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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluation of Irradiation Creep Effects in HT9 Cladding for FAST Experiments

The push for advanced reactor fuels for improved reactor safety and efficiency had led to a renewed interest in metallic fuel for nuclear reactor applications. Experimental investigation is necessary to ensure a robust understanding of the thermomechanical properties of new metallic fuel designs. Unfortunately, with the current experimental facilities, thoroughly investigating the responses of metallic fuel burnup would take a prohibitively long time. To alleviate this, the Fission Accelerated Steady State Test (FAST) was developed to accelerate the irradiation testing while simultaneously decreasing the sensitivity to fabrication tolerances by reducing the fuel diameter and scaling the experiment. This method successfully scales the radiation effects on the fuel, but the HT9 cladding is not exposed to prototypic radiation conditions. This raises questions on whether the FAST experiment results are truly indicative of the HT9 cladding performance due to radiation induced creep effects not being appropriately accounted for. Using BISON fuel performance code, the simulated FAST cladding strain is compared to simulated EBR-II cladding strain. This is done through a sensitivity study of input parameters and scaling of neutron fluence on the cladding. This allows a parametric comparison of physical phenomena on the effective difference between cladding strains between FAST and equivalent burnup EBR-II fuel pins. The results show that the irradiation induced deformation (creep or swelling) is insignificant compared to the thermal-mechanical deformation. Therefore, the difference between the FAST experiment cladding and the EBR-II experiment cladding is negligible and comparison of fuel system performance between the two experiments is appropriate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗
DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
NASA NTRS1984

Decimetric type III radio bursts and associated hard X-ray spikes

For a relatively weak solar flare on August 6, 1981, at 10:32 UT, a detailed comparison is made between hard X-ray spikes and decimetric type III radio bursts. The hard X-ray observations are made at energies above 30 keV, and the radio data are obtained in the frequency range from 100 to 1000 MHz. The time resolution for all the data sets is approximately 0.1 s or better. The dynamic radio spectrum exhibits many fast drift type III radio bursts with both normal and reverse slope, whereas the X-ray time profile contains many well resolved short spikes with durations less than or equal to 1 s. Some of the X-ray spikes are seen to be associated in time with reverse-slope bursts, indicating either that the electron beams producing the radio burst contain two or three orders of magnitude more fast electrons than has previously been assumed or that the electron beams can induce the acceleration of additional electrons or occur in coincidence with this acceleration. A case is presented in which a normal slope radio burst at approximately 600 MHz occurs in coincidence with the peak of an X-ray spike to within 0.1 s.

Dennis, B. R.↗
NASA NTRS2005

Observations with NASA's Rossi X-ray Timing Explorer (RXTE)

Over the past decade our understanding of accreting neutron stars has been revolutionized. Observations with NASA's Rossi X-ray Timing Explorer (RXTE) have resulted in the discovery of fast, coherent X-ray intensity oscillations (hereafter, "burst oscillations") during thermonuclear X-ray bursts from 13 low mass X-ray binaries (LMXBs). Although many of their detailed properties remain to be fully understood, it is now beyond doubt that these oscillations result from spin modulation of the thermonuclear burst flux from the neutron star surface. In addition, RXTE observations led to the discovery of the first accreting millisecond pulsars, the sample of which now includes six systems, several of which are in extremely compact binary systems with essentially massive planet companions. These millisecond timing phenomena are providing powerful new probes of the formation, evolution and structure of neutron stars. I will describe recent efforts to constrain neutron star structure using detailed modelling of their properties. I will also discuss what the observed distribution of neutron star spin frequencies is telling us about the torques which may act to limit the ultimate spin up of accreting neutron stars.

Source record↗
DOE OSTI2021

Methodologies for Design, Characterization and Testing of Electrolytes that Enable Extreme Fast Charging of Lithium-ion Cells

Selection, testing and validation of electrolyte candidates for Li-ion cells are discussed, based on a 10-minute target for extreme fast charge (XFC). A combination of modeling and laboratory measurements create a timely and synergistic approach to identifying candidate electrolyte formulations. Multi-solvent systems provide a balanced set of properties, wherein lower molecular-weight solvents offer reduced viscosity, increased species diffusivity, and mitigation of concentration polarization at high charge rates. Carefully selected formulations can exhibit peak conductivity and usable conductivity range of two to three times that of the baseline EC-EMC (3:7, wt.) + LiPF 6 . Candidates are also chosen based on stability and longevity within the cell environment. Lab testing coincides with property predictions from the Advanced Electrolyte Model (AEM) and a macro-scale cell model. Furthermore, cell testing utilized coin and pouch cells having NMC532 or NMC811 cathodes with graphite electrodes. Results indicate combinations of low-molecular weight solvents are key for fast-charge electrolytes as they extend the useful conductivity range to both low and higher salt concentrations, and possess higher self-diffusivities compared to conventional solvents. This reduces impacts from concentration polarization. The choice of electrolyte also influences the tendency for lithium metal deposition at the anode, as showcased by experimental and modeling results herein.

25 ENERGY STORAGE↗
DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1986

Time scale analysis of a digital flight control system

In this paper, consideration is given to the fifth order discrete model of an aircraft (longitudinal) control system which possesses three slow (velocity, pitch angle and altitude) and two fast (angle of attack and pitch angular velocity) modes and exhibits a two-time scale property. Using the recent results of the time scale analysis of discrete control systems, the high-order discrete model is decoupled into low-order slow and fast subsystems. The results of the decoupled system are found to be in excellent agreement with those of the original system.

Naidu, D. S.↗
DOE OSTI2022

Understory plant communities show resistance to drought, hurricanes, and experimental warming in a wet tropical forest

Global climate change has led to rising temperatures and to more frequent and intense climatic events, such as storms and droughts. Changes in climate and disturbance regimes can have non-additive effects on plant communities and result in complicated legacies we have yet to understand. This is especially true for tropical forests, which play a significant role in regulating global climate. We used understory vegetation data from the Tropical Responses to Altered Climate Experiment (TRACE) in Puerto Rico to evaluate how plant communities responded to climate warming and disturbance. The TRACE understory vegetation was exposed to a severe drought (2015), 2 years of experimental warming (4°C above ambient in half of the plots, 2016–2017 and 2018–2019), and two major hurricanes (Irma and María, September 2017). Woody seedlings and saplings were censused yearly from 2015 to 2019, with an additional census in 2015 after the drought ended. We evaluated disturbance-driven changes in species richness, diversity, and composition across ontogeny. We then used Bayesian predictive trait modeling to assess how species responded to disturbance and how this might influence the functional structure of the plant community. Our results show decreased seedling richness after hurricane disturbance, as well as increased sapling richness and diversity after warming. We found a shift in species composition through time for both seedlings and saplings, yet the individual effects of each disturbance were not significant. At both ontogenetic stages, we observed about twice as many species responding to experimental warming as those responding to drought and hurricanes. Predicted changes in functional structure point to disturbance-driven functional shifts toward a mixture of fast-growing and drought-tolerant species. Our findings demonstrate that the tropical forest understory community is more resistant to climatic stressors than expected, especially at the sapling stage. However, early signs of changes in species composition suggest that, in a warming climate with frequent droughts and hurricanes, plant communities might shift over time toward fast-growing or drought-tolerant species.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

GaAs-based photorefractive time-integrating correlator

A potential application of the photorefractive time-integrating correlator is the real-time radar jamming interference rejection system, using the adaptive filter method; a fast photorefractive crystal is needed for adapting a rapidly changing jamming signal. An effort is presently made to demonstrate and characterize a GaAs-based photorefractive time-integrating correlator, since GaAs crystals are 2-3 orders of magnitude faster than most other alternatives.

