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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 OSTI2025

Emerging Threats in Transportation Security Related to Intelligent Transportation Systems (ITS)

Transport of high-consequence shipments requires a resilient and robust systems of systems to guarantee cargo arrival. Furthermore, rising adoption of technologies such as connected and automated vehicles (CAVs), intelligent infrastructure, and vehicle-to-everything (V2X) communication presents unique challenges for securing transportation systems. Within these Intelligent Transportation Systems (ITS), several additional vulnerabilities exist that create pathways for adversarial attacks and cargo interception. For example, connectivity provides cyber pathways directly into vehicle systems and infrastructure for malicious actors. Furthermore, advanced vehicle automation exposes additional vehicle control necessary for shipment interception otherwise unavailable to adversaries. Within this paper, we will discuss the specific threats introduced by ITS-enabled technologies currently deployed and in development. These include those mentioned related to connectivity and automation, but will be expanded into grid, infrastructure, and vehicle specific threats. In addition, we will discuss how to potentially mitigate these emerging challenges as well as how to safeguard transportation systems from next generation attacks.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗
DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are at the forefront in advancing the way we interact and perceive with the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as Radar, LiDAR and Video Imaging which are the most popular modalities for ITS. Real-time perception data from these sensors allows intelligent infrastructure side decision making to improve the energy, efficiency and safety at traffic intersections. As traffic departments across the United States are transitioning from traditional loop detectors / emulators and embracing newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception which is reliable, inexpensive, easy to setup and has robust performance in varying weather conditions. However, choosing a sensor which checks all boxes is not straightforward as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long range vehicles and weather resistance but lacks high resolution. LiDAR is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines Radar, LiDAR and camera sensors capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. Through this evaluation, we hope to draw attention to the necessity of National Renewable Energy Laboratory's (NREL) Infrastructure Perception and Control (IPC) framework which presents a multi-sensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like Radar, LiDAR and cameras, offers the most robust solution for enhancing the safety and efficiency in intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Conserved ABC Transport System Regulated by the General Stress Response Pathways of Alpha- and Gammaproteobacteria

ABSTRACT Brucella abortus σ E1 is an EcfG family sigma factor that regulates the transcription of dozens of genes in response to diverse stress conditions and is required for maintenance of chronic infection in a mouse model. A putative ATP-binding cassette transporter operon, bab1_0223-bab1_0226 , is among the most highly activated gene sets in the σ E1 regulon. The proteins encoded by the operon resemble quaternary ammonium-compatible solute importers but are most similar in sequence to the broadly conserved YehZYXW system, which remains largely uncharacterized. Transcription of yehZYXW is activated by the general stress sigma factor σ S in Enterobacteriaceae , which suggests a functional role for this transport system in bacterial stress response across the classes Alphaproteobacteria and Gammaproteobacteria . We present evidence that B. abortus YehZYXW does not function as an importer of known compatible solutes under physiological conditions and does not contribute to the virulence defect of a σ E1 -null strain. The sole in vitro phenotype associated with genetic disruption of this putative transport system is reduced growth in the presence of high Li + ion concentrations. A crystal structure of B. abortus YehZ revealed a class II periplasmic binding protein fold with significant structural homology to Archaeoglobus fulgidus ProX, which binds glycine betaine. However, the structure of the YehZ ligand-binding pocket is incompatible with high-affinity binding to glycine betaine. This is consistent with weak measured binding of YehZ to glycine betaine and related compatible solutes. We conclude that YehZYXW is a conserved, stress-regulated transport system that is phylogenetically and functionally distinct from quaternary ammonium-compatible solute importers. IMPORTANCE Brucella abortus σ E1 regulates transcription in response to stressors encountered in its mammalian host and is necessary for maintenance of chronic infection in a mouse model. