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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Search for the NΔ resonance in the 𝛾𝑑 → 𝑑𝜋 +𝜋 − reaction

A dibaryon which is an object with baryon number B = 2 has been studied for a long time. Dyson and Xuong classified non-strangeness dibaryon states based on SU(6) symmetries in 1960?s. In the framework, the deuteron is classified as one of the sextet states of dibaryons. Although dibaryon have been an interesting subject of research for a long time, most of the experimental studies up to the early 2000?s were unsuccessful. The CELCIUS/WASA collaboration reported this state via the double-pionic fusion reaction (?= ! 3c0c0) in 2009. Thereafter, the WASA-at-COSY collaboration revealed properties of the isoscaler resonance state via the ?= ! 3c0c0 reaction in 2011. The dibaryon resonance state with isospin ? = 0 and spin ( = 3 thought to be a ?03 which was predicted by Dyson and Xuong at 2.35 GeV?22 with a configuration of ??. The reported mass and width of that state were 2?37 GeV?22 and 0?07 GeV?22, espectively. The mass was ?0?08 GeV?22 smaller than that of 2?, the width was narrower than that of single ?. This surprising result made dibaryon study come back into the limelight. ?12 is one of the dibaryon states classified by Dyson and Xuong with isospin ? = 1, spin ( = 2. This state can be regarded as an s-wave #? resonance. ?12 is an interesting state from the point of view of the possibilities of existence as an internal structure of ?03 and contribution to many-body effects in nuclei. Though there were some experimental clues and theoretical studies of this state, it was unclear whether the obtained experimental results represented a real resonance or not due to the difficulty of separation from kinematical effects. Very recently, the FOREST group at Tohoku University reported a photoproduced isovector dibaryon state at mass of 2.14 GeV?22 in the 3c0 invariant mass spectra of the W3 ! 3c0c0 reaction. The most probable ?% configuration was 2¸ although they didn?t exclude the possibility of ?% = 1¸ or 3?. They separated the dibaryon production process from conventional pion production process for the first time using angular distribution of deuteron. We investigated the W3 ! 3c¸c? reaction for study of a possible #? dibaryon state using a deuterium target at the Research Center for Electron Photon Science, Tohoku University, Japan. In the experiment, ?3 ? 1012 tagged photon beam at energies ranging from 0.8 to 1.1 GeV was impinged to the liquid deuterium target (?520 mg?cm2) and the charged particles in the final state: deuteron, c¸, and c?, were detected by a magnetic spectrometer with a large solid angle named NKS2. NKS2 had capabilities of reconstructing momentum of charged particles, multi-track analysis, and ??c separation. We performed two different analyses named 2-track analysis and 3-track analysis. The 2-track (3-track) analysis was for events in which two (three) particles of 3c¸c? in the final state, including deuteron, were detected by NKS2. In the 3-track and 2-track analysis, ?2000? ?15000 events were identified as the W3 ! 3c¸c? reaction events, respectively. The 2-track analysis with higher statistics was mainly used to derive the cross sections, and the 3-track analysis was used to check the consistency of the 2-track analysis. In this thesis, we have shown the total cross section, the differential cross sections of the W3 ! 3c¸c? reaction in the region of jC j ¡ 0?15 GeV2. This is the world?s first measurement of this reaction in this energy region. Dibaryon resonance structures were observed below the #? threshold in the differential cross section of the invariant mass of 3c?. The mass and width of the structure were consistent with these of ?12 measured by the W3 ! 3c0c0 reaction. The mechanism of the production process was discussed based on the angular distribution of emitted deuteron.

Toyama, Yuichi↗
DOE OSTI2022

Photovoltaic Plant and Battery Energy Storage System Integration at NREL's Flatirons Campus

Although utility-scale solar photovoltaic (PV) power plants are becoming a cost-effective energy resource, there is belief within the energy industry that the increasing penetrations of PV technologies could potentially impact grid reliability. This is due to the variability across timescales, the forecast uncertainty of the solar energy resource, and the impacts on both distribution and transmission systems. This can cause utilities to severely limit PV installations or to assign PV integration costs when considering a least-cost portfolio of resources. As California and other regions in the United States are marching toward fulfilling - and probably exceeding - their renewables portfolio standards goals, grid operators are beginning to face operational challenges that could have implications for existing renewable and nonrenewable generators and that will shape opportunities for future projects. In this work, we focused on developing controls and conducting demonstrations for AC-coupled PV-battery energy storage systems (BESS) in which PV and BESS are collocated and share a point of common coupling (PCC).

