Diving deep into microbial genomic data – big findings in small microbes
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Biological Science↗
SEARCH · Engineering Papers
Results for “big”
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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DEVELOPMENT OF BIG-DATA EDGE-COMPUTING ANALYTIC FRAMEWORK FOR DISTRIBUTED FIBER OPTIC SENSORS
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02 PETROLEUM↗
Ab Initio Prediction of alpha(d, gamma)6Li At Big Bang Nucleosynthesis Energies
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Physics - Nuclear physics and radiation physics↗
Applications in Energy and Combustion Science BLASTNet: A Call for Community-Involved Big Data in Combustion Machine Learning.
Abstract not provided.
Chung, Wai Tong↗
Context-aware Neural-accelerated Visualization Pipeline for Big Volumetric Data
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Shadi, Kamal↗
Big Data and AI at DoE's Legacy Sites - 20546
More than 30 years have passed since DOE started the decommissioning of nuclear weapon complexes and the clean-up of soil and groundwater. All the sites have been collecting and archiving soil and groundwater monitoring datasets; particularly contaminant concentration time-series. These datasets provide unparalleled opportunities to understand the system behavior (including more fundamental hydrological and geochemical processes, the response to various perturbations, the long-term trend and environmental decay rate towards the regulatory limit). This understanding is critical for providing multiple lines of evidences that can support site closure. In this study, we explore the machine learning (ML) and artificial intelligence (AI) applications to the long-term soil and groundwater management at DoE's legacy sites. ML can improve our understanding of the subsurface systems, which is critical for long-term monitoring and management of the sites, while AI can automate or support some of decision-making processes (e.g., anomaly detection, monitoring well placements). The particular focuses are to develop general algorithms to: (1) to identify distinct spatiotemporal patterns and to identify several groups that have similar temporal behaviors, using unsupervised clustering methods, (2) identify the different temporal scales of hydrological responses to climate perturbations by time-series analysis, and (3) reduce the number of monitoring wells by identifying the minimum sufficient number of wells to capture the heterogeneity of the groundwater contaminant plume and concentration distribution, using the Gaussian Process model. We demonstrate our methodology at the Savannah River Site F-Area. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Experimental Quantum Chromodynamics at LANL. A deep look on how complicated quarks and gluons behave inside protons and in a Big-Bang matter.
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Atomic, Nuclear and Particle Physics↗
Field Study of 120-volt Heat Pump Water Heaters in the Big Easy
To meet long-term goals for reducing carbon emissions and lessen the impacts of climate change, the U.S. plans to decarbonize its building stock, which includes the replacement of fossil fuel-burning end uses with energy efficient electric alternatives. As part of this strategy, the replacement of fossil fuel water heaters with heat pump water heaters (HPWH) has the potential to avoid substantial carbon emissions. An estimated 10-15 million single-family homes with fossil fuel water heaters do not have the electrical panel capacity to install a 240-volt, 30-amp HPWH. For these homes, a technology recently introduced to the market, the 120-volt plug-in HPWH, can provide energy efficient electrification of water heating without an expensive panel and wiring retrofit. This paper presents the results of an ongoing 120-volt HPWH field study conducted in 17 homes in New Orleans, LA. Key installation scenarios are profiled for retrofitting from gas-fired water heaters to 120-volt HPWHs, accounting for space, air volume, air temperature, condensate drainage, and electrical. Each HPWH had its surrounding air temperature, relative humidity, inlet and outlet water temperature, flow, and energy consumption monitored. Using these data, hot water delivery and energy efficiency performance were analyzed based on home characteristics. Hot water run outs were investigated to understand how hot water usage, inlet water temperature, and surrounding air temperature impact the HPWH’s ability to meet load. From these results, best practices for 120-volt HPWH siting, sizing, and installation were developed. In addition, results are explored further to add insight for electrification policies and product development.
