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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Uncertainty guided online ensemble for non-stationary data streams in fusion science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior with distribution drifts, resulted by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with such non-stationary data streams. Online learning techniques have been leveraged in other domains, however it has been largely unexplored for fusion applications. In this paper, we investigate online learning for continuous adaptation to drifting data streams in the prediction of Toroidal Field (TF) coils deflection at the DIII-D fusion facility. We further address the short-term performance degradation inherent to standard online learning, which arises because ground truth is unavailable at prediction time. To mitigate this issue, we propose an uncertainty-guided online ensemble framework. The method leverages the Deep Gaussian Process Approximation (DGPA) for calibrated uncertainty estimation and uses these uncertainty measures to guide a meta-algorithm that aggregates predictions from learners trained over different historical horizons. Our results show that online learning reduces prediction error by 80% compared to a static model. The online ensemble and the proposed uncertainty-guided ensemble further reduce error by approximately 6%, and 10% respectively, relative to standard single-model online learning, while also providing calibrated uncertainty estimates to support operational decision-making.

AI↗
DOE OSTI2021

Conservation management decreases surface runoff and soil erosion

Conservation management practices – including agroforestry, cover cropping, no-till, reduced tillage, and residue return – have been applied for decades to control surface runoff and soil erosion, yet results have not been integrated and evaluated across cropping systems. In this study we collected data comparing agricultural production with and without conservation management strategies. We used a bootstrap resampling analysis to explore interactions between practice type, soil texture, surface runoff, and soil erosion. We then used a correlation analysis to relate changes in surface runoff and soil erosion to 13 other soil health and agronomic indicators, including soil organic carbon, soil aggregation, infiltration, porosity, subsurface leaching, and cash crop yield. Across all conservation management practices, surface runoff and erosion had respective mean decreases of 67% and 80% compared with controls. Use of cover cropping provided the largest decreases in erosion and surface runoff, thus emphasizing the importance of maintaining continuous vegetative cover on soils. Coarse- and medium-textured soils had greater decreases in both erosion and runoff than fine-textured soils. Changes in surface runoff and soil erosion under conservation management were highly correlated with soil organic carbon, aggregation, porosity, infiltration, leaching, and yield, showing that conservation practices help drive important interactions between these different facets of soil health. This study offers the first large-scale comparison of how different conservation agriculture practices reduce surface runoff and soil erosion, and at the same time provides new insight into how these interactions influence the improvement or loss of soil health.

58 GEOSCIENCES↗
DOE OSTI2023

Short-lead seasonal precipitation forecast in northeastern Brazil using an ensemble of artificial neural networks

This study assesses the deterministic and probabilistic forecasting skill of a 1-month-lead ensemble of Artificial Neural Networks (EANN) based on low-frequency climate oscillation indices. The predictand is the February-April (FMA) rainfall in the Brazilian state of Ceará, which is a prominent subject in climate forecasting studies due to its high seasonal predictability. Additionally, the study proposes combining the EANN with dynamical models into a hybrid multi-model ensemble (MME). The forecast verification is carried out through a leave-one-out cross-validation based on 40 years of data. The EANN forecasting skill is compared with traditional statistical models and the dynamical models that compose Ceará’s operational seasonal forecasting system. A spatial comparison showed that the EANN was among the models with the smallest Root Mean Squared Error (RMSE) and Ranked Probability Score (RPS) in most regions. Moreover, the analysis of the area-aggregated reliability showed that the EANN is better calibrated than the individual dynamical models and has better resolution than Multinomial Logistic Regression for above-normal (AN) and below-normal (BN) categories. It is also shown that combining the EANN and dynamical models into a hybrid MME reduces the overconfidence of the extreme categories observed in a dynamically-based MME, improving the reliability of the forecasting system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Finely Dispersed Micro- and Nano-Gold Recovery Using Thermomorphic Polymer with Diphenylphosphine

The article reports test data on adsorption and flotation characteristics of thermomorphic polymer joined with diphenylphosphine—TMPD. The test materials are natural pyrite and arsenopyrite, and models of gold-bearing sulfide minerals. Electron microscopy and X-ray structure analysis prove that reductive adsorption of gold at the surface of sulfide minerals from HAuCl{sub 4} solution allows modeling natural aggregates of sulfides and finely dispersed gold. UV spectrophotometry proves selective adsorption of TMPD at gold. Laser scanning microscopy shows connection of TMPD with micro- and nano-size gold on polished sections of pyrite and arsenopyrite. During monomineral flotation, joint use of TMPD and butyl xanthate at a ratio of 1:1 doubles the yield of gold-bearing sulfides and enables maximum recovery of gold minerals at the total consumption of reagents reduced by 30–50%. It is found that TMPD is selective relative to gold-bearing minerals and its combination with xanthate ensures a considerable increment in gold-bearing mineral recovery by flotation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

FrESCO

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information and summary statistics about cancer prevalence to facilitate population level monitoring of cancer incidence. Extracting cancer phenotype from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating this information extraction process from cancer pathology reports has the potential to improve not only the quality of the data by extracting information in a consistent manner across registries, but to improve the quality of patient outcomes by reducing the time to assimilate new data and enabling time-sensitive applications such as precision medicine. Here we present FrESCO: Framework for Exploring Scalable Computational Oncology, a modular deep-learning natural language processing (NLP) library for extracting pathology information from clinical text documents.

Spannaus, Adam [Oak Ridge National Lab. (ORNL), Oa↗
DOE OSTI2019

Development of Waste Inventory for Probabilistic Performance Assessment Modeling - 19361

Estimation of radioactive waste inventory is a key initial step in the development of an environmental fate and transport model for performance assessment (PA) of radioactive waste sites. PA model output is often sensitive to parameters that represent inventory as a source term, yet estimation is a difficult problem. Inventory estimation for a probabilistic performance assessment (PPA) is related to, but distinct from, that performed for waste excavation, characterization, and offsite disposal. The latter appropriately focuses on obtaining the most detailed information possible on specific hazards and locations; however, these questions cannot be fully answered without intrusive site characterization efforts. This type of characterization is often not feasible when assembling information regarding a source term in a PPA model. Development of waste inventory for a PPA is one piece of a larger hierarchical model. The physical process model represented by Goldsim computer code represents one level of the hierarchy, and the second level of the hierarchy involves estimation of inputs such as inventory, transport, and risk parameters. The estimation of inputs is not a straightforward problem. The parameters of a computer model often do not have an equivalence to the physical quantities they describe, and estimation of the physical quantities themselves can be difficult due to limitations of available information. Inventory information for the West Valley Site in upstate New York is based on data from historical shipping and disposal forms. In the 1990's, the West Valley Demonstration Project (WVDP) compiled information from existing databases and historical waste records into one complete modern database. A conceptual model was then applied and used with recorded information to characterize the waste mass and radionuclide composition for each waste burial. Information was ultimately aggregated over all waste records to estimate the mass of each radionuclide within each trench, hole, or caisson. Three decades later, we revisit the master database, make updates with newly-identified information, and incorporate the conceptual model previously used for inventory estimation in the hierarchical modeling framework. We characterize uncertainty using probability distributions for waste mass and radionuclide composition at the individual shipment or individual burial level. Uncertainty incorporated at the lowest level of the hierarchy is ultimately carried through to uncertainty in PPA model endpoints. Sensitivity analysis of early model results is then applied to identify influential inputs and guide subsequent efforts towards parameters that drive risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Gap-filled meteorological data (2011-2020) and modeled potential evapotranspiration data from the KCOMTCRE2 WeatherUnderground weather station, from the East River Watershed, Colorado

This dataset is a gap-filled meteorological dataset (years 2011-2020) that includes modeled potential evapotranspiration from a station near the pumphouse on the East River (KCOMTCRE2 WeatherUnderground ) near the top of the ridge at the Pumphouse PLM wells. These datasets are useful as model inputs. The KOMTCRE2 station is located on Mt. Crested Butte in Colorado. More information can be found at: https://www.wunderground.com/dashboard/pws/KCOMTCRE2/table/2020-12-7/2020-12-7/daily. The purpose of this dataset is to use as input to hydrological and flow-reactive transport models as meteorological forcing. One attached file includes metadata files with definitions for all variables and units. Subsequent files include the same time series dataset, but aggregated and gap-filled at different time-stamp intervals. These include 5 minute time-series, 15 minute time-series, 30 minute time-series, 1 hour time-series, daily time-series, and hourly and daily modeled evapotranspiration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Wavelet analysis of molecular dynamics: Efficient extraction of time-frequency information in ultrafast optical processes

New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet “complete” spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ultra-High-Performance Concrete And Advanced Manufacturing Methods For Modular Construction