Liu, Duncan T. H.↗
DOE OSTI2020

Detection Limits and Near‐Field Ground Motions of Fast and Slow Earthquakes

Abstract We investigate theoretical limits to detection of fast and slow seismic events, and spatial variations of ground motion expected from M 6 earthquakes at short epicentral distances. The analyses are based on synthetic velocity seismograms calculated with the discrete wavenumber method assuming seismic velocities and attenuation properties of the crust in Southern California. The examined source properties include different magnitudes ( M −1.0 to M 6.0), static stress drops (0.1–10 MPa), and slow and fast ruptures (0.1–0.9 of shear wave velocity). For the M 6 events we also consider variations in rise times producing crack‐ and pulse‐type events and different rupture directivities. Slow events produce ground motion with considerably lower amplitude than corresponding regular fast earthquakes with the same magnitude, and hence are significantly more difficult to detect. The static stress drop and slip rise time also affect the maximum radiated seismic motion, and hence event detectability. Apart from geometrical factors, the saturation and depletion of seismic ground motion at short epicentral distances stem from radiation pattern, earthquake size (magnitude, stress drop), and rupture directivity. The rupture velocity, rise time, and directivity affect significantly the spatial pattern of the ground motions. The results can help optimizing detection of slow and fast small earthquakes and understand the spatial distribution of ground motion generated by large events.

58 GEOSCIENCES↗
DOE OSTI2022

The potential of caproate (hexanoate) production using Clostridium kluyveri syntrophic cocultures with Clostridium acetobutylicum or Clostridium saccharolyticum

Caproate (hexanoate) and other medium-chain fatty acids are valuable platform chemicals produced by processes utilizing petroleum or plant oil. Clostridium kluyveri , growing on short chain alcohols (notably ethanol) and carboxylic acids (such as acetate) is noted for its ability to perform chain elongation to produce 4- to 8-carbon carboxylates. C. kluyveri has been studied in monoculture and coculture conditions, which lead to relatively modest carboxylate titers after long fermentation times. To assess the biosynthetic potential of C. kluyveri for caproate production from sugars through coculture fermentations, in the absence of monoculture data in the literature suitable for our coculture experiments, we first explored C. kluyveri monocultures. Some monocultures achieved caproate titers of 150 to over 200 mM in 40–50 h with a production rate of 7.9 mM/h. Based on that data, we then explored two novel, syntrophic coculture partners for producing caproate from sugars: Clostridium acetobutylicum and Clostridium saccharolyticum . Neither species has been cocultured with C. kluyveri before, and both demonstrate promising results. Our experiments of C. kluyveri monocultures and C. kluyveri — C. saccharolyticum cocultures demonstrate exceptionally high caproate titers (145–200 mM), fast production rates (3.25–8.1 mM/h), and short fermentation times (18–45 h). These results represent the most caproate produced by a C. kluyveri coculture in the shortest known fermentation time. We also explored the possibility of heterologous cell fusion between the coculture pairs similar to the results seen previously in our group with C. acetobutylicum and Clostridium ljungdahlii. Fusion events were observed only in the C. acetobutylicum — C. kluyveri coculture pair, and we offer an explanation for the lack of fusion between C. saccharolyticum and C. kluyveri . This work supports the promise of coculture biotechnology for sustainable production of caproate and other platform chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fast and accurate simulations of calorimeter showers with normalizing flows

In this study, we introduce caloflow, a fast detector simulation framework based on normalizing flows. For the first time, we demonstrate that normalizing flows can reproduce many-channel calorimeter showers with extremely high fidelity, providing a fresh alternative to computationally expensive geant4 simulations, as well as other state-of-the-art fast simulation frameworks based on generative adversarial networks (GANs) or variational autoencoders (VAEs). In addition to the usual histograms of physical features and images of calorimeter showers, we introduce a new metric for judging the quality of generative modeling: the performance of a classifier trained to differentiate real from generated images. We show that GAN-generated images can be identified by the classifier with nearly 100% accuracy, while images generated from caloflow are better able to fool the classifier. More broadly, normalizing flows offer several advantages compared to other state-of-the-art approaches (GANs and VAEs), including tractable likelihoods, stable and convergent training, and principled model selection. Normalizing flows also provide a bijective mapping between data and the latent space, which could have other applications beyond simulation, for example, to detector unfolding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1995

