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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Benefit Analysis of Long-Duration Energy Storage in Power Systems with High Renewable Energy Shares

The integration of high shares of variable renewable energy raises challenges for the reliability and cost-effectiveness of power systems. The value of long-duration energy storage, which helps address variability in renewable energy supply across days and seasons, is poised to grow significantly as power systems shift to larger shares of variable generation such as wind and solar. This study explores the system-level services and associated benefits of long-duration energy storage on the 2050 Western Interconnection (WI). The operation of the future WI system with 85% renewable penetration is simulated using a two-stage production cost model. The impact of long duration energy storage on systemwide operations is examined for the 2050 WI system, using a range of round-trip efficiencies corresponding to four different energy storage technologies. The analysis projects the energy storage dispatch profile, system-wide production cost savings (from both diurnal and seasonal operation), and impacts on generation mix, and change in renewable generation curtailment.

25 ENERGY STORAGE↗
DOE OSTI2024

Dual material fused filament fabrication of composite core‐shell structures with improved impact resistance and interfacial adhesion

The mechanical performance of parts produced by fused filament fabrication (FFF) has been limited due to the presence of voids and poor interlayer welding. Recent advancements in FFF have enabled the fabrication of void-free objects with strong interlayer welding through the use of semicrystalline polymer shells such as high-density polyethylene (HDPE) along with a high viscosity core polymer like acrylonitrile-butadiene-styrene (ABS). Furthermore, the zero-shear viscosity (η0) of ABS is three orders of magnitude higher than HDPE making the ABS-HDPE core-shell configuration preferable. ABS holds the shape by preventing bulk flow and part bending while HDPE promotes full surface contact across the layers. Most polymers, however, are immiscible which causes a weak weld line along the core-shell interface. Herein, maleic anhydride (MAH) is grafted to the butadiene segment of the ABS core thereby compatibilizing the interface with HDPE, improving the interfacial adhesion. Attenuated total reflectance-Fourier transform infrared spectroscopy was employed to confirm successful grafting. Using a custom-made die affording the core-shell structure, the ABS-g-MAH is shown to improve the impact resistance by 253% and 16% compared to neat HDPE and ABS specimens, respectively. Additionally, a 10% increase compared to the unmodified ABS-HDPE core-shell configuration is observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impacts of Resolution on Heavy‐Precipitating Storms in Climate Model Hindcasts

The present study investigates the impact of horizontal resolutions on heavy‐precipitating storms using the Energy Exascale Earth System Model version2 (E3SMv2) at low (∼100 km, LR) and high (∼25 km, HR) resolutions through short‐range hindcasts. The short‐range hindcast approach ensures a faithful comparison of model resolution in simulating the same storm events under a controlled large‐scale environment. Using a phenomenon‐based framework, we attribute precipitation to specific storm types: tropical cyclones (TCs), extratropical cyclones, atmospheric rivers, and mesoscale convective systems (MCSs). Our findings show that E3SM hindcasts with both HR and LR configurations significantly underestimate storm‐associated precipitation intensity but overestimate precipitation from other sources. Furthermore, both HR and LR hindcasts face significant challenges in accurately simulating extreme precipitation events, particularly over MCS hotspots. Nevertheless, HR simulations capture more detailed and intense precipitation patterns with an improved representation of storm dynamics. HR hindcasts produce 16% more storm precipitation compared to LR. For precipitation extremes, HR simulates a 33% higher 99th percentile precipitation magnitudes compared to LR, and most of the increment comes from these four heavy‐precipitating storm types. The increase in precipitation mainly comes from stratiform precipitation rather than convective precipitation. The improvement in HR simulations varies across different storm types with TC showing the largest improvement. The phenomenon‐based approach provides important insights into precipitation simulations especially for extremes. Our results emphasize the need for further refinement in high‐resolution models to improve the accuracy of precipitation predictions, which is crucial for better understanding and mitigating climate change impacts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Landing impact studies of a 0.3-scale model air cushion landing system for a Navy fighter airplane

An experimental study was conducted in order to determine the landing-impact behavior of a 0.3-scale, dynamically (but not physically) similar model of a high-density Navy fighter equipped with an air cushion landing system. The model was tested over a range of landing contact attitudes at high forward speeds and sink rates on a specialized test fixture at the Langley aircraft landing loads and traction facility. The investigation indicated that vertical acceleration at landing impact was highly dependent on the pitch angle at ground contact, the higher acceleration of approximately 5g occurring near zero body-pitch attitude. A limited number of low-speed taxi tests were made in order to determine model stability characteristics. The model was found to have good pitch-damping characteristics but stability in roll was marginal.

Leland, T. J. W.↗
NASA NTRS1977

A prediction model to forecast the cost impact from a break in the production schedule

The losses which are experienced after a break or stoppage in sequence of a production cycle portends an extremely complex situation and involves numerous variables, some of uncertain quantity and quality. There are no discrete formulas to define the losses during a gap in production. The techniques which are employed are therefore related to a prediction or forecast of the losses that take place, based on the conditions which exist in the production environment. Such parameters as learning curve slope, number of predecessor units, and length of time the production sequence is halted are utilized in formulating a prediction model. The pertinent current publications related to this subject are few in number, but are reviewed to provide an understanding of the problem. Example problems are illustrated together with appropriate trend curves to show the approach. Solved problems are also given to show the application of the models to actual cases or production breaks in the real world.

Delionback, L. M.↗
DOE OSTI2023

ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites

Zeolites are one of the most widely used materials in the chemical industry due to their nanometer-sized pores that can adsorb and react upon molecules selectively. With hundreds of known framework topologies and hundreds of thousands of computationally predicted structures, the ability to rapidly predict zeolite performance allows researchers to prioritize their efforts on the most promising structures for a given application. Although the accuracy of forcefield-based atomistic simulations has advanced significantly in the past two decades, these simulations can be computationally expensive, especially for long-chain, complex molecules. Here, we present ZeoNet, a representation learning framework using convolutional neural networks (ConvNets) and 3D volumetric representations for predicting adsorption in zeolites. ZeoNet was trained on the task of predicting Henry's constants for adsorption, k H , of n-octadecane in more than 330 000 known and predicted zeolite materials. Employing a 3D grid based on the distances to solvent-accessible surfaces, a volumetric representation that can be generated efficiently, the best-performing ZeoNet achieved a correlation coefficient r 2 = 0.977 and a mean-squared error MSE = 3.8 in ln k H , which corresponds to an error of 9.3 kJ mol -1 in adsorption free energy. In comparison, a model based on hand-designed geometric features has values of r 2 = 0.783 and MSE = 35.7. ZeoNet is also relatively efficient and can process ≈8 structures per second on an Nvidia RTX 2080TI GPU, orders of magnitude faster than forcefield-based simulations. A systematic analysis was conducted to investigate how the choice of ConvNet architectures, the linear dimension (L) and spatial resolution (Δd) of the distance grids, batch size, optimizer, and learning rate impact the model performance. We found that ConvNets based on the ResNet architecture offer the best tradeoff between expressiveness and efficiency. The performance for all models reaches a plateau at L = 30–45 Å and depends less sensitively on grid resolution, with a small benefit around Δd = 0.30–0.45 Å. Finally, saliency maps were visualized to identify which regions of the materials contributed the most to model predictions. It was found, interestingly, that the predictions are driven primarily by the accessible pore volume rather than the region occupied by the framework atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Previous efforts to model uranyl fluoride formation in an impinging jet gas reactor underpredicted spatial mixing and overpredicted chemical conversion into particulates. The previous fluid dynamics model was based on the solution of the Reynolds Averaged Navier Stokes equations. After simulating fluid dynamics, aerosol dynamics were superimposed onto CFD-simulated gas reactant species concentrations. The current work explores the influence of complex unsteady flow features on the overall flow physics and chemistry for a low Reynolds number, opposed flow, impinging jet gas reactor where there is a low Reynolds number cross flow. The objective of this study was to assess the impact of model formulation on scalar mixing and transport. Here, transient flow simulations were performed using Scale Resolving Simulations. Large-Eddy Simulations with the dynamic Smagorinsky turbulence model were performed along with simulations which directly resolved the flow. Average and root-mean-square (RMS) velocities and species concentrations were computed along with modeled and resolved turbulence kinetic energy (TKE), modeled turbulence dissipation, and modeled turbulent viscosity. Lagrangian flow tracers were also used to quantify species concentrations along path lines emanating from the jet tips. Transient simulation data were compared to results from RANS simulations using the k-ω shear stress transport (SST) model and Reynolds Stress Model (RSM). Transient simulations showed spatial mixing patterns which were more consistent with experimental data and helped elucidate the process of particle formation observed in experiments.

