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At least 37 records · Page 2

Oxygen consumption of animals under conditions of hypokinesia

The influence of hypokinesia on the oxygen consumption of rats, dog, and squirrels was investigated. Three periods of gaseous exchange were revealed in rats under conditions of a limited motor activity. During the first 10-15 days O2 consumption displayed a sharp elevation; on the 20th-30th day, it became stabilized at a higher level (in comparison with control) and it sharply rose again on the 40th-100th day. In dogs, hypokinesia produced a reduction of O2 consumption and then a tendency to its elevation was seen. A short period of physical exercises in squirrels after hypokinesia led to increased oxygen consumption at rest.

Loginova, Y. N.

Measured effect of wind generation on the fuel consumption of an isolated diesel power system

The Block Island Power Company (BIPCO), on Block Island, Rhode Island, operates an isolated electric power system consisting of diesel generation and an experimental wind turbine. The 150-kW wind turbine, designated MOD-OA by the U.S. Department of Energy is typically operated in parallel with two diesel generators to serve an average winter load of 350 kW. Wind generation serves up to 60 percent of the system demand depending on wind speed and total system load. Results of diesel fuel consumption measurements are given for the diesel units operated in parallel with the wind turbine and again without the wind turbine. The fuel consumption data are used to calculate the amount of fuel displaced by wind energy. Results indicate that the wind turbine displaced 25,700 lbs. of the diesel fuel during the test period, representing a calculated reduction in fuel consumption of 6.7 percent while generating 11 percent of the total electric energy. The amount of displaced fuel depends on operating conditions and system load. It is also shown that diesel engine throttle activity resulting from wind gusts which rapidly change the wind turbine output do not significantly influence fuel consumption.

Stiller, P. H.

Influence of simulated microgravity on the maximal oxygen consumption of nontrained and trained rats

The effects of microgravity and endurance training (TR) on maximal O2 consumption was investigated in trained and nontrained (NT) rats subjected to head-down suspension (HDS) by comparing maximal O2 consumption, treadmill run time (RT), and mechanical efficiency (ME) of treadmill running in HDS rats, both NT and TR, and in respective cage controls. It was found that HDS for 28 days was associated with significant reduction in absolute maximal O2 consumption in both TR and NT rats. Relative maximal O2 consumption, however, was significantly reduced in TR but not NT rats. Reductions in RT and ME occurring in both TR and NT rats after 28 days of HDS were similar. The TR rats exhibited greater diuretic, natriuretic, and kaliuretic responses to HDS than the NT rats.

Woodman, Christopher R.

Development of a Complete Landsat Evapotranspiration and Energy Balance Archive to Support Agricultural Consumptive Water Use Reporting and Prediction in the Central Valley, CA

Mapping evapotranspiration (ET) from agricultural areas in Californias Central Valley is critical for understanding historical consumptive use of surface and groundwater. In addition, long histories of ET maps provide valuable training information for predictive studies of surface and groundwater demands. During times of drought, groundwater is commonly pumped to supplement reduced surface water supplies in the Central Valley. Due to the lack of extensive groundwater pumping records, mapping consumptive use using satellite imagery is an efficient and robust way for estimating agricultural consumptive use and assessing drought impacts. To this end, we have developed and implemented an algorithm for automated calibration of the METRIC remotely sensed surface energy balance model on NASAs Earth Exchange (NEX) to estimate ET at the field scale. Using automated calibration techniques on the NEX has allowed for the creation of spatially explicit historical ET estimates for the Landsat archive dating from 1984 to the near present. Further, our use of spatial NLDAS and CIMIS weather data, and spatial soil water balance simulations within the NEX METRIC workflow, has helped overcome challenges of time integration between satellite image dates. This historical and near present time archive of agricultural water consumption for the Central Valley will be an extremely useful dataset for water use and drought impact reporting, and predictive analyses of groundwater demands.

valleys

From roads to roofs: How urban and rural mobility influence building energy consumption

In this article, understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS

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

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

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

Energy consumption: Past, present, future

The energy consumption history of the United States and the changes which could occur in consumption characteristics in the next 50 years are presented. The various sources of energy are analyzed to show the limitations involved in development and utilization as a function of time available. Several scenarios were prepared to show the consumption and supply of energy under varying conditions.

Source record

Respiration, respiratory metabolism and energy consumption under weightless conditions

Changes in the physiological indices of respiration, respiratory metabolism and energy consumption in spacecrews under weightlessness conditions manifest themselves in increased metabolic rates, higher pulmonary ventilation volume, oxygen consumption and carbon dioxide elimination, energy consumption levels in proportion to reduction in neuroemotional and psychic stress, adaptation to weightlessness and work-rest cycles, and finally in a relative stabilization of metabolic processes due to hemodynamic shifts.

