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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Engine-in-the-Loop Study of a Hierarchical Predictive Online Controller for Connected and Automated Heavy-Duty Vehicles

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. This work is experimentally experimentally validated via a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve the closed-loop validation of the proposed control strategies, both individually and combined. These studies show that this hierarchy of algorithms is capable of running online, with the round-trip communication delay inherent in EIL simulation being one of the key factors affecting the EIL results. Moreover, the EIL studies are encouraging, both in terms of the successful hierarchical integration of the underlying algorithms and also in the resulting fuel savings seen in the EIL tests. In particular, the EIL results suggest that an aggressive overall goal of reducing vehicle fuel consumption by 15-20% or more is potentially achievable, especially in urban/suburban scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1995

Overview of thermal barrier coatings in diesel engines

An understanding of delamination mechanisms in thermal barrier coatings has been developed for diesel engine applications through rig tests, structural analysis modeling, nondestructive evaluation, and engine evaluation of various thermal barrier coatings. This knowledge has resulted in improved thermal barrier coatings which survive abusive cyclic fatigue tests in high output diesel engines. Although much conflicting literature now exists regarding the impact of thermal barrier coatings on engine performance and fuel consumption, the changes in fuel consumption appear to be less than a few percent and can be negative for state-of-the-art diesel engines. The ability of the thermal barrier coating to improve fuel economy tends to be dependent on a number of factors including the fuel injection system, combustion chamber design, and the initial engine fuel economy. Limited investigations on state-of-the-art diesel engines have indicated that the surface connected porosity and coating surface roughness may influence engine fuel economy. Current research efforts on thermal barrier coatings are primarily directed at reducing in-cylinder heat rejection, thermal fatigue protection of underlying metal surfaces and a possible reduction in diesel engine emissions. Significant efforts are still required to improve the plasma spray processing capability and the economics for complex geometry diesel engine components.

Yonushonis, Thomas M.↗
DOE OSTI2023

Analysis of Uncertainty Impacts on Emissions and Fuel Economy Evaluation for Chassis Dynamometer Testing

This study illustrates a methodology for quantifying the uncertainties encountered in the measurement of tailpipe emissions and in the fuel consumption measurements for light-duty conventional vehicles tested on a four-wheel drive chassis dynamometer. The study leverages high-fidelity experimental data collected over three standard drive cycles, UDDS, HWY and US06, intended to simulate a wide range of operating conditions. Here, a method is developed to estimate the measurement uncertainties in fuel consumption for a test cycle, which occur due to the accumulation of measurement uncertainties propagated through the system. The uncertainty determination model uses statistical analysis and standard propagation techniques to evaluate and combine the uncertainties introduced from various sources (including the vehicle, chassis dynamometer, driver, and instrumentation). The analysis also examines three different experimental methods for determining the fuel consumption: 1) carbon mass balance, 2) volumetric fuel scale and 3) gravimetric fuel scale, and takes into consideration the properties of the instrumentation used. The results show that the most significant influence on the determination of the emissions comes from the concentration measurement, and similarly the biggest impact on the total fuel consumption uncertainty comes from the uncertainty in the determination of the carbon dioxide mass, due to the large presence of this pollutant in the overall emissions. It was found that the fuel consumption uncertainties are in the range of ±1-2% for all three methods analyzed, with the lowest values being obtained for measurements performed using the gravimetric method for all three drive cycles considered.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1977

The aircraft energy efficiency active controls technology program

Broad outlines of the NASA Aircraft Energy Efficiency Program for expediting the application of active controls technology to civil transport aircraft are presented. Advances in propulsion and airframe technology to cut down on fuel consumption and fuel costs, a program for an energy-efficient transport, and integrated analysis and design technology in aerodynamics, structures, and active controls are envisaged. Fault-tolerant computer systems and fault-tolerant flight control system architectures are under study. Contracts with leading manufacturers for research and development work on wing-tip extensions and winglets for the B-747, a wing load alleviation system, elastic mode suppression, maneuver-load control, and gust alleviation are mentioned.

