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At least 343 records · Page 19

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DOE OSTI2024

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗

DOE OSTI2021

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗

DOE OSTI2022

Out of Distribution Detection with Neural Network Anchoring

This is code to reproduce and build on OOD detection from the paper "Out of Distribution Detection with Neural Network Anchoring". Our goal here is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable this, we propose a new training strategy called anchoring that can estimate appropriate temperature values for each sample, leading to state-of-the-art OOD detection performance across several benchmarks. Using NTK theory, we show that this temperature function estimate is closely linked to the epistemic uncertainty of the classifier, which explains its behavior. In contrast to some of the best-performing OOD detection approaches, our method does not require exposure to additional outlier datasets, custom calibration objectives, or model ensembling. Through empirical studies with different OOD detection settings - far OOD, near OOD, and semantically coherent OOD - we establish a highly effective OOD detection approach.

Thiagarajan, Jayaraman↗

DOE OSTI2025

Activation Domain Hunter (ADhunter) v2.0

ADhunter is a software program that enables accurate identification and quantification of transcriptional activation domains. Unlike previous software, ADhunter uses protein representations from a pre-trained protein language model, model ensembling, and a training dataset from a diverse sampling of protein sequence space for state-of-the-art performance. These advantages enable improved perception of transcriptional activation domains across sequence space that can be used for mapping natural genetic circuits and engineering synthetic genetic circuits. In particular, ADhunter enables fine-tuned control of gene expression through synthetic transcription factors that can be used for complex control of cellular programs.

Waldburger, Lucas [Lawrence Berkeley National Labo↗

DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

58 GEOSCIENCES↗

DOE OSTI2024

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗

DOE OSTI2020

Distinct responses of Asian summer monsoon to black carbon aerosols and greenhouse gases

Black carbon (BC) aerosols emitted from natural and anthropogenic sources induce positive radiative forcing and global warming, which in turn significantly affect the Asian summer monsoon (ASM). However, many aspects of the BC effect on the ASM remain elusive and largely inconsistent among previous studies, which is strongly dependent on different low-level thermal feedbacks over the Asian continent and the surrounding ocean. This study examines the response of the ASM to BC forcing in comparison with the effect of doubled greenhouse gases (GHGs) by analyzing the Precipitation Driver Response Model Intercomparison Project (PDRMIP) simulations under an extremely high BC level (10 times modern global BC emissions or concentrations, labeled BC×10) from nine global climate models (GCMs). The results show that although BC and GHGs both enhance the ASM precipitation minus evaporation (P–E; a 13.6 % increase for BC forcing and 12.1 % for GHGs from the nine-model ensemble, respectively), there exists a much larger uncertainty in changes in ASM P–E induced by BC than by GHGs. The summer P–E is increased by 7.7 % to 15.3 % due to these two forcings over three subregions, including East Asian, South Asian and western North Pacific monsoon regions. Further analysis of moisture budget reveals distinct mechanisms controlling the increases in ASM P–E induced by BC and GHGs. The change in ASM P–E by BC is dominated by the dynamic effect due to the enhanced large-scale monsoon circulation, whereas the GHG-induced change is dominated by the thermodynamic effect through increasing atmospheric water vapor. Radiative forcing of BC significantly increases the upper-level atmospheric temperature over the Asian region to enhance the upper-level meridional land–sea thermal gradient (MLOTG), resulting in a northward shift of the upper-level subtropical westerly jet and an enhancement of the low-level monsoon circulation, whereas radiative forcing of GHGs significantly increases the tropical upper-level temperature, which reduces the upper-level MLOTG and suppresses the low-level monsoonal circulation. Hence, our results indicate a different mechanism of BC climate effects under the extremely high BC level: that BC forcing significantly enhances the upper-level atmospheric temperature over the Asian region, determining ASM changes, instead of low-level thermal feedbacks as indicated by previous studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Distinct responses of Asian summer monsoon to black carbon aerosols and greenhouse gases

