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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Unsupervised Azimuth Estimation of Solar Arrays in Low-Resolution Satellite Imagery through Semantic Segmentation and Hough Transform

This paper explains the use of a convolutional neural network (CNN) to segment solar panels in a satellite image containing solar arrays, and extract associated metadata from the arrays. A novel unsupervised technique is introduced to estimate the azimuth of each individual solar panel from the predicted mask of the convolutional neural network. This pipeline was developed with the aim of extracting necessary metadata for a solar installation, using only a set of latitude–longitude coordinates. Azimuth prediction results for 669 individual solar installations associated with 387 sites located across the United States are provided. A mean average error and median average error of 21.65 degrees and 1.0 degrees were obtained, respectively, when predicting the azimuth of the solar fleet data set, with about 80% of the results within an error of zero degrees of the ground truth azimuth value and about 85% within an error of 25 degrees. The predicted azimuth was then used to estimate the energy conversion of the solar arrays. Results show a 90.9 and 90.6 R-squared value for estimating alternating current (AC) and direct current (DC) energy, respectively, and a mean absolute percentage error (MAPE) of 1.70% in estimating the alternating current (AC) energy using the fully automated algorithm.

14 SOLAR ENERGY↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2020

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗
DOE OSTI2014

Selective catalytic reduction of nitric oxide with ethanol/gasoline blends over a silver/alumina catalyst

Lean gasoline engines running on ethanol/gasoline blends and equipped with a silver/alumina catalyst for selective catalytic reduction (SCR) of NO by ethanol provide a pathway to reduced petroleum consumption through both increased biofuel utilization and improved engine efficiency relative to the current stoichiometric gasoline engines that dominate the U.S. light duty vehicle fleet. A pre-commercial silver/alumina catalyst demonstrated high NO x conversions over a moderate temperature window with both neat ethanol and ethanol/gasoline blends containing at least 50% ethanol. Selectivity to NH 3 increases with HC dosing and ethanol content in gasoline blends, but appears to saturate at around 45%. NO 2 and acetaldehyde behave like intermediates in the ethanol SCR of NO. NH 3 SCR of NO x does not appear to play a major role in the ethanol SCR reaction mechanism. Ethanol is responsible for the low temperature SCR activity observed with the ethanol/gasoline blends. In conclusion, the gasoline HCs do not deactivate the catalyst ethanol SCR activity, but they also do not appear to be significantly activated by the presence of ethanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dynamic load balancing with enhanced shared-memory parallelism for particle-in-cell codes

Furthering our understanding of many of today’s interesting problems in plasma physics – including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects – requires large-scale kinetic simulations using particle-in-cell (PIC) codes. However, these simulations are extremely demanding, requiring that contemporary PIC codes be designed to efficiently use a new fleet of exascale computing architectures. To this end, the key issue of parallel load balance across computational nodes must be addressed. We discuss the implementation of dynamic load balancing by dividing the simulation space into many small, self-contained regions or ‘‘tiles,’’ along with shared-memory (e.g., OpenMP) parallelism both over many tiles and within single tiles. The load balancing algorithm can be used with three different topologies, including two space-filling curves. Here, we tested this implementation in the code Osiris and show low overhead and improved scalability with OpenMP thread number on simulations with both uniform load and severe load imbalance. Compared to other load-balancing techniques, our algorithm gives order-of-magnitude improvement in parallel scalability for simulations with severe load imbalance issues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Enabling CCS via Low-temperature Geothermal Energy Integration for Fossil-fired Power Generation

Here, among the key barriers to commercial scale deployment is the cost associated with CO 2 capture. This is particularly true for existing large, fossil-fired assets that account for a large fraction of the electricity generation fleet in developed nations, including the U.S. Fitting conventional combustion technologies with CO 2 capture systems can carry an energy penalty of thirty percent or more, resulting in an increased price of power to the grid, as well as an overall decrease in net plant output. Taken together with the positive growth in demand for electricity, this implies a need for accelerated capital build-out in the power generation markets to accommodate both demand growth and decreased output at retrofitted plants. In this paper, the authors present the results of a study to assess the potential to use geothermal energy to provide boiler feedwater preheating, capturing efficiency improvements designed to offset the losses associated with CO 2 capture. Based on NETL benchmark cases and subsequent analysis of the application using site-specific data from the North Valmy power plant, several cases for CO 2 capture were evaluated. These included geothermally assisted MEA capture, CO2BOLs capture, and stand-alone hybrid power generation, compared with a baseline, no-geothermal case. Based on Case 10, and assuming 2.7 MMlb/h of geothermally sourced 150 ºC water, the parasitic power load associated with MEA capture could be offset by roughly seven percent, resulting in a small (~1 percent) overall loss to net power generation, but at levelized costs of electricity similar to the no-geothermal CCS case. For the CO 2 BOLs case, the availability of 150°C geothermal fluid could allow the facility to not only offset the net power decrease associated with CO 2 BOLs capture alone, but could increase nameplate capacity by two percent. The geothermally coupled CO 2 BOLs case also decreases LCOE by 0.75 ¢/kWh relative to the non-hybrid CO 2 BOLs case, with the improved performance over the MEA case driven by the lower regeneration temperature and associated duty for CO 2 BOLs relative to MEA.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicles driving schedules

