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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A dimensionality reduction algorithm for mapping tokamak operational regimes using a variational autoencoder (VAE) neural network

Abstract A variational autoencoder (VAE) is a type of unsupervised neural network which is able to learn meaningful data representations in a reduced dimensional space. We present an application of VAE in identifying the operational stability boundary of tokamak plasma discharges. This model was implemented using a dataset of over 3000 discharges from the high beta tokamak-extended pulse (HBT-EP) device. We found the VAE model to be capable of forming a continuous low-dimensional operational space map and identifying the operational boundaries using a specified warning time window. By projecting the operational parameters onto the same reduced space, this provides an intuitive way for the machine operator or an automated control system to perform disruption avoidance using a relevant control actuator as a discharge approaches a boundary. Pre-programmed GPU control experiments were conducted to demonstrate this control technique using HBT-EP’s saddle control coils as a horizontal position actuator, showing the ability to avoid the oncoming disruptive event and extend the duration of the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Support of the Development of EPP Plus SMT Design Method (FY2020 Test Results)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) analysis and Simplified Model Test (SMT) design methodology continued in FY 2020. The previously developed single-bar SMT (SBSMT) technique was successfully extended to tubular shaped Alloy 617 specimens for evaluation of the effect of primary pressure load on SMT creep-fatigue (CF) properties at 950°C. A series of pressurized SMT tests were performed with various elastic follow-up factors and strain ranges. The results show that the primary pressure load reduces the SMT CF cycles. The reduction of SMT CF life due to primary load was found to be dependent on strain ranges, elastic follow up and test temperatures. These results are crucial for verification of the EPP strain range analysis in the EPP+SMT evaluation procedure. Additionally, hold time effect on the SMT CF life cycles is a determining factor for generating the EPP+SMT CF design curves. Lack of test data in the high cycle and low strain range region results in major uncertainty in developing the design curves. In FY2020, experiments were designed, and testing started on Alloy 617 at 950°C to fill the gap in experimental data. The on-going CF and additional SMT CF with elastic follow-up at low strain ranges will generate the information needed to verify the methods for extrapolation to long hold time and finalize the EPP+SMT design method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Know Your Enemy - Implementation of Bioremediation within a Suspected DNAPL Source Zone Following High-Resolution Site Characterization at Contractors Road Heavy Equipment Area, Kennedy Space Center, Florida

The National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), has adopted high-resolution site characterization (HRSC) sampling techniques during baseline sampling prior to implementation of remedies to confirm and refine the conceptual site model (CSM). HRSC sampling was performed at Contractors Road Heavy Equipment Area (CRHE) prior to bioremediation implementation to verify the extent of the trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) source area (defined as the area with TCE concentrations above 1% solubility) and its daughter product dissolved plume that had been identified during previous HRSC events. The results of HRSC pre-bioremediation implementation sampling suggested that the TCE source area was larger than originally identified during initial site characterization activities, leading to a design refinement to improve electron donor distribution and increase the likelihood of achieving remedial objectives. Approach/Activities: HRSC was conducted from 2009 through 2014 to delineate the vertical and horizontal extent of chlorinated volatile organic compounds (CVOCs) in the groundwater. Approximately 2,340 samples were collected from 363 locations using direct push technology (DPT) groundwater sampling techniques. Samples were collected from up to 14 depth intervals at each location using a 4-foot sampling screen. This HRSC approach identified a narrow (approx. 5 to 30 feet wide), approximately 3,000 square foot TCE DNAPL source area (maximum detected TCE concentration of 160,000 micrograms per liter [micro-g/L] at DPT sampling location DPT0225). Prior to implementation of a bioremediation interim measure, HRSC baseline sampling was conducted using DPT groundwater sampling techniques. Concentrations of TCE were an order of magnitude lower than previous reported (12,000 micro-g/L maximum at DPT sampling location DPT0225) at locations sampled adjacent to previous sampling locations. To further evaluate the variability in concentrations observed additional sampling was conducted in 2016. The results identified higher concentrations than originally detected within the previously defined source area and the presence of source zone concentrations upgradient of the previously defined source area (maximum concentration observed 570,000 micro-g/L). The HRSC baseline sampling data allowed for a revision of the bioremediation design prior to implementation. Bioremediation was implemented within the eastern portion of the source area in November and December 2016 and quarterly performance monitoring was completed in March and June 2017. Reductions in CVOC concentrations from baseline were observed at all performance monitoring wells in the treatment area, and by June 2017, an approximate 95% CVOC mass reduction was observed based on monitoring well sampling results. Results/Lessons Learned: The results of this project suggest that, due to the complexity of DNAPL source zones, HRSC during pre-implementation baseline sampling in the TCE source zone was an essential strategy for verifying the treatment area and depth prior to remedy implementation. If the upgradient source zone mass was not identified prior to bioremediation implementation, the mass would have served as a long-term source for the dissolved plume.

Chrest, Anne↗
DOE OSTI2019

Characterization of Complex Interactions at the Gas–Solid Interface with in Situ Spectroscopy: The Case of Nitrogen-Functionalized Carbon

Interactions at the gas-solid interface drive physicochemical processes in many energy and environmental applications; yet, the challenges associated with characterization and development of these dynamic interactions in complex systems limit progress in developing effective materials. Thus, structure-property-performance correlations greatly depend on the development of advanced techniques and analysis methods for the investigation of gas-solid interactions. In this work, adsorption behavior of O 2 and humidified O 2 on nitrogen-functionalized carbon (N-C) materials was investigated to provide a better understanding of the role of nitrogen species in the oxygen reduction reaction (ORR). N-C materials were produced by solvothermal synthesis and N-ion implantation, resulting in a set of materials with varied nitrogen amount and speciation in carbon matrices with different morphologies. Adsorption behavior of the N-C samples was characterized by in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and ambient pressure X-ray photoelectron spectroscopy (AP-XPS) experiments. A novel analysis approach for the interpretation of AP-XPS data was developed, allowing both the determination of overall adsorption behavior of each N-C material and identification of which nitrogen species were responsible for adsorption. The complementary information provided by in situ DRIFTS and AP-XPS suggests that O 2 adsorption primarily takes place on either electron-rich nitrogen species like pyridine, hydrogenated nitrogen species, or graphitic nitrogen. Adsorption of O 2 and H 2 O occurs competitively on solvothermally prepared N-Cs, whereas adsorption of H 2 O and O 2 occurs at different sites on N-ion implanted N-Cs, highlighting the importance of tuning the composition of N-C materials to promote the most efficient ORR pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Nonlinear proper orthogonal decomposition for convection-dominated flows

Autoencoder techniques find increasingly common use in reduced order modeling as a means to create a latent space. This reduced order representation offers a modular data-driven modeling approach for nonlinear dynamical systems when integrated with a time series predictive model. In this Letter, we put forth a nonlinear proper orthogonal decomposition (POD) framework, which is an end-to-end Galerkin-free model combining autoencoders with long short-term memory networks for dynamics. By eliminating the projection error due to the truncation of Galerkin models, a key enabler of the proposed nonintrusive approach is the kinematic construction of a nonlinear mapping between the full-rank expansion of the POD coefficients and the latent space where the dynamics evolve. We test our framework for model reduction of a convection-dominated system, which is generally challenging for reduced order models. Our approach not only improves the accuracy, but also significantly reduces the computational cost of training and testing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This paper highlights the potential conflict between electricity prices and carbon emissions and the resulting trade-offs in carbon-aware and cost-aware load scheduling. To address this trade-off, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2012

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Diallo, Ousmane H.↗
NASA NTRS2020

Thermal Protection System to Enable Ice Giant Aerocapture Mission for Delivering both an Orbiter and an in situ Probe

