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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimized Dispatch of Distributed Energy Resources for Resiliency and Power Quality Improvements at the Grid-Edge

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

Chowdhury, Prithwiraj Roy↗
DOE OSTI2017

Assessing Intra-arterial Complications of Planning and Treatment Angiograms for Y-90 Radioembolization

PurposeTo report hepatic arterial-related complications encountered during planning and treatment angiograms for radioembolization and understand any potential-associated risk factors.Materials and Methods518 mapping or treatment angiograms for 180 patients with primary or metastatic disease to the liver treated by Yttrium-90 radioembolization between 2/2010 and 12/2015 were retrospectively reviewed. Intra-procedural complications were recorded per SIR guidelines. Patient demographics, indication for treatment, prior exposure to chemotherapeutic agents, operator experience, and disease burden were reviewed. Technical variables including type of radioembolic (glass vs. resin microspheres), indication for angiography (mapping vs. treatment), variant anatomy, and attempts at coil embolization were also assessed.ResultsThirteen (13/518, 2.5%) arterial-related complications occurred in 13 patients. All but two complications resulted during transcatheter coil embolization to prevent non-target embolization. Complications included coil migration (n = 6), arterial dissection (n = 2), focal vessel perforation (n = 2), arterial thrombus (n = 2), and vasospasm prohibiting further arterial sub-selection (n = 1). Transarterial coiling was identified as a significant risk factor of complications on both univariate and multivariate regression analysis (odds ratio 7.8, P = 0.004). Usage of resin microspheres was also a significant risk factor (odds ratio 9.5, P = 0.042). No other technical parameters or pre-procedural variables were significant after adjusting for confounding on multivariate analysis (P > 0.05).ConclusionIntra-procedural hepatic arterial complications encountered during radioembolization were infrequent but occurred mainly during coil embolization to prevent non-target delivery to extra-hepatic arteries.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such “free” model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process—the genetic algorithm (GA)—has become especially popular. As applied to modeling, GAs represent a Darwinian process: an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as “parents” who pass their parameters onto a new generation. At the U.S. Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to “score” the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions. Significance Statement We wanted to develop a forecasting system by which a weather model is run over the Savannah River Site each day and repeatedly adjusted according to how well it performed the previous day. To run the model, a series of values (parameters) must be set to control how the model will calculate winds, temperatures, and other desired variables. Each day the model was run several times using different combinations of these parameters and later compared with observed meteorological conditions. Parameters that produced the most accurate forecasts were preferentially reused to create the forecasts for the next day. The process was tested for the summer of 2020 and exhibited lower errors than forecasts produced by the model using default values of the parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

On the challenges facing the handling of solid biomass feedstocks: On the Challenges Facing the Handling of Solid Biomass Feedstocks

With a major global emphasis on the management of waste, alternative resources and a shift to environmentally sustainable technologies, demand for large volumes of heterogeneous solid biomass feedstocks for energy or chemical use is expected to rise significantly. In transforming a sporadic supply of a low-value, highly variable product, to continuous and controlled high throughput systems, a thorough understanding of the feedstock properties will increase in importance. Appropriate characterisation tests are necessary to define technical specification and selection criteria for handling equipment and to appraise the requirement and location for additional processes or pre-treatment to be integrated into the handling chain. Such tests may also influence the material characteristics to be used in the conversion process. In this paper, we discuss the main feedstock attributes associated with a number of handling chain phases and the approach to obtain them. Lastly, the framework for a holistic approach to the characterisation and design of biomass feedstock handling systems for further development and practical implementation is also proposed.

09 BIOMASS FUELS↗
DOE OSTI2018

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

We measure the clustering of DES year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of 6.6×10 5 luminous red galaxies selected using the redMaGiC algorithm over an area of 1321 square degrees, in the redshift range 0.15 z /(1+z)=0.017. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample’s robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto- and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be b(σ 8 /0.81)| z=0.24 =1.40±0.07, b(σ 8 /0.81)| z=0.38 =1.60±0.05, b(σ 8 /0.81)| z=0.53 =1.60±0.04 for galaxies with luminosities L/L * >0.5, b(σ 8 /0.81)| z=0.68 =1.93±0.04 for L/L * >1 and b(σ 8 /0.81)| z=0.83 =1.98±0.07 for L/L * >1.5, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurements of Density and Sound Speed in Mixtures Relevant to Supercritical CO2 Cycles

