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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Mercury Methylation and Soil Organic Matter Degradation in Incubations with Added Acetate, Isotope-Labeled Mercury, and Selective Microbial Inhibitors, Teller and Council Sites, Seward Peninsula, 2018-2019

This dataset provides the results of laboratory soil microcosm incubation experiments conducted under anaerobic conditions with added acetate, isotope-labeled mercury, and selective microbial inhibitors (2-bromoethanesulfonate and sodium molybdate). The microcosms contained soil collected in August 2018 from the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) near Intensive Site 9 (TL_IS_9) and from the Council Road Site (CN_MM71). Incubations were conducted at 8°C for 180 days (Teller incubations) or 60 days (Council incubations). The microcosm headspace was sampled at designated intervals for greenhouse gas concentrations, then destructively harvested and extracted using ultrapure water and 0.1 M KCl for analysis of the porewater geochemistry. This dataset contains one pdf, two csv data files, and one zipped file with raw data.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of Cyber Threat Awareness on Driver Response to an Unexpected Vehicle Cyberattack

Here, the integration of advanced cyber-physical systems in heavy vehicles introduces new vulnerabilities by expanding the possibility of cyberattacks. The objective of this study is to evaluate (1) how threat awareness influences driver response to an unexpected cyberattack, (2) how the provision of a basic cyberattack response protocol influences driver performance, and (3) how professionally trained versus standard drivers compare in their responses to a cyberattack. An on-road driving study (N = 50) was conducted using a medium heavy-duty vehicle. Participants were divided into three groups: Control, which remained unaware of any potential cyberattack; Aware, which was informed about the potential cyberattack; and Aware + Protocol, which received the same warning as the Aware group with the addition of a basic cyberattack response protocol. An instrument cluster cyberattack was executed at the same location for all participants. The findings highlight the essential role of awareness and response protocol in enhancing driver response to an unexpected vehicle cyberattack. The Aware + Protocol group had the highest stop rate (100%) and the shortest stopping distances (224 m for standard drivers and 254 m for professionals), compared to the Control group (828 and 520 m, respectively). Aware + Protocol also had the fastest reaction time, averaging 7.53 s, versus 16.12 s (Aware) and 30.29 s (Control). These results emphasize that awareness alone is insufficient. Providing drivers with clear, actionable protocols significantly improves their ability to react quickly and safely to cyberattacks, enhancing overall road safety.

Cybersecurity↗
DOE OSTI2025

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying the Contributions of Aerosol- and Snow-Produced ClNO 2 through Observations and 1D Modeling

Nitryl chloride (ClNO 2 ) is a radical reservoir that forms and accumulates in the nocturnal atmospheric boundary layer influenced by combustion emissions and chloride (e.g., sea salt and road salt). Upon sunrise, ClNO 2 rapidly photolyzes to generate highly reactive chlorine radicals (Cl • ) that affect the air quality by generating secondary air pollutants. Recent studies have shown road salt aerosols and saline snowpack to be sources of ClNO 2 in the wintertime urban environment; however, the quantitative contributions of each chloride source are not known. In this study, we examine the vertically resolved contributions of aerosol particles and saline snowpack as sources of ClNO 2 by using an observationally constrained snow–atmosphere coupled one-dimensional model applied to wintertime Kalamazoo, Michigan, U.S. Model simulations show that ClNO 2 emitted from urban snowpack can be vertically transported throughout the entire atmospheric boundary layer and can be a significant source of ClNO 2 , contributing up to ~60% of the ClNO 2 budget near the surface. Here, modeled snowpack ClNO 2 emission rates were 6 (±7) times higher than the observationally derived emission rates, suggesting that not all snow chloride is available for reaction. ClNO 2 production from both aerosol particles and snow emissions are required to best simulate the observed surface-level ClNO 2 . Using the traditional bulk parameterization for ClNO 2 produced from particles significantly overestimated ClNO 2 due to the assumption of having equivalent dinitrogen pentoxide (N 2 O 5 ) uptake and chloride availability for the entire particle population. In comparison, the chemically resolved surface area-based parameterization slightly underestimated the observations and had uncertainties deriving from ClNO 2 production from residential wood burning particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Real-Time Gear-Shift Optimization for an Autonomous Wheel Loader