42 ENGINEERING↗
DOE OSTI2022

DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware

Spiking Neural Networks (SNNs) are an emerging computation model that uses event-driven activation and bio-inspired learning algorithms. SNN-based machine learning programs are typically executed on tile-based neuromorphic hardware platforms, where each tile consists of a computation unit called a crossbar, which maps neurons and synapses of the program. However, synthesizing such programs on an off-the-shelf neuromorphic hardware is challenging. This is because of the inherent resource and latency limitations of the hardware, which impact both model performance, e.g., accuracy, and hardware performance, e.g., throughput. We propose DFSynthesizer, an end-to-end framework for synthesizing SNN-based machine learning programs to neuromorphic hardware. The proposed framework works in four steps. First, it analyzes a machine learning program and generates SNN workload using representative data. Second, it partitions the SNN workload and generates clusters that fit on crossbars of the target neuromorphic hardware. Third, it exploits the rich semantics of the Synchronous Dataflow Graph (SDFG) to represent a clustered SNN program, allowing for performance analysis in terms of key hardware constraints such as number of crossbars, dimension of each crossbar, buffer space on tiles, and tile communication bandwidth. Finally, it uses a novel scheduling algorithm to execute clusters on crossbars of the hardware, guaranteeing hardware performance. We evaluate DFSynthesizer with 10 commonly used machine learning programs. Our results demonstrate that DFSynthesizer provides a much tighter performance guarantee compared to current mapping approaches.

Computer Science↗
NASA NTRS1982

Impact into the earth's ocean floor - Preliminary experiments, a planetary model, and possibilities for detection

Impact processes and plate tectonics are invoked in an experimental study of craters larger than 100 km in diameter on the ocean floor. Although the results obtained from 22-caliber (383 m/sec) ammunition experiments using dense, saturated sand as a target medium cannot be directly scaled to large events, the phenomenology exhibited is that expected of actual craters on the ocean floor: steep, mixed ejecta plume, gravitational adjustment of the crater to form a shallow basin, and extensive reworking of the ejecta, rim, and floor materials by violent collapse of the transient water cavity. Excavation into the mantle is predicted, although asthenospheric influence on outer ring formation is not. The clearest geophysical signature of such a crater is not topography; detection should instead be based on gravity and geoid anomalies due to uplift of the Moho, magnetic anomalies, and seismic resolution of the Moho uplift and crater formation fault planes.

Mckinnon, W. B.↗
NASA NTRS1978

Modeling of thruster and solar array characteristics in the JPL low-thrust trajectory analysis

Recent advances in thruster and solar array technology have resulted in the possibility of performing many high energy space missions previously considered infeasible. This capability was demonstrated by an extensive study last year of a comet Halley rendezvous mission. In order to perform this extremely high energy mission, several advanced concepts in electric propulsion technology were investigated; notably the use of very high power, lightweight solar arrays which directly powered the beam supply of the electric propulsion thrusters, and the use of solar concentrators on the arrays together with conventional thrusters and power processors. These technology advances have directly impacted the modeling of the solar arrays and thrusters in the programs used in generating low-thrust trajectories. The intent of this paper is to discuss the modeling of the solar arrays and thrusters as employed in the trajectory programs presently being used in low-thrust mission studies at JPL.

