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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Integrating Mercury Concentrations in American Alligators ( Alligator mississippiensis ) with Hunter Consumption Surveys to Estimate Exposure Risk

Mercury is a naturally occurring element but is also considered a widespread contaminant due to global anthropogenic activity. Even in moderate amounts, mercury (Hg) is an established neurotoxin and is associated with a range of adverse outcomes both in humans and wildlife. Humans in the United States are most commonly exposed to Hg through contaminated food or drinking water, and the consumption of game species, particularly those occupying higher trophic levels, has the potential to expose hunters to high concentrations of Hg. In the present study, we determined Hg concentrations in tail muscle and blood from American alligators (Alligator mississippiensis) inhabiting a region (Savannah River Site, SC, USA) with known Hg contamination. We then integrated these data with alligator harvest records and previously published surveys of alligator meat consumption patterns to estimate potential exposure risk. We found that the average Hg concentrations in tail muscle (1.34 mg/kg, wet wt) from sampled alligators exceeded the recommended threshold for Hg exposure based on the World Health Organization's guidelines (0.5mg/kg, wet wt). In addition, based on regional consumption patterns reported for both adults and children, we estimated Hg exposures (x¯ Adult = 0.419 μg/kg/day, x¯ Child = 2.24 μg/kg/day) occurring well above the US Environmental Protection Agency methylmercury reference dose of 0.1 μg/kg/day. Although the two reservoirs sampled in the present study are not currently open to alligator hunting, they are connected to waters that are publicly accessible, and the extent of alligator mobility across these sites is not known. Together, the findings reported in the present study further demonstrate the need for active monitoring of Hg concentrations in game species, which can convey substantial exposure risks to the public.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Alcohol consumption and breast cancer risk in Japan: A pooled analysis of eight population‐based cohort studies

Abstract Although alcohol consumption is reported to increase the incidence of breast cancer in European studies, evidence for an association between alcohol and breast cancer in Asian populations is insufficient. We conducted a pooled analysis of eight large‐scale population‐based prospective cohort studies in Japan to evaluate the association between alcohol (both frequency and amount) and breast cancer risk with categorization by menopausal status at baseline and at diagnosis. Estimated hazard ratios (HR) and 95% confidence intervals were calculated in the individual cohorts and combined using random‐effects models. Among 158 164 subjects with 2 369 252 person‐years of follow‐up, 2208 breast cancer cases were newly diagnosed. Alcohol consumption had a significant association with a higher risk of breast cancer in both women who were premenopausal at baseline (regular drinker compared to nondrinker: HR 1.37, 1.04‐1.81, ≥23 g/d compared to 0 g/d: HR 1.74, 1.25‐2.43, P for trend per frequency category: P = .017) and those who were premenopausal at diagnosis (≥23 g/d compared to 0 g/d: HR 1.89, 1.04‐3.43, P for trend per frequency category: P = .032). In contrast, no significant association was seen in women who were postmenopausal at baseline or at diagnosis, despite a substantial number of subjects and long follow‐up period. Our results revealed that frequent and high alcohol consumption are both risk factors for Asian premenopausal breast cancer, similarly to previous studies in Western countries. The lack of a clear association in postmenopausal women in our study warrants larger investigation in Asia.

Iwase, Madoka↗
DOE OSTI2025

Microbial O 2 consumption as a function of pore structure in soils of sorghum, switchgrass, and prairie vegetation systems

Abstract Microscale O 2 availability in soil, a main factor influencing microbial processing of soil carbon and nitrogen, is a function of O 2 diffusion and microbial O 2 consumption. While O 2 diffusivity is widely studied, it is difficult to quantify the rate of microbial O 2 consumption ( MO ). In this study, we quantified the MO using O 2 microsensor profiling to compare MO in different soils and vegetation systems while manipulating the soil pore structure. Soil samples were collected from three bioenergy vegetation systems, sorghum ( Sorghum bicolor L. Moench), switchgrass ( Panicum virgatum L.), and prairie, at an experimental site in Southeast Michigan, and from switchgrass and prairie systems at two sites in South and North Wisconsin. We prepared soil cores with two contrasting pore structures, that is, large (>30 µm Ø) pore‐dominated soil (LP) and small (<10 µm Ø) pore‐dominated soil (SP), from the same 1‐ to 2‐mm soil size fraction. We quantified MO (nmol O 2 cm −3 s −1 ) using a microprofiler with an oxygen (OX‐100 µm) microsensor (Unisense) pre‐ and post‐38‐day incubation. Across all studied systems, there was a trend for a decrease in SP MO post‐incubation, suggesting a change in microbial metabolism to lower O 2 utilization. However, sizeable microbial O 2 consumption continued in the LP soils, further corroborated by a positive correlation between the C‐CO 2 emission rate and the post‐incubation MO , highlighting that LP provided a better physical microenvironment for the soil microbes.

