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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Storing files in a parallel computing system based on user-specified parser function

Techniques are provided for storing files in a parallel computing system based on a user-specified parser function. A plurality of files generated by a distributed application in a parallel computing system are stored by obtaining a parser from the distributed application for processing the plurality of files prior to storage; and storing one or more of the plurality of files in one or more storage nodes of the parallel computing system based on the processing by the parser. The plurality of files comprise one or more of a plurality of complete files and a plurality of sub-files. The parser can optionally store only those files that satisfy one or more semantic requirements of the parser. The parser can also extract metadata from one or more of the files and the extracted metadata can be stored with one or more of the plurality of files and used for searching for files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Characterizing U.S. Heat Demand for Potential Application of Geothermal Direct Use: Preprint

In this paper, we assess the U.S. demand for low-temperature thermal energy at the county resolution for four major end-use sectors: residential buildings, commercial buildings, manufacturing facilities, and agricultural facilities. Existing, publicly available data on the U.S. thermal demand market are characterized by coarse spatial resolution, with assessments typically at the state-level or larger. For many uses, these data are sufficient; however, our research was motivated by an interest in assessing the potential demand for direct use (DU) of low-temperature (30 degrees to 150 degrees C) geothermal heat. The availability and quality of geothermal resources for DU applications are highly spatially heterogeneous; therefore, to assess the potential market for these resources, it is necessary to understand the spatial variation in demand for low-temperature resources at a local resolution. This paper presents the datasets and methods we used to develop county-level estimates of the thermal demand for the residential, commercial, manufacturing, and agricultural sectors. Although this analysis was motivated by an interest in geothermal energy deployment, the results are likely to have broader applications throughout the energy industry. The county-resolution thermal demand data developed in this study for four major U.S. sectors may have far-reaching implications for building technologies, industrial processes, and various distributed renewable energy thermal resources (e.g. biomass, solar).

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Characterizing U.S. Heat Demand Market for Potential Application of Geothermal Direct Use

In this paper, we assess the U.S. demand for low-temperature thermal energy at the county resolution for four major end-use sectors: residential buildings, commercial buildings, manufacturing facilities, and agricultural facilities. Existing, publicly available data on the U.S. thermal demand market are characterized by coarse spatial resolution, with assessments typically at the state-level or larger. For many uses, these data are sufficient; however, our research was motivated by an interest in assessing the potential demand for direct use (DU) of low-temperature (30 degrees to 150 degrees C) geothermal heat. The availability and quality of geothermal resources for DU applications are highly spatially heterogeneous; therefore, to assess the potential market for these resources, it is necessary to understand the spatial variation in demand for low-temperature resources at a local resolution. This paper presents the datasets and methods we used to develop county-level estimates of the thermal demand for the residential, commercial, manufacturing, and agricultural sectors. Although this analysis was motivated by an interest in geothermal energy deployment, the results are likely to have broader applications throughout the energy industry. The county-resolution thermal demand data developed in this study for four major U.S. sectors may have far-reaching implications for building technologies, industrial processes, and various distributed renewable energy thermal resources (e.g. biomass, solar).

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Chapter 12 - Responses of alpine plant communities to climate warming

Alpine plant communities occur at the cold edge of vascular plant distributions, with many species having special adaptations to short growing seasons, low temperatures, and infertile soils. Climate warming has the potential to alter alpine plant phenology and physiology, species interactions, community structure, species distributions, and ecosystem processes through effects on temperature, snow, and moisture regimes. Here, we review the state of understanding of alpine species, community, and ecosystem responses to climate change, with an emphasis on what has been learned from controlled experiments. We conclude that many alpine plant communities are already responding to climate warming, with changes contingent on hydroclimate setting and local edaphic factors that modulate species use of greater nitrogen and phosphorous availability, migration to newly suitable sites, and success relative to neighboring species and migrants from lower elevations. Understanding the complex set of interactions required for predicting future change calls for more integrated experiments that explicitly address multiple interacting abiotic and biotic factors.