Abstract The objective of this research is to validate properties of mixtures relevant to supercritical carbon dioxide (sCO2) power cycles. Direct-fired sCO2 cycles are a promising technology for the future power generation systems. The working fluid of sCO2 cycles will be near and above critical point of CO2. One of the challenges is that the simulation of mixtures should consider real gas behavior. Expected operating conditions of Allam cycles reach up to 300 bar and 1000 °C. Characterizing the mixtures at the extreme conditions is an important issue in current researches and industrial applications. Thermophysical properties of mixtures may be beyond the valid range of the widely used database such as NIST REFPROP. Experimental data of mixture properties in the literature are limited which is necessary to develop high-fidelity design tools for sCO2 power cycles. We measured the density and sound speed of several multi-component mixtures. A temperature-controlled high-pressure test cell was used for the density measurements. Sound speed was measured by resonant frequency detection using an external speaker and a piezoelectric pressure sensor. Mixtures studied in this work include carbon dioxide, methane, oxygen, and water vapor. Properties of pure CO2 were measured to show the validity of our technique. Compositions were selected to be close to frozen mixtures at the inlet, mid-progress, and exhaust conditions of a model sCO2 combustor in the previous numerical simulation work. Corresponding reaction progress variables (RPV) were RPV = 0, 0.5, and 1. Temperature and pressure conditions of experiments are 310–450 K and 0–150 bar. In our study, density and sound speed from the NIST REFPROP database agree with experimental measurements within the range of our measurement uncertainties.

Energy & Fuels↗
DOE OSTI2020

A Model Tree Generator (MTG) Framework for Simulating Hydrologic Systems: Application to Reservoir Routing

Data-driven algorithms have been widely used as effective tools to mimic hydrologic systems. Unlike black-box models, decision tree algorithms offer transparent representations of systems and reveal useful information about the underlying process. A popular class of decision tree models is model tree (MT), which is designed for predicting continuous variables. Most MT algorithms employ an exhaustive search mechanism and a pre-defined splitting criterion to generate a piecewise linear model. However, this approach is computationally intensive, and the selection of the splitting criterion can significantly affect the performance of the generated model. These drawbacks can limit the application of MTs to large datasets. To overcome these shortcomings, a new flexible Model Tree Generator (MTG) framework is introduced here. MTG is equipped with several modules to provide a flexible, efficient, and effective tool for generating MTs. The application of the algorithm is demonstrated through simulation of controlled discharge from several reservoirs across the Contiguous United States (CONUS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Method for Integrating an UBEM with GIS for Spatiotemporal Visualization and Analysis

Leveraging Geographic Information Systems (GIS) for spatiotemporal visualization and analysis of simulated UBEM datasets and real-world data simultaneously can assist in identifying opportunities, as well as potential barriers, to energy efficient and climate adaptation strategies. However, current GIS-based models that support interactive exploration of adaptation strategies and future scenarios are scarce and do not easily incorporate building energy use data for visual analysis over time. This paper describes a workflow to integrate simulated building energy consumption data associated with variable energy efficiency scenarios within a GIS platform for interactive spatiotemporal visualization to support climate adaptation decision-making. The contribution of the work presented is in the ability to selectively view and analyze simulated building energy performance data layered with other real-world geospatial data through an automated feedback loop between an UBEM and ArcGIS. An interactive interface is designed in ArcGIS to enable users to explore building performance scenarios spatially and over time. Using a downtown neighborhood in Syracuse, New York, USA, as a case study, preliminary results demonstrate how the workflow provides insight into existing energy use issues and potential for implementing strategies such as energy load shifting or building retrofits. A discussion includes opportunities as well as challenges to the workflow in facilitating understanding of urban energy model outputs by multiple stakeholders in evaluating potential energy efficient strategies.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2019

Collaborative Research On Ecophysiological Controls on Amazonian Precipitation Seasonality And Variability

