Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Energy use”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Climate change impacts on the energy system: a model comparison

Increasing renewable energy use is an essential strategy for mitigating climate change. Nevertheless, the sensitivity of renewable energy to climatic conditions means that the energy system’s vulnerability to climate change can also become larger. In this research, we used two integrated assessment models and data from four climate models to analyse climate change impacts on primary energy use at a global and regional scale under a low-level (RCP2.6) and a medium-level (RCP6.0) climate change scenario. The impacts are analysed on the energy system focusing on four renewable sources (wind, solar, hydropower, and biomass). Globally, small climate impacts on renewable primary energy use are found in both models (5% for RCP2.6 and 6% for RCP6.0). These impacts lead to a decrease in the use of fossil sources for most regions, especially for North America and Europe under the RCP60 scenario. Overall, IMAGE and GCAM provide a similar signal impact response for most regions. E.g. in Asia (excluding China and India), climate change induces an increase in wind and hydropower use under the RCP6.0 scenarios; however, for India, a decrease in solar energy use can be expected under both scenarios and models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Consumable development to tailor residual stress in parts fabricated using directed energy deposition processes

Distortion and residual stresses are major challenges that limit the ability to fabricate large scale structures using Additive Manufacturing (AM). Researchers worldwide are evaluating techniques to induce compressive residual stress in the parts via intermittent rolling. While reasonable success has been documented, the idea of lowering the martensite start temperature to induce compressive stresses has not been evaluated in the context of AM, despite demonstrated success by the welding community. This study validates the hypothesis that, by a proper selection of materials and process parameters, one may effectively reduce distortion and induce a compressive residual stress in AM parts. Using neutron diffraction to measure residual stresses in parts, we demonstrate that, in addition to selection of the correct materials, the inter pass temperature plays a major role in controlling the residual stress evolution. The observations relating to the residual stresses are rationalized based on a microstructural evolution in these samples. Based on this preliminary study, a strategy to fabricate large structures with minimal distortion and residual stress is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO 2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.

Quan, Steven Jige↗
DOE OSTI2022

Search of strong lens systems in the Dark Energy Survey using convolutional neural networks

We present our search for strong lens, galaxy-scale systems in the first data release of the Dark Energy Survey (DES), based on a color-selected parent sample of 18 745 029 luminous red galaxies (LRGs). We used a convolutional neural network (CNN) to grade this LRG sample with values between 0 (non-lens) and 1 (lens). Our training set of mock lenses is data-driven, that is, it uses lensed sources taken from HST-COSMOS images and lensing galaxies from DES images of our LRG sample. A total of 76 582 cutouts were obtained with a score above 0.9, which were then visually inspected and classified into two catalogs. The first one contains 405 lens candidates, of which 90 present clear lensing features and counterparts, while the other 315 require more evidence, such as higher resolution imaging or spectra, to be conclusive. A total of 186 candidates are newly identified by our search, of which 16 are among the 90 most promising (best) candidates. The second catalog includes 539 ring galaxy candidates. This catalog will be a useful false positive sample for training future CNNs. For the 90 best lens candidates we carry out color-based deblending of the lens and source light without fitting any analytical profile to the data. This method is shown to be very efficient in the deblending, even for very compact objects and for objects with a complex morphology. Finally, from the 90 best lens candidates, we selected 52 systems with one single deflector to test an automated modeling pipeline that has the capacity to successfully model 79% of the sample within an acceptable computing runtime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Enhancing Building Resilience: Maintaining Energy Efficiency and Thermal Comfort During Power Outages in Cold Climates

The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort during cold snaps, while modern airtight buildings are more vulnerable to overheating during heatwaves. Various passive energy efficiency measures, such as improved infiltration control, thermal windows, solar-controlled windows, and cool envelopes, were evaluated for their ability to mitigate thermal discomforts. Solar controlled windows and weatherstripping contribute to reducing cold thermal discomfort by 21% during a power-interrupted cold snap. Solar-controlled windows were found to reduce hot thermal discomfort by 34% during a future power-interrupted heatwave. The study highlights the importance of targeted retrofitting strategies to enhance thermal resilience, especially during power outages, to ensure occupant safety and comfort during extreme climate events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Electrolyzer and Fuel Cell Recycling for a Circular Hydrogen Economy