Winkler, Daniel E.↗
DOE OSTI2023

DER Cybersecurity R&D

The National Renewable Energy Laboratory (NREL) conducted more than 30 assessments for utilities across the United States with a cybersecurity assessment tool based on the U.S. Department of Energy (DOE) Cybersecurity Capability Maturity Model (C2M2) and the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF) and focused on business process. With funding from the DOE Office of Renewable Energy and Energy Efficiency Federal Energy Management Program, NREL modified the current cyber governance assessment tool to include an assessment process specifically for distributed energy resources (DERs). The Distributed Energy Resources Cybersecurity Framework (DER-CF) was developed to help federal agencies mitigate gaps in their cybersecurity posture for distributed energy systems.

cybersecurity valuation↗
DOE OSTI2021

Gauge-invariant TMD factorization for Drell-Yan hadronic tensor at small x

The Drell-Yan hadronic tensor for electromagnetic (EM) current in the Sudakov region s?Q2?q2? is obtained with 1Q2 accuracy. In the leading order in Nc the higher-twist quark-quark-gluon TMDs reduce to leading-twist TMDs due to QCD equation of motion. The resulting tensor for unpolarized hadrons is EM gauge-invariant and depends on two leading-twist TMDs: f1 responsible for total DY cross section, and Boer-Mulders function h?1. The order-of-magnitude estimates of angular distributions for DY process seem to agree with LHC results at corresponding kinematics.

Balitsky, Ian↗
DOE OSTI2017

Decision Analyses Related to Groundwater Remediation - 17051

Traditional decision analyses of groundwater remediation scenarios frequently fail because the probability of adverse, unanticipated events occurring is often high. This is driven by many factors including that (1) the models developed to represent the flow and transport in contaminated aquifers are typically simpler than reality and do not account for all the important governing processes, (2) probability distributions are assigned to critical performance parameters (such as model inputs or characteristics of the engineered remediation systems) even though some of these parameters might be unknown or not be very well constrained. However, there is a novel decision analysis methodology and a computational tool based on Bayesian Information-Gap Decision Theory (BIG-DT) that are designed to mitigate the shortcomings of the models and probabilistic decision analyses by leveraging a non-probabilistic decision theory -- information-gap decision theory. The new decision analysis methodology considers possible models that have not been explicitly enumerated and does not require us to commit to a particular probability distribution for model and remediation-design parameters. Both the set of possible models and the set of possible probability distributions grow as the degree of uncertainty increases. The fundamental question that BIG-DT asks is 'How large can these sets be before a particular decision results in an undesirable outcome?'. The decision that allows these sets to be the largest is considered to be the best option. In this way, BIG-DT enables robust decision-support for groundwater remediation problems. Here, we apply BIG-DT to a representative groundwater remediation scenario where different options for hydraulic containment and pump and treat are being considered. BIG-DT requires many model runs and high-performance computing resources are needed when complex models are used. We demonstrate the BIG-DT analyses on a series of synthetic problems that are designed to be consistent with real-world problems such as Los Alamos National Laboratory (LANL) contamination sites. We also discuss a general framework for how the BIG-DT analyses will be carried out at the chromium groundwater contamination site at LANL. BIG-DT is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is part of the MADS framework (http://mads.lanl.gov and http://madsjulia.github.io/Mads.jl). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Residential Home Decarbonization Using Advanced Micro-CHP