Black carbon (BC) aerosols emitted from natural and anthropogenic sources induce positive radiative forcing and global warming, which in turn significantly affect the Asian summer monsoon (ASM). However, many aspects of the BC effect on ASM remain elusive and largely inconsistent among previous studies, which is strongly dependent on different low-level thermal feedbacks over the Asian continent and the surrounding ocean. This study examines the response of ASM to BC forcing in comparison with the effect of doubled greenhouse gases (GHGs) by analyzing the Precipitation Driver Response Model Intercomparison Project (PDRMIP) simulations under an extreme high BC level (10 times modern global BC emissions or concentrations, labeled by BC $\times$ 10) from nine global climate models (GCMs). The results show that although BC and GHGs both enhance the ASM precipitation minus evaporation (P–E) (a 13.6 % increase for BC forcing and 12.1 % for GHGs from the nine-model ensemble, respectively), there exists a much larger uncertainty in changes in ASM P–E induced by BC than by GHGs. The summer P–E is increased by 7.7 % to 15.3 % due to these two forcings over three sub-regions including East Asian, South Asian, and western North Pacific monsoon regions. Further analysis of moisture budget reveals distinct mechanisms controlling the increases in ASM P–E induced by BC and GHGs. The change in ASM P–E by BC is dominated by the dynamic effect due to the enhanced large-scale monsoon circulation, whereas the GHG-induced change is dominated by the thermodynamic effect through increasing atmospheric water vapor. Radiative forcing of BC significantly increases the upper-level atmospheric temperature over the Asian region to enhance the upper-level meridional land-sea thermal gradient (MLOTG), resulting in a northward shift of the upper-level subtropical westerly jet and an enhancement of the low-level monsoon circulation; whereas radiative forcing of GHGs significantly increases the tropical upper-level temperature, which reduces the upper-level MLOTG and suppresses the low-level monsoonal circulation. Hence, our results indicate a different mechanism of BC climate effects under the extreme high BC level, that BC forcing significantly enhances the upper-level atmospheric temperature over the Asian region, determining ASM changes, instead of low-level thermal feedbacks as indicated by previous studies.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

The modification and application of Kuo's parameterization of cumulus convection in middle latitudes

An evaluation to reveal physical insight into the involved mechanisms through a combination of the large scale heat and moisture budgets and formulation of the latent heat released was performed. To improve upon the treatment of the interaction of deep convection with the environment, modifications consisting of considerations of the large scale moisture supply and of the vertical transport of moisture and of dry static energy inside the cloud are made. Also, a two layer cloud ensemble model is combined with the modified scheme. An examination of the modified scheme is performed by combining the large scale heat and moisture budgets and the modified formulation of the latent heat released. The modified parameterization procedures are compared with the original scheme, and the results of tests of both schemes are discussed. A variational optimization scheme is developed to analyze the wind field such that the integrated continuity equation and the global boundary condition are satisfied.

Liang, W. J.↗

NASA NTRS1982

Interaction of a cumulus cloud ensemble with the large-scale environment. III - Semi-prognostic test of the Arakawa-Schubert cumulus parameterization

The verification of the Arakawa and Schubert (1974) cumulus parameterization is continued using a semiprognostic approach. Observed data from Phase III of GATE are used to provide estimates of the large-scale forcing of a cumulus ensemble at each observation time. Instantaneous values of the precipitation and the warming and drying due to cumulus convection are calculated using the parameterization. The results show that the calculated precipitation agrees very well with estimates from the observed large-scale moisture budget and from radar observations. The calculated vertical profiles of cumulus warming and drying also are quite similar to the observed. It is shown that the closure assumption adopted in the parameterization (the cloud-work function quasi-equilibrium) results in errors of generally less than 10% in the calculated precipitation. The sensitivity of the parameterization to some assumptions of the cloud ensemble model and the solution method for the cloud-base mass flux is investigated.

Lord, S. J.↗

NASA NTRS1984

A numerical study of the vertical transport of momentum in a tropical rainband

The vertical transport of horizontal momentum in a convective tropical rainband is studied using a two-dimensional cloud ensemble model. Twelve simulations are made under the same large-scale conditions. The vertical transports of v momentum (parallel to the rainband) are essentially the same in all of the simulations, even though the structure of the clouds is different in each of the runs. The magnitude of the v-momentum transport by clouds is fairly large. It takes only half of a day to smooth out the tropical low-level easterly jet parallel to the rainband if no other processes are operating. The vertical transports of u momentum (perpendicular to the rainband) are quite different in all of the simulations. This difference can be explained by the dissimilarities in the distributions of horizontal momentum associated with various cloud configurations. The simulated vertical transports of horizontal momentum are compared with those computed with the Schneider and Lindzen scheme. The results suggest that their scheme is basically correct and usable if some improvements are made.

Soong, S.-T.↗

NASA NTRS1985

Response of cumulus clouds to large-scale forcing and cumulus parameterization

Using the cumulus ensemble model (Soong and Ogura, 1980), statistical properties of cumulus clouds that occur in response to the imposed large scale forcing were investigated both in the tropical and midlatitude situtations. A strong drying process was found to occur in the boundary layer in association with deep convection in a midlatitude case. The Arakawa-Schubert (1974) cumulus parameterization scheme was tested semi-prognostically against both the model result and the observation in a tropical rain event that occurred in GATE. The Cloud heating and drying effects predicted by the Arakawa-Schubert scheme were found to agree well both with the observation and the model result. However, it was also found that the Arakawa-Schuber scheme underestimates both condensation and evaporation rates substantially. An inclusion of the downdraft effect, as formulated by Johnson (1976), appears to alleviate this deficiency. This downdraft effect may be important in predicting the behavior of the boundary accurately.