Kasyan, I. I.

Study of Turbofan Engines Designed for Low Enery Consumption

Subsonic transport turbofan engine design and technology features which have promise of improving aircraft energy consumption are described. Task I addressed the selection and evaluation of features for the CF6 family of engines in current aircraft, and growth models of these aircraft. Task II involved cycle studies and the evaluation of technology features for advanced technology turbofans, consistent with initial service in 1985. Task III pursued the refined analysis of a specific design of an advanced technology turbofan engine selected as the result of Task II studies. In all of the above, the impact upon aircraft economics, as well as energy consumption, was evaluated. Task IV summarized recommendations for technology developments which would be necessary to achieve the improvements in energy consumption identified.

Neitzel, R. E.

Cost/benefit tradeoffs for reducing the energy consumption of the commercial air transportation system

The fuel saving potential and cost effectiveness of numerous operational and technical options proposed for reducing the fuel consumption of the U.S. commercial airline fleet was examined and compared. The impact of the most promising fuel conserving options on fuel consumption, passenger demand, operating costs and airline profits when implemented in the U.S. domestic and international airline fleets was determined. A forecast estimate was made of the potential fuel savings achievable in the U.S. scheduled air transportation system. Specifically, the means for reducing the jet fuel consumption of the U.S. scheduled airlines in domestic and international passenger operations were investigated. A design analysis was made of two turboprop aircraft as possible fuel conserving derivatives of the DC-9-30.

Kraus, E. F.

Computer simulated building energy consumption for verification of energy conservation measures in network facilities

A computer program called ECPVER (Energy Consumption Program - Verification) was developed to simulate all energy loads for any number of buildings. The program computes simulated daily, monthly, and yearly energy consumption which can be compared with actual meter readings for the same time period. Such comparison can lead to validation of the model under a variety of conditions, which allows it to be used to predict future energy saving due to energy conservation measures. Predicted energy saving can then be compared with actual saving to verify the effectiveness of those energy conservation changes. This verification procedure is planned to be an important advancement in the Deep Space Network Energy Project, which seeks to reduce energy cost and consumption at all DSN Deep Space Stations.

Plankey, B.

Energy consumption analysis of the Venus Deep Space Station (DSS-13)

This report continues the energy consumption analysis and verification study of the tracking stations of the Goldstone Deep Space Communications Complex, and presents an audit of the Venus Deep Space Station (DSS 13). Due to the non-continuous radioastronomy research and development operations at the station, estimations of energy usage were employed in the energy consumption simulation of both the 9-meter and 26-meter antenna buildings. A 17.9% decrease in station energy consumption was experienced over the 1979-1981 years under study. A comparison of the ECP computer simulations and the station's main watt-hour meter readings showed good agreement.

Hayes, N. V.

Effect of 29 days of simulated microgravity on maximal oxygen consumption and fat-free mass of rats

Effects of a 29-days exposure to simulated microgravity on the values of maximal oxygen consumption and fat-free mass (FFM) and on the mechanical efficiency of running were investigated in rats randomly assigned to one of three regimens: head-down suspension (HDS) at 45 deg, horizontal suspension (HS), or cage control (CC). Before suspension and on days 7, 14, 21, and 28, five exercise performance tests were carried out, with measurements related to maximal oxygen consumption, treadmill run time, and mechanical efficiency. It was found that maximal oxygen consumption of both HDS and HS groups decreased significantly at day 7, after which the HDS rats remained decreased while the HS rats returned to presuspension values. Apparent mechanical efficiency in the HDS and HS groups decreased by 22-35 percent during the experimental period, and FFM decreased significantly.

Woodman, Christopher R.

Oxygen Consumption of Tilapia and Preliminary Mass Flows through a Prototype Closed Aquaculture System

Performance of NASA's prototype CELSS Breadboard Project Closed Aquaculture System was evaluated by estimating gas exchange quantification and preliminary carbon and nitrogen balances. The total system oxygen consumption rate was 535 mg/hr kg/fish (cv = 30%) when stocked with Tilapia aurea populations (fresh weights of 97 +/- 19 to 147 +/- 36 g/fish for various trials). Oxygen consumption by T. aurea (260 mg/hr kg/fish) contributed to approximately one-half of total system demand. Continuous carbon dioxide quantification methods were analyzed using the,relation of carbon dioxide to oxygen consumption. Overall food conversion rates averaged 18.2 +/- 3.2%. Major pathways for nitrogen and carbon in the system were described with preliminary mass closure of 60-80% and 60% for nitrogen and carbon.

Muller, Matthew S.