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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Transportation Energy Futures Series: Effects of Travel Reduction and Efficient Driving on Transportation: Energy Use and Greenhouse Gas Emissions

Since the 1970s, numerous transportation strategies have been formulated to change the behavior of drivers or travelers by reducing trips, shifting travel to more efficient modes, or improving the efficiency of existing modes. This report summarizes findings documented in existing literature to identify strategies with the greatest potential impact. The estimated effects of implementing the most significant and aggressive individual driver behavior modification strategies range from less than 1% to a few percent reduction in transportation energy use and GHG emissions. Combined strategies result in reductions of 7% to 15% by 2030. Pricing, ridesharing, eco-driving, and speed limit reduction/enforcement strategies are widely judged to have the greatest estimated potential effect, but lack the widespread public acceptance needed to accomplish maximum results. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

Transportation Energy Futures Series: Effects of Travel Reduction and Efficient Driving on Transportation: Energy Use and Greenhouse Gas Emissions

Since the 1970s, numerous transportation strategies have been formulated to change the behavior of drivers or travelers by reducing trips, shifting travel to more efficient modes, or improving the efficiency of existing modes. This report summarizes findings documented in existing literature to identify strategies with the greatest potential impact. The estimated effects of implementing the most significant and aggressive individual driver behavior modification strategies range from less than 1% to a few percent reduction in transportation energy use and GHG emissions. Combined strategies result in reductions of 7% to 15% by 2030. Pricing, ridesharing, eco-driving, and speed limit reduction/enforcement strategies are widely judged to have the greatest estimated potential effect, but lack the widespread public acceptance needed to accomplish maximum results. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Citywide Impacts of E-Commerce: Does Parcel Delivery Travel Outweigh Household Shopping Travel Reductions?

E-commerce has facilitated online ordering of goods by households in recent years. This technological advancement has disrupted shopping related transportation. While the National Household Travel Survey (NHTS [1]) finds that household shopping frequency has declined in the last 10-20 years, deliveries by parcel delivery trucks and vans [2] have increased. However, the net effect of these phenomena on overall trip making, vehicle-miles traveled (VMT) and fuel consumption has not been quantified. From a regional planning perspective, understanding the net effect is important for informing city policies--for example, in regards to land use and transportation planning. The objective of this research is to address this gap. In this study, the net regional impact of e-commerce on transportation and fuel consumption is evaluated. The approach relies on a powerful, agent-based modeling framework (POLARIS [3]) that models decisions made by individual household and commercial agents. E-commerce demand is modeled for each household using a bilevel multinomial probit structure that evaluates e-commerce participation and ordering frequency. Last-mile delivery tours were constructed using GIS-based tools and information from a major parcel delivery company [4]. After integrating the resulting supply and demand models with all other passenger and commercial traffic within POLARIS, a traffic simulation was performed and subsequently VMT and energy consumption were analyzed. The study finds that while e-commerce has generated an increase in parcel truck delivery trips, the net effect of e-commerce is a reduction in VMT and fuel consumption due major reductions in these quantities via shopping trip reductions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A GPU-based Approach for Path Planning Optimization via Travel Length Reduction

Typically, before constructing an object with an additive manufacturing system, the 3D object must be sent through a process called slicing. Slicing converts a 3D object commonly in the form of an STL file into a set of layers by horizontally intersecting a plane with the object at various heights. At each height, called a layer, multiple 2D polygons can be generated. Each polygon represents a boundary for solid geometry and is called an island. Each island is then comprised of multiple path types in an attempt to optimally fill the polygon. To move between each island and each islands’ paths, travels are inserted. Travels are simply motion by the system to move from one area of construction to another. Travels do not contribute to the construction of the object, and so, are considered wasted motion. In large-scale additive manufacturing, objects can be quite large and the distance between islands can be large as well. As a result, these travels can waste a significant amount of time. Ideally, travels would be as short as possible, however, computing global minimal travel paths is computationally expensive. To combat this problem, researchers at Oak Ridge National Lab developed a GPU-based approach to travel insertion based on a unique factoradic representation. This representation was then utilized by the GPU to solve the Traveling Salesman Problem (TSP). This algorithm was able to compute global minimal travel paths quickly resulting in faster object construction. A general investigation was also carried out to determine when a GPU vs CPU implementation would be beneficial.

