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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Raman Response in the Nematic Phase of FeSe

Raman experiments on bulk FeSe revealed that the low-frequency part of the B 1g Raman response R B1 g (Ω), which probes nematic fluctuations, rapidly decreases below the nematic transition at T n ~ 85 K. Such behavior is expected when a gap opens up and at a first glance is inconsistent with the fact that FeSe remains a metal below Tn. We argue that the drop of R B1 g (Ω) can be ascribed to the fact that the nematic order drastically changes the orbital content of low-energy excitations near hole and electron pockets, making them nearly mono-orbital. In this situation, the B 1g Raman response gets reduced by the same vertex corrections that enforce charge conservation in the symmetric Raman channel. The reduction holds at low frequencies and gives rise to gaplike behavior of R B1 g (Ω). Here, we also show that the enhancement of the B 1g Raman response near T n is consistent with the sign change of the nematic order parameter between hole and electron pockets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Quantum Simulation for High-Energy Physics

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in quantum information sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This Roadmap is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles

Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils’ inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗
DOE OSTI2023

ERSAP: Toward Better NP Data-Stream Analytics With Flow-Based Programming

This paper presents an reactive, actor-model and FBP paradigm based framework that we develop to design data-stream processing applications for HEP and NP. This framework encourages a functional decomposition of the overall data processing application into small mono-functional artifacts. Artifacts that are easy to understand, develop, deploy and debug. The fact that these artifacts (actors) are programmatically independent they can be scaled and optimized independently, which is impossible to do for components of the monolithic application. One of the important advantages of this approach is fault tolerance where independent actors can come and go on the data-stream without forcing the entire application to crash. Furthermore, it also makes it is easy to locate the faulty actor in the data pipeline. Due the fact that the actors are loosely coupled, and that the data (inevitably) carries the context, they can run on heterogeneous environments, utilizing different accelerators. This paper describes the main design concepts of the framework and presents a ?proof of concept? application design and deployment results obtain processing on-beam calorimeter streaming data.

Gyurjyan, V.↗
DOE OSTI2022

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Significance of the Direct Excitation Mechanism for High-Frequency Response of Premixed Flames to Flow Oscillations

Premixed flames are sensitive to flow disturbances, which can arise from acoustic or vortical fluctuations. For transverse instabilities, it is known that a dominant mechanism for flame response is “injector coupling,” whereby pressure oscillations associated with transverse waves excite axial flow disturbances. These axial flow disturbances then excite heat release oscillations. The objective of this paper is to consider another mechanism—the direct sensitivity of the unsteady heat release to transverse acoustic waves—and to compare its significance relative to the induced axial disturbances, in a linear framework. The rate at which the flame adds energy to the disturbance field is quantified using the Rayleigh criterion and evaluated over a range of control parameters, such as flame length and swirl number. The results show that radial modes induce heat release fluctuations that always add energy to the acoustic field, whereas heat release fluctuations induced by mixed radial-azimuthal modes can add or remove energy. These amplification rates are then compared to the flame response from induced axial fluctuations. For combustor-centered flames, these results show that the direct excitation mechanism has negligible amplification rates relative to the induced axial mechanism for radial modes. For transverse modes, the fact that the nozzle is located at a pressure node indicates that negligible induced axial velocity disturbances are excited; as such, the direct mechanism dominates. As a result, for flames that are not centered on pressure nodes, the direct mechanism for mixed modes dominates for certain nozzle locations and flame angles.

42 ENGINEERING↗
DOE OSTI2023

Reman Co-Design: A Combined Design and Remanufacturing Optimization Framework for the Sustainable Design of High-Value Components

Remanufacturing is a process that returns end-of-life equipment to as-new conditions and offers numerous environmental and economic benefits. To fully capitalize on remanufacturing, its synergistic interactions with design must be fully realized and addressed during the design stage. Although this fact is widely recognized in the literature, most of the current studies focus primarily either on the design or remanufacturing aspects of design for remanufacturing (DfRem). In an effort to offer a more integrated DfRem approach than those reported in the literature, we propose a new combined design and remanufacturing optimization (reman co-design) framework that takes a holistic approach by leveraging the intricate interplay between design and remanufacturing. Here, the aim of this formulation is to identify the optimal decisions that maximize the benefits of remanufacturing throughout the entire lifespan of a product. To showcase the utility of the new formulation, we are using a case study of a hydraulic manifold, (re)manufactured by John Deere. Using this industry example, we compare the results of reman co-design to the ones from a decoupled remanufacturing design approach. Results reveal that remanufacturing benefits are better realized and improved upon when using the developed reman co-design approach.

design for X↗
DOE OSTI2024

Optimal spectral resolution for solids and liquids using FT and other infrared spectrometers: How much resolution do you really need?