Off-road vehicles, such as wheel loaders, consume a significant amount of fuel during the transportation of materials. The gear-shifting process is crucial in fuel savings for transportation, and therefore, optimization of gearshifts is important for vehicle control. For an autonomous off-road vehicle, there is potential for more fuel savings by proper coordination of gearshift optimization and optimization of other control inputs. This brief proposes a new method for integrating gear-shifting into transportation optimization for an autonomous wheel loader to minimize fuel consumption. Furthermore, tests conducted on short loading cycles show that this method can save around 10%–20% of fuel on average compared with a conventional gearshift-scheduling method.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

A Global Rapid Integrated Monitoring System for Water Cycle and Water Resource Assessment (Global-RIMS)

The main focus of our work was to solidify underlying data sets, the data processing tools and the modeling environment needed to perform a series of long-term global and regional hydrological simulations leading eventually to routine hydrometeorological predictions. A water and energy budget synthesis was developed for the Mississippi River Basin (Roads et al. 2003), in order to understand better what kinds of errors exist in current hydrometeorological data sets. This study is now being extended globally with a larger number of observations and model based data sets under the new NASA NEWS program. A global comparison of a number of precipitation data sets was subsequently carried out (Fekete et al. 2004) in which it was further shown that reanalysis precipitation has substantial problems, which subsequently led us to the development of a precipitation assimilation effort (Nunes and Roads 2005). We believe that with current levels of model skill in predicting precipitation that precipitation assimilation is necessary to get the appropriate land surface forcing.

Roads, John↗
DOE OSTI2020

Community Engagement - A Citizen-Centric Approach to Seeking a Social License - 20017

The long regulatory road has finally been completed-after years of effort a Record of Decision has been signed and a Permit to Construct has been granted or a Permit to Operate has been obtained. But what about the other road that should be taken in parallel-community engagement? Working with the public is not a sequential activity, rather it is a consequential one and needs to be integrated with overall project planning. Unless you have effectively, meaningfully, and patiently engaged with the project's communities of impact, you may find your project trying to obtain a social license or a social license to operate (SLO). The SLO has its origins in the mining industry and its roots in the business model of corporate social responsibility and sustainability. These latter practices are well known to the US DOE and its contractor community. Aspects of the SLO are emerging as individuals and communities are becoming more informed and have increased expectations for being able to influence and shape decisions. When local community issues are not sought out, listened to, or addressed early, and questions are left unanswered, they can become agenda items for larger unaffiliated groups, and project loss (through delays and/or cancellation) can occur. Issues can transition from resolvable to intractable, a type of SLO face-off. Social media campaigns, serial negative media coverage, and protest signs at project sites opposing regulatory decisions already made are no longer anomalies. These types of incidents demonstrate the increasingly delicate relationship between approved regulatory/technical decisions and public acceptance of those decisions. A SLO is not a requirement. However, the building-blocks of a SLO - working with members of affected communities to build understanding, potentially to obtain and maintain community acceptance or even gain approval or support - are evidence of leadership by project sponsors. Actions taken, or not taken, by project sponsors truly have the ability to influence an outcome. While projects are not assured of success or failure, engaging the community in an empowered process is an investment of time and resources toward success for the project and thus for the communities of impact. Authors Note: Extensive literature searches were performed in developing this paper. The majority of the published literature on SLO as a 'movement' was found from sources in Canada, the European Union (Germany and France in particular), South Asia, South Korea, and many Latin American countries. The literature addressed resource development (mining), infrastructure, and energy projects. Articles written by US sources often spoke to origins and structural theory, specific project issues such as Not in My Back Yard (NIMBY) and to protests/demonstrations related to those projects, rather than systemic opposition/conflict phenomena. For these reasons many international SLO experiences and sources are cited in the discussion. The authors recognize these non-US experiences with SLO as having a 'forecast' value to US projects, especially those related to nuclear projects of any type, waste treatment and disposal, energy development (especially fossil fuels as well as alternative sources), mining, and infrastructure. The body of future SLO experiences in the US will shape the future responses to it. (authors)