Ogura, Y.↗

NASA NTRS1987

Statistical properties of a cloud ensemble - A numerical study

The statistical properties of cloud ensembles under a specified large-scale environment, such as mass flux by cloud drafts and vertical velocity as well as the condensation and evaporation associated with these cloud drafts, are examined using a three-dimensional numerical cloud ensemble model described by Soong and Ogura (1980) and Tao and Soong (1986). The cloud drafts are classified as active and inactive, and separate contributions to cloud statistics in areas of different cloud activity are then evaluated. The model results compare well with results obtained from aircraft measurements of a well-organized ITCZ rainband that occurred on August 12, 1974, during the Global Atmospheric Research Program's Atlantic Tropical Experiment.

Tao, Wei-Kuo↗

NASA NTRS1990

The application of optical potentials for reactive scattering - A case study

A precise method is presented for measuring decay fractions of metastable cluster ions with corrections concerning instrumental artifacts and ion trajectory of parents and daughters. Experimental data are used to derive the Gspann parameter and heat capacity of clusters as described in Klots' evaporative ensemble model. The model is applied to obtain binding energies of ammonia cluster ions. The deduced binding energy values are in very good agreement with both thermochemical data and Engelking's (1986) modified statistical theory.

Neuhauser, Daniel↗

NASA NTRS1990

Triplets of galaxies: Their dynamics, evolution, and the origin of chaos in them

Recently Karachentsev's group at The Smithsonian Astrophysical Observatory (SAO) (6-meter Telescope Observatory) published a list of 84 triple systems of galaxies with their distances, radial (line of sight) velocities, and angular sizes (Karachentseva et al., 1988). This gives a new ground for studies of the dark matter problem which fills the gap between the large cosmic scales (White, 1987; Dekel and Rees, 1987, and Einasto et al., 1977) and the scale of individual galaxies (Erickson et al., 1987). The data on the typical velocity dispersions and linear dimension of the triplets indicate that they contain considerable amounts of dark matter (see also earlier work of Karachentseva et al., 1979). Numerical simulations show that the statistical characteristics of the Karachentsev triplets can be imitated by model ensembles of triple systems with dark matter masses M sub d = (1-3 x 10(exp 12) M sub O, which is almost ten times greater than the typical mass of stellar galaxies estimated by the standard mass-to-luminosity ration (Kiseleva and Chernin, 1988). Here, the authors report that important information can be drawn from the data on the visible configurations of these systems. The statistics of configurations provide an independent evidence for dark matter in the triplets; moreover, it enables one to argue that dark matter seems to be distributed over the whole volume of the typical triplet forming its common corona rather than concentrated within individual coronae (or haloes) of the member galaxies.

Chernin, Arthur D.↗

NASA NTRS1992

Semiprognostic tests of the Arakawa-Schubert cumulus parameterization using simulated data

Semiprognostic tests are performed against data simulated by a cumulus ensemble model to evaluate the Arakawa-Schubert (A-S) cumulus parametrization. It is found that the A-S cumulus parametrization is generally valid despite the existence of mesoscale organization in cumulus convection. The nondiagnostic and nondeterministic aspects of the A-S cumulus parametrization are examined by testing the sensitivity of the parametrization to the horizontal grid resolution. It is also shown that the inclusion of convective-scale downdrafts improves the results of semiprognostic tests.

Xu, Kuan-Man↗

NASA NTRS1991

Comparison of numerically-simulated microphysical characteristics of convective storms with multiparameter radar observations during COHMEX

The microphysical/dynamical nature and evolution of numerically simulated convective storms observed on July 11, 1986 during the Cooperative Huntsville Meteorological Experiments are investigated with the Goddard Cumulus Ensemble model. The model-simulated hydrometeor and radar reflectivity structure is verified with results derived from the multiparameter radar observations, which includes a description of the reflectivity, differential reflectivity, linear depolarization ratio, and hail signal for two thunderstorm cases analyzed by Fulton and Heymsfield (1990). Radar analysis shows the storm to split with the newer more vigorous cell in the SE quadrant. Echo tops are near 15 km while peak reflectivities exceed 50 dBZ. Preliminary model simulations likewise show a splitting storm with regeneration occurring on the SSE flank. Echo tops are around 14 km with peak reflectivities over 45 dBZ.

Tao, W.-K.↗