Small modular reactors (SMR) allow for less onsite construction, increase nuclear material security, and provide a flexible and cost-effective energy alternative. SMR can be factory-built as modular components, and shipped to desired locations for fast assembly. This project successfully developed a new class of ultra-high performance concrete (UHPC), which features a compressive strength greater than 22 ksi (150 MPa) without special treatment and self-consolidating characteristics desired for SMR modular construction. With an ultra-high strength and dense microstructure, it will facilitate rapid construction of steel plate-concrete (SC) beams and walls with thinner and lighter modules, and can withstand harsh environments and mechanical loads anticipated during the service life of nuclear power plants. In addition, the self-consolidating characteristics are crucial for the fast construction and assembly of SC modules with reduced labor costs and improved quality. Following the UHPC material development, the capacity of producing self-consolidating UHPC in mass quantities was investigated and compared to accepted self-consolidating concrete standards. With slightly adjusted mixing procedure using large-scale gravity-based mixers (compared with small-scale force-based mixer), the self-consolidating UHPC has been successfully processed at six cubic yards; the product met both minimum compressive strength requirements and self-consolidating concrete standards. Steel plate-UHPC beams (15 ft. long, 12 in. wide and 16 in. deep) and wall panels (40 in. X 40 in. X 3 in.) were then constructed using the self-consolidating UHPC without any external vibration. Quality control guidelines for producing UHPC in large scale were developed. When the concrete is replaced by UHPC in a steel plate concrete (SC) beam, it is critical to evaluate its structural behavior with both flexure and shear-governed failure modes. In recent years, SC has been widely used for buildings and nuclear containment structures to resist lateral forces induced by severe earthquakes and heavy winds. SC modules have good potential for SMR because of their cost-effectiveness and reduced construction time. However, the minimum shear reinforcement (i.e. cross tie) ratio needs to be determined for the steel plate-UHPC (S-UHPC) beams to exhibit a ductile failure mode. In this project, S-UHPC beams were designed and constructed. The beams were tested to evaluate structural capacity and identify the minimum cross ties ratios. In addition, as the bond between UHPC and steel plate is essential for ensuring structural integrity under shear and flexure, it was measured and examined in this project through digital image correlation system and smart piezoelectric aggregate sensors. Large-scale testing and finite element simulation were also performed on S-UHPC wall panels. New bond slip-based constitutive models of steel plate were developed for S-UHPC, which were used in finite element analysis program to predict S-UHPC behavior under shear. The results were well validated through experimental data. The long-term durability of UHPC were established in this project. UHPC specimens were tested under free shrinkage, restrained shrinkage, elevated temperature, water permeation, chloride diffusion, corrosion, and alkali silica reaction. UHPC has demonstrated significantly improved durability compared with control concrete specimens. This research led to a new generation of steel plate-UHPC modules for SMR that can provide large benefits to the electric power industry. Taking advantage of the high strength and durability of UHPC, their modularity and ease of assembly can address the high cost barriers of typical nuclear power plants.

42 ENGINEERING↗
DOE OSTI2017

High Performance Data Transfer for Distributed Data Intensive Sciences

We report on the development of ZX software providing high performance data transfer and encryption. The design scales in: computation power, network interfaces, and IOPS while carefully balancing the available resources. Two U.S. patent-pending algorithms help tackle data sets containing lots of small files and very large files, and provide insensitivity to network latency. It has a cluster-oriented architecture, using peer-to-peer technologies to ease deployment, operation, usage, and resource discovery. Its unique optimizations enable effective use of flash memory. Using a pair of existing data transfer nodes at SLAC and NERSC, we compared its performance to that of bbcp and GridFTP and determined that they were comparable. With a proof of concept created using two four-node clusters with multiple distributed multi-core CPUs, network interfaces and flash memory, we achieved 155Gbps memory-to-memory over a 2x100Gbps link aggregated channel and 70Gbps file-to-file with encryption over a 5000 mile 100Gbps link.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Availability Estimates of Low-Cost, Dispatch-Constrained Electricity (LDE)

This dataset accompanies the report "Potential Availability of and Supply Curves for Low-Cost, Dispatch-Constrained Electricity", which provides initial estimates of the quantity and availability of the potential low-cost, dispatch-constrained electricity (LDE) resource in the United States under scenarios with high variable renewable energy (VRE) penetrations. The analysis also estimates supply curves that can be used in subsequent analysis of the opportunity to use the LDE. The estimated LDE resource could be used for various applications that value low-cost electricity and can operate at reduced capacity factors, including electrolytic hydrogen production and carbon capture. The analysis accompanying this dataset was performed in 2018-2019 to support an analysis of "The Technical and Economic Potential of the H2@Scale Concept within the United States" ( https://www.nlr.gov/docs/fy21osti/77610.pdf ). This dataset includes the quantity of estimated LDE resource for each hour of the year in 2050, aggregated to both the national level and the ReEDS balancing area level. As described in the accompanying report, the ReEDS model was used to project the evolution of the power sector over time. Links to the mapping of ReEDS balancing areas to states and ReEDS balancing area shape files are provided. This dataset also includes the report figure data.