In this study we investigate the possibility of using spectral resolutions for infrared measurements of solids and liquids that are not powers of two, e.g. are not at 1, 2, 4, 8, or 16 cm-1 resolution. In almost all reported literature of the last fifty years the resolution used to record for a Fourier transform infrared spectrum has been a power of two. This stems from the fact that 1) the Cooley-Tukey algorithm used to compute such a transform was constructed to use only powers of two and was also driven by 2) the fact that the computing horsepower required to compute the Fourier transform increases as N?log?_2 (N), where N is the number of points in the interferogram (spectrum). For typical spectra, however, the CPU time is no longer a consideration. Our study is based on both liquid and solid spectra, all of which were recorded at 2 cm-1 resolution. There were at total of 70 solids spectra representing 2,472 spectral peaks and 61 liquids spectra (1,765 spectral peaks), each peak being inspected for being singlet / multiplet in nature. Of the 1,765 liquid bands examined, only 27 had widths less than 5 cm-1. Of the 2,472 solid bands examined, only 39 peaks have widths less than 5 cm-1. For liquids, the mean peak width is 24.7 cm-1 but the median peak width is 13.7 cm-1, and, similarly, for solids, the mean peak width is 22.2 cm-1 but the median peak width is 11.2 cm-1. In both cases, solids and liquids, a skewed peak widths distribution was observed, the peak of the distribution representing narrower bands in the 7 to 9 cm-1 FWHM range but displaying a long tail to the very broad bands, with some displaying spectral widths of 100 cm-1 or more. Because one of the most important criteria for successful instrumental design in IR spectroscopy is the spectral resolution, the data were further analyzed showing that a value to resolve 95% of all bands is 5.7 cm-1 for liquids and 5.3 cm-1 for solids; such a resolution would capture the native linewidth (no instrumental broadening) of 95% of all the solids and liquid bands, respectively. Based on the present results we suggest that, when accounting only for intrinsic linewidths an optimized resolution of 6.0 cm-1 will capture 91% of all condensed-phase bands for IR detection of chemical, mineral, and biological materials.

Forland, Brenda M.↗
DOE OSTI2026

Contrasting effects of glutamate and branched-chain amino acid metabolism on acid tolerance in a Castellaniella isolate from acidic groundwater

Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Concepts for Neutrino Applications

Will neutrinos find uses outside basic science? It may be too early to say, but neutrino physicists have already imagined a variety of possibilities from the relatively modest to the more blue-sky. In this review, we survey the range of proposed applications, most involving nuclear reactors and other fission sources. We give special attention to the most recent proposals, including verifying submarine reactor integrity, safeguarding advanced nuclear power plants, and monitoring spent nuclear fuel. All of these concepts take advantage of the fact that neutrinos pass through barriers other signals cannot penetrate. That same fact creates the central challenge for neutrino applications: the size and complexity of detectors needed to collect a signal. Although the weakly interacting nature of neutrinos makes them fundamentally difficult to use, developments in detector technology are making some ideas more feasible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The phylogenetic roots of addiction: compulsive drug seeking, natural and drug-sensitive reward, and the acquisition of learned habits

Our rational faculties permit us humans to maximize the utility of our actions. We perform a fundamental type of cost-benefit analysis in which we frame a problem, assign values to the different paths, and then choose from among a set of available options, the course that promises the most favorable outcome. So why then does addiction appear to be so impervious to the associated costs, so unaffected by undesired consequences, and ultimately so resistant to cognitive oversight? The answer may likely be found in the fact that the drivers for compulsive drug seeking and drug taking are located in affective brain circuits, circuits that are structured and patterned by learning with repeated activation. These deep processes exhibit significant resistance to control by our cognitive faculties. The general consensus is that addiction arises from mechanisms that overvalue the magnitude of reward, discount the associated risks, and thereby bias individuals towards compulsive pursuit of addictive drugs. Behavioral disruption and dependence appear to arise at the intersection of a number of connected but separate phenomena: expectations for the occurrence of specific events, behaviors that seek encounters with them, the ability to notice and learn nonrandom, co-occurring conditions, the prediction and valuation of consequences, the forming of enduring memories, and the drivers of focused behavior through compulsion, habits, and acquired routines. It is important to recognize that each one of these individual faculties are present and well developed across the entire phylogenetic tree of bilateral metazoans. The goal of this special volume is dedicated to exploring the degree to which inherent elements can account for addiction and addiction-associated phenomena. In much of the literature on addiction, the underlying processes are often viewed as distinctly mammalian, arising, in part, from the strong cognitive capacities of this taxon. Some phenomena may even be regarded to exist only in primates, or even solely in humans. This supposition arises from the fact that studies are conducted almost exclusively in mammals and primates, while evolutionary antecedents of the behavior are rarely considered. A more comprehensive perspective that examines drug reward and reinforcement in a wider range of organisms demonstrates that many of the component traits are actually well developed across the greater metazoan lineage, and they may well predate the emergence of a mammalian clade by a wide margin. The collection of papers assembled here supports the notion that the capacity to associate cues and quences has not arisen in mammals de novo. Rather, the neural mechanisms for detecting contingencies and for predicting future outcomes are very deeply rooted across broad phylogenetic divisions. Our understanding of an ability to associate paired events has been enriched by work in invertebrate preparations in both classical and operant conditioning scenarios [Cook and Carew, 1986, 1989a, 1989b]. The ability to learn allows us to connect cues and behavioral actions to their associated consequences. Pavlovian conditioning enriches surrounding cues with predictive value. Outcomes with positive valence generate appetitive responses and approach to the associated cues, while those perceived as aversive bring cue avoidance and withdrawal. Humans are not the only life forms capable of such short- and long-term modulations of behavior

