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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗
DOE OSTI2024

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗
DOE OSTI2020

Compact ultrastable laser system for spectroscopy of {sup 2}S{sub 1/2} → {sup 2}D{sub 3/2} quadrupole transition in {sup 171}Yb{sup +} ion

We report the results of studying a compact laser system designed for manipulating a quantum state of the optical qubit based on the {sup 2}S{sub 1/2} → {sup 2}D{sub 3/2} quadrupole transition in the {sup 171}Yb{sup +} ion at a wavelength of 435.5 nm. An emission power of the laser system reaches 500 μW at λ = 435.5 nm and the relative frequency instability of at most 3 × 10{sup −15} is achieved at averaging intervals from 0.5 to 50 s with a subtracted linear frequency drift. The compactness of the developed system makes it possible to employ it in transportable systems including optical clocks. (laser spectroscopy)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Optimization of a buncher for High Energy H- Beam Transport [Slides]

Accelerators and beam transport systems typically contain numerous beamline devices, diagnostics, system study, and upgrade. Routinely TRACE, MADX and TRANSPORT codes are used for the beam envelope prediction and optimization. Unknown problems of accelerators and beam-transport are addressed based on R&D, such as LFB voltage variation effect study. A nominal diagnostic have used in non-traditional beam transport path to address scientific question (such as use of a BPM in the air). High energy beam operation is a methodical process and routine R&D is required to maintain high standards to deliver beam.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Vehicle Technologies Fiscal Year 2025 Annual Report

Research and development at NLR supports the U.S. Department of Energy's Vehicle Technologies Office in advancing low-cost, abundant, and secure energy technologies to accelerate a more affordable, reliable, efficient, and globally competitive U.S. transportation system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Condenser Enclosure Vibration Isolation Mount Selection

A mini split cooling system will be used to maintain temperature requirements in a mobile secure transport system. While the split cooling system was designed to be used in static residential or commercial applications, it was selected for this transportation application due to a unique set of security requirements. However, the system’s ability maintain reliability and survive prolonged long-term shock and vibration is a significant concern. The mitigation strategy is to select vibration isolation mounts and perform lifetime shock and vibration testing to demonstrate survivability. The goal of this study is to generate a finite element model of the system and perform modal analysis to inform selection of vibration mounts to minimize the amount of vibrational energy transferred to the split cooling system. The scope of this report is limited to study of the condensing unit only, and geometric variation of the assembly will not be allowed.

42 ENGINEERING↗
DOE OSTI2022

Characterizing the Number of Kinesin Motors Bound to Microtubules in the Gliding Motility Assay Using FLIC Microscopy [Book Chapter]

Intracellular transport by kinesin motors moving along their associated cytoskeletal filaments, microtubules, is essential to many biological processes. This active transport system can be reconstituted in vitro with the surface-adhered motors transporting the microtubules across a planar surface. In this geometry, the kinesin-microtubule system has been used to study active self-assembly, to power microdevices, and to perform analyte detection. Fundamental to these applications is the ability to characterize the interactions between the surface tethered motors and microtubules. Further, Fluorescence Interference Contrast (FLIC) microscopy can illuminate the height of the microtubule above a surface, which, at sufficiently low surface densities of kinesin, also reveals the number, locations, and dynamics of the bound motors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Inequality and the Future of Electric Mobility in 36 U.S. Cities: An Innovative Methodology and Comparative Assessment

Electric vehicles are seen as one of the technological solutions to transition our transportation systems away from carbon, and cities offer unique opportunities to electrify transportation. To be equitable, however, this transition will not merely require technological innovations. Acknowledging socio-spatial inequalities and creating strategies to address them are critical - yet relatively underexplored - dimensions of the transportation transition. This paper integrates relevant literature into a micro-urban social typology (MUST) approach that uses agglomerative clustering techniques to examine, first, the factors and attributes defining transportation inequities within 36 U.S. cities, and, second, the implications of these inequities for policies that foster a more equitable transportation transition. By combining socio-spatial and transportation data, we identified five MUSTs: Wealthy, Urban Disadvantaged, Urban Renters, Middle-Class Homeowners, and Rural/Exurban. Rather than being tied to any particular indicator (e.g., homeownership), these MUSTs contain intersecting factors and features of inequities. We compare transportation and health outcomes across MUSTs, and the results suggest that user-centric strategies and public investments are necessary to foster true transportation equity. These must go beyond the electrification of private vehicles and should be tailored to the specific characteristics of each MUST. These could include electric carpooling for the rural/exurban MUST and electrification of transit for the urban disadvantaged and renter MUSTs. Our typology offers a critical next step toward informing transportation transition policies to target critical sociodemographic, economic, and techno-infrastructural factors.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗
DOE OSTI2025

An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.

Ma, Ke↗
DOE OSTI2024

Study on Conversion from an Existing Alternating Current Medium-Voltage Line to a Direct Current Line: A Case of Load or Source Expansion

Simultaneous increase of power generation through renewable systems and load due owing to the rapid growth in electrified road transportation systems, leads to new challenges in the design, operation, and protection of distribution-level electrical power systems. This paper addresses challenges related to the integration of new sources or loads to a distribution grid through long alternating current lines. The International Council on Large Electric Systems medium-voltage benchmark model developed for North America was used for simulation studies. Use cases were developed to illuminate the issues related to long alternating current lines and the usefulness of medium-voltage direct current lines in a distribution network.