Chakraborty, Poulamee [Department of Plant Soil an↗
DOE OSTI2023

Deep Reinforcement Learning Based Smart Water Heater Control for Reducing Electricity Consumption and Carbon Emission

Water heating is the third largest electricity consumer in U.S. households, after space heating and cooling. Thus, water heaters represent a significant potential for reducing electricity consumption and associated CO2 emissions of residential buildings. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity consumption and the CO2 emissions of a heat pump water heater without affecting user comfort. In this approach, a set of RL agents focusing on either electricity saving or emission reduction, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on different hot water usage and Marginal Operating Emissions Rate (MOER) profiles. The testing results showed that the RL agents that focus on electricity saving can save electricity in the range of 12–22% by operating the water heater with maximum heat pump efficiency and minimum electric element utilization. On the other hand, the RL agents that focus on emission reduction reduced emissions in the range of 18–37% by making use of the variable MOER values. These RL agents used the heat pump and/or an element when the MOER values are low due to the availability of renewable energy sources (e.g., solar and wind) and mostly avoided the periods of carbon-intensive periods. Overall, these results showed that the proposed RL approach can help minimize the electricity consumption and the CO2 emissions of a heat pump water heater without having any prior knowledge about the device.

Amasyali, Kadir↗
DOE OSTI2019

Effect of solvent fractionation pretreatment on energy consumption of cellulose nanofabrication from switchgrass

Lignin-containing cellulose nanofibers (L-CNFs) with various lignin contents were produced by a grinding process from switchgrass, which were pretreated using organosolv fractionation. The effect of different fractionation conditions (temperature and time) and different number of grinder passes on the energy consumption and morphologies of L-CNFs were investigated. Results revealed that nanosized fibers were found in organosolv-fractionated samples before grinding. After several grinding passes, L-CNFs with a similar degree of fibrillation as commercial cellulose nanofibers (CNF) were obtained from the fractionated materials. It is beneficial to save energy consumption in the grinding process. The dimensions and dispersion of L-CNFs were significantly influenced by the lignin content in the L-CNFs. Longer and well-separated nanofibrils were observed from transmission electron microscopy and fluorescence microscopy with appropriate residual lignin (~ 13.7 ± 1.59%) in the L-CNFs compared to those of L-CNFs with either lower or higher lignin contents. Thus, microsized and nanosized lignin particles were successfully obtained in a single process, and they not only facilitated L-CNFs dispersion but also help to decrease the energy consumption during the grinding process.

09 BIOMASS FUELS↗
DOE OSTI2018

miR-124-3p affects the formation of intramuscular fat through alterations in branched chain amino acid consumption in sheep

Highlights: • BCKDHA gene is a target gene of miR-124-3p. • miR-124-3p inhibits the adipogenic differentiation of stromal vascular fractions. • Branched chain amino acids consumption is vital for the adipogenic differentiation of stromal vascular fractions. Intramuscular fat is used to determine meat quality in animals; however, factors affecting branched chain amino acid (BCAA) catabolism, which fuels adipogenesis and lipogenesis, remain unclear. To better understand the post-transcriptional influence on BCAA catabolism during adipogenesis, we investigated the role of miR-124-3p. Stromal vascular fraction (SVF) cells were isolated from skeletal muscle of sheep, and induced to differentiate. We determined the roles of miR-124-3p and its predicted target, branched chain keto acid dehydrogenase E1, alpha polypeptide (BCKDHA), in adipogenic differentiation and lipogenesis of SVFs after overexpressing or inhibiting miR-124-3p or BCKDHA, respectively. miR-124-3p altered the luciferase activity of constructs containing 3′-UTR of BCKDHA and the formation of lipid droplets, along with the adipogenic markers and BCAA consumption. Besides, the adipogenic performance and BCAA consumption in BCKDHA-overexpressing or knocked-down SVFs and the expression of adipogenic marker genes were altered. We demonstrate that miR-124-3p is an important factor for adipogenesis and provide insights into the formation of intramuscular fat in animals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Mitigation of emissions and energy consumption due to light-duty vehicle size increases