14 SOLAR ENERGY↗
DOE OSTI2023

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

Deep decarbonization of power system operations requires the maximal utilization of available renewable resources. At distribution-level operations, however, grid operators can face numerous challenges in integrating renewables at scale owing to the inherent intermittence of renewable energy resources. These include phenomena such as voltage fluctuations, which are typically mitigated through control actuators such as on-load tap changers (OLTC) as well as energy storage devices, such as battery energy storage systems (BESS). On the one hand, high intermittence of the available renewable portfolio may require increasingly aggressive control of actuators, thereby accelerating the probability of equipment failure. On the other hand, integrating BESS operations and having a diverse renewable generation portfolio can typically help stagger power/energy flow to mitigate the aforementioned adverse impacts. In this paper, we employ a Bayesian framework for equipment lifetime estimation to understand the impact of including tidal energy resources and BESS in distribution system operations for feeders having substantial distribution photovoltaic generation. Our results indicate that while tidal energy alone may slightly decrease equipment reliability, the adverse impact on reliability is significantly magnified by a generation portfolio consisting of tidal generation and photovoltaic generation. Here, we also study the tidal and photovoltaic hosting capacity problem with and without energy storage systems using equipment reliability as an added constraint. We conclude that energy storage increases the reliability-constrained hosting capacity of the distribution system.

14 SOLAR ENERGY↗
DOE OSTI2023

OH density, flux and loss probability measurements in a room temperature atmospheric pressure surface discharge by microscopic laser induced fluorescence

Many applications involving atmospheric pressure plasma-substrate interactions are enabled by the large fluxes of short-lived reactive species such as OH radicals to the substrate, nonetheless, the accurate measurement of radical densities and fluxes at substrates at atmospheric pressure has received little attention to date, particularly for surface ionization waves. We report the measurement of the OH density distribution in a surface discharge on a fused silica (quartz) substrate generated by an impinging atmospheric pressure plasma jet in dry and humid helium. The OH density is measured by microscopic laser induced fluorescence with a spatial resolution of 10 µm in the direction perpendicular to the quartz substrate. The measured OH diffusive flux varied for the investigated experimental conditions by almost three orders of magnitude and had a maximum value of 1.7 × 10 15 cm -2 s -1 . The corresponding surface loss probability of OH on the quartz surface was determined to be ~0.01. The high spatial resolution was required to accurately resolve the near surface gradient of OH radicals.

plasma-surface interactions↗
DOE OSTI2023

Verifying the Computational Integrity of Power Grid Controls with Zero-Knowledge Proof

The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources with rising dependence on communication infrastructure. A common assumption made for most existing distributed/decentralized controllers is that local controllers would faithfully follow the designated controller dynamics based on the data received from communication channels. However, with increased probability of cyberattacks on Operational Technology infrastructure, such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. In this work, we leverage a cryptography technology known as zero-knowledge scalable transparent arguments of knowledge (zk-STARK) to verify the computational integrity of power grid control algorithms, with projected linear dynamics-based control schemes as the initial proof-of-concept test case. The method presented here converts the cybersecurity challenge of data integrity for grid control into a subset of computational integrity.

computational integrity↗
DOE OSTI2020

Giant virus diversity and host interactions through global metagenomics

Our current knowledge about nucleocytoplasmic large DNA viruses (NCLDVs) is largely derived from viral isolates that are co-cultivated with protists and algae. Here we reconstructed 2,074 NCLDV genomes from sampling sites across the globe by building on the rapidly increasing amount of publicly available metagenome data. This led to an 11-fold increase in phylogenetic diversity and a parallel 10-fold expansion in functional diversity. Analysis of 58,023 major capsid proteins from large and giant viruses using metagenomic data revealed the global distribution patterns and cosmopolitan nature of these viruses. The discovered viral genomes encoded a wide range of proteins with putative roles in photosynthesis and diverse substrate transport processes, indicating that host reprogramming is probably a common strategy in the NCLDVs. Furthermore, inferences of horizontal gene transfer connected viral lineages to diverse eukaryotic hosts. We anticipate that the global diversity of NCLDVs that we describe here will establish giant viruses-which are associated with most major eukaryotic lineages-as important players in ecosystems across Earth's biomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Occlusion-Perturbed Deep Learning for Probabilistic Solar Forecasting via Sky Images

Solar forecasting is shifting to the probabilistic paradigm due to the inherent uncertainty within the solar resource. Input uncertainty quantification is one of the widely used and best-performing ways to model solar uncertainty. However, compared to other sources of inputs, such as numerical weather prediction models, pure sky image-based probabilistic solar forecasting lags behind. In this research, an occlusion-perturbed convolutional neural network, named the PSolarNet, is developed. The PSolarNet provides very short-term deterministic forecasts, forecast scenarios, and probabilistic forecasts of the global horizontal irradiance from sky image sequences. Case studies based on 6 years of open-source data show that the developed PSolarNet is able to generate accurate 10-minute ahead deterministic forecasts with a 5.62% normalized root mean square error, realistic and diverse forecast scenarios with a 0.966 average correlation with the actual time series, and reliable and sharp probabilistic forecasts with a 2.77% normalized continuous ranked probability score.