Ice Giant Missions launched in the next decade can have significantly reduced trip times by incorporating aerocapture as the primary method for orbit insertion instead of conventional propulsive techniques. Furthermore, a mass-efficient aerocapture system for a Neptune mission also enables the delivery of an orbiter, an atmospheric probe for in situ measurements to anchor global data collected by the orbiter, and possibly a lander at Triton. Aerocapture requires a Thermal Protection System (TPS) for the atmospheric entry, and it needs to be robust and mass efficient due to the size of the aeroshell required and the large heat load. Currently there are capable ablative thermal protection materials available, e.g., HEEET (Heatshield for Extreme Entry Environments Technology) and PICA (Phenolic-Impregnated Carbon Ablator) family. In this white paper, we show that the heat-shield TPS mass fraction can be as low as 5% to as high as 20% depending on total trip time reduction and other parameters. Further mass savings in the thermal protection system can be achieved with the use of conformal PICA, either standalone or in combination with HEEET with detailed design. We advocate the mission designers to consider aerocapture for Ice Giant missions so the science community can confidently consider missions to the Ice Giants to achieve unparalleled science in the coming decade.

E Venkatapathy↗
NASA NTRS2012

On Advanced Estimation Techniques for Exoplanet Detection and Characterization using Ground-based Coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We propose a formal comparison of techniques using a blind data challenge with an evaluation of performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012

coronagraphs↗
DOE OSTI2020

Characterization and differentiation of aluminum powders used in improvised explosive devices – Part 1: Proof of concept of the utility of particle micromorphometry

Abstract Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial‐scale and consumer products, and produced using unsophisticated “kitchen chemistry” techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced “in‐house” from Al‐containing spray paints and ball‐milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z‐focus; 17 size and shape parameters were measured for all particles. Approximately 37,000–2,500,000 particles/sample were analyzed using an open‐source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using “in‐house” methods were analyzed using ANOVA to assess the within‐ and between‐sample variation. High within‐sample variation was noted; however, ANOVA and post‐hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between‐sample variation was substantially larger than the within‐sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within‐sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

Baldaino, JenaMarie↗
NASA NTRS1993

A novel potential/viscous flow coupling technique for computing helicopter flow fields

The primary objective of this work was to demonstrate the feasibility of a new potential/viscous flow coupling procedure for reducing computational effort while maintaining solution accuracy. This closed-loop, overlapped velocity-coupling concept has been developed in a new two-dimensional code, ZAP2D (Zonal Aerodynamics Program - 2D), a three-dimensional code for wing analysis, ZAP3D (Zonal Aerodynamics Program - 3D), and a three-dimensional code for isolated helicopter rotors in hover, ZAPR3D (Zonal Aerodynamics Program for Rotors - 3D). Comparisons with large domain ARC3D solutions and with experimental data for a NACA 0012 airfoil have shown that the required domain size can be reduced to a few tenths of a percent chord for the low Mach and low angle of attack cases and to less than 2-5 chords for the high Mach and high angle of attack cases while maintaining solution accuracies to within a few percent. This represents CPU time reductions by a factor of 2-4 compared with ARC2D. The current ZAP3D calculation for a rectangular plan-form wing of aspect ratio 5 with an outer domain radius of about 1.2 chords represents a speed-up in CPU time over the ARC3D large domain calculation by about a factor of 2.5 while maintaining solution accuracies to within a few percent. A ZAPR3D simulation for a two-bladed rotor in hover with a reduced grid domain of about two chord lengths was able to capture the wake effects and compared accurately with the experimental pressure data. Further development is required in order to substantiate the promise of computational improvements due to the ZAPR3D coupling concept.