An efficient micro-combined heat and power (CHP) prototype was developed to provide heat and electricity for single-family homes and light commercial buildings. The unit can be installed independently at the point of energy consumption. Consequently, it enables cost-effectively and flexibly matching heat and electrical loads, simplifying distribution and installation processes, and recovering and storing waste heat as hot water. The analyzed results show that the micro-CHP using natural gas as fuel achieves 10.68%–32.80% CO2 reduction in the selected five home applications. The potential effect of H2 on decarbonization of these home was also evaluated, finding that the micro-CHP using a blended fuel with H2 and natural gas can further reduce CO2 emissions. However, the 50% CO2 reduction in the micro-CHP requires at least 70%–90% of H2 in the blend with natural gas. Overall, the micro-CHP technology demonstrates a solid potential to accelerate micro-CHP adoption in residential and light commercial markets, thereby promoting broader micro-CHP acceptance and use in the future for building decarbonization.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗
DOE OSTI2025

EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator

A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Distributed Energy Resources Cybersecurity Framework: Applying the NIST Risk Management Process

In an effort to strengthen the cybersecurity posture for federal agencies and reduce the time and complexities of following the Risk Management Framework (RMF) six-step process, the National Renewable Energy Laboratory has dedicated research into expanding the existing Distributed Energy Resources Cybersecurity Framework to provide functionality that aids in the RMF steps. Users will have the opportunity to learn, document, and review the framework, saving time and resources. Existing functionality within the web application will continue to be available with added features for usability.

14 SOLAR ENERGY↗
DOE OSTI2018

Statistical Analysis of the First Passage Path Ensemble of Jump Processes

The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes

Increasing evidence emerged for non-random spatial distributions for microbes, but the underlying processes resulting in microbial assemblage variation among and within Earth’s ecosystems is still lacking. For instance, some studies showed that the deterministic processes by habitat specialization are important, while other studies hold that bacterial communities are assembled by neutral forces. Here we examine the relative importance of deterministic and stochastic processes for bacterial communities from subsurface environments, as well as stream biofilm, lake water, lake sediment and soil using pyrosequencing of 16S rRNA gene. We show that there is a general pattern in phylogenetic signal in species niches across recent evolutionary time for all studied habitats, enabling us to infer the influences of community assembly processes from patterns of phylogenetic turnover in community composition. The phylogenetic dissimilarities among habitat types were significantly higher than within them, and the communities were clustered according to their original habitat types. For communities within habitat types, the highest phylogenetic turnover rate through space was observed in subsurface environments, followed by stream biofilm on mountainsides, whereas the sediment assemblages across regional scales showed the lowest turnover rate. Quantifying phylogenetic turnover as the deviation from a null expectation suggested that measured environmental variables imposed strong selection on bacterial communities for nearly all sample groups, and for three sample groups, that spatial distance reflects unmeasured environmental variables that impose selection, as opposed to spatial isolation. Such characterization of spatial and environmental variables proved essential for proper interpretation of partial mantel results based on observed beta diversity metrics. In summary, our results clearly indicate a dominant role of deterministic processes on bacterial assemblages and highlight that bacteria show strong habitat associations that have likely emerged through evolutionary adaptation.

Bacteria↗
DOE OSTI2014

Modeling self-subtraction in angular differential imaging: Application to the HD 32297 debris disk

We present a new technique for forward-modeling self-subtraction of spatially extended emission in observations processed with angular differential imaging (ADI) algorithms. High-contrast direct imaging of circumstellar disks is limited by quasi-static speckle noise, and ADI is commonly used to suppress those speckles. However, the application of ADI can result in self-subtraction of the disk signal due to the disk's finite spatial extent. This signal attenuation varies with radial separation and biases measurements of the disk's surface brightness, thereby compromising inferences regarding the physical processes responsible for the dust distribution. To compensate for this attenuation, we forward model the disk structure and compute the form of the self-subtraction function at each separation. As a proof of concept, we apply our method to 1.6 and 2.2 μm Keck adaptive optics NIRC2 scattered-light observations of the HD 32297 debris disk reduced using a variant of the 'locally optimized combination of images' algorithm. We are able to recover disk surface brightness that was otherwise lost to self-subtraction and produce simplified models of the brightness distribution as it appears with and without self-subtraction. From the latter models, we extract radial profiles for the disk's brightness, width, midplane position, and color that are unbiased by self-subtraction. Our analysis of these measurements indicates a break in the brightness profile power law at r ≈ 110 AU and a disk width that increases with separation from the star. We also verify disk curvature that displaces the midplane by up to 30 AU toward the northwest relative to a straight fiducial midplane.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-E-J-268: Change of CT Number During the Course of Chemoradiation Therapy for Pancreatic Cancer

