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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗
NASA NTRS1984

The crustal tectonics and history of Europa: A structural, morphological, and comparative analysis

An evaluation of surface features and structures on the Galilean moon Europa is made using the available high resolution Voyager imagery, low resolution support imaging, and what understanding of ice structure and mechanical behavior science has that is applicable to the problem. A general discussion of the history of Europa studies and the fundamental global morphology is undertaken. The visible lineament and terrain patterns are described, and possible origins discussed. Observations of faulting and block rotation previously described are amplified. A comparison of Europa's structures to terrestrial sea ice and lava lake crust features is also included. Finally, an attempt is made at synthesizing a unified model for the evolution of Europa's crust is presented which is compared with models developed by others.

Schenk, P. M.↗
NASA NTRS1987

Transparent Analogs for Alloy Phase Studies

Report describes experiments to add information to data base supporting use of transparent, partially miscible liquids and solids as analogs in studies of alloy solidification. Behavior of these materials observed directly while they undergo liquid/liquid and liquid/solid phase transformations. Light-scattering techniques used to determine phase boundaries. Transparent analogs allow observation of both solidification patterns and processes leading to those patterns, whereas metal alloys require tedious post-solidification metallographic analyses because processes not generally observed. Experiments with transparent substances safer and cheaper since conducted at much lower temperatures.

Frazier, D. O.↗
NASA NTRS1987

Investigation of helicopter rotor blade/wake interactive impulsive noise

An analysis of the Tip Aerodynamic/Aeroacoustic Test (TAAT) data was performed to identify possible aerodynamic sources of blade/vortex interaction (BVI) impulsive noise. The identification is based on correlation of measured blade pressure time histories with predicted blade/vortex intersections for the flight condition(s) where impulsive noise was detected. Due to the location of the recording microphones, only noise signatures associated with the advancing blade were available, and the analysis was accordingly restricted to the first and second azimuthal quadrants. The results show that the blade tip region is operating transonically in the azimuthal range where previous BVI experiments indicated the impulsive noise to be. No individual blade/vortex encounter is identifiable in the pressure data; however, there is indication of multiple intersections in the roll-up region which could be the origin of the noise. Discrete blade/vortex encounters are indicated in the second quadrant; however, if impulsive noise were produced here, the directivity pattern would be such that it was not recorded by the microphones. It is demonstrated that the TAAT data base is a valuable resource in the investigation of rotor aerodynamic/aeroacoustic behavior.

Miley, S. J.↗
NASA NTRS1990

Non-Lipschitzian neural dynamics

A novel approach is presented which is motivated by an attempt to remove one of the most fundamental limitations of artificial neural networks: their rigid behavior as compared with even the simplest biological systems. It is demonstrated that non-Lipschitzian dynamics, based on the faliure of the Lipschitz conditions at repellers, displays a new qualitative effect, i.e., a multichoice response to periodic external excitations. This makes it possible to construct unpredictable systems, represented in the form of coupled activation and learning dynamical equations. It is shown that unpredictable systems can be controlled by sign strings which uniquely define the system behavior by specifying the direction of the motions at the critical points. Unpredictable systems driven by sign strings are extremely flexible and can serve as a powerful tool for complex pattern recognition.

Barhen, Jacob↗
NASA NTRS1995

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 45: A comparison of the information-seeking behaviors of three groups of US aerospace engineers

To understand the transfer of scientific and technical information (STI) in aerospace, it is necessary to understand the characteristics and behaviors of those who create and use STI. In this paper, we analyze the similarities and differences in the scientific and technical information-seeking behaviors of three groups of US aerospace engineers and scientists. We describe some of their demographic characteristics and their duties and responsibilities as a method of understanding their STI use patterns. There is considerable diversity among aerospace engineers in their use of STI. In general, engineers engaged in research use more STI than those who are in design/development and manufacturing/production. Research engineers also use different standards to determine the STI sources and products that they will use.