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The contribution of bioenergy to the decarbonization of transport: a multi-model assessment

The expected growth in the demand for passenger and freight services exacerbates the challenges of reducing transport GHG emissions, especially as commercial low-carbon alternatives to petroleum fuels are limited for shipping, air and long-distance road travel. Biofuels can offer a pathway to significantly reduce emissions from these sectors, as they can easily substitute for conventional liquid fuels in internal combustion engines. In this paper, we assess the potential of bioenergy to reduce transport GHG emissions through an analysis leveraging various integrated assessment models and scenarios, as part of the 33rd Energy Modeling Forum study (EMF-33). Furthermore, we find that bioenergy can contribute a significant, albeit not dominant, proportion of energy supply to the future transport sector: in scenarios aiming to keep the temperature increase below 2 °C by the end of the twenty-first century, models project that in 2100 bioenergy can provide on average 42 EJ/yr (ranging from 5 to 85 EJ/yr) for transport (compared to 3.7 EJ in 2018), mainly through lignocellulosic fuels. This makes up 9–62% of final transport energy use. Only a small amount of bioenergy is projected to be used in transport through electricity and hydrogen pathways, with a larger role for biofuels in road passenger transport than in freight. The association of carbon capture and storage (CCS) with bioenergy technologies (BECCS) is a key determinant in the role of biofuels in transport, because of the competition for biomass feedstock to provide other final energy carriers along with carbon removal. Among models that consider CCS in the biofuel conversion process the average market share of biofuels is 21% in 2100 (ranging from 2 to 44%), compared to 10% (0–30%) for models that do not. Cumulative direct emissions from the transport sector account for half of the emission budget (from 306 to 776 out of 1,000 GtCO 2 ). However, the carbon intensity of transport decreases as much as other energy sectors in 2100 when accounting for process emissions, including carbon removal from BECCS. Lignocellulosic fuels become more attractive for transport decarbonization if BECCS is not feasible for any energy sectors. Since global transport service demand increases and biomass supply is limited, its allocation to and within the transport sector is uncertain and sensitive to assumptions about political as well as technological and socioeconomic factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Characterization of recent wild pig-vehicle collisions in Georgia, USA

Vehicle collisions with wild pigs (Sus scrofa) are reported almost everywhere this species is found. However, this is one of the least studied and characterized forms of damage that these invasive animals cause in the United States (U.S.). Here, we analyzed 518 wild pig-vehicle collisions (WPVCs) that took place statewide in Georgia between 2015 and 2021. From that dataset, we analyzed several parameters in order to better understand and characterize these accidents on a scale that had previously not been done in the U.S. Wild pig-vehicle collisions were reported from 105 out of the 159 counties in Georgia, increasing in number annually over the seven-year period. WPVCs were most likely to occur in the fall (37%). A duration weighted time of day analysis showed that WPVCs were most frequent at dusk. Most (97%) reported accidents were caused by live wild pigs, with the remainder being due to collisions with already dead or road-killed pigs. Most (86%) collisions involved a single wild pig while the remainder occurred with two or more pigs. Collisions occurred mostly with passenger cars on dry, straight, and level two-lane blacktop roads under dark, unlighted conditions. Nine percent of the vehicle accidents involving wild pigs resulted in injuries to the drivers and passengers. Some of the most severe injuries reported were caused by swerving to avoid striking wild pigs. No human fatalities were recorded due to these accidents. Wild pig-vehicle collisions are costly and dangerous and should be closely monitored and mitigated by the agencies responsible for motorist safety, transportation infrastructure, and wildlife management.