Purpose: It has been observed radiation can induce changes in CT number (CTN) inside tumor during the course of radiation therapy (RT) for several tumor sites including lung and head and neck, suggesting that the CTN change may be potentially used to assess RT response. In this study, we investigate the CTN changes inside tumor during the course of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily diagnostic-quality CT data acquired during IGRT for 17 pancreatic head cancer patients using an in-room CT (CTVision, Siemens) were analyzed. All patients were treated with a radiation dose of 50.4 in 1.8 Gy per fraction. On each daily CT set, The contour of the pancreatic head, included in the treatment target, was generated by populating the pancreatic head contour from the planning CT or MRI using an auto-segmentation tool based on deformable registration (ABAS, Elekta) with manual editing if necessary. The CTN at each voxel in the pancreatic head contour was extracted and the 3D distribution of the CTNs was processed using MATLAB. The mean value of CTN distribution was used to quantify the daily CTN change in the pancreatic head. Results: Reduction of CTN in pancreatic head was observed during the CRT delivery in 14 out the 17 (82%) patients studied. Although the average reduction is only 3.5 Houncefield Unit (HU), this change is significant (p<0.01). Among them, there are 7 patients who had a CTN drop larger than 5 HU, ranging from 6.0 to 11.8 HU. In contrast to this trend, CTN was increased in 3 patients. Conclusion: Measurable changes in the CT number in tumor target were observed during the course of chemoradiation therapy for the pancreas cancer patients, indicating this radiation-induced CTN change may be used to assess treatment response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Drop size distribution broadening mechanisms in a bin microphysics Eulerian model

In this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting model simulations of an idealized ice-free cumulus cloud. Additionally, sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision-coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 m to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision-coalescence, dilution, etc.) are turned off, there is a reduction of DSD width by up to ~20-50% when the vertical grid spacing is decreased from 100 m to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

MAGNETOROTATIONALLY DRIVEN SUPERNOVAE AS THE ORIGIN OF EARLY GALAXY r-PROCESS ELEMENTS?

We examine magnetorotationally driven supernovae as sources of r-process elements in the early Galaxy. On the basis of thermodynamic histories of tracer particles from a three-dimensional magnetohydrodynamical core-collapse supernova model with approximated neutrino transport, we perform nucleosynthesis calculations with and without considering the effects of neutrino absorption reactions on the electron fraction (Y{sub e} ) during post-processing. We find that the peak distribution of Y{sub e} in the ejecta is shifted from {approx}0.15 to {approx}0.17 and broadened toward higher Y{sub e} due to neutrino absorption. Nevertheless, in both cases, the second and third peaks of the solar r-process element distribution can be reproduced well. The rare progenitor configuration that was used here, characterized by a high rotation rate and a large magnetic field necessary for the formation of bipolar jets, could naturally provide a site for the strong r-process in agreement with observations of the early Galactic chemical evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Transverse momentum distributions at large- x

We investigate the collinear matching of transverse momentum dependent (TMD) distributions at large values of x, computing and resumming the leading large-x asymptotics for matching coefficients. The large-x resummation is done directly within TMD distributions, ensuring the process-independence of the result. The derived resummation formulas are valid for all TMD distributions (except the pretzelosity). Their application improves perturbative convergence, provides practical estimation for unknown higher-order contributions, and sets restrictions for the nonperturbative part of models. Using the known anomalous dimensions, resummation can reach N 3 LL, often exceeding the accuracy of known coefficient functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