Borish, Michael↗
DOE OSTI2021

Roads less traveled: Nitrogen reduction reaction catalyst design strategies for improved selectivity

Direct electrochemical nitrogen reduction for ammonia production is necessary to reduce the use of fossil fuels from conventional Haber–Bosch methods. Applications of nitrogen reduction electrocatalysts remain inhibited by slow reaction kinetics and low faradaic efficiencies because of competitive H2 production pathways. Current strategies to address this challenge in selectivity have focused on catalyst design, reactor configuration, and electrolyte conditions. This brief review discusses the thermodynamic and kinetic challenges in the field as well as current underused approaches for selective catalyst development including bimetallic catalysts, transition metal nitrides, and carbon supports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Clean Cities and Communities Partnership 2023 Activity Report

This is the 2023 report for the Clean Cities and Communities (CC&C) partnership. It tracks the metrics that have been reported by individual coalitions and aggregated to the national level. It looks at the various outreach activities, grant activities, and implementation of clean transportation technologies. Such technologies include natural gas vehicles, electric vehicles, propane vehicles, hydrogen fuel cell vehicles, biodiesel, ethanol, idle reduction technologies, fuel economy improvement technologies, vehicle-miles-traveled reduction technologies, and off-road technologies. The CC&C partnership had an energy use impact of over 1 billion gallons in 2023 and reduced emissions by nine million tons. Outreach, engagement, and training activities increased 18% from last year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2014

Push-Pull Locomotion for Vehicle Extrication

For applications in which unmanned vehicles must traverse unfamiliar terrain, there often exists the risk of vehicle entrapment. Typically, this risk can be reduced by using feedback from on-board sensors that assess the terrain. This work addressed the situations where a vehicle has already become immobilized or the desired route cannot be traversed using conventional rolling. Specifically, the focus was on using push-pull locomotion in high sinkage granular material. Push-pull locomotion is an alternative mode of travel that generates thrust through articulated motion, using vehicle components as anchors to push or pull against. It has been revealed through previous research that push-pull locomotion has the capacity for generating higher net traction forces than rolling, and a unique optical flow technique indicated that this is the result of a more efficient soil shearing method. It has now been found that pushpull locomotion results in less sinkage, lower travel reduction, and better power efficiency in high sinkage material as compared to rolling. Even when starting from an "entrapped" condition, push-pull locomotion was able to extricate the test vehicle. It is the authors' recommendation that push-pull locomotion be considered as a reliable back-up mode of travel for applications where terrain entrapment is a possibility.

extrication↗
NASA NTRS2017

Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing

As NASA strives to explore the surface of the Moon and Mars, there is a continued need for improved tire and vehicle development. When tires or vehicles are being designed for off-road conditions where significant thrust generation is required, such as climbing out of craters on the Moon, it is important to use a standard test method for evaluating their tractive performance. The drawbar pull (DP) test is a way of measuring the net thrust generated by tires or a vehicle with respect to performance metrics such as travel reduction, sinkage, or power efficiency. DP testing may be done using a single tire on a traction rig, or with a set of tires on a vehicle; this report focuses on vehicle DP tests. Though vehicle DP tests have been used for decades, there are no standard procedures that apply to exploration vehicles. This report summarizes previous methods employed, shows the sensitivity of certain test parameters, and provides a body of knowledge for developing standard testing procedures. The focus of this work is on lunar applications, but these test methods can be applied to terrestrial and planetary conditions as well. Section 1.0 of this report discusses the utility of DP testing for off-road vehicle evaluation and the metrics used. Section 2.0 focuses on test-terrain preparation, using the example case of lunar terrain. There is a review of lunar terrain analogs implemented in the past and a discussion on the lunar terrain conditions created at the NASA Glenn Research Center, including methods of evaluating the terrain strength variation and consistency from test to test. Section 3.0 provides details of the vehicle test procedures. These consist of a review of past methods, a comprehensive study on the sensitivity of test parameters, and a summary of the procedures used for DP testing at Glenn.

wheel↗
DOE OSTI2022

Optimizing lane reversals in transportation networks to reduce traffic congestion: A global optimization approach