heat pump water heater, 120-volt, Residential buil↗
Individual Data Sparsity in Smart Thermostat Big Data: Impacts on Modeling Thermostat Use Behavior Dynamics
This study explores the impacts of the sparsity of individual thermostat interaction data on modeling thermostat use behavior dynamics using a dataset of over 100,000 smart thermostats. In developing a data-driven model of Thermal Frustration Theory (TFT), we investigate the challenges and trade-offs in clustering occupant data to enhance predictive accuracy. Our findings reveal that a single, aggregated model fails to capture the diversity of occupant behaviors, resulting in extremely poor prediction performance. Conversely, excessive clustering exacerbates data sparsity, undermining model reliability. By identifying an optimal clustering strategy, we achieve a balance that significantly improves the prediction of manual setpoint changes during demand response (DR) events, enhancing energy management and occupant comfort
Fannon, David↗
Chemistream: Big Data Materials on HPC Clouds
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cloud computing↗
Trends in actinide electronic structure revealed from asymmetric, isostructural transuranic metallocenes
The study of actinide electronic structure and bonding within rigorously controlled environments is fundamental to advancing nuclear applications. Here, we report a new set of isostructural actinide organometallics; An(COT big ) 2 , (An = Th, U, Np, and Pu), where COT big is the bulky 1,4-bis(triphenylsilyl)-substituted cyclooctatetraenyl dianion (1,4-(Ph 3 Si) 2 C 8 H 6 ) 2 -. The actinide(IV) metallocene sandwiches have a clam-shell structure, offering a new molecular symmetry to explore f-orbital contributions in bonding. Combined experimental and computational studies reveal that An(COT big ) 2 complexes strongly differ from the previously published coplanar An(COT) 2 sandwiches due to the bent geometry and electron-withdrawing nature of the substituents. While COT big displays comparatively weaker electron donation, the low-energy f-f transitions in An(COT big ) 2 have increased molar absorptivity consistent with the removal of the parity selection rule and better energetic matching between ligand and actinide 5f orbitals as the series is traversed. For Pu(COT big ) 2 , covalent mixing of donor 5f metal orbitals and the ligand-π orbitals is especially strong.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint
The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.
access↗
Hybrid Absorption–Crystallization Strategies for the Direct Air Capture of CO2 Using Phase-Changing Guanidium Bases: Insights from in Operando X-ray Scattering and Infrared Spectroscopy Measurements
Efforts to limit rising concentrations of CO 2 have motivated the development of negative emission technologies. Direct air capture (DAC) of CO 2 is one of the negative emissions technologies that has been proposed for the direct removal of CO 2 from the atmosphere. Phase-changing bis(iminonoguanidine) (BIG) sorbents have been developed for the direct air capture of CO 2 . These phase changing sorbents, specifically glyoxal-bis(iminoguanidine) (GBIG), involve (1) CO 2 absorption with aqueous amino acid salts, such as K- or Na-glycinate to yield bicarbonate-rich solutions, (2) crystallization of the bicarbonate anions with a BIG solid, which regenerates the amino acid, and (3) solid-state CO 2 release from the carbonate crystals and BIG regeneration. Despite the promising potential of these materials, their structural evolution during the thermal regeneration of the BIG solids, chemical regeneration of the sodium or potassium glycinate solvents, and the crystallization behavior of CO 2 -loaded BIG bicarbonate remain to be evaluated and understood in detail. The aim of this study is to probe these knowledge gaps. In situ wide-angle X-ray Scattering (WAXS) results show that CO 2 and water molecules in GBIG bicarbonate are simultaneously released in a single step during the thermal regeneration of the sorbent at 97 – 134 °C. In situ ATR-FTIR measurements showed that sodium glycinate and GBIG bicarbonate are simultaneously generated when GBIG, glycine, and sodium bicarbonate are reacted. The crystallization of GBIG bicarbonate from GBIG and CO 2 -loaded monoethanolamine (MEA) occurs rapidly in the first 10 min of the reaction, as determined using in situ GI-SAXS measurements. Overall, the insights from these studies are essential for the scalable implementation of CO 2 capture technologies using these phase-changing sorbents.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Root traits of perennial C 4 grasses contribute to cultivar variations in soil chemistry and species patterns in particulate and mineral‐associated carbon pool formation