The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Impacts of the consumer heterogeneity in fuel economy valuation on compliance with fuel economy standards

This study quantified the significance of assuming heterogeneity in consumer valuation of fuel economy on the estimated compliance with fuel economy standards, with two approaches. One is mathematical derivation on how the heterogeneity affects the estimated market acceptance of high-efficiency vehicles. The other is a consumer choice based simulation method to analyze the heterogeneity impacts on the compliance with the fuel economy standards for the entire light duty vehicle fleet in the United States. Our findings suggest that the direction of the impact of heterogeneity assumption depends on market positions of high-efficiency vehicles: (1) with the “Likely-Accept” condition, where high-efficiency vehicles sell well and higher achieved fuel economy is expected, the heterogeneity assumption can add additional risks to the compliance; and (2) with the “Likely-Reject” condition where the fuel economy standards may have difficulty in compliance, the heterogeneity can reduce the risks and improve the compliance outcome. It is concluded that consideration of fuel economy valuation heterogeneity is important in fuel economy standard analysis. In conclusion, it is hoped that such consideration may provide a framework to reconcile the different views on consumer valuation of fuel economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Fuel consumption impacts of auto roof racks

The after-market roof rack is one of the most common components attached to a vehicle for carrying over-sized items, such as bicycles and skis. It is important to understand these racks' fuel consumption impacts on both individual vehicles and the national fleet because they are widely used. We estimate the national fuel consumption impacts of roof racks using a bottom-up approach. Our model incorporates real-world data and vehicle stock information to enable assessing fuel consumption impacts for several categories of vehicles, rack configurations, and usage conditions. In addition, the model draws on two new data-gathering techniques, on-line forums and crowd-sourcing. The results show that nationwide, roof racks are responsible for 0.8‰ of light duty vehicle fuel consumption in 2015, corresponding to 100 million gallons of gasoline per year. Sensitivity analyses show that results are most sensitive to the fraction of vehicles with installed roof racks but carrying no equipment. Here, the aerodynamic efficiency of typical roof racks can be greatly improved and reduce individual vehicle fuel consumption; however, government policies to minimize extensive driving with empty racks--if successful--could save more fuel nationally.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Early nuclear retirements in deregulated U.S. markets: Causes, implications and policy options

Here, electricity prices have fallen significantly since 2008, putting commercial nuclear reactors in the United States under substantial financial pressure. In this market environment driven by persistently low natural gas prices and stagnant electricity demand, we estimate that about two thirds of the 100 GW nuclear capacity are uncompetitive over the next few years under the current trajectory. Among those, 18 GW are retiring or are merchant plants at high risk of retiring prematurely. The potential consequences of the hypothetical withdrawal of 20 GW of nuclear capacity include: 1) a ~3.2% increase in carbon emissions if replaced by gas-fired units or 2) a significant increase in cost if replaced by renewables. Without a carbon price, out-of-the-market payments would be needed to effectively maintain merchant nuclear capacity. Filling the revenue gap would come at a fleet-average cost of 3.5-5.5/ MWh for these plants, which is much lower than the cost of subsidizing wind power. The policy support could take the form of direct zero-emission credits, renewable portfolio standard expansion, or clean capacity market mechanisms. As a last resort, the exercise of a new mothballing status could prevent the irreversible retirement of nuclear power assets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Environmentally significant shifts in trace element emissions from coal plants complying with the 1990 Clean Air Act Amendments