Bayesian model averaging↗
DOE OSTI2022

Oxygen isotopes of anhydrous primary minerals show kinship between asteroid Ryugu and comet 81P/Wild2

The extraterrestrial materials returned from asteroid (162173) Ryugu consist predominantly of low-temperature aqueously formed secondary minerals and are chemically and mineralogically similar to CI (Ivuna-type) carbonaceous chondrites. Here, we show that high-temperature anhydrous primary minerals in Ryugu and CI chondrites exhibit a bimodal distribution of oxygen isotopic compositions: 16 O-rich (associated with refractory inclusions) and 16 O-poor (associated with chondrules). Both the 16 O-rich and 16 O-poor minerals probably formed in the inner solar protoplanetary disk and were subsequently transported outward. The abundance ratios of the 16 O-rich to 16 O-poor minerals in Ryugu and CI chondrites are higher than in other carbonaceous chondrite groups but are similar to that of comet 81P/Wild2, suggesting that Ryugu and CI chondrites accreted in the outer Solar System closer to the accretion region of comets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Robust Resilient Signal Reconstruction under Adversarial Attacks

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We include a new challenge of robust estimation of the attack support. The problem is then cast as a constrained optimization problem merging promising techniques in the area of deep learning and estimation theory. A pruning algorithm is developed to reduce the "false positive" uncertainty of data-driven attack localization results, thereby improving the probability of correct signal reconstruction. Sufficient conditions for the correct reconstruction and the associated reconstruction error bounds are obtained for both exact and inexact attack support estimation. Moreover, a simulation of a water distribution system is presented to validate the proposed techniques.

Robust, Signal reconstruction, Resilient estimator↗
DOE OSTI2020

Radar-derived precipitation climatology for wind turbine blade leading edge erosion

Wind turbine blade leading edge erosion (LEE) is a potentially significant source of revenue loss for wind farm operators. Thus, it is important to advance understanding of the underlying causes, to generate geospatial estimates of erosion potential to provide guidance in pre-deployment planning, and ultimately to advance methods to mitigate this effect and extend blade lifetimes. This study focuses on the second issue and presents a novel approach to characterizing the erosion potential across the contiguous USA based solely on publicly available data products from the National Weather Service dual-polarization radar. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments. Results from these locations demonstrate the high spatial variability in precipitation-induced erosion potential, illustrate the importance of low-probability high-impact events to cumulative annual total kinetic energy transfer and emphasize the importance of hail as a damage vector.

Letson, Frederick (ORCID:0000000192750359)↗
DOE OSTI2022

Occlusion-Perturbed Deep Learning for Probabilistic Solar Forecasting via Sky Images: Preprint

Solar forecasting is shifting to the probabilistic paradigm due to the inherent uncertainty within the solar resource. Input uncertainty quantification is one of the widely used and best-performing ways to model solar uncertainty. However, compared to other sources of inputs, such as numerical weather prediction models, pure sky image-based probabilistic solar forecasting lags behind. In this research, an occlusion-perturbed convolutional neural network, named the PSolarNet, is developed. The PSolarNet provides very short-term deterministic forecasts, forecast scenarios, and probabilistic forecasts of the global horizontal irradiance from sky image sequences. Case studies based on 6 years of open-source data show that the developed PSolarNet is able to generate accurate 10-minute ahead deterministic forecasts with a 5.62% normalized root mean square error, realistic and diverse forecast scenarios with a 0.966 average correlation with the actual time series, and reliable and sharp probabilistic forecasts with a 2.77% normalized continuous ranked probability score.

Bayesian model averaging↗
DOE OSTI2023

Physics-based Induced Earthquake Forecasting: Process Understanding, and Hazards Mitigation

Disposal of saltwater co-produced with oil and gas is linked to elevated seismicity in the Central and Midwest US. There is a concern that these events may lead to widespread damage and an overall increase in seismicity. Thus an improved understanding of the spatially and temporally variable deformation and stress field associated with fluid injection operation is critically necessary for evaluating time-varying seismic hazards. Despite the improvements in seismic monitoring capacity and the resulting decrease in the magnitude detection threshold, estimates of induced earthquake probability remain elusive due to insufficient models incapable of accounting for the complex physics governing the process of induced seismicity. The proposed research effort will comprehensively analyze, integrate, and interpret geodetic, injection, and seismic data in the vicinity of the injection sites in Oklahoma to resolve the 4-dimensional distribution of pore pressure and stress in the shallow crust. This project, in particular, is focused on exploring the statistical relation between injection operation and increased earthquake hazard. The amplitude of and the extent to which pore pressure changes are determined by some factors, in particular, the hydrogeological properties of the rocks, such as diffusivity. Thus the available deformation data will be used to constrain hydrogeological properties of the medium, to accurately resolve the evolution of crustal stresses due to fluid injection. Having the time-varying models of stress changes, a statistical framework will be implemented to estimate the time-dependent probability of large earthquakes on the nearby fault systems. These data and models help to improve seismic hazard estimates and aid in constructing operational-induced earthquake forecast models. This information can also be integrated into the updated U.S. National Seismic Hazard Map, which local communities and authorities use in their earthquake risk estimates and mitigation efforts.