Abstract Recent studies have indicated that the C 4 perennial bioenergy crops switchgrass ( Panicum virgatum ) and big bluestem ( Andropogon gerardii ) accumulate significant amounts of soil carbon (C) owing to their extensive root systems. Soil C accumulation is likely driven by inter‐ and intraspecific variability in plant traits, but the mechanisms that underpin this variability remain unresolved. In this study we evaluated how inter‐ and intraspecific variation in root traits of cultivars from switchgrass (Cave‐in‐Rock, Kanlow, Southlow) and big bluestem (Bonanza, Southlow, Suther) affected the associations of soil C accumulation across soil fractions using stable isotope techniques. Our experimental field site was established in June 2008 at Fermilab in Batavia, IL. In 2018, soil cores were collected (30 cm depth) from all cultivars. We measured root biomass, root diameter, specific root length, bulk soil C, C associated with coarse particulate organic matter (CPOM) and fine particulate organic matter plus silt‐ and clay‐sized fractions, and characterized organic matter chemical class composition in soil using high‐resolution Fourier‐transform ion cyclotron resonance mass spectrometry. C 4 species were established on soils that supported C 3 grassland for 36 years before planting, which allowed us to use differences in the natural abundance of stable C isotopes to quantify C 4 plant‐derived C. We found that big bluestem had 36.9% higher C 4 plant‐derived C compared to switchgrass in the CPOM fraction in the 0–10 cm depth, while switchgrass had 60.7% higher C 4 plant‐derived C compared to big bluestem in the clay fraction in the 10–20 cm depth. Our findings suggest that the large root system in big bluestem helps increase POM‐C formation quickly, while switchgrass root structure and chemistry build a mineral‐bound clay C pool through time. Thus, both species and cultivar selection can help improve bioenergy management to maximize soil carbon gains and lower CO 2 emissions.
60 APPLIED LIFE SCIENCES↗
Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository
The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.
access↗
Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy
Solar-induced chlorophyll fluorescence (SIF) has long been regarded as a proxy for photosynthesis and has shown superiority in estimating gross primary production (GPP) compared to traditional vegetation indices, especially in evergreen ecosystems. However, current SIF-based GPP estimations regard the canopy as a large leaf and seldom consider the impact of interactions among light, canopy structure, and leaf physiology. In this study, we proposed GPP estimation models with different descriptions of light–structure–physiology interactions (including the layered model, the two-leaf model, and the layered two-leaf model) and compared their performances with the big-leaf model using half-hourly (or hourly) observations at evergreen needleleaf forest sites. First, we found that the big-leaf model underestimated GPP, especially at noon. All models showed higher accuracy than that of the big-leaf model. Second, we investigated the diurnal dynamics of GPP estimations in each canopy layer and found that models with a two-leaf assumption captured the diurnal variations in GPP better than that with the layered assumption. Here we also deduced that the poor performance of the big-leaf model was related to its overestimation of the overall light stress on the redox state of PSII reaction centers (qL). Finally, we noticed that the qL at the canopy scale had lower sensitivity to light change than the single-leaf qL and that the light response of canopy-scale qL was influenced by the leaf area index during seasonal cycles. Overall, this study describes methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale. Further, it indicates the need to consider the description of light distribution within the canopy in next-generation terrestrial biosphere models, even if they incorporate SIF to constrain their parameterization. Thus, upscaling the established leaf-scale mechanistic SIF-GPP relationship or findings to canopy-scale applications still requires much work, especially when there are significant changes in environmental conditions and their within-canopy distributions.
59 BASIC BIOLOGICAL SCIENCES↗