Abstract Electrolyzers and fuel cells will be crucial for achieving global clean hydrogen and industrial decarbonization goals. However, the nascent clean hydrogen sector faces uncertainties around material supply chains and technology end‐of‐life management. This work aims to guide the transition to a circular hydrogen economy by using process modeling, techno‐economic analysis, and life cycle assessment to evaluate the material cost, energy use, greenhouse gas (GHG) emissions, toxicity, and water use of five potential recycling strategies for proton exchange membrane electrolyzers (PEMWE) and fuel cells (PEMFC). Hydrometallurgy, acid dissolution, and electrochemical dissolution are shown to offer 2–7 times improvement across all assessed metrics relative to the manufacturing of PEMWE and PEMFC from raw materials. Recycling can also lower the raw material demand, material cost, energy use, and GHG emissions associated with PEMWE and PEMFC deployment in the United States in 2050 by 23%, 19%, 21%, and 16%, respectively. This study provides key insights into the costs, benefits, and complexities of recycling strategies for PEMWE and PEMFC, aiding the development of a circular economy that is synergistic with clean hydrogen deployment.

08 HYDROGEN↗
NASA NTRS1973

Energy storage using high pressure electrolysis and methods for reconversion

Theoretical and experimental studies on high pressure electrolysis producing hydrogen and oxygen for energy storage and reconversion are reported. Moderate temperature, high pressure hydrogen/oxygen fuel cells with nickel electrodes are investigated for effects of pressure, temperature, and membrane porosity. Test results from an aphodid burner turbine generator combination obtained 40 percent kilowatt hours out of the fuel cell divided by kilowatt hours into the electrolyzer. It is concluded that high pressure hydrogenation of organic materials can be used to synthesize hydrozenes and methanes for making synthetic vehicular fuels.

Hughes, W. L.↗
DOE OSTI2025

Accelerating Innovative Energy Solutions Using Combustion Simulations

Combustion-based transportation, electricity generation, and industrial heating in manufacturing constitute the three largest sectors of energy demand. Some of the recent technology development in these sectors are: switching to low-carbon fuels for the transportation sector, increasing energy efficiency in the power sector, and capturing carbon emissions from conventional power generators. Several teams at the National Renewable Energy Laboratory have been actively advancing research in these areas by leveraging computational modeling of combustion processes across the heavy-duty land based transportation, aviation, and power generation sectors. This article summarizes some of these efforts, demonstrating the potential of advanced computational techniques to generate technological solutions that will transform the global energy system.

08 HYDROGEN↗
DOE OSTI2022

Smart Ventilation Controls for Occupancy and Auxiliary Fan Use Across U.S. Climates