Jaldanki, Sreenivasa↗
DOE OSTI2020

Approximation Framework of Embodied Energy of Safety: Insights and Analysis

Transportation safety, as a critical component of an efficient and reliable transportation system, has been extensively studied with respect to societal economic impacts by transportation agencies and policy officials. However, the embodied energy impact of safety, other than induced congestion, is lacking in studies. This research proposes an energy equivalence of safety (EES) framework to provide a holistic view of the long-term energy and fuel consequences of motor vehicle crashes, incorporating both induced congestion and impacts from lost human productivity resulting from injury and fatal accidents and the energy content resulting from all consequences and activities from a crash. The method utilizes a ratio of gross domestic product (GDP) to national energy consumed in a framework that bridges the gap between safety and energy, leveraging extensive studies of the economic impact of motor vehicle crashes. The energy costs per fatal, injury, and property-damage-only (PDO) crashes in gasoline gallon equivalent (GGE) in 2017 were found to be 200,259, 4442, and 439, respectively, which are significantly greater than impacts from induced congestion alone. The results from the motor vehicle crash data show a decreasing trend of EES per crash type from 2010 and 2017, due primarily in part to a decreasing ratio of total energy consumed to GDP over those years. In addition to the temporal analysis, we conducted a spatial analysis addressing national-, state-, and local-level EES comparisons by using the proposed framework, illustrating its applicability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

ADETS User Manual

ADETS (Automated DEpletion Transport System) calculates coupled neutronic/isotopic results for nuclear systems and produces a large number of criticality and burnup results based on various material feed/removal specifications, power(s), and time intervals. ADETS is a fully automated tool that links the LANL MCNP Monte Carlo transport code with the SCALE system, specifically ORIGEN-ARP (radioactive decay and burnup code). Additionally, ADETS can compute the dose at various distances of the reactor using a point gamma source, whose characteristics are computed by ORIGEN-ARP. In addition, ADETS is fully coupled with the Uncertanty Quantification, Probabilistic Risk Assessment, Parameter Optimization and Data Analysis code RAVEN (developed at the Idaho National Laboratory as well). RAVEN is released with ADETS but MCNP and SCALE (ORIGEN-ARP) are not included.

42 ENGINEERING↗
DOE OSTI2022

A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids

Abstract In this study, a spectral model for convective transport is coupled to a thermal population model on a two‐dimensional horizontal “microgrid,” covering the typical gridbox size of general circulation models. The goal is to explore new ways of representing impacts of spatial organization in cumulus cloud fields. The thermals are considered the smallest building block of convection, with thermal life cycle and movement represented through binomial functions. Thermals interact through two simple rules, reflecting pulsating growth and environmental deformation. Long‐lived thermal clusters thus form on the microgrid, exhibiting scale growth and spacing that represent simple forms of spatial organization and memory. Size distributions of cluster number are diagnosed from the microgrid through an online clustering algorithm, and provided as input to a spectral multiplume eddy‐diffusivity mass flux scheme. This yields a decentralized transport system, in that the thermal clusters acting as independent but interacting nodes that carry information about spatial structure. The main objectives of this study are (a) to seek proof of concept of this approach, and (b) to gain insight into impacts of spatial organization on convective transport. Single‐column model experiments demonstrate satisfactory skill in reproducing two observed cases of continental shallow convection. Metrics expressing self‐organization and spatial organization match well with large‐eddy simulation results. We find that in this coupled system, spatial organization impacts convective transport primarily through the scale break in the size distribution of cluster number. The rooting of saturated plumes in the subcloud mixed layer plays a key role in this process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Novel sterol binding domains in bacteria

Sterol lipids are widely present in eukaryotes and play essential roles in signaling and modulating membrane fluidity. Although rare, some bacteria also produce sterols, but their function in bacteria is not known. Moreover, many more species, including pathogens and commensal microbes, acquire or modify sterols from eukaryotic hosts through poorly understood molecular mechanisms. The aerobic methanotroph Methylococcus capsulatus was the first bacterium shown to synthesize sterols, producing a mixture of C-4 methylated sterols that are distinct from those observed in eukaryotes. C-4 methylated sterols are synthesized in the cytosol and localized to the outer membrane, suggesting that a bacterial sterol transport machinery exists. Until now, the identity of such machinery remained a mystery. In this study, we identified three novel proteins that may be the first examples of transporters for bacterial sterol lipids. The proteins, which all belong to well-studied families of bacterial metabolite transporters, are predicted to reside in the inner membrane, periplasm, and outer membrane of M. capsulatus, and may work as a conduit to move modified sterols to the outer membrane. Quantitative analysis of ligand binding revealed their remarkable specificity for 4-methylsterols, and crystallographic structures coupled with docking and molecular dynamics simulations revealed the structural bases for substrate binding by two of the putative transporters. Their striking structural divergence from eukaryotic sterol transporters signals that they form a distinct sterol transport system within the bacterial domain. Finally, bioinformatics revealed the widespread presence of similar transporters in bacterial genomes, including in some pathogens that use host sterol lipids to construct their cell envelopes. The unique folds of these bacterial sterol binding proteins should now guide the discovery of other proteins that handle this essential metabolite.

59 BASIC BIOLOGICAL SCIENCES↗