Hood, R. V., Jr.↗
NASA NTRS1983

Performance of high-altitude, long-endurance, turboprop airplanes using conventional or cryogenic fuels

An analytical study has been conducted to evaluate the potential endurance of remotely piloted, low speed, high altitude, long endurance airplanes designed with 1990 technology. The baseline configuration was a propeller driven, sailplane like airplane powered by turbine engines that used JP-7, liquid methane, or liquid hydrogen as fuel. Endurance was measured as the time spent between 60,000 feet and an engine limited maximum altitude of 70,000 feet. Performance was calculated for a baseline vehicle and for configurations derived by varying aerodynamic, structural or propulsion parameters. Endurance is maximized by reducing wing loading and engine size. The level of maximum endurance for a given wing loading is virtually the same for all three fuels. Constraints due to winds aloft and propulsion system scaling produce maximum endurance values of 71 hours for JP-7 fuel, 70 hours for liquid methane, and 65 hours for liquid hydrogen. Endurance is shown to be strongly effected by structural weight fraction, specific fuel consumption, and fuel load. Listings of the computer program used in this study and sample cases are included in the report.

Liu, G. C.↗
NASA NTRS2010

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Ng, Hok K.↗
NASA NTRS2018

Vehicle-Level System Impact of Boundary Layer Ingestion for the NASA D8 Concept Aircraft

The purpose of this study was to evaluate the vehicle-level impact of a boundary layer ingestion (BLI) propulsion system on a commercial transport aircraft concept. The NASA D8 (ND8) aircraft was chosen as the BLI concept aircraft to be studied. A power balance methodology developed by the Massachusetts Institute of Technology was adapted for use with the existing NASA sizing and performance tools to model the fuel consumption impact of BLI on the ND8. A key assumption for the BLI impact assessment was a 3.5% efficiency penalty associated with designing a fan for and operating in the distorted flow caused by BLI. The ND8 was compared to several other ND8-like aircraft that did not utilize BLI in order to determine the fuel consumption benefit attributable to BLI. Analytically “turning off” BLI on the ND8 without accounting for the physical requirements of redirecting the boundary layer or resizing the aircraft to meet the performance constraints resulted in a 2.8% increase in block fuel consumption to fly the design mission. When this non-physical aircraft was resized to meet the performance constraints, the block fuel consumption was 4.0% greater than the baseline ND8. The ND8 was also compared to an ND8-like aircraft with conventionally podded engines under the wing. This configuration had a 5.6% increase in block fuel consumption compared to the baseline ND8. This result is more reflective of the real world impact if BLI is not an available technology for the ND8 design. The BLI benefit results presented for this study should not be applied to other aircraft that have a propulsion-airframe integration design or BLI implementation different from the ND8.

Marien, Ty V.↗
NASA NTRS1981

An investigation of drag reduction for tractor trailer vehicles with air deflector and boattail

A wind tunnel investigation was conducted to determine the influence of several physical variables on the aerodynamic drag of a trailer model. The physical variables included: a cab mounted wind deflector, boattail on trailer, flow vanes on trailer front, forced transition on trailer, and decreased gap between tractor and trailer. Tests were conducted at yaw angles (relative wind angles) of 0, 5, 10, 20, and 30 degrees and Reynolds numbers of 3.58 x 10 to the 5th power 6.12 x 10 to the 5th power based upon the equivalent diameter of the vehicles. The wind deflector on top of the cab produced a calculated reduction in fuel consumption of about 5 percent of the aerodynamic portion of the fuel budget for a wind speed of 15.3 km/hr (9.5 mph) over a wind angle range of 0 deg to 180 deg and for a vehicle speed of 88.5 km/hr (55 mph). The boattail produced a calculated 7 percent to 8 percent reduction in fuel consumption under the same conditions. The decrease in gap reduced the calculated fuel consumption by about 5 percent of the aerodynamic portion of the fuel budget.