The Clean Air Act Amendments of 1990 (CAAAs) reduced criteria air pollution from coal-fired power plants (CFPPs) in the United States, but compliance strategies additionally altered the magnitude and phase of environmentally significant trace element emissions. This report quantitatively assesses changes in trace element emissions stemming from CAAAs compliance, attributes these changes to specific CAAAs compliance strategies, and discusses implications for future environmental regulatory design. We combine plant-level coal purchase and installed air pollution control device data with a trace element partitioning model to approximate changes in trace element mass entering and exiting CFPPs in the solid, liquid, and gas phase between 1993 and 2017. Though US coal combustion decreased by 2% during this period, the vast majority of trace element emissions reductions stem from the 18-64% reductions in the fleet-wide average concentrations of arsenic, bromine, chloride, lead, mercury, and selenium in the combusted coal. Combined with the installation of air pollution control technologies, these shifts concluded in nationwide reductions of gas phase trace element emissions by between 49 and 68% for the elements included in this study. In contrast, installation of flue gas desulfurization devices increased the mass of trace elements discharged in wastewater. This work reinforces the value of multi-phase emissions regulations in ensuring that contaminants are not shunted from regulated to unregulated phases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Two trillion gallons: Fuel savings from fuel economy improvements to US light-duty vehicles, 1975–2018

Since 1975, the fuel economy of new light-duty vehicles sold in the U.S. has almost doubled. Fuel economy improvements on laboratory tests gradually became real improvements on the road as newer, more efficient vehicles replaced older less efficient ones. Fleet-wide fuel economy gains produced large fuel savings. In this paper, we show that fuel economy gains measured on laboratory test cycles, adjusted for on-road conditions and weighted by the distribution of vehicles by age and their relative use, closely match estimates by the Federal Highway Administration based primarily on traffic counts and motor fuel tax records. Furthermore, adjusting for the rebound effect of fuel economy on vehicle miles traveled, we estimate the fuel savings, CO 2 emissions reductions and dollars saved on fuel due to fuel economy improvements over the past 43 years. Through the end of 2018, estimated cumulative fuel savings amount to approximately 2 trillion gallons of gasoline. We estimate that roughly one-fifth of the savings can be attributed to gasoline price increases over the period and four-fifths to fuel economy and greenhouse gas (ghg) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Carbon footprint as an environmental sustainability indicator for the particleboard produced in Pakistan

This study quantified the carbon footprint of particleboard production in Pakistan using a cradle-to-gate life cycle assessment approach. The system boundary comprised raw materials acquisition, transport, particleboard manufacture and finished product distribution. Primary data were collected through surveys and meetings with particleboard manufacturers. Secondary data were taken from the literature. Greenhouse gas emissions from off-site industrial operations of the particleboard industry represented 52% of the total emissions from the production of 1.0 m{sup 3} of particleboard in Pakistan. The on-site industrial operations cause direct greenhouse gas emissions and accounted for 48% of the total emissions. These operations included energy consumption in stationary sources, the company-owned vehicle fleet, and the distribution and marketing of the finished product. The use of natural gas combustion in the stationary and mobile sources, raw material transport and urea-formaldehyde resin production chain accounted for the highest emissions from the particleboard production chain in Pakistan. The identification of the major hotspots in the particleboard production chain can assist the wood panel industry to improve their environmental profile. More efforts are needed to investigate the urea-formaldehyde resin production chain and substitution of roundwood with wood and agri-residues to assess the potential improvements. In addition, renewable energy sources should be encouraged to avoid greenhouse gas emissions by substituting fossil energy. This study also provides a benchmark for future research work to formulate comprehensive greenhouse gas emissions reduction plans, because no previous research work is available on the carbon footprint of particleboard production in Pakistan. - Highlights: • We conducted the first carbon footprint assessment of particleboard produced in Pakistan. • System boundary comprised raw materials acquisition, particleboard manufacture and distribution. • Off-site industrial operations were accounted for highest emissions (52%) followed by on-site operations (48%). • Natural gas, materials transport and UF resin use accounted for highest emissions. • Identified potential strategies for GHG emissions reductions from PB production in Pakistan.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A real-time energy and cost efficient vehicle route assignment neural recommender system

Here, this paper presents a neural network recommender system algorithm for assigning vehicles to routes based on energy and cost criteria. In this work, we applied this new approach to efficiently identify the most cost-effective medium and heavy duty truck (MDHDT) powertrain technology, from a total cost of ownership (TCO) perspective, for given trips. We employ a machine learning based approach to efficiently estimate the energy consumption of various candidate vehicles over given routes, defined as sequences of links (road segments), with little information known about internal dynamics, i.e. using high level macroscopic route information. A complete recommendation logic is then developed to allow for real-time optimum assignment for each route, subject to the operational constraints of the fleet. We show how this framework can be used to (1) efficiently provide a single trip recommendation with a top-k vehicles star ranking system, and (2) engage in more general assignment problems where n vehicles need to be deployed over m (m ≤ n) trips. This new assignment system has been deployed and integrated into the POLARIS. Transportation System Simulation Tool for use in research conducted by the Department of Energy's Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium (SMART, 2024).

Energy consumption↗
DOE OSTI2020

Quantifying the impacts of micro- and mild- hybrid vehicle technologies on fleetwide fuel economy and electrification

Micro- and mild-hybridization (jointly labeled as M-HEV) is gaining popularity as a cost-effective technology for fuel economy improvement, but whether and how M-HEV may compete against less efficient conventional internal combustion engine vehicles (ICEV), more efficient full hybrid electric vehicles (HEV), and plug-in electric vehicles (PEV) is not well understood. As such, this study aims at evaluating the impact of the market adoption of M-HEV on the average fuel economy of the new vehicle fleet and on the sales share of PEVs. The study reviews recent sales trends and market forecasts, and uses published estimates of manufacturing cost and fuel economy of M-HEV with an existing discrete choice model (Market Acceptance of Advanced Automotive Technologies or MA3T) to project the market penetration and impacts of M-HEV under different scenarios of M-HEV choice positions, designed to enhance conclusion robustness. It is found that among engine-based powertrain choices, micro-HEV appears to be the most cost-effective, followed by ICEVs, mild-HEV and finally full HEVs. M-HEV technologies are likely to improve fleetwide average fuel economy without significant adverse effects on sales of plug-in electric vehicles, and are likely to remain highly competitive outside PEVs through 2050.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

The impact of Uber and Lyft on vehicle ownership, fuel economy, and transit across U.S. cities

We estimate the effects of transportation network companies (TNCs) Uber and Lyft on vehicle ownership, fleet average fuel economy, and transit use in U.S. urban areas using a set of difference-in-difference propensity score-weighted regression models that exploit staggered market entry across the U.S. from 2011 to 2017. We find evidence that TNC entry into urban areas causes an average 0.7% increase in vehicle registrations with significant heterogeneity in these effects across urban areas: TNC entry produces larger vehicle ownership increases in urban areas with higher initial ownership (car-dependent cities) and in urban areas with lower population growth (where TNC-induced vehicle adoption outpaces population growth). We also find no statistically significant average effect of TNC entry on fuel economy or transit use but find evidence of heterogeneity in these effects across urban areas, including larger transit ridership reductions after TNC entry in areas with higher income and more childless households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Moving toward a framework for electricity and heat equivalence in energy systems analysis

Sustaining, maintaining, and upgrading the electricity grid, while meeting decarbonization goals is a challenge facing policymakers, regulators, grid operators, and investors. Simultaneously meeting demands for future capacity, retiring older inefficient technologies, and addressing externalities from energy production and use requires more diverse and inclusive technologies to avoid constraints and shortfalls in grid capability. Changing the energy production paradigm by encouraging alternative technologies was a key driver for FERC Order 2222. This stimulus for developing new small-scale generation will complement and supplement the existing fleet only if it attracts new investment. This investment must reflect technology that goes beyond the energy-only characteristics of traditional generation, creating systems where suites of energy-equivalent outputs are enhanced by environmental quality benefits and offsets. We use energy system designs to highlight the contribution that measuring and accounting for equivalency values provides net increases in capacity, electricity, and alternative fuels while simultaneously reducing carbon waste impacts.

42 ENGINEERING↗
DOE OSTI2023

Assessing the cost-effectiveness of carbon neutrality for light-duty vehicle sector in China

China’s progress in decarbonizing its transportation, particularly vehicle electrification, is notable. However, the economically effective pathways are underexplored. To find out how much cost is necessary for carbon neutrality for the light-duty vehicle (LDV) sector, this study examines twenty decarbonization pathways, combining the New Energy and Oil Consumption Credit model and the China-Fleet model. We find that the 2060 zero-greenhouse gas (GHG) emission goal for LDVs is achievable via electrification if the battery pack cost is under CNY483/kWh by 2050. However, an extra of CNY8.86 trillion internal subsidies is needed under pessimistic battery cost scenarios (CNY759/kWh in 2050) to eliminate 246 million tonnes of CO 2 -eq by 2050 ensuring over 80% market penetration of battery electric vehicles (BEVs) in 2050. Moreover, the promotion of fuel cell electric vehicles is synergy with BEVs to mitigate the carbon abatement difficulties, decreasing up to 34% of the maximum marginal abatement internal investment.

54 ENVIRONMENTAL SCIENCES↗