58 GEOSCIENCES↗
DOE OSTI2022

Statistical analysis of S—N type environmental fatigue data of Ni-base alloy welds using weibull distribution

In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve + NUREG/CR-6909 F en model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Evidence Theory Representations for Properties Associated With Weak Link/Strong Link Systems, Part 2: Failure Time and Failure Temperature

The use of evidence theory and associated cumulative plausibility functions (CPFs), cumulative belief functions (CBFs), cumulative distribution functions (CDFs), complementary cumulative plausibility functions (CCPFs), complementary cumulative belief functions (CCBFs), and complementary cumulative distribution functions (CCDFs) in the analysis of loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems is introduced and illustrated. Article content includes cumulative and complementary cumulative belief, plausibility, and probability for (i) time at which LOAS occurs for a one WL/two SL system, (ii) time at which a two-link system fails, (iii) temperature at which a two-link system fails, and (iv) temperature at which LOAS occurs for a one WL/two SL system. The presented results can be generalized to systems with more than one WL and two SLs.

42 ENGINEERING↗
DOE OSTI2023

Optimizing design and dispatch of a resilient renewable energy microgrid for a South African hospital

Lack of access to reliable energy is a major concern for countries in sub-Saharan Africa. The national grids are unable to consistently satisfy demand. Therefore, users turn to distributed generation systems in the form of back-up generators. However, such systems are usually designed based on a rule of thumb. We employ a mixed-integer linear programming model that considers several options such as renewable energy, combined heat and power, and storage technologies, in addition to those on-site, to provide optimal design and dispatch decisions that minimize total cost. We apply this model to a case study for a hospital in South Africa, considering its need for reliable electricity in light of multiple outages that might occur over the course of a year, as well as its high heating and cooling loads. Our results show that optimal design and dispatch decisions for the distributed generation system address reliability challenges, regardless of the time at which they occur. And, these solutions yield millions of dollars in savings, suggesting that technologies such as the absorption chiller may be overlooked in typical designs; its integration can reduce demand charges even in the absence of combined heat and power. We show that total cost is most sensitive to changes in site electrical demand, followed by capital cost, fuel cost, photovoltaic production, and monthly demand charges; changes in fuel cost primarily affect system sizes of combined heat and power and the absorption chiller, while photovoltaic system size is more sensitive to the changes in capital and fuel costs, photovoltaic resource availability, and hourly electrical demand. Finally, an outage simulator demonstrates the ability of our optimized system to sustain with no interruptions in power five-hour outages with probability 1.0 and ten-hour outages with probability 0.65, significant improvements over 0.5 and 0.0, respectively, under a business-as-usual case.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Müllerian mimicry and the coloration patterns of sympatric coral snakes

Abstract Coral snakes in the genus Micrurus are venomous, aposematic organisms that signal danger to predators through vivid coloration. Previous studies found that they serve as models to several harmless species of Batesian mimics. However, the extent to which Micrurus species engage in Müllerian mimicry remains poorly understood. We integrate detailed morphological and geographical distribution data to investigate if coral snakes are Müllerian mimics. We found that coloration is spatially structured and that Micrurus species tend to be more similar where they co-occur. Though long supposed, we demonstrate for the first time that coral snakes might indeed be Müllerian mimics as they show some convergence in coloration patterns. Additionally, we found that the length of red-coloured rings in Micrurus is conserved, even at large geographic scales. This finding suggests that bright red rings may be under more substantial stabilizing selection than other aspects of coloration and probably function as a generalized signal for deterring predators.

Evolutionary Biology↗
DOE OSTI2021

A Privacy-Preserving Distributed Control of Optimal Power Flow

Here, we consider a distributed optimal power flow formulated as an optimization problem that maximizes a nondifferentiable concave function. Solving such a problem by the existing distributed algorithms can lead to data privacy issues because the solution information exchanged within the algorithms can be utilized by an adversary to infer the data. To preserve data privacy, in this paper we propose a differentially private projected subgradient (DP-PS) algorithm that includes a solution encryption step. We show that a sequence generated by DP-PS converges in expectation, in probability, and with probability 1. Moreover, we show that the rate of convergence in expectation is affected by a target privacy level of DP-PS chosen by the user. We conduct numerical experiments that demonstrate the convergence and data privacy preservation of DP-PS.

24 POWER TRANSMISSION AND DISTRIBUTION↗