We developed and deployed a robust and accurate instrumentation package for measurement of solar induced chlorophyll fluorescence (SIF) from above a plant canopy. The sensor collects light from identical up and down facing hemispheric collectors. A fiber optic transmits the collected light (selected by a rotatable prism) to spectrometers located at the base of the tower. Spectra of the down welling and upwelling light were collected alternatively and stored for later analysis. SIF was retrieved by a spectral unmixing approach using high resolution spectra in the 730-760 nm band. Most other ground-based sensors base their analysis on O 2 -alpha band (760-780 nm) for SIF retrieval. We found that the former gave identical results when the atmosphere was clear, but the former was more stable in the cloudy conditions that often prevailed in the Amazon. The mechanical design and software developed for the system are available on request. The sensor was mounted near the top of an 80 m tower at K34 near Manaus in the Brazilian Amazon Forest. The sensor system proved weather-tight and functioned flawlessly over the time of deployment. Our experiment was cut short at 6 months by failure of air conditioning infrastructure at the tower. We found that SIF emitted by canopy was remarkably stable when scaled by the downwelling photosynthetically active radiation or the upwelling near infrared light. We detected a 3.4% increase in SIF over the course of the dry season. This finding is consistent with the observation that several trees in the field of view flushed new leaves in the dry season. We saw no evidence of drought stress or photo damage of the forest canopy during our study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ultracool dwarfs candidates based on 6 yr of the Dark Energy Survey data

ABSTRACT We present a sample of 19 583 ultracool dwarf candidates brighter than z ≤23 selected from the Dark Energy Survey DR2 coadd data matched to VHS DR6, VIKING DR5, and AllWISE covering ∼ 480 deg2. The ultracool candidates were first pre-selected based on their (i–z), (z–Y), and (Y–J) colours. They were further classified using a method that compares their optical, near-infrared, and mid-infrared colours against templates of M, L, and T dwarfs. 14 099 objects are presented as new L and T candidates and the remaining objects are from the literature, including 5342 candidates from our previous work. Using this new and deeper sample of ultracool dwarf candidates we also present: 20 new candidate members to nearby young moving groups and associations, variable candidate sources and four new wide binary systems composed of two ultracool dwarfs. Finally, we also show the spectra of 12 new ultracool dwarfs discovered by our group and presented here for the first time. These spectroscopically confirmed objects are a sanity check of our selection of ultracool dwarfs and photometric classification method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Impact of feed variability on cesium removal with multiple actual waste samples from the Hanford site

Here, the Tank Side Cesium Removal (TSCR) system, under development by Washington River Protection Solutions (WRPS), will send initial low-activity Hanford waste tank supernate feeds to the Hanford Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) Facility. In addition to entrained solids removal from the supernate, the primary goal of TSCR is to remove cesium-137 ( 137 Cs) by ion exchange, allowing contact handling of the liquid effluent product at WTP. Crystalline silicotitanate (CST) ion exchange media, manufactured by Honeywell UOP (product IONSIV™ R9140-B), was selected as the ion exchange media at TSCR. This lot of material was found to have superior performance in comparison to historic batches of CST. Ion exchange column and batch contact testing with supernate from Hanford tanks AP-105, AP-107 and AW-102 was performed to assess the impact of feed variability on system performance. These tests demonstrated that batch contact measurements provide a reasonable prediction of column capacities with some deviation in performance attributed to column dynamics. In addition, the variability in CST capacity for cesium in the various actual waste samples does not track with historical understanding of the competing cations, suggesting that tank waste samples contain other components that may significantly impact cesium loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Sifting for Sapphires: Systematic Selection of Tidal Disruption Events in iPTF

We present results from a systematic selection of tidal disruption events (TDEs) in a wide-area (4800~deg 2 ), g+R band, Intermediate Palomar Transient Factory (iPTF) experiment. Our selection targets typical optically-selected TDEs: bright (>60\% flux increase) and blue transients residing in the center of red galaxies. Using photometric selection criteria to down-select from a total of 493 nuclear transients to a sample of 26 sources, we then use follow-up UV imaging with the Neil Gehrels Swift Telescope, ground-based optical spectroscopy, and light curve fitting to classify them as 14 Type Ia supernovae (SNe Ia), 9 highly variable active galactic nuclei (AGNs), 2 confirmed TDEs, and 1 potential core-collapse supernova. We find it possible to filter AGNs by employing a more stringent transient color cut (g-r< -0.2 mag); further, UV imaging is the best discriminator for filtering SNe, since SNe Ia can appear as blue, optically, as TDEs in their early phases. However, when UV-optical color is unavailable, higher precision astrometry can also effectively reduce SNe contamination in the optical. Our most stringent optical photometric selection criteria yields a 4.5:1 contamination rate, allowing for a manageable number of TDE candidates for complete spectroscopic follow-up and real-time classification in the ZTF era. We measure a TDE per galaxy rate of $1.7^{+2.9}_{-1.3}$ ×10 -4 gal -1 yr -1 (90% CL in Poisson statistics). This does not account for TDEs outside our selection criteria, thus may not reflect the total TDE population, which is yet to be fully mapped.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Schedule Management Optimization (SMO) Domain Model (V.1.2)