Nonlinear MHD interactions in some solar coronal structures

The magnetohydrodynamic (MHD) interactions of solar coronal fast shock waves of flare and/or nonflare origin with the boundaries of such structures like the streamer and the coronal hole are considered. These boundaries are treated as MHD tangential discontinuities (TD). Different parameters of the observed corona are used. The general case of oblique interaction is studied. It is shown that a fast shock wave is usually refracted as a fast shock wave inside the coronal streamer. But for a special case of the velocity shear across a TD a slow shock wave may be generated. On the contrary the shock wave is refracted inside the coronal hole, indeed as a slow shock wave. The significance of different effects due to the interaction of fast and slow shock waves with the coronal magnetic field is noticed, especially at the time of coronal mass ejection (CME). Thus slow shock waves may help to 'open' the coronal magnetic field, and fast shock waves - to 'close' it. It is also shown, that an oblique fast MHD coronal shock wave may trigger an instability at the boundary of a streamer considered as a TD. It might have a relation with the observed abrupt process of disappearance of the streamer's boundary in the solar corona.

Grib, S. A.↗
DOE OSTI2024

Seismic monitoring of EGS fracture stimulations at Utah FORGE (Part 1): Time-lapse variations of b-values and Shear-wave Splitting Rates of induced microearthquakes

Characterizing geologic formations near geothermal wells is crucial for efficient extraction of subsurface geothermal energy resources. To monitor effective fracture stimulation of enhanced geothermal systems (EGS), we analyze a catalog of induced microearthquakes to characterize seismicity induced by Phase 2C fracture stimulations of the Utah FORGE project and derive the b-values for 424 induced microearthquakes in three stages of fracture stimulation. Here, we find the time-lapse variations of these b-values. We apply eigenvector rotation and waveform correlation to 3C geophone data to separate fast S 1 and slow S 2 waves, determine their directions, measure their lag time, and calculate the S-wave splitting rate (SSR) for six induced microearthquakes in Stage 1 and 21 in Stage 3. Both SSR values and b-values increase with time. The increase in these values may be related to heavily fractured zones created by fracture stimulations during Stage 2 injections. Large and highly variable SSR values in Stage 3 may reflect heterogeneities in the fracture zones. Time-lapse variations of SSR values and b-values may be one of the most useful approaches to monitoring and characterizing the effectiveness and efficiency of various types of fracture stimulations.

58 GEOSCIENCES↗
NASA NTRS1986

Modular, Fast, Two-Dimensional Cyclic Convolver

Proposed high-throughput, real-time synthetic-aperture-radar (SAR) processor built using new, modular, two-dimensional cyclic convolver architecture based on polynomial factorization and designed for very-large-scale integrated (VLSI) circuitry. New architecture reduces cost, size, and power dissipation of SAR processor in comparison to high-speed array-processor approach. Processor also used for other image-and data-processing applications involving two-dimensional Fourier transforms.

Liu, K. Y.↗
DOE OSTI2021

Interposed pulsed power system for fast separation of radioactive beams

This paper presents the novel design of an interposed pulsed power system, developed to drive a fast-switching magnet with a large multi-mH load inductance, and high field amplitude (> 1 T). This modulator can produce variable flat-top pulses from 1 to 30 ms with rise and fall times of less than 0.5 ms at a variable duty cycle of 3–91% into a heavily inductive load. The system employs a novel over-voltage topology to overcome the inherent inductance and achieve the fast rise and fall times, switching to a precision DC supply to efficiently maintain the flattop without requiring many-kV voltage. We present a power source design consideration, including the results of computer modeling as well as the first experimental results of a modulator scaled test model will also be presented.

47 OTHER INSTRUMENTATION↗