Smart Ventilation has been developed as a way to reduce the energy associated with ventilation by changing when ventilation happens and how much ventilation occurs at any given time. In high performance buildings with low envelope and appliance related loads, ventilation is becoming a bigger part of the total building energy use and needs to be addressed if performance targets are to be met. This work explores the development and performance of smart ventilation controls based on occupancy and auxiliary fan operation that provide annual dwelling unit ventilation equivalence to ASHRAE Standard 62.2-2016. A prototype high performance home compliant with U.S. DOE Building America Zero Energy Ready program requirements was simulated using the REGCAP tool with and without smart controls across 15 U.S. DOE climate zones. Balanced and unbalanced IAQ fans were independently simulated, and all smart controlled fans had airflows double the reference 62.2-2016 airflow. Three idealized occupancy patterns were examined: 1st shift (a typical daily work/school absence), an extended 1st shift with more time spent out of the home evenings and weekends and 3rd shift (night work). The Occupancy controller turns the IAQ fan off during unoccupied periods, and it resumes ventilation upon their return. While unoccupied, contaminants are allowed to accumulate in the space, because occupants are not exposed to these contaminants. When occupants return home, they are exposed to these higher contaminant concentrations, and the controller increases the ventilation rate sufficiently to ensure equivalence with a continuous IAQ fan. Accounting for pollutant emissions that occur during unoccupied periods (as required by ASHRAE 62.2-2016), sharply distinguishes our occupancy controls from past Demand Controlled Ventilation systems. This new accounting method results in equivalent contaminant exposure, as well as lower reductions in average ventilation rates and lower energy savings. Smart controls were demonstrated that saved HVAC energy (i.e., avoided heating/cooling load, as well as fan energy)—averaging between 6 and 46% of ventilation-related energy use depending on the control strategy and occupancy pattern assumptions. The greatest savings were in the combined Auxiliary Fan + Occupancy control. Energy savings increased with climate heating demand and longer unoccupied time periods. The 3rd shift occupancy pattern had better performance, due to the thermal benefit of reducing the ventilation rate during the cold nighttime hours. This same effect provided a cooling energy benefit in hotter locations for the 1st shift. Overall, savings from occupancy-based smart controls were low, because of the recovery period required after occupants return home, during which the airflow is double the 62.2 reference. This recovery is required to maintain equivalence with the ASHRAE standard. Occupancy-based control performance was improved when combined with sensing auxiliary fans and when providing a pre-occupancy flush out of one- or two-hours. Performance was similarly improved if the ASHRAE Standard were to recognize that pollutant emissions are lower during unoccupied periods, iii allowing a lower target ventilation rate during unoccupied periods (not currently in the standard) (see Full vs. Half AEQ in this report). Finally, over-sized unbalanced fans that are cycled on-and-off by a smart controller (or timer) were found to substantially increase annual average air exchange and energy use relative to a continuous unbalanced fan due to the effects of superposition with natural infiltration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

The COVID-19 pandemic highlights the importance of improving building indoor air quality to reduce occupants' chances of contracting airborne illness. The ASHRAE Epidemic Task Force (ASHRAE-ETF) released several COVID-19 mitigation strategies at the onset of the pandemic. This study explores four of those recommendations for reducing transmission of COVID-19 inside buildings: (1) 100% outdoor air ventilation, (2) MERV-13 or better filters, (3) demand control ventilation removal, and (4) HVAC flushing mode. These recommendations were simulated and assessed using ComStock, a model of the U.S. commercial building stock. The study showed the 100% outdoor air ventilation recommendation had the largest impact on energy consumption, noncoincident peak demand, and thermostat violations. Removing demand control ventilation had the smallest national aggregate impact, installing MERV-13 filters led to slight increases in energy use and peak demand, and HVAC outdoor air flushing led to modest energy use and peak demand increases.

building energy modelling↗
NASA NTRS1995

Using Density Functional Theory (DFT) for the Calculation of Atomization Energies

The calculation of atomization energies using density functional theory (DFT), using the B3LYP hybrid functional, is reported. The sensitivity of the atomization energy to basis set is studied and compared with the coupled cluster singles and doubles approach with a perturbational estimate of the triples (CCSD(T)). Merging the B3LYP results with the G2(MP2) approach is also considered. It is found that replacing the geometry optimization and calculation of the zero-point energy by the analogous quantities computed using the B3LYP approach reduces the maximum error in the G2(MP2) approach. In addition to the 55 G2 atomization energies, some results for transition metal containing systems will also be presented.

Bauschlicher, Charles W., Jr.↗
DOE OSTI2024

Nonconvex Robust Optimization for the Design and Operation of Advanced Energy Systems Using PyROS

This work discusses recent advances of the two-stage robust optimization (RO) solver PyROS and applications to advanced energy systems optimization. To demonstrate the computational performance and reliability of PyROS, a study on a monoethanolamine (MEA)-based CO2 absorption flowsheet is presented. (Near-)robust feasible designs for CO2 absorption flowsheet at high carbon capture are obtained with the PyROS solver. The results demonstrate that the PyROS solver, including recent extensions to multi-stage RO settings, provides a reliable avenue to optimize the design and operation of advanced energy systems subject to various sources of parametric uncertainty.

