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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 19 records

On Road vs. Off Road Low Load Cycle Comparison

Reducing criteria pollutants while reducing greenhouse gases is an active area of research for commercial on-road vehicles as well as for off-road machines. The heavy duty on-road sector has moved to reducing NOx by 82.5% compared to 2010 regulations while increasing the engine useful life from 435,000 to 650,000 miles by 2027 in the United States (US). An additional certification cycle, the Low Load Cycle (LLC), has been added focusing on part load operation having tight NOx emissions levels. In addition to NOx, the total CO2 emissions from the vehicle will also be reduced for various model years. The off-road market is following with a 90% NOx reduction target compared to Tier 4 Final for 130-560 kW engines along with greenhouse gas targets that are still being established. The off-road market will also need to certify with a Low Load Application Cycle (LLAC), a version of which was proposed for evaluation in 2021. Since the LLAC has not been finalized, this study is being conducted to compare and contrast the LLC for on-road with the LLAC for off-road as there might be some shared learnings. A US off-road production 2023 Fiat Powertrain 13L engine and aftertreatment system was chosen for this work. This engine is used in production for both off-road and on-road products, so it is a good choice for this study. The associated off-road aftertreatment system was aged for more relevant comparisons. The engine calibration was not altered for either of the low load cycles. This study shows that the cycles are quite different in nature as the market needs are different. The LLC includes a large fraction of operation at idle and lower speeds, representing products that use the engine primarily for motive power, where lower vehicle speed means a lower engine speed and load. The LLAC has more time and load spent at high speeds and slightly higher loads. The off-road products represented by this cycle often use the engine to drive auxiliary equipment which means higher parasitic loads and hand/fixed throttle. The comparison will include the use profiles, tailpipe NOx and greenhouse gas emissions (CO2, N2O).

McCarthy, James↗

Conceptual design and analysis of roads and road construction machinery for initial lunar base operations

Recent developments have made it possible for scientists and engineers to consider returning to the Moon to build a manned lunar base. The base can be used to conduct scientific research, develop new space technology, and utilize the natural resources of the Moon. Areas of the base will be separated, connected by a system of roads that reduce the power requirements of vehicles traveling on them. Feasible road types for the lunar surface were analyzed and a road construction system was designed for initial lunar base operations. A model was also constructed to show the system configuration and key operating features. The alternate designs for the lunar road construction system were developed in four stages: analyze and select a road type; determine operations and machinery needed to produce the road; develop machinery configurations; and develop alternates for several machine components. A compacted lunar soil road was selected for initial lunar base operations. The only machinery required to produce this road were a grader and a compactor. The road construction system consists of a main drive unit which is used for propulsion, a detachable grader assembly, and a towed compactor.

Sines, Jeffrey L.↗

The road plan model: Information model for planning road building activities

The general building contractor is presented with an information model as an approach for deriving a high-level work plan of construction activities applied to road building. Road construction activities are represented in a Road Plan Model (RPM), which is modeled in the ISO standard STEP/EXPRESS and adopts various concepts from the GARM notation. The integration with the preceding road design stage and the succeeding phase of resource scheduling is discussed within the framework of a Road Construction Model. Construction knowledge is applied to the road design and the terrain model of the surrounding road infrastructure for the instantiation of the RPM. Issues regarding the implementation of a road planner application supporting the RPM are discussed.

Azinhal, Rafaela K.↗

Unofficial Road Building in the Brazilian Amazon: Dilemmas and Models for Road Governance

Unofficial roads form dense networks in landscapes, generating a litany of negative ecological outcomes, but unofficial roads in frontier areas are also instrumental in local livelihoods and community development. This trade-off poses dilemmas for the governance of unofficial roads. Unofficial road building in frontier areas of the Brazilian Amazon illustrates the challenges of 'road governance.' Both state-based and community based governance models exhibit important liabilities for governing unofficial roads. Whereas state-based governance has experienced difficulties in adapting to specific local contexts and interacting effectively with local interest groups, community-based governance has a mixed record owing to social inequalities and conflicts among local interest groups. A state-community hybrid model may offer more effective governance of unofficial road building by combining the oversight capacity of the state with locally grounded community management via participatory decision-making.

Perz, Stephen G.↗

Fleet-Level Energy and Emissions Analysis of the US Off-Road Sector with VISION: Off-Road

In the United States (US), the off-road sector (i.e., agriculture, construction, etc.) contributes to approximately 10% of the country’s transportation greenhouse gas (GHG) emissions, similar to the aviation sector. The off-road sector is extremely diverse; as the EPA MOVES model classifies it into 11 sub-sectors, which include 85 different types of equipment. These equipment types have horsepower ranging from 1 to greater than 3000 and have very different utilization, which makes decarbonization a complex endeavor. To address this, Argonne’s on-road vehicle fleet model, VISION, has been expanded to the off-road sector. The GHG emission factors for several energy carriers (biofuels, electricity, and hydrogen) have been incorporated from Argonne’s GREET model for a sector-wide well-to-wheel (WTW) GHG emissions analysis of the present and future fleet. Several technology adoption and energy decarbonization scenarios were modeled to better understand the appropriate actions required to drive towards net-zero emissions of the off-road sector. Results show that WTW decarbonization up to 67% can be achieved from 2023 to 2050 in a business-as-usual scenario. But with aggressive sales increases of electric and hydrogen powertrains, WTW decarbonization up to 77% can be achieved, which can further increase to 85% if electricity production is aggressively decarbonized by 2035.

lifecycle↗

On the road performance tests of electric test vehicle for correlation with road load simulator

A dynamometer (road load simulator) is used to test and evaluate electric vehicle propulsion systems. To improve correlation between system tests on the road load simulator and on the road, similar performance tests are conducted using the same vehicle. The results of track tests on the electric propulsion system test vehicle are described. The tests include range at constant speeds and over SAE J227a driving cycles, maximum accelerations, maximum gradability, and tire rolling resistance determination. Road power requirements and energy consumption were also determined from coast down tests.

Dustin, M. O.↗

Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network

Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.

Kumarasamy, Vijayalakshmi K [The University of Ten↗

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

Spatio-temporal and weather characterization of road loads of electrified heavy-duty commercial vehicles across U.S. interstate roads

Adoption of battery electric vehicles (BEV) in heavy duty (HD) commercial freight transportation is difficult due to technological and economic hurdles. Beyond safety and compliance, fleet and operational logistics necessitate both high uptime and parity with diesel system productivity/Total Cost of Ownership to support widespread deployment of electric powertrains. However, relatively high energy storage costs, along with the higher weight of BEV systems, limit the viability of HD commercial freight transport to shorter-range applications where smaller batteries will serve for mission energy requirements (single operational shift). Knowing the energy consumption and operating variations of these commercial vehicle systems is crucial for effectively sizing the energy storage systems. This paper is the first in a series of studies to understand the regional specific operating design domain variations of commercial Class 8 HD trucks and the associated impact to their energy requirements. In particular, the local weather conditions are shown to influence the total vehicle energy usage. Further, the impact of temperature, pressure, and humidity changes are shown to impact the local air density. This is needed to calculate aerodynamic drag on vehicles and has been found to play a significant role in the overall performance of a vehicle. Although the methodology of calculating air density varies only slightly throughout the literature, the application to transportation has still been limited. This study provides a means by which air density can be estimated for the contiguous U.S. using the NOAA MADIS dataset. These air density estimates were then used to determine vehicle performance in varying regions of the country to highlight the importance of consideration of weather variables when monitoring vehicle performance, but also to provide recommendations based on these locales upon fleet conversion to BEVs.

Moore, Amy↗

Unofficial Road Building in the Amazon: Socioeconomic and Biophysical Explanations

Roads have manifold social and environmental impacts, including regional development, social conflicts and habitat fragmentation. 'Road ecology' has emerged as an approach to evaluate the various ecological and hydrological impacts of roads. This article aims to complement road ecology by examining the socio-spatial processes of road building itself. Focusing on the Brazilian Amazon, a heavily-studied context due to forest fragmentation by roads, the authors consider non-state social actors who build 'unofficial roads' for the purpose of gaining access to natural resources to support livelihoods and community development. They examine four case studies of roads with distinct histories in order to explain the socio-spatial processes behind road building in terms of profit maximization, land tenure claims, co-operative and conflictive political ecologies, and constraints as well as opportunities afforded by the biophysical environment. The study cases illustrate the need for a multi-pronged theoretical approach to understanding road building, and call for more attention to the role of non-state actors in unofficial road construction.

Perz, Stephen G.↗

GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

Wang, Jie↗

Los Alamos National Laboratory Floodplain Assessment for the West Road Maintenance Project

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing to take action at Los Alamos National Laboratory (LANL) and do maintenance on West Road at locations along its entirety from the intersection with West Jemez Road/New Mexico State Road 501 (NM 501) to the intersection with Dulce Street through Los Alamos Canyon. The proposed West Road Maintenance Project is intended to improve vehicular and pedestrian safety on West Road by reducing traffic hazards associated with poor road conditions and unsafe roadside parking. Proposed road maintenance and improvement activities throughout the length of West Road include asphalt milling and resurfacing of approximately 2.06 miles (mi.) of the road. West Road crosses approximately 0.35 mi. (1,900 feet (ft.)) of the Los Alamos Canyon floodplain at the bottom of Los Alamos Canyon. Project activities within the floodplain include: 1) mill and resurface the roadway, 2) replace existing guardrails, 3) block access to the informal roadside parking along either side of West Road in Los Alamos Canyon, 4) install trail signage and perform trail maintenance, and 5) restore habitat and reduce wildland fire risk through invasive species removal.

54 ENVIRONMENTAL SCIENCES↗

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

Gardner, Margaret E.↗

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