Sauer, C. G., Jr.↗
DOE OSTI2023

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗
NASA NTRS1997

The Cretaceous-Tertiary Impact Crater and the Cosmic Projectile that Produced it

Evidence gathered to date from topographic data, geophysical data, well logs, and drill-core samples indicates that the buried Chicxulub basin, the source crater for the approximately 65 Ma Cretaceous-Tertiary (K/T) boundary deposits, is approximately 300 km in diameter. A prominent topographic ridge and a ring of gravity anomalies mark the position of the basin rim at approximately 150 km from the center. Wells in this region recovered thick sequences of impact-generated breccias at 200-300 m below present sea level. Inside the rim, which has been severely modified by erosion following impact, the subsurface basin continues to deepen until near the center it is approximately 1 km deep. The best planetary analog for this crater appears to be the 270 km-diameter Mead basin on Venus. Seismic reflection data indicate that the central zone of downward displacement and excavation (the transient crater is approximately 130 km in diameter, consistent with previous studies of gravity anomaly data). Our analysis of projectile characteristics utilizes this information, coupled with conventional scaling relationships, and geochemical constraints on the mass of extraterrestrial material deposited within the K/T boundary layer. Results indicate that the Chicxulub crater would most likely be formed by a long-period comet composed primarily of nonsilicate materials (ice, hydrocarbons, etc.) and subordinate amounts (less than or equal to 50 percent) primitive chondritic material. This collision would have released the energy equivalent to between 4 x 10(exp 8) and 4 x 10(exp 9) megatons of TNT. Studies of terrestrial impact rates suggest that such an event would have a mean production rate of approximately 1.25 x 10(exp -9) y(exp -1). This rate is considerably lower than that of the major mass extinctions over the last 250 million years (approximately 5 x 10(exp -7) y(exp -1). Consequently, while there is substantial circumstantial evidence establishing the cause-effect link between the Chicxulub basin forming event and the K/T biological extinctions, the results of our analysis do not support models of impact as a common or singular causative agent of mass extinctions on Earth.

Sharpton, Virgil L.↗
NASA NTRS1998

Tests of the Giant Impact Hypothesis

The giant impact hypothesis has gained popularity as a means of explaining a volatile-depleted Moon that still has a chemical affinity to the Earth. As Taylor's Axiom decrees, the best models of lunar origin are testable, but this is difficult with the giant impact model. The energy associated with the impact would be sufficient to totally melt and partially vaporize the Earth. And this means that there should he no geological vestige of Barber times. Accordingly, it is important to devise tests that may be used to evaluate the giant impact hypothesis. Three such tests are discussed here. None of these is supportive of the giant impact model, but neither do they disprove it.

Jones, J. H.↗
NASA NTRS2013

The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

trajectory prediction uncertainty↗
DOE OSTI2023

Euler–Lagrange stochastic modeling of droplet breakup and impact in supersonic flight

Blunt bodied aircraft traveling supersonically in weather environments may be damaged by impacts with water droplets and other airborne particles, such as snow and ice. Prior to an impact, these particles will encounter a bow shock that causes a discontinuity in their relative velocity with the gas phase, which can lead droplets to breakup into smaller droplets. These smaller droplets are more easily diverted from colliding with the blunt body due to their significantly reduced inertia relative to the initial rain droplets. One-way coupled Euler–Lagrange simulations are used to study the dynamics of droplets approaching a blunt body in steady two dimensional and axi-symmetric flow fields using a stochastic version of the Taylor analogy breakup model for the breakup dynamics. Ultimately, the dominant mechanism determining engineering quantities of interest was observed to be a competition between breakup time and the time available for a droplet to reach the body after encountering the bow shock. At Mach numbers 2, 3, and 6, the competition between these mechanisms was the dominant factor determining the momentum transfer to the blunt body via droplet collisions, which can be well characterized by a scaling relation.

Briney, Sam (ORCID:0000000179061081)↗
DOE OSTI2024

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Effects of surface runoff and infiltration partition methods on hydrological modeling: A comparison of four schemes in two watersheds in the Northeastern US

The ratio according to which the precipitation/snowmelt is divided into surface and subsurface water is of primary importance to watershed scale hydrological modeling. The present study compared four different surface runoff and infiltration partition methods in the Richards-equation-based SWAT model (RSWAT), i.e., daily curve number method (DC-RSWAT), hourly curve number method (HC-RSWAT), Green-Ampt method (GA-RSWAT), and effective infiltration capacity method (EIC-RSWAT). These four versions of RSWAT and a daily-curve-number-based SWAT (DC-SWAT) were used to simulate daily flow rate (from 2001 to 2015) at the outlets of the Tuckahoe Creek Watershed (TCW) and Greensboro Watershed (GW) of the Chesapeake Bay in Maryland. Parameter sensitivity analysis, calibration, and prediction uncertainty analysis were conducted. The results indicate that surface runoff and infiltration partition methods have pronounced impacts on model performance. Comparative analysis showed that DC-RSWAT outperformed other versions of RSWAT for both calibration (from 2001 to2007) and validation (from 2008 to 2015) periods in the two test watersheds. In general, DC-RSWAT achieved more accurate deterministic flow simulation and reliable uncertainty estimation than other versions. As such, daily-curve-number method is recommended for surface runoff and infiltration partition in RSWAT for simulating stream flow.

hydrology, modeling, streamflow↗
NASA NTRS1998

Fifteen Years of Laboratory Astrophysics at Ames

Tremendous strides have been made in our understanding of interstellar material over the past fifteen years thanks to significant, parallel developments in two closely related areas: observational astronomy and laboratory astrophysics. Fifteen years ago the composition of interstellar dust was largely guessed at, the concept of ices in dense molecular clouds ignored, and the notion of large, abundant, gas phase, carbon-rich molecules widespread throughout the interstellar medium (ISM) considered impossible. Today the composition of dust in the diffuse ISM is reasonably well constrained to cold refractory materials comprised of amorphous and crystalline silicates mixed with an amorphous carbonaceous material containing aromatic structural units and short, branched aliphatic chains. In the dense ISM, these cold dust particles are coated with mixed-molecular ices whose compositions are very well known. Lastly, the signature of carbon-rich polycyclic aromatic hydrocarbons (PAHs), shockingly large molecules by early interstellar chemistry standards, is widespread throughout the ISM. This great progress has only been made possible by the close collaboration of laboratory experimentalists with observers and theoreticians, all with the goal of applying their skills to astrophysical problems of direct interest to NASA programs. Such highly interdisciplinary collaborations ensure fundamental, in depth coverage of the wide-ranging challenges posed by astrophysics. These challenges include designing astrophysically focused experiments and data analysis, tightly coupled with astrophysical searches spanning 2 orders of magnitude in wavelength, and detailed theoretical modeling. The impact of our laboratory has been particularly effective as there is constant cross-talk and feedback between quantum theorists; theoretical astrophysicists and chemists; experimental physicists; organic, physical and petroleum chemists; and infrared and UV/Vis astronomers. In this paper, two examples of the Ames Program will be given. We have been involved in identifying 9 out of the 14 interstellar pre-cometary ice species known, determined their abundances and the physical nature of the ice structure. Details on our ice work are given in the paper by Sandford et al. Our group is among the pioneers of the PAH model. We built the theoretical framework, participated in the observations and developed the experimental techniques needed to test the model. We demonstrated that the ubiquitous infrared emission spectrum associated with many interstellar objects can be matched by laboratory spectra of neutral and positively charged PAHs and that PAHs were excellent candidates for the diffuse interstellar band (DIB) carriers. See Salama et al. and Hudgins et al.

Allamandola, L. J.↗