Schedule Management Optimization (SMO) is a tool for automatically generating a schedule of project tasks. Project scheduling is traditionally achieved with the use of commercial project management software or case-specific optimization formulations. Commercial software packages are useful tools for managing and visualizing copious amounts of project task data. However, their ability to automatically generate optimized schedules is limited. Furthermore, there are many real-world constraints and decision variables that commercial packages ignore. Case-specific optimization formulations effectively identify schedules that optimize one or more objectives for a specific problem, but they are unable to handle a diverse selection of scheduling problems. SMO enables practitioners to generate optimal project schedules automatically while considering a broad range of real-world problem characteristics. SMO has been designed to handle some of the most difficult scheduling problems – those with resource constraints, multiple objectives, multiple inventories, and diverse ways of performing tasks. This report contains descriptions of the SMO modeling concepts and explains how they map to real-world scheduling considerations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

THE H α EMISSION OF NEARBY M DWARFS AND ITS RELATION TO STELLAR ROTATION

The high-energy emission from low-mass stars is mediated by the magnetic dynamo. Although the mechanisms by which fully convective stars generate large-scale magnetic fields are not well understood, it is clear that, as for solar-type stars, stellar rotation plays a pivotal role. We present 270 new optical spectra of low-mass stars in the Solar Neighborhood. Combining our observations with those from the literature, our sample comprises 2202 measurements or non-detections of H α emission in nearby M dwarfs. This includes 466 with photometric rotation periods. Stars with masses between 0.1 and 0.6 M {sub ⊙} are well-represented in our sample, with fast and slow rotators of all masses. We observe a threshold in the mass–period plane that separates active and inactive M dwarfs. The threshold coincides with the fast-period edge of the slowly rotating population, at approximately the rotation period at which an era of rapid rotational evolution appears to cease. The well-defined active/inactive boundary indicates that H α activity is a useful diagnostic for stellar rotation period, e.g., for target selection for exoplanet surveys, and we present a mass-period relation for inactive M dwarfs. We also find a significant, moderate correlation between L{sub Hα} / L{sub bol} and variability amplitude: more active stars display higher levels of photometric variability. Consistent with previous work, our data show that rapid rotators maintain a saturated value of L{sub Hα} / L {sub bol}. Our data also show a clear power-law decay in L{sub Hα} / L{sub bol} with Rossby number for slow rotators, with an index of −1.7 ± 0.1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Spectroscopic Analysis of Milky Way Outer Halo Satellites: Aquarius II and Boötes II

In this paper, we present a chemical and kinematic analysis of two ultrafaint dwarf galaxies (UFDs), Aquarius II (Aqu II) and Boötes II (Boo II), using Magellan/IMACS spectroscopy. We present the largest sample of member stars for Boo II (12), and the largest sample of red giant branch members with metallicity measurements for Aqu II (eight). In both UFDs, over 80% of targets selected based on Gaia proper motions turned out to be spectroscopic members. In order to maximize the accuracy of stellar kinematic measurements, we remove the identified binary stars and RR Lyrae variables. For Aqu II, we measure a systemic velocity of -65.3 ± 1.8 km s-1 and a metallicity of [Fe/H] = $-2.57^{+0.17}_{-0.17}$. When compared with previous measurements, these values display a ~6 km s -1 difference in radial velocity and a decrease of 0.27 dex in metallicity. Similarly for Boo II, we measure a systemic velocity of $-130.4^{+1.4}_{-1.1}$ km s -1 , more than 10 km s -1 different from the literature, a metallicity almost 1 dex smaller at [Fe/H] = $-2.71^{+0.11}_{-0.10}$, and a velocity dispersion 3 times smaller at σ v hel = $2.9^{+1.6}_{-1.2}$km s -1 . Additionally, we derive systemic proper-motion parameters and model the orbits of both UFDs. Finally, we highlight the extremely dark-matter-dominated nature of Aqu II and compute the J-factor for both galaxies to aid searches of dark matter annihilation. Despite the small size and close proximity of Boo II, it is an intermediate target for the indirect detection of dark matter annihilation due to its low-velocity dispersion and corresponding low dark matter density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