This paper studies how to reduce the overall travel time of commuters in a transportation network by reversing the direction of some lanes in the network using a macroscopic network-wide perspective. Similar to the Network Design Problem, the lane reversal problem has been shown to be NP-hard given the dependence of the users’ route selection on the lane direction decision. Herein, we propose and compare three efficient methods to solve the routing and lane reversal problem jointly. First, we introduce an alternating method that decouples the routing and lane assignment problems. Second, we propose a Frank–Wolfe method that jointly takes gradient steps to adjust both the lane assignment and routing decisions. Third, we propose a convex approximation method that uses a threshold-based approach to convexify the joint routing and lane reversal objective. The convex approximation method is advantageous since it finds a global optimum solution for the approximated problem and it enables the possibility to include linear constraints. Using this method, we extend the main formulation to be able to limit a maximum number of reversed lanes, as well as to incorporate multiple origin–destination (OD) patterns. We test the proposed methods in a case study using the transportation network of Eastern Massachusetts where our results indicate an overall reduction in travel times of 4.7% by selecting the best 15 reversals. Moreover, using a small test network, we investigate the performance of the lane reversal strategies as a function of the OD demand symmetry. As expected, we observe that when the OD demand is very asymmetric (e.g., for a single OD pair, evacuations, large events), the reduction in travel times is larger than the symmetric case, reaching travel time reductions of 60%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Development of Emergency Vehicle Preemption Strategies on Smart Corridors in a Digital Twin Environment

Emergency Response Vehicles (ERVs), such as firetrucks, ambulances, etc. operate with the purpose of saving lives and mitigating property damage. As such, ERV travel-time reductions may result in significant benefits to the community. A common strategy to improve travel times is Emergency Vehicle Preemption (EVP). EVP seeks to reduce ERV delays by providing the right-of-way to ERVs as they approach an intersection. This study proposes a new Dynamic Preemption strategy that determines the need for preemption prior to the ERV reaching the vicinity of the intersection, utilizing real-time data streams. This paper evaluates the effectiveness of some existing and proposed preempt control strategies using a digital twin testbed consisting of a series of signalized intersections on an urban arterial in Georgia. The best EVP strategy maximizes the improvement in ERV travel time while minimizing the adverse effect of preemption on the traffic in conflicting directions. Therefore, this study evaluates both the positive impact of EVP on the ERV as well as the adverse impact on the cross-street traffic. The study found that the potential exists for significant improvements in ERV travel time with the proposed Dynamic Preemption strategy, with minimal impact to the conflicting traffic. For the simulation corridor there was a 20% reduction in the ERV travel times with the implementation of the Dynamic Preemption strategy, compared to traditional EVP practices.

Roy, Somdut [Georgia Institute of Technology]↗
DOE OSTI2022

Mobility Energy Productivity Evaluation of Prediction-Based Vehicle Powertrain Control Combined with Optimal Traffic Management

Transportation vehicle and network system efficiency can be defined in two ways: 1) reduction of travel times across all the vehicles in the system, and 2) reduction in total energy consumed by all the vehicles in the system. The mechanisms to realize these efficiencies are treated as independent (i.e., vehicle and network domains) and, when combined, they have not been adequately studied to date. This research aims to integrate previously developed and published research on Predictive Optimal Energy Management Strategies (POEMS) and Intelligent Traffic Systems (ITS), to address the need for quantifying improvement in system efficiency resulting from simultaneous vehicle and network optimization. POEMS and ITS are partially independent methods which do not require each other to function but whose individual effectiveness may be affected by the presence of the other. In order to evaluate the system level efficiency improvements, the Mobility Energy Productivity (MEP) metric is used. MEP specifically measures the connectedness of a system while accounting for time and energy externalities of modes that provide mobility in a given location. A SUMO model is developed to reflect real traffic patterns in Fort Collins, Colorado and data is collected by a probe SUMO vehicle which is validated against data collected on a real vehicle driving the same routes through the city. Individual vehicle and system level efficiencies are calculated using SUMO outputs for scenarios which integrate POEMS and ITS independently as well as jointly. Results from application of POEMS and ITS show improvement in energy consumption and travel times respectively when compared to the respective baseline scenarios. Our conclusion is that there are promising synergistic benefits to travel time and energy efficiency when POEMS and ITS are combined.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

Transportation Energy Futures Series: Alternative Fuel Infrastructure Expansion: Costs, Resources, Production Capacity, and Retail Availability for Low-Carbon Scenarios

The petroleum-based transportation fuel system is complex and highly developed, in contrast to the nascent low-petroleum, low-carbon alternative fuel system. This report examines how expansion of the low-carbon transportation fuel infrastructure could contribute to deep reductions in petroleum use and greenhouse gas (GHG) emissions across the U.S. transportation sector. Three low-carbon scenarios, each using a different combination of low-carbon fuels, were developed to explore infrastructure expansion trends consistent with a study goal of reducing transportation sector GHG emissions to 80% less than 2005 levels by 2050.These scenarios were compared to a business-as-usual (BAU) scenario and were evaluated with respect to four criteria: fuel cost estimates, resource availability, fuel production capacity expansion, and retail infrastructure expansion.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Energy and mobility impacts of connected autonomous vehicles with co-optimization of speed and powertrain on mixed vehicle platoons