Muirhead, V. U.↗
DOE OSTI2024

Propulsion Electrification Architecture Selection Process and Cost of Carbon Abatement Analysis for Heavy-Duty Off-Road Material Handler

The heavy-duty off-road industry continues to expand efforts to reduce fuel consumption and CO 2 e (carbon dioxide equivalent) emissions. Many manufacturers are pursuing electrification to decrease fuel consumption and emissions. Future policies will likely require electrification for CO2e savings, as seen in light-duty on-road vehicles. Electrified architectures vary widely in the heavy-duty off-road space, with parallel hybrids in some applications and series hybrids in others. The diverse applications for different types of equipment mean different electrified configurations are required. Companies must also determine the value in pursuing electrified architectures; this work analyzes a range of electrified architectures, from micro hybrids to parallel hybrids to series hybrids to a BEV, looking at the total cost, total CO 2 e, and cost per CO 2 e (cost of carbon abatement, or cost of carbon reduction) using data for the year 2021. This study is focused on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i. This machine’s specialty application, including events like unloading large oil pipes from a railcar, requires a unique electrified architecture that suits its specific needs. However, the results from this study may be extrapolated to similar machinery to inform fuel savings options across the heavy-duty off-road industry. In this study, a unique electrified architecture is determined for the Cary-Lift. This architecture is informed by multiple rounds of a Pugh matrix decision analysis to select a shortened list of desirable electrified architectures. The shortened list is modeled and simulated to determine CO 2 e, cost, and cost per CO 2 e. A final architecture is determined as a plug-in series hybrid that reduces fuel consumption by 65%, targeting the large fuel and CO 2 e savings that are likely to be required for the future of the heavy-duty off-road industry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Low-Temperature Plasma Assisted Kinetics Study of Ethanol

Abstract: Non- equilibrium plasma assisted kinetics of ethanol at 0.5 atm over a temperature range of 523-1203 K were studied at stoichiometric conditions by using a plasma flow reactor (PFR). The effects of plasma chemistry on fuel and its influence on neutral chemistry is decoupled with both experimental and modelling efforts. Enhanced reactivity was observed experimentally in both plasma-assisted oxidation and pyrolysis cases with fuel consumption beginning at temperatures as low as 523 K. Absolute fuel consumption was observed at temperatures nearly 200 K earlier than pure thermal reactions highlighting the effectiveness of non-equilibrium plasma to promote reactivity. Modelling results illustrated the effect of electron impact reactions towards accelerating fuel consumption and promoting low temperature chemistry by generating excited state N2 and reactive O and OH radicals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each n close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces green- house gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.

vehicle platooning, sensor performance, semi-auton↗
DOE OSTI2023

Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information

Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

47 OTHER INSTRUMENTATION↗
NASA NTRS2010

Fuel Efficient Strategies for Reducing Contrail Formations in United States Air Space

This paper describes a class of strategies for reducing persistent contrail formation in the United States airspace. The primary objective is to minimize potential contrail formation regions by altering the aircraft's cruising altitude in a fuel-efficient way. The results show that the contrail formations can be reduced significantly without extra fuel consumption and without adversely affecting congestion in the airspace. The contrail formations can be further reduced by using extra fuel. For the day tested, the maximal reduction strategy has a 53% contrail reduction rate. The most fuel-efficient strategy has an 8% reduction rate with 2.86% less fuel-burnt compared to the maximal reduction strategy. Using a cost function which penalizes extra fuel consumed while maximizing the amount of contrail reduction provides a flexible way to trade off between contrail reduction and fuel consumption. It can achieve a 35% contrail reduction rate with only 0.23% extra fuel consumption. The proposed fuel-efficient contrail reduction strategy provides a solution to reduce aviation-induced environmental impact on a daily basis.