Georgia↗
DOE OSTI2024

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗
DOE OSTI2025

An approach for spent nuclear fuel containment integrity verification using gas tagging

Verification of containment integrity is required for spent nuclear fuel (SNF) managed by the commercial nuclear industry and U.S. Department of Energy (DOE), especially after extended storage. Certain SNF storage systems, such as the DOE road-ready dry storage system, hold several packaged containments within a welded over-canister. These packaged containments are called Department of Energy Standard Canisters (DOESCs). DOESC leakage identification is challenging because their containment boundary cannot be accessed for testing and their contents (i.e., SNF and fill gas) are often similar. There are concerns that this could result in costly characterization and repackaging operations of DOE road-ready dry storage systems if compromised DOESCs are suspected. Here, to address these concerns, this paper presents an approach for applying a gas tagging process using xenon to uniquely identify compromised inaccessible containments following extended storage. The containments considered for this application are seven DOESCs, each packaged within a single over-canister. Two different SNF loading configurations from the Advanced Test Reactor and Fort Saint Vrain nuclear power plant are considered. These configurations are used to represent research reactor aluminum-clad spent nuclear fuel (ASNF) and TRi-structural ISOtropic (TRISO) SNF types. Results for this application show that for ASNF and TRISO type fuels for which the selected fuels are representative, the volume of taggant required at loading is determined primarily by the lower detection limit and leak rate of taggant from a compromised DOESC, rather than the amount of fission-generated xenon in the loaded fuel. While the application presented is suited for larger leaks, smaller leaks could be detected by modifying certain design parameters. This gas tagging approach can also be applied to other DOE containments and advanced reactor SNF storage systems.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2020

Recent developments in catalyst-related PEM fuel cell durability

Cost and durability remain the two major barriers to the widespread commercialization of polymer electrolyte membrane fuel cell (PEMFC)-based power systems, especially for the most impactful but challenging fuel cell electric vehicle (FCEV) application. Commercial FCEVs are now on the road; however, their PEMFC systems do not meet the cost targets established by the U.S. Department of Energy, primarily due to the high platinum loading needed on the cathode to achieve the requisite performance and lifetime. Furthermore, while the activities of a number of commercial Pt-based alloy cathode catalysts exceed the beginning-of-life (BOL) targets, these activities, and the overall cathode performance, degrade via a variety of mechanisms described herein. Degradation is mitigated in current FCEVs by utilizing a cathode catalyst with a lower BOL activity (e.g., much lower transition metal alloy content and larger BOL nanoparticle size), necessitating higher catalyst loadings, and through the utilization of system controls that avoid conditions known to exacerbate degradation processes, such as limiting the fuel cell stack voltage range. The design and development of active and robust materials and eliminating the need for vehicle mitigation strategies would greatly simplify the operating system, allowing for greater transient operation, avoiding large hybridization, and curtailing of fuel cell power. Although system mitigation strategies have provided the near-term pathway for FCEV commercialization, material-specific solutions are required to further reduce costs and improve operability and efficiency. Future material developments should focus on stabilization of the electrode structure and minimization of the catalyst particle susceptibility to dissolution caused by oxide formation and reduction over PEMFC cathode-relevant operating potentials plus minimization of support corrosion. Ex situ accelerated stress tests have provided insight into the processes responsible for material and performance degradation and will continue to provide useful information on the relative stability of materials and benchmarks for robust and stable materials-based solutions not requiring system mitigation strategies to achieve adequate lifetime.

25 ENERGY STORAGE↗
DOE OSTI2024

Coal-derived electrically conductive asphalt pavements for snow/ice melting: From laboratory to field