Sherman, Jason↗
DOE OSTI2022

U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies: Preprint

The COVID-19 pandemic highlights the importance of improving building indoor air quality to reduce occupants’ chances of contracting airborne illness. The ASHRAE Epidemic Task Force (ASHRAE-ETF) released several COVID-19 mitigation strategies at the onset of the pandemic. This study explores four of those recommendations for reducing transmission of COVID-19 inside buildings: (1) 100% outdoor air ventilation, (2) MERV-13 or better filters, (3) demand control ventilation removal, and (4) HVAC flushing mode. These recommendations were simulated and assessed using ComStock, a model of the U.S. commercial building stock. The study showed the 100% outdoor air ventilation recommendation had the largest impact on energy consumption, noncoincident peak demand, and thermostat violations. Removing demand control ventilation had the smallest national aggregate impact, installing MERV-13 filters led to slight increases in energy use and peak demand, and HVAC outdoor air flushing led to modest energy use and peak demand increases.

building energy modelling↗
DOE OSTI2023

Self-Sustainable IoT-Based Remote Sensing Powered by Energy Harvesting Using Stacked Piezoelectric Transducer and Thermoelectric Generator

We propose a self-powered remote multi-sensing system for traffic sensing which is powered by the collective energy harvested from the mechanical vibration of the road caused by the passing vehicles and from the temperature gradient between the asphalt of the road and the soil underneath. A stacked piezoelectric transducer converts mechanical vibrations into electrical energy and a thermoelectric generator harvests the thermal energy from the thermal gradient. Electrical energy signals from the stacked piezoelectric transducer and the thermoelectric generators are converted into usable DC power to recharge the battery using AC-DC and DC-DC converters working simultaneously. The multi-sensing system comprises an embedded system with a microcontroller that acquires data from the sensors and sends the sensory data to an IoT transceiver which transmits the data as RF packets to an ethernet gateway. The gateway converts the RF packets into Internet Protocol (IP) packets and sends them to a remote server. Laboratory and road-testing results showed over 98% sensory data accuracy with the system functioning solely powered by the energy harvested from the alternative energy sources. The successful maximum transmission distance obtained between the IoT, and the gateway was approximately 1 mile, which is a considerable transmission distance achieved in an urban environment. Successful operation of the self-powered multi-sensing system under both laboratory and road conditions contributes considerably to the fields of energy harvesting and self-powered remote sensing systems. The energy flow chart and efficiency for the steps in the system were found to be mechanical power from vehicles to the energy harvester of 0.25%, stacked PZT transducer efficiency was found to be 37%, and for the TEGs the efficiency is 11%. AC-to-DC and DC-to-DC converters’ efficiencies were found to be 90% and 11%. The wireless communication RF transceiver efficiency was found to be 62.5%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Turbulence-parameter estimation for current-energy converters using surrogate model optimization

Surrogate models maximize information utility by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain simulations to estimate array efficiencies and environmental impacts. Meso-scale models typically represent turbines as actuator discs that act as momentum sinks and sources of turbulence and its dissipation. An OpenFOAM model was developed where actuator disc k-ε turbulence was characterized using an approach developed for flows through vegetative canopies. Turbine-wake data from laboratory flume experiments collected at two influent turbulence intensities were used to calibrate parameters in the turbulence-source terms in the k-ε equations. Additionally, parameter influences on longitudinal wake profiles were estimated using Gaussian process regression with subsequent optimization minimizing the objective function within 3.1% of those obtained using the full model representation, but for 74% of the computational cost (far fewer model runs). This framework facilitates more efficient parameterization of the turbulence-source equations using turbine-wake data.

16 TIDAL AND WAVE POWER↗
NASA NTRS1995

Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

Li, Zhanqing↗