Summa, J. Michael↗
NASA NTRSDate not supplied

Durability of Geopolymer Lunar Concrete From Exposure in Low Earth Orbit

Constructing infrastructure autonomously with concrete materials through additive manufacturing techniques on the lunar surface is a feasible option. The environmental and exposure conditions that the lunar concrete material will undergo are more extreme than on Earth and studying the durability aspect is important to scaling up the implementation of such materials. Conditions that the material will be exposed to include a hard vacuum, extreme temperatures, and ultraviolet radiation. To that end, geopolymer lunar concrete and ordinary portland cement paste samples were placed outside the International Space Station (ISS) for an approximate six-month exposure period. The samples were part of the 15th Materials International Space Station Experiment (MISSE-15) mission and were mounted in the zenith direction. After the exposure time, results for the samples exhibited discoloration, microstructural cracking, and an overall reduction in volume compared to data collected beforehand. The intent of this work was to characterize geopolymer lunar concrete durability in terms of the lunar environmental conditions in LEO and potential exposure scenarios from a simulated subscale rocket engine plume. To understand the durability of samples in space environment conditions, samples were placed outside the International Space Station (ISS) for a six-month period on the MISSE-FF. Additionally, to test the material's durability if implemented for use in a landing pad, samples were created for an experiment that mimics the exposure of the material to a rocket engine associated with the human lander system. This work is essential to progressing and scaling up geopolymer lunar concrete for implementation as the material's durability is assessed.

Peter J Collins↗
DOE OSTI2020

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
NASA NTRS1994

Effects of 5 weeks of lower limb suspension on muscle size and strength

Lack of weight-bearing, as occurs in space, appears to be associated with reductions in strength and mass of skeletal muscle. Very limited data, however, is at hand describing changes in skeletal muscle size and function following manned space missions. Our current knowledge therefore is mainly based on studies of space flown rats. It is obvious though that this information, only in part can be extrapolated to humans. A few bed rest studies have demonstrated that decreases in strength and muscle size are substantial. At this time, however, the magnitude or time course of such changes either in response to space flight or simulations of microgravity have not been defined. In the last few years we have employed a human model to simulate unloading of lower limb skeletal muscles that occurs in microgravity. This model was essentially adopted from the rat hindlimb suspension technique. The purpose of this study was to assess the magnitude of decreases in muscle strength and size as a result of five weeks of unilateral lower limb suspension.

Non-NASA Center↗
NASA NTRS1994

High dimensional feature reduction via projection pursuit

The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many more spectral intervals than previously possible. An example of that technology is the AVIRIS system, which collects image data in 220 bands. As a result of this, new algorithms must be developed in order to analyze the more complex data effectively. Data in a high dimensional space presents a substantial challenge, since intuitive concepts valid in a 2-3 dimensional space to not necessarily apply in higher dimensional spaces. For example, high dimensional space is mostly empty. This results from the concentration of data in the corners of hypercubes. Other examples may be cited. Such observations suggest the need to project data to a subspace of a much lower dimension on a problem specific basis in such a manner that information is not lost. Projection Pursuit is a technique that will accomplish such a goal. Since it processes data in lower dimensions, it should avoid many of the difficulties of high dimensional spaces. In this paper, we begin the investigation of some of the properties of Projection Pursuit for this purpose.

Jimenez, Luis↗
DOE OSTI2024

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Adapting In Situ Accelerators for Sparsity With Granular Matrix Reordering

Neural network (NN) inference is an essential part of modern systems and is found at the heart of numerous applications ranging from image recognition to natural language processing. In situ NN accelerators can efficiently perform NN inference using resistive crossbars, which makes them a promising solution to the data movement challenges faced by conventional architectures. Although such accelerators demonstrate significant potential for dense NNs, they often do not benefit from sparse NNs, which contain relatively few non-zero weights. Processing sparse NNs on in situ accelerators results in wasted energy to charge the entire crossbar where most elements are zeros. To address this limitation, this paper proposes Granular Matrix Reordering (GMR): a preprocessing technique that enables an energy-efficient computation of sparse NNs on in situ accelerators. GMR reorders the rows and columns of sparse weight matrices to maximize the crossbars' utilization and minimize the total number of crossbars needed to be charged. The reordering process does not rely on sparsity patterns and incurs no accuracy loss. Finally, GMR achieves an average of 28% and up to 34% reduction in energy consumption over seven pruned NNs across four different pruning methods and network architectures.

97 MATHEMATICS AND COMPUTING↗