Timely removal of ice and snow from roads is critical to safe, fast, and uninterrupted transportation networks in cold regions. Constructing electrically conductive asphalt pavements to melt the ice and snow on the roads through resistive eating is an emerging alternative technology to traditional snow/ice removal approaches such as utilizing snowplow machines and deicing chemicals. Carbon-based fibers and fillers including carbon fiber and graphite have been widely reported to make electrically conductive hot mix asphalt mixtures for pavement snow/ice-melting applications. This study aimed to develop and demonstrate a novel type of electrically conductive asphalt pavements for snow/ice-melting, which utilizes electrically conductive cold mix asphalt (CMA) mixtures incorporating coal-derived carbon-based coke aggregate as resistive heating elements. Both laboratory experiments and field tests were conducted to investigate the electrical, mechanical, and thermal properties of such electrically conductive asphalt mixtures and pavements. The laboratory experiment results indicated that the electrically conductive CMA mixtures incorporating coke aggregate had sufficiently high electrical conductivity and satisfactory mechanical performance and the pavement prototype slab utilizing a thin layer of such CMA mixtures could successfully raise the pavement surface temperatures to 8.3–11.7 °C rom a low temperature of –5 °C with an input power density of 473 W/m 2 . The field test results showed that the full-scale coal-derived electrically conductive asphalt pavements were able to increase the pavement surface temperatures when electricity was applied, but the magnitude of temperature increase was highly dependent on the power density. Furthermore, it is promising to use coke aggregate to construct coal-derived electrically conductive asphalt pavements for snow/ice melting.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transportation in net-zero emissions futures: Insights from the EMF-37 model intercomparison study

Transportation is currently the largest source of U.S. anthropogenic CO 2 emissions, at about a third of the total. Achieving net-zero emissions by mid-century will require substantial reductions in transportation emissions across passenger and freight travel. Here we leverage a model intercomparison study to explore the role of transportation in scenarios achieving net-zero economy-wide CO 2 emissions by 2050. We find the transport sector is poised to play the most significant role in reducing demand-side emissions, mostly driven by technology substitution, as modeling results suggest a limited role for mode shifting and for reduced use of personal car travel in the U.S. Among various technology solutions, models show agreement that passenger on-road vehicles will largely transition to electric vehicles (EVs), while solutions to decarbonize heavier travel modes are more diverse and include greater use of liquid biofuels and hydrogen. Research should continue to investigate the evolution of on-road electrification, the role of biofuels and hydrogen across heavier travel modes, and the role of mode shifting and travel behavior change to support personal transportation decarbonization at national and regional scales to temper the rapid growth in clean fuel and electricity demand.

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 OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗
DOE OSTI2025

Strategies to mitigate urban heat: Effects on overheating and cloud formation

This study evaluates the effectiveness of various urban heat island (UHI) overheating mitigation strategies and their associated impacts on urban cloud dynamics and thermal processes. This study shows cloud-resolving and urban-resolving modeling results estimating the impact of Houston-Galveston heat mitigation scenarios and other resilient strategies contemplated in the Climate Adaptation Plan and Resilient Houston reports. The simulated scenarios include high intensity green rooftops, rooftop photovoltaic solar panels, enhanced urban irrigation, white/cool roofs and roads, and street trees. We contrast the adaptation scenarios against a present baseline case, a no city scenario and a larger and denser city as projected by the Houston-Galveston Area Council for 2045. During the daytime, cooling strategies such as cool roofs, cool roads, and green roofs exhibit superior performance in mitigating urban overheating. At night, enhanced urban irrigation emerges as the most effective cooling intervention. Cooling strategies significantly reduce sensible heat flux partitioning during the day, a process that reduces the uplift of air, suppressing the formation of urban shallow cumulus clouds. The extent of urban cloud mixing ratio is reduced in proportion to the decrease in sensible heating. Under the BEP-Tree scenario, which includes wind effects and evapotranspiration driven by a stomatal conductance model, urban trees demonstrated negligible environmental cooling effects and minimal urban cloud modifications. In contrast, the scenarios with more urban cooling and higher latent heat fluxes led to suppressed urban clouds. The net cooling effect achieved by the heat mitigation strategies is influenced by a combination of indirect processes, including the reduction of downwelling longwave radiation flux, due to reduced cloud presence, while some warming is attributed to a modest increase in shortwave radiation that offsets the cooling benefit. Additionally, reduced heat dissipation, weakened thermal gradients, and diminished vertical mixing over urban areas further moderate the cooling potential. These findings highlight the pivotal role of clouds and moist atmospheric processes in shaping the UHI effect and offer insights for designing more effective urban cooling strategies.

albedo changes↗