Analysts need to consider the shift of light-duty vehicle sales from cars to light trucks to accurately project fuel consumption, greenhouse gas emissions, and consumer spending. Here, we find that energy consumed by on-road light-duty vehicles in the United States can vary by 10% by changing assumptions regarding the sales mix. Scenarios aligned with third-party forecasts, assuming a greater sales proportion of light trucks and fewer cars, yield petroleum consumption 3–8% higher than forecasts from the U.S. Energy Information Administration (EIA), with greenhouse gas emissions 5–7% higher and a 4–9% increase in consumer spending on vehicles and fuel. This incremental energy consumption can be offset by additional technologies for these vehicles. If most sedans were phased out in favor of larger sport utility vehicles, we find a sales share of 30% battery electric vehicles or 39% hybrid electric vehicles would equal the emissions of the EIA Reference Case.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Pre-treating anaerobic mixed microflora with waste frying oil: A novel method to inhibit hydrogen consumption

Highlights: • Waste frying oil was successfully used as an inhibitor for H{sub 2} consumption during dark fermentation of mixed cultures. • Methane production in pre-treated cultures decreased significantly. • Duration of pre-treatment and concentration of waste frying oil affected H{sub 2} production. • Volatile fatty acids accumulation increased with waste frying oil concentration. - Abstract: An innovative method was introduced to inhibit methanogenic H{sub 2} consumption during dark fermentative hydrogen production by anaerobic mixed cultures. Waste frying oil was used as an inhibitor for hydrogenotrophic methanogens. Simultaneous effect of waste frying oil concentrations (0–20 g/L) and initial pH (5.5, 6.5 and 7.5) on inhibition of methanogenic H{sub 2} consumption and enhancement of H{sub 2} accumulation were investigated using glucose as substrate. Enhanced hydrogen yields with decreased methane productions were observed with increasing the waste frying oil concentrations. On average, CH{sub 4} productions from glucose in the cultures received 10 g/L WFO were reduced by 88%. Increased WFO concentration up to 20 g/L led to negligible CH{sub 4} productions and in turn enhanced H{sub 2} yields. Hydrogen yields of 209.26, 195.35 and 185.60 mL/g glucose{sub added} were obtained for the cultures pre-treated with 20 g/L waste frying oil with initial pH of 5.5, 6.5 and 7.5 respectively. H{sub 2} production by pre-treated cultures was also studied using a synthetic food waste. Anaerobic mixed cultures were pre-treated with 10 g/L WFO and varying durations (0, 24 and 48 h). A H{sub 2} yield of 71.46 mL/g VS was obtained for cultures pre-treated with 10 g/L WFO for 48 h that was 475% higher than untreated control. This study suggests a novel and inexpensive approach for suppressing hydrogenotrophic methanogens during dark fermentative H{sub 2} production.

08 HYDROGEN↗
DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗
DOE OSTI2020

Energy consumption and cooperation for optimal sensing

Abstract The reliable detection of environmental molecules in the presence of noise is an important cellular function, yet the underlying computational mechanisms are not well understood. We introduce a model of two interacting sensors which allows for the principled exploration of signal statistics, cooperation strategies and the role of energy consumption in optimal sensing, quantified through the mutual information between the signal and the sensors. Here we report that in general the optimal sensing strategy depends both on the noise level and the statistics of the signals. For joint, correlated signals, energy consuming (nonequilibrium), asymmetric couplings result in maximum information gain in the low-noise, high-signal-correlation limit. Surprisingly we also find that energy consumption is not always required for optimal sensing. We generalise our model to incorporate time integration of the sensor state by a population of readout molecules, and demonstrate that sensor interaction and energy consumption remain important for optimal sensing.