08 HYDROGEN↗
DOE OSTI2013

Automated Translation and Thermal Zoning of Digital Building Models for Energy Analysis

Building energy simulation is valuable during the early stages of design, when decisions can have the greatest impact on energy performance. However, preparing digital design models for building energy simulation typically requires tedious manual alteration. This paper describes a series of five automated steps to translate geometric data from an unzoned CAD model into a multi-zone building energy model. First, CAD input is interpreted as geometric surfaces with materials. Second, surface pairs defining walls of various thicknesses are identified. Third, normal directions of unpaired surfaces are determined. Fourth, space boundaries are defined. Fifth, optionally, settings from previous simulations are applied, and spaces are aggregated into a smaller number of thermal zones. Building energy models created quickly using this method can offer guidance throughout the design process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Variability in Wind Energy Generation across the Contiguous United States

ERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Additionally, gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

17 WIND ENERGY↗
DOE OSTI2016

The transcriptional regulator c2h2 accelerates mushroom formation in Agaricus bisporus

The Cys2His2 zinc finger protein gene c2h2 of Schizophyllum commune is involved in mushroom formation. Its inactivation results in a strain that is arrested at the stage of aggregate formation. In this study, the c2h2 orthologue of Agaricus bisporus was over-expressed in this white button mushroom forming basidiomycete using Agrobacterium-mediated transformation. Morphology, cap expansion rate, and total number and biomass of mushrooms were not affected by overexpression of c2h2. However, yield per day of the c2h2 overexpression strains peaked 1 day earlier. These data and expression analysis indicate that C2H2 impacts timing of mushroom formation at an early stage of development, making its encoding gene a target for breeding of commercial mushroom strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems

Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗
DOE OSTI2013

CAN WE REPRODUCE THE X-RAY BACKGROUND SPECTRAL SHAPE USING LOCAL ACTIVE GALACTIC NUCLEI?

The X-ray background (XRB) is due to the aggregate of active galactic nuclei (AGNs), which peak in activity at z {approx} 1 and is often modeled as the sum of different proportions of unabsorbed, moderately, and heavily absorbed AGN. We present the summed spectrum of a complete sample of local AGN (the Northern Galactic Cap of the 58 month Swift/BAT catalog, z < 0.2) using 0.4-200 keV data and directly determine the different proportions of unabsorbed, moderately and heavily absorbed AGN that make up the summed spectrum. This stacked low redshift AGN spectrum is remarkably similar in shape to the XRB spectrum (when shifted to z {approx} 1), but the observed proportions of different absorption populations differ from most XRB synthesis models. AGN with Compton-thick absorption account for only {approx}12% of the sample, but produce a significant contribution to the overall spectrum. We confirm that Compton reflection is more prominent in moderately absorbed AGN and that the photon index differs intrinsically between unabsorbed and absorbed AGN. The AGN in our sample account for only {approx}1% of the XRB intensity. The reproduction of the XRB spectral shape suggests that strong evolution in individual AGN properties is not required between z {approx} 0 and 1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Exploring the Feasibility of a Carbon Dioxide Storage Hub in Western North Dakota

The University of North Dakota Energy & Environmental Research Center (EERC) and project partner ONEOK, Inc. (ONEOK) are investigating the feasibility of establishing a CO2 (carbon dioxide) storage hub in western North Dakota—in the heart of the Williston Basin. The conceived Roughrider Carbon Storage Hub would store CO2 captured from six gas-processing plants owned and operated by project partner ONEOK and a planned gas-to-liquids plant. This 2-year U.S. Department of Energy-sponsored Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Phase II feasibility study is evaluating the aggregation of the CO2 captured from these seven sources for injection into stacked geologic storage complexes. The proposed hub includes several aspects that make it a highly qualified candidate for a feasibility study with a notably reduced project risk profile. These include 1) a project partner (ONEOK) with a committed goal to reduce greenhouse gas emissions; 2) prior subsurface data analysis supporting a potential stacked storage configuration with adequate CO2 storage resource; 3) commitment from local, regional, and state-level stakeholders; and 4) a state with U.S. Environmental Protection Agency underground injection control Class VI primacy. ONEOK’s assets in the Williston Basin provide significant environmental benefits by capturing and processing natural gas that may otherwise be flared or vented. Storing CO2 from these gas-processing facilities will reduce overall CO2 emissions in the basin while providing essential services to producers there and contributing to continued energy independence in the domestic markets.

03 NATURAL GAS↗