Kennedy, John M.↗
NASA NTRS2002

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗
NASA NTRS2016

Exercise Effects on the Brain and Sensorimotor Function in Bed Rest

Long duration spaceflight microgravity results in cephalad fluid shifts and deficits in posture control and locomotion. Effects of microgravity on sensorimotor function have been investigated on Earth using head down tilt bed rest (HDBR). HDBR serves as a spaceflight analogue because it mimics microgravity in body unloading and bodily fluid shifts. Preliminary results from our prior 70 days HDBR studies showed that HDBR is associated with focal gray matter (GM) changes and gait and balance deficits, as well as changes in brain functional connectivity. In consideration of the health and performance of crewmembers we investigated whether exercise reduces the effects of HDBR on GM, functional connectivity, and motor performance. Numerous studies have shown beneficial effects of exercise on brain health. We therefore hypothesized that an exercise intervention during HDBR could potentially mitigate the effects of HDBR on the central nervous system. Eighteen subjects were assessed before (12 and 7 days), during (7, 30, and ~70 days) and after (8 and 12 days) 70 days of 6-degrees HDBR at the NASA HDBR facility in UTMB, Galveston, TX, US. Each subject was randomly assigned to a control group or one of two exercise groups. Exercise consisted of daily supine exercise which started 20 days before the start of HDBR. The exercise subjects participated either in regular aerobic and resistance exercise (e.g. squat, heel raise, leg press, cycling and treadmill running), or aerobic and resistance exercise using a flywheel apparatus (rowing). Aerobic and resistance exercise intensity in both groups was similar, which is why we collapsed the two exercise groups for the current experiment. During each time point T1-weighted MRI scans and resting state functional connectivity scans were obtained using a 3T Siemens scanner. Focal changes over time in GM density were assessed using voxel based morphometry (VBM8) under SPM. Changes in resting state functional connectivity was assessed using both a region of interest (ROI, or seed-to-voxel) approach as well as a whole brain intrinsic connectivity (i.e., voxel-to-voxel) analysis. For the ROI analysis we selected 11 ROIs of brain regions that are involved in sensorimotor function (i.e., L. Insular C., L. Putamen, R. Premotor C., L.+R. Primary Motor C., R. Vestibular C., L. Posterior Cingulate G., R. Cerebellum Lobule V + VIIIb + Crus I, and the R. Superior Parietal G.) and correlated their time course of brain activation during rest with all other voxels in the brain. The whole brain connectivity analysis tests changes in the strength of the global connectivity pattern between each voxel and the rest of the brain. Functional mobility was assessed using an obstacle course. Vestibular contribution to balance was measured using Neurocom Sensory Organization Test 5. Behavioral measures were assessed pre-HDBR, and 0, 8 and 12 days post-HDBR. Linear mixed models were used to test for effects of time, group, and group-by-time interactions. Family-wise error corrected VBM revealed significantly larger increases in GM volume in the right primary motor cortex in bed rest control subjects than in bed rest exercise subjects. No other significant group by time interactions in gray matter changes with bed rest were observed. Functional connectivity MRI revealed that the increase in connectivity during bed rest of the left putamen with the bilateral midsagittal precunes and the right cingulate gyrus was larger in bed rest control subjects than in bed rest exercise subjects. Furthermore, the increase in functional connectivity with bed rest of the right premotor cortex with the right inferior frontal gyrus and the right primary motor cortex with the bilateral premotor cortex was smaller in bed rest control subjects than in bed rest exercise subjects. Functional mobility performance was less affected by HDBR in exercise subjects than in control subjects and post HDBR exercise subjects recovered faster than control subjects. The group performance differences and GM changes were not related. Exercise in HDBR partially mitigates the adverse effect of HDBR on functional mobility, particularly during the post-bed rest recovery phase. In addition, exercise appears to result in differential brain structural and functional changes in motor regions such as the primary motor cortex, the premotor cortex and the putamen. Whether these central nervous system changes are related to motor behavioral changes including gait and balance warrants further research.

Koppelmans, V.↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗
DOE OSTI2016

Strontium isotope investigation of ungulate movement patterns on the Pleistocene Paleo-Agulhas Plain of the Greater Cape Floristic Region, South Africa

Middle Stone Age sites located within the Greater Cape Floristic Region on the South African southern coast have material culture with early evidence for key modern human behaviors such as projectile weaponry, large animal hunting, and symbolic behavior. In order to interpret how and why these changes evolved, it is necessary to understand their ecological context as it has direct relevance to foraging behavior. During periods of lowered sea level, a largely flat and vast expanse of land existed south of the modern coastline, but it is now submerged by higher sea levels. This exposed area, the Paleo-Agulhas Plain, likely created an ecological context unlike anything in the region today, as evidenced by fossil assemblages dominated by migratory ungulates. One hypothesis is that the Paleo-Agulhas Plain supported a migration ecosystem of large grazers driven by summer rainfall, producing palatable forage during summer in the east, and winter rainfall, producing palatable forage during winter in the west. Furthermore, ungulates may have been moving from the coastal plain in the south to the interior north of the Cape Fold Mountains, as observed for elephants in historic times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Non-Altermagnetic Origin of Exchange Bias Behaviors in Incoherent RuO 2 /Fe Bilayer Heterostructures