Sridhar, Banavar↗
DOE OSTI2023

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗
NASA NTRS1980

Vehicle testing of Cummins turbocompound diesel engine

Two turbocompound diesel engines were installed in Class VIII heavy-duty vehicles to determine the fuel consumption potential and performance characteristics. One turbocompound powered vehicle was evaluated at the Cummins Pilot Center where driveability, fuel consumption, torsional vibration, and noise were evaluated. Fuel consumption testing showed a 14.8% benefit for the turbocompound engine in comparison to a production NTC-400 used as a baseline. The turbocompound engine also achieved lower noise levels, improved driveability, improved gradeability, and marginally superior engine retardation. The second turbocompound engine was placed in commercial service and accumulated 50,000 miles on a cross-country route without malfunction. Tank mileage revealed a 15.92% improvement over a production NTCC-400 which was operating on the same route.

Brands, M. C.↗
DOE OSTI2021

Extreme Miller cycle with high intake boost for improved efficiency and emissions in heavy-duty diesel engines

This study experimentally investigates the impact of extreme Miller cycle strategies paired with high intake manifold pressures on the combustion process, emissions, and thermal efficiency of heavy-duty diesel engines. Well-controlled experiments isolating the effect of Miller cycle strategies on the combustion process were conducted at constant engine speed and load (1160 rpm, 1.76 MPa net IMEP) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Late intake valve closing (LIVC) timing strategies were compared to a conventional intake valve profile under either constant cylinder composition, constant engine-out NO x emission, or constant overall turbocharger efficiency (η TC ) to investigate the operating constraints that favor Miller cycle operation over the baseline strategy. Furthermore, utilizing high boost with conventional intake valve closing timing resulted in improved fuel consumption at the expense of sharp increases in peak cylinder pressures, engine-out NO x emissions, and reduced exhaust temperatures. Miller cycle without EGR at constant λ demonstrated LIVC strategies effectively reduce engine-out NO x emissions by up to 35%. However, Miller cycle associated with very aggressive LIVC timings led to fuel consumption penalties due to increased pumping work and exhaust enthalpy. LIVC strategies allowed for increased charge dilution at the baseline NO x constraint of 3.2 g/kWh, resulting in significant fuel consumption benefits over the baseline case without compromising exhaust temperatures or peak cylinder pressures. As Miller cycle implementation was shown to affect the boundary conditions dictating η TC , the LIVC and conventional IVC cases were studied at an equivalent η TC point representative of high boost operation. With high boost, LIVC yielded reduced NO x emissions, reduced peak cylinder pressures, and elevated exhaust temperatures compared to the conventional IVC case without compromising fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Optimizing bioenergy biofuel harvest: a comparative analysis of stepwise and integrated methods for economic and environmental sustainability

Switchgrass is a promising bioenergy feedstock due to its high biomass yield potential, adaptability to marginal lands, and low carbon intensity for feedstock production. However, accurate cost estimation and assessment of greenhouse gas (GHG) emissions for the energy-intensive harvesting process are essential for evaluating the sustainability of bioenergy. This study provides a comparative analysis of two harvesting methods: the Stepwise Method, which separates operations into multiple stages, and the Integrated Method, which combines mowing and raking into a single pass. The analysis was conducted under four scenarios based on field sizes and biomass yields. Using three years of field-scale switchgrass harvest data from 125 sites, GHG emissions, energy consumption, and harvesting costs were quantified using the GREET model and techno-economic analysis. Additionally, regression analysis identified key climate and operational factors affecting fuel consumption. The Stepwise method was the most cost-effective for large fields with high biomass yield, achieving the lowest harvesting costs ($37.70 per ton). In contrast, the Integrated Method performed better in small fields and low-yield conditions, reducing GHG emissions by 9 % and energy use by 5 %. Regression analysis confirmed that a larger field size reduced fuel consumption, while higher biomass yield and longer operational time increased fuel use. Maximum temperature also contributed to a slight increase in fuel consumption. Furthermore, these results provide actionable insights for optimizing harvesting strategies based on field-specific conditions and operational goals, contributing to the economic and environmental sustainability of bioenergy production.

60 APPLIED LIFE SCIENCES↗