Ngampruetikorn, Vudtiwat↗
DOE OSTI2017

GRACE satellite observations reveal the severity of recent water over-consumption in the United States

Changes in the climate and population growth will critically impact the future supply and demand of water, leading to large uncertainties for sustainable resource management. In the absence of on-the-ground measurements to provide spatially continuous, high-resolution information on water supplies, satellite observations can provide essential insight. Here, we develop a technique using observations from the Gravity Recovery and Climate Experiment (GRACE) satellite to evaluate the sustainability of surface water and groundwater use over the continental United States. We determine the annual total water availability for 2003–2015 using the annual variability in GRACE-derived total water storage for 18 major watersheds. The long-term sustainable water quantity available to humans is calculated by subtracting an annual estimate of the water needed to maintain local ecosystems, and the resulting water volumes are compared to reported consumptive water use to determine a sustainability fraction. We find over-consumption is highest in the southwest US, where increasing stress trends were observed in all five basins and annual consumptive use exceeded 100% availability twice in the Lower Colorado basin during 2003–2015. By providing a coarse-scale evaluation of sustainable water use from satellite and ground observations, the established framework serves as a blueprint for future large-scale water resource monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Understanding the critical chemistry to inhibit lithium consumption in lean lithium metal composite anodes

Lithium metal has been deemed by many as the “Holy Grail” of anode materials due to its high theoretical capacity (~3860 mA h g -1 ), redox potential of -3.040 V vs. SHE, and light weight. The goal of this work is to investigate the relationship between a lean lithium metal anode and its consumption as a function of host materials, electrochemical protocol and electrolyte composition. With the use of carbon nanofibers, lithium metal has been electrodeposited onto the host matrix and used in a battery with a LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathode. The mass-loading of lithium can be easily controlled and utilized to investigate the practicality of an anode limited battery (i.e., limited lithium with an effective thickness <15 μm) in a high surface area matrix. We then quantify the consumption rate of active lithium using different electrolyte additives and current rates in full cells and observe that the lithium consumption behavior in an anode-limited cell is different from that in an anode-excess cell. Our results highlight the necessity of applying truly lithium-limited cells when evaluating the electrochemical properties of lithium anodes and electrolyte additives. By extending this method to a standard graphite host, full cells can retain 75% of their initial capacities after 1000 cycles. The present study demonstrates the importance of graphitic carbon in increasing the lifespan of limited lithium (<15 μm) for practical lithium metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2019

Inequity in consumption of goods and services adds to racial–ethnic disparities in air pollution exposure

Fine particulate matter (PM 2.5 ) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM 2.5 exposure to the human activities responsible for PM 2.5 pollution. We use these results to explore “pollution inequity”: the difference between the environmental health damage caused by a racial–ethnic group and the damage that group experiences. We show that, in the United States, PM 2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a “pollution advantage”: They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a “pollution burden” of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM 2.5 exposures declined ∼50% during 2002–2015 for all three racial–ethnic groups, but pollution inequity has remained high.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2018

Optimal Energy Consumption Forecast for Grid Responsive Buildings: A Sensitivity Analysis

It is envisioned that building systems will become active participants in the smart grid operation by controlling their energy consumption to optimize complex criteria beyond ensuring local end-use comfort satisfaction. A forecast of the building energy consumption will be necessary to enable integration between building and grid operation. Such forecast will be affected by parametric and measurement uncertainty. In this paper we develop a methodology for quantifying the sensitivity of optimal hourly energy consumption forecasts to various sources model and measurement uncertainty. We demonstrate the approach for a building heating ventilation and air conditioning (HVAC) system use-case.