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Convective and Turbulent Motions in Nonprecipitating Cu. Part III: Characteristics of Turbulence Motions

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the -11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov -5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm 2 s -3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m 2 s -1 near cloud base to 25 m 2 s -1 near cloud top. In conclusion, the possible role of turbulence in the process of lateral entrainment and mixing is discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fast truncated SVD of sparse and dense matrices on graphics processors

We investigate the solution of low-rank matrix approximation problems using the truncated singular value decomposition (SVD). For this purpose, we develop and optimize graphics processing unit (GPU) implementations for the randomized SVD and a blocked variant of the Lanczos approach. Our work takes advantage of the fact that the two methods are composed of very similar linear algebra building blocks, which can be assembled using numerical kernels from existing high-performance linear algebra libraries. Furthermore, the experiments with several sparse matrices arising in representative real-world applications and synthetic dense test matrices reveal a performance advantage of the block Lanczos algorithm when targeting the same approximation accuracy.

Computer Science↗
DOE OSTI2026

Data for FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Genomics↗
DOE OSTI2020

Tracking the SARS-CoV-2 Epidemic Using the Evolutionary Rate

This project aimed to track the developing COVID-19 epidemic through measuring the virus evolutionary rate. This may give us a way to estimate the impact of prevention campaigns and other changes in the epidemiology that we otherwise would have difficulty to estimate. Based on our previous knowledge of how viruses are affected by their environment, we investigated how spread and prevention measures may affect the virus evolutionary rate. We found that SARS-CoV-2, which causes the COVID-19 epidemic, evolves relatively slow as compared to other RNA viruses. Thus, this makes it hard to see rate changes and track the spread at a fine scale. This did in fact mislead several high-profile reports in the early phases of the epidemic. We published comments and editorials in leading journals on this. Because the COVID-19 epidemic is till ongoing, and much data is still incoming, it is likely that evolutionary-epidemiological analyses will reveal important facts later on.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Improved Understanding of Zircaloy Hydrogen Pickup Mechanisms in BWRs. NSUF Report (Final Report)

Using an instrumented autoclave operating at 288°C and 1100 psi, electrical impedance spectroscopy (EIS) measurements were taken from three neutron irradiated fuel channel samples (Zircaloy-2 and Zircaloy-4). The three high priority fuel channel samples were tested at 288°C using a simulated PWR water with the AC frequency range extending down through 10 -4 Hz, with corresponding DC measurements to validate the resistance measurements. EIS measurements were also taken at room temperature using a simulated PWR water from four neutron irradiated fuel channel samples (Zircaloy-2 and Zircaloy-4). and four water rod samples (Zircaloy-2). EIS measurements were also performed on unirradiated Zircaloy-2 tubes that were previously oxidized in autoclaves at various temperatures for different time durations to obtain oxide layers of different thicknesses. These experiments proved to be more challenging than anticipated because of the small size of the samples, which required development of fixtures to allow valid testing of the materials, some of which are radioactive, under pressure and temperature. Equivalent circuits were used to model the data. Some samples resulted in Nyquist plots where the arcs were too close to each other resulting in the inability to separate the different oxide morphological thicknesses. Microstructural characterization in the form of optical microscopy, scanning electron microscopy and (scanning) transmission electron microscopy was performed to document the microstructural features of the oxidized Zr-2 and Zr-4 samples (oxide and metal/oxide interface) and to interpret the EIS results. At the start of this work, it was assumed that despite the laminar cracks and porosity visible in both optical and SEM, the oxide scale is dense near the metal, effectively preventing the water from contacting the metal directly. While it is generally accepted that the large laminar cracks pores allow the water to percolate into the oxide film, it is unknown just how deep it can go, and how interconnected is the porosity, which will dictate how much the porosity is connected electrically to the water within the oxide scale. The EIS results demonstrated that there is in fact a distribution of oxide thicknesses over the various samples, and within each material condition, that are communicating to the liquid. This is derived from the fact that Nyquist plots have an arc radius whose center point is often below the Z’ axis, implying that instead of a single oxide thickness, these oxides have a distribution of thicknesses. This distribution of thicknesses produces arcs that are not clearly separable in most of the samples.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The Electric Grid, Distributed Generation, and Grid Interconnection

This fact sheet is part of the Community Planning for Solar toolkit designed to help Massachusetts municipalities and others proactively plan for solar development in their communities. This fact sheet will walk you through the electricity system, and help you understand how the grid is changing as distributed generation (DG) electricity sources become more common.

14 SOLAR ENERGY↗