Initially identified as a promising altermagnetic (AM) candidate, rutile RuO 2 has since become embroiled in controversy due to contradictory findings of modeling and measurements of the magnetic properties of bulk crystals and thin films. For example, despite observations of a bulk nonmagnetic state using density functional theory, neutron scattering, and muon spin resonance measurements, patterned RuO 2 Hall bars and film heterostructures display magnetotransport signatures of magnetic ordering. Among the characteristics routinely cited as evidence for AM is the observation of exchange bias (EB) in an intimately contacted Fe-based ferromagnetic (FM) layer, which can arise due to interfacial coupling with a compensated antiferromagnet. Here, within this work, the origins of this EB coupling in Ru-capped RuO 2 /Fe bilayers are investigated using polarized neutron diffraction, polarized neutron reflectometry, cross-sectional transmission electron microscopy, and super conducting quantum interference device measurements. These experiments reveal that the EB behavior is driven by the formation of an iron oxide interlayer containing Fe 3 O 4 that undergoes a magnetic transition and pins interfacial moments within Fe at low temperature. These findings are confirmed by comparable measurements of Ni-based heterostructures, which do not display EB coupling, as well as magnetometry of additional Fe/Ru bilayers that display oxide-driven EB coupling despite the absence of the epitaxial RuO 2 layer. While these results do not directly refute the possibility of AM ordering in RuO 2 thin films, they reveal that EB, and related magnetotransport phenomena, cannot alone be considered evidence of this characteristic in the rutile structure due to interfacial chemical disorder.

RuO2↗
DOE OSTI2015

Simultaneous X-ray diffraction and phase-contrast imaging for investigating material deformation mechanisms during high-rate loading

Using a high-speed camera and an intensified charge-coupled device (ICCD), a simultaneous X-ray imaging and diffraction technique has been developed for studying dynamic material behaviors during high-rate tensile loading. A Kolsky tension bar has been used to pull samples at 1000 s -1 and 5000 s -1 strain-rates for super-elastic equiatomic NiTi and 1100-O series aluminium, respectively. By altering the ICCD gating time, temporal resolutions of 100 ps and 3.37 µs have been achieved in capturing the diffraction patterns of interest, thus equating to single-pulse and 22-pulse X-ray exposure. Furthermore, the sample through-thickness deformation process has been simultaneously imaged via phase-contrast imaging. It is also shown that adequate signal-to-noise ratios are achieved for the detected white-beam diffraction patterns, thereby allowing sufficient information to perform quantitative data analysis diffraction via in-house software ( WBXRD_GUI ). Of current interest is the ability to evaluate crystal d -spacing, texture evolution and material phase transitions, all of which will be established from experiments performed at the aforementioned elevated strain-rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Magnetic Properties and Photocatalytic Behavior of Co Co-doped BiFeO{sub 3}:Er

The multiferroic materials Bi{sub 0.95}Er{sub 0.05}Fe{sub 1−x}Co{sub x} O{sub 3} (x = 0, 0.01, 0.03, and 0.05) are synthesized by solvothermal method. X-ray diffraction pattern is used to confirm the formation of rhombohedral crystal structure. TEM images show agglomerated nanosize particles. With the concentration of Co, a red shift is observed in the charge transfer transition of O{sub 2p}-Fe{sub 3d} band and band gap decreases. At higher concentration of Co, the saturation magnetization enhances and coercivity also varies with the concentration of Co. The photocatalytic degradation of methylene blue is evaluated under the visible light with the assistance of H{sub 2}O{sub 2}. With the increase in Co concentration, the photocatalytic activity decreases. The main species responsible for the degradation is found out using scavengers like ammonium oxalate, silver nitrate, p-benzoquinone, and tert-butyl-alcohol. The possible mechanism for the degradation of dye is explained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Effect of annealing time, weight pressure and cobalt doping on the electrical and magnetic behavior of barium titanate

BaTi{sub 0.5}CO{sub 0.5}O{sub 3} (BTCO) nanoparticles were prepared by the solid state reaction technique using different starting materials and the microstructure examined by XRD, FESEM, BDS and VSM. X-ray diffraction and electron diffraction patterns showed that the nanoparticles were the tetragonal BTCO phase. The BTCO nanoparticles prepared from the starting materials of as prepared titanium-oxide, Cobalt -oxide and barium carbonate have spherical grain morphology, an average size of 65 nm and a fairly narrow size distribution. The nano-scale presence and the formation of the tetragonal perovskite phase as well as the crystallinity were detected using the mentioned techniques. Dielectric properties of the samples were measured at different frequencies. Broadband dielectric spectroscopy is applied to investigate the electrical properties of disordered perovskite-like ceramics in a wide temperature range. The doped BTCO samples exhibited low loss factor at 1 kHz and 1 MHz frequencies respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structure, nanomechanics, and dynamics of dispersed surfactant‐free clay nanocomposite films

