPU systems. To show the general applicability of the fused BPT technique, we have incorporated it into two state-of-the-art influence maximization parallel implementations (gIM and Ripples). Our experiments on up to 4K nodes of the OLCF Frontier supercomputer (32,768 GPUs and 196K CPU cores) show strong scaling behavior, and that fused BPTs can improve the performance of these implementations up to 34x (for gIM) and ~360x (for Ripples).

Neff, Reece W.↗
DOE OSTI2021

Detecting Arsenic Contamination Using Satellite Imagery and Machine Learning

Arsenic, a potent carcinogen and neurotoxin, affects over 200 million people globally. Current detection methods are laborious, expensive, and unscalable, being difficult to implement in developing regions and during crises such as COVID-19. This study attempts to determine if a relationship exists between soil’s hyperspectral data and arsenic concentration using NASA’s Hyperion satellite. It is the first arsenic study to use satellite-based hyperspectral data and apply a classification approach. Four regression machine learning models are tested to determine this correlation in soil with bare land cover. Raw data are converted to reflectance, problematic atmospheric influences are removed, characteristic wavelengths are selected, and four noise reduction algorithms are tested. The combination of data augmentation, Genetic Algorithm, Second Derivative Transformation, and Random Forest regression (R 2 =0.840 and normalized root mean squared error (re-scaled to [0,1]) = 0.122) shows strong correlation, performing better than past models despite using noisier satellite data (versus lab-processed samples). Three binary classification machine learning models are then applied to identify high-risk shrub-covered regions in ten U.S. states, achieving strong accuracy (=0.693) and F1-score (=0.728). Overall, these results suggest that such a methodology is practical and can provide a sustainable alternative to arsenic contamination detection.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1974

The particle background observed by the X-ray detectors onboard Copernicus

The design and characteristics of low energy detectors on the Copernicus satellite are described. The functions of the sensors in obtaining data on the particle background. The procedure for processing the data obtained by the satellite is examined. The most significant positive deviations are caused by known weak X-ray sources in the field of view. In addition to small systemic effects, occasional random effects where the count rate increases suddenly and decreases within a few frames are analyzed.

Davison, P. J. N.↗
NASA NTRS1977

Satellite Doppler data processing using a microcomputer

A microcomputer which was developed to compute ground radio beacon position locations using satellite measurements of Doppler frequency shift is described. Both the computational algorithms and the microcomputer hardware incorporating these algorithms were discussed. Results are presented where the microcomputer in conjunction with the NIMBUS-6 random access measurement system provides real time calculation of beacon latitude and longitude.

Schmid, P. E.↗
NASA NTRS1980

Digital simulation of dynamic processes in radiometer systems

The development and application of several computer programs for simulating different classes of microwave radiometers are described. The programs are dynamic in nature, and they may be used to determine the instantaneous behavior of system variables as a function of time. Some of the programs employ random variable models in the simulations so that the statistical nature of the results may be investigated. The programs have been developed to utilize either the Continuous System Modeling Program or the Advanced Continuous System Language. The validity of most of the programs was investigated using statistical tests, and the results show excellent correlation with theoretical predictions. The programs are currently being used in the investigation of new design techniques for microwave radiometers.

Stanley, W. D.↗
NASA NTRS1992

Polarimetric remote sensing of sea ice in the Beaufort Sea

Data were collected in March 1988 with the Jet Propulsion Laboratory (JPL) polarimetric airborne synthetic aperture radar (SAR). Full covariance matrices were obtained from the scattering data with proper consideration of the polarimetric calibration. Images were processed to form the sea ice scenes in the Beaufort sea. These scenes contain various ice types including thin ice, thick first-year ice, and multiyear ice. Sea ice was modeled as a layer random medium and the polarimetric backscattering coefficients were calculated under the distorted Born approximation with effective permittivities obtained from the strong fluctuation theory. Sea ice signatures remotely observed by the JPL SAR over the Beaufort sea ice scenes were interpreted by comparing their behavior at different incident angles with results obtained from the theoretical model.

Nghiem, S. V.↗
NASA NTRS1992

SIMBAD quality-control

The astronomical database SIMBAD developed at the Centre de donnees astronomiques de Strasbourg presently contains 760,000 objects (stellar and non-stellar). It has the unique characteristic of being structured specifically for astronomical objects. All types of heterogeneous data (bibliographic references, measurements, and sets of identification) are connected with each object. The attributes that define quality of the database include the following. Reliability: cross-identification should not rely upon just exact values object coordinates. It also means that information attached to one simple object should be consistent. The existing data must be controlled in order to start with a reliable base and to cross-identify new data assuring the quality as data grows. Exhaustivity: delays between publication of new informations and their inclusion in the database should be as short as possible. The integrity of the database has to be maintained as data accumulates. Taking the amount of data into consideration and the rate of new data production, it is necessary to use automatic methods. One of the possibilities is to use multivariate data analysis. The factor-space is a n-dimensional relevancy space which is described by the n-axes representing a set of n subject matter headings; the words and phrases can be used to scale the axes and the documents are then a vector average of the terms within them. The application reported herein is based on the NASA-STI bibliographical database. The selected data concern astronomy, astrophysics, and space radiation (102,963 references from 1975 to 1991 included 8070 keywords). The F-space is built from this bibliographical data. By comparing the F-space position obtained from the NASA-STI keywords with the F-space position obtained from the SIMBAD references, the authors will be able to show whether it is possible to retrieve information with a restricted set of words only. If the comparison is valid, this will be a way to enter bibliographic information in the SIMBAD quality control process. Furthermore, it is possible to connect the physical measurements of stars from SIMBAD to literature concerning these stars from the NASA-STI abstracts. The physical properties of stars (e.g. UBV colors) are not randomly distributed. Stars are distributed among different clusters in a physical parameter space. The authors will show that there are some relations between this classification and the literature concerning these objects clusters in a factor space. They will investigate the nature of the relationship between the SIMBAD measurements and the bibliography. These would be new relationships that are not pre-established by an astronomer. In addition, the bibliography could be neutral information that can be used in combination with the measured parameters.

Lesteven, Soizick↗