Kundu, Soumya↗
DOE OSTI2022

Reducing Memory Consumption in Calico with Shared Memory

This document details the work to reduce memory consumption in Calico. Calico is SimTools’ Constructive Solid Geometry (CSG) and geometry painting library. It is primarily used to paint material volume fractions in the Eulerian meshes of the physics codes. Calico provides point-in-body checks for the geometry supplied by an Oso model, which are then aggregated by the host codes. In addition, Calico can be used to build Oso models and is used by Ingen for that purpose. Oso models, and thus Calico, provide support for various CSG primitives such as spheres, cylinders, surfaces generated by rotating tabular curve data, and STL files as well as binary combinations of those primitives. Prior to refactoring Calico will run out of memory on CTS-1 machines when 36 MPI ranks are used per node when reading STL models on the order of 1.5 GB. This limitation is a bottleneck in designer workflow. This problem has been alleviated through the use of data structures to both reduce memory consumption and to leverage MPI-3 shared memory. This report details the data structures targeted for refactoring in Calico, the methods and implementation details for reducing memory consumption and leveraging shared memory, and results for one test problem. Results show a memory reduction when loading a 1 GB STL file by a factor of 27.5, from 93.4 to 3.4 GB.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations

Addressing the "Red-AI" trend of rising energy consumption by large-scale neural networks, this study investigates the measured energy consumption of training various fully connected neural network architectures. We introduce the BUTTER-E dataset, an augmentation to the BUTTER Empirical Deep Learning dataset, containing energy consumption and performance data from 41,129 individual experimental runs spanning 30,582 distinct configurations: 13 datasets, 20 sizes (trainable parameters), 8 "shapes", and 14 depths on both CPUs and GPUs using node-level watt-meters. This dataset reveals the complex relationship between dataset size, network structure, and energy use. Our analysis uncovers a surprising, hardware-mediated non-linear relationship between energy efficiency and network design, challenging the assumption that reducing the number of parameters or FLOPs is the best way to achieve greater energy efficiency. We propose a straightforward and effective energy model that accounts for network size, computing, and memory hierarchy. Highlighting the need for cache-considerate algorithm development, we suggest a codesign approach to energy efficient network, algorithm, and hardware design. This work contributes to the fields of sustainable computing and Green AI, offering practical guidance for creating more energy-efficient neural networks and promoting sustainable AI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Consumption Patterns of a Generalist Omnivore: Eastern Box Turtle Diets in the Long Island Pine Barrens

Eastern Box Turtles (Terrapene carolina) are diet generalists and as such are predicted to have diverse diets in which familiar, low-quality foods are eaten consistently at low levels, and high-quality foods are rare but eaten whenever available. Previous work showed that they feed opportunistically on seasonally available plants (shoots, leaves, flowers, and fruit), invertebrates, mushrooms, and occasionally carrion. We used fecal samples to test optimal foraging predictions relevant to diet generalists and also whether the Eastern Box Turtle diets varied seasonally in a northeastern U.S. pine-oak habitat. We found that in-depth prey species consumption patterns of six different individuals were similar to those of the sampled population overall. Leaf and stem material was consumed by 100% of the turtles in all months despite being lower-quality than other prey available. Invertebrates were consumed by at least 80% of turtles in every study period; Coleopterans were found more commonly than other invertebrates. Snails were not eaten by more than 20% of the turtles in any study period, and mushroom consumption varied from 31–75% of samples in different study periods. Monthly diet overlap was measured using both Pianka’s Index of Overlap (PIO) and the Morisita–Horn Index (MH). The PIO method indicated that the prey consumption patterns were broadly similar from June–October, while the M–H method showed that only the July vs. August comparison was highly similar. The turtle diets changed only slightly between seasons, and they conform to predictions of diet generalist models usually applied to mammals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption

The past decade has seen a substantial increase in the use of small unmanned aerial vehicles (UAVs) in both civil and military applications. This article addresses an important aspect of refueling in the context of routing multiple small UAVs to complete a surveillance or data collection mission. Specifically, this article formulates a multiple-UAV routing problem with the refueling constraint of minimizing the overall fuel consumption for all the vehicles as a two-stage stochastic optimization problem with uncertainty associated with the fuel consumption of each vehicle. The two-stage model allows for the application of sample average approximation (SAA). Although the SAA solution asymptotically converges to the optimal solution for the two-stage model, the SAA run time can be prohibitive for medium- and large-scale test instances. Hence, we develop a tabu search-based heuristic that exploits the model structure while considering the uncertainty in fuel consumption. Extensive computational experiments corroborate the benefits of the two-stage model compared to a deterministic model and the effectiveness of the heuristic for obtaining high-quality solutions.

42 ENGINEERING↗