The current work presents a new approach to achieve high quality dispersion of surfactant‐free nanoclay tactoid particles in sub‐micron thin films despite the absence of organic modifier. Natural Montmorillonite particles, Cloisite, were dispersed in thin films of polycaprolactone (PCL) through a flow coating technique assisted by ultra‐sonication. Wide‐angle X‐ray scattering (WAXS), grazing‐incidence wide‐angle X‐ray scattering (GI‐WAXS), and transmission electron microscopy (TEM) were used to confirm the level of natural clay dispersion down to the level of tactoids (sub‐micron scale stacks of clay sheets). These characterization techniques were carried out in conjunction with an analysis of nanomechanical properties via strain‐induced buckling instability for modulus measurements (SIEBIMM), a high‐throughput technique to characterize thin film mechanical properties. The buckling patterns indicate that the natural clay tactoids separate buckling‐enhancing (high‐modulus) crystalline regions and interconnect buckling‐suppressing amorphous (low‐modulus) regions. Due to the tactoid length scale, the glass transition behavior of the composites as characterized by broadband dielectric relaxation spectroscopy was unmodified by the clay. Likewise, the glass transition temperature, T g , and fragility (slope of relaxation time behavior approaching T g ), remain unaffected, indicating that these dispersed tactoids do not induce pronounced confinement effects on dynamics. POLYM. ENG. SCI., 58:1285–1295, 2018. © 2018 Society of Plastics Engineers

Zhang, Xiao↗
DOE OSTI2019

Electrochemical Investigations of Magnetic Co{sub 3}O{sub 4} Nanoparticles as an Active Electrode for Supercapacitor Applications

This attempt reports on cobalt oxide (Co{sub 3}O{sub 4}) nanoparticles (NPs) prepared through the traditional chemical reflux method to examine the behavior of supercapacitor performance. The synthesized NPs were characterized using several analytical tools such as ultraviolet-visible spectroscopy (UV), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) pattern, and scanning electron microscope (SEM) with energy dispersive X-ray spectroscopy (EDX). Moreover, the electrochemical performance was analyzed using galvanostatic charge and discharge studies (GCD), cyclic voltammetry (CV) studies as well as electrochemical impedance spectroscopy (EIS). The cubical phase of Co{sub 3}O{sub 4} was identified from the XRD pattern and also the average crystalline size was measured by Scherrer’s equation. FTIR confirmed the functional group of Co{sub 3}O{sub 4} NPs. SEM images revealed the hexagonal-shaped nanoflakes-like morphology of the sample. From the elemental analysis, the formation of pure Co{sub 3}O{sub 4} NPs by means of high purity and composition ratio of cobalt with oxygen was found. Vibrating sample magnetometer (VSM) plot scrutinized the magnetic performance of Co{sub 3}O{sub 4} NPs{sub .} The Co{sub 3}O{sub 4} NPs modified electrode has delivered maximum specific capacitance as 1413 Fg{sup −1} at a current density of 1 Ag{sup −1} which maintains tremendous cycling stability within the retention ratio of 98.4% after 1000 cycles. .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Recovering fine details from under-resolved electron tomography data using higher order total variation ℓ 1 regularization

Over the last decade or so, reconstruction methods using ℓ 1 regularization, often categorized as compressed sensing (CS) algorithms, have significantly improved the capabilities of high fidelity imaging in electron tomography. The most popular ℓ 1 regularization approach within electron tomography has been total variation (TV) regularization. In addition to reducing unwanted noise, TV regularization encourages a piecewise constant solution with sparse boundary regions. In this paper we propose an alternative ℓ 1 regularization approach for electron tomography based on higher order total variation (HOTV). Like TV, the HOTV approach promotes solutions with sparse boundary regions. In smooth regions however, the solution is not limited to piecewise constant behavior. We demonstrate that this allows for more accurate reconstruction of a broader class of images – even those for which TV was designed for – particularly when dealing with pragmatic tomographic sampling patterns and very fine image features. In conclusion, we develop results for an electron tomography data set as well as a phantom example, and we also make comparisons with discrete tomography approaches.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