Intersections are known to be traffic bottlenecks where a significant amount of energy consumption could be caused due to deceleration/acceleration in the presence of red signals. With an increased level of connectivity and automation of intelligent transportation systems, connected autonomous vehicles (CAVs) are expected to be able to proactively adjust their driving strategies subject to constraints imposed by the predicted future traffic. As a result, many potential benefits can be achieved, such as improved energy efficiency, enhanced traffic safety, among many others. Notably, the way CAVs are controlled affects the following legacy vehicles (LVs) due to complex traffic dynamics. Here, we are particularly interested in studying the energy and mobility impact of CAVs with an improved traffic prediction method on mixed vehicle platoons at various market penetration rates. Leveraging traffic prediction, CAVs are controlled with co-optimization of their speed and gear position. Specifically, a traffic prediction framework in a rolling horizon fashion is employed based upon a modified Payne–Whitham (PW) model capable of handling mixed traffic consisting of CAVs and LVs. The prediction error of the modified PW model is reduced by 53.62% compared to that of the standard PW model under test scenarios. According to the predicted traffic conditions, speed and gear position of CAVs are co-optimized with the primary goal of minimizing energy consumption when driving on a signalized arterial. The energy benefits achieved by CAVs and the impact of CAVs on LVs behind are studied comprehensively for mixed vehicle platoons. The lead LV follows a real-world speed profile collected on TH-55 in Minnesota. Numerical results show that energy benefits achieved by the vehicle platoon range from 2% to 16%, and a 1% to 5% reduction in travel time for LVs behind CAVs is also observed, at different penetration rates of CAVs in various traffic scenarios. Furthermore, it is observed that CAVs using the proposed eco-driving approach appear to have a positive impact on the LVs behind in terms of energy consumption, regardless of the driving styles of the LVs ahead.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2018

Impact of connected and automated vehicles on traffic flow

In this paper, we investigate the impact of connected and automated vehicles (CAVs) on traffic flow at merging roadways and develop a microscopic simulation framework to explore the implications on fuel consumption and travel time. In this framework, we use optimal control to simulate the behavior of CAVs and the Gipps car following model to capture the behavior of human-driven vehicles. The simulation results show that CAVs can contribute to significant fuel consumption and travel time reduction for diverse traffic conditions under average and high congestion scenarios. Furthermore, we show that CAVs allow for more stable traffic patterns even for high density traffic.

Rios Torres, Jackeline↗
DOE OSTI2013

Transportation Energy Futures Series: Effects of the Built Environment on Transportation: Energy Use, Greenhouse Gas Emissions, and Other Factors

Planning initiatives in many regions and communities aim to reduce transportation energy use, decrease emissions, and achieve related environmental benefits by changing land use. This report reviews and summarizes findings from existing literature on the relationship between the built environment and transportation energy use and greenhouse gas emissions, identifying results trends as well as potential future actions. The indirect influence of federal transportation and housing policies, as well as the direct impact of municipal regulation on land use are examined for their effect on transportation patterns and energy use. Special attention is given to the 'four D' factors of density, diversity, design and accessibility. The report concludes that policy-driven changes to the built environment could reduce transportation energy and GHG emissions from less than 1% to as much as 10% by 2050, the equivalent of 16%-18% of present-day urban light-duty-vehicle travel. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Built Environment Analysis Tool: April 2013

This documentation describes the tool development. It was created to evaluate the effects of built environment scenarios on transportation energy and greenhouse gas (GHG) emissions. This documentation also provides guidance on how to apply the tool.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Transportation Energy Futures Series: Effects of the Built Environment on Transportation: Energy Use, Greenhouse Gas Emissions, and Other Factors

Planning initiatives in many regions and communities aim to reduce transportation energy use, decrease emissions, and achieve related environmental benefits by changing land use. This report reviews and summarizes findings from existing literature on the relationship between the built environment and transportation energy use and greenhouse gas emissions, identifying results trends as well as potential future actions. The indirect influence of federal transportation and housing policies, as well as the direct impact of municipal regulation on land use are examined for their effect on transportation patterns and energy use. Special attention is given to the 'four D' factors of density, diversity, design and accessibility. The report concludes that policy-driven changes to the built environment could reduce transportation energy and GHG emissions from less than 1% to as much as 10% by 2050, the equivalent of 16%-18% of present-day urban light-duty-vehicle travel. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

33 ADVANCED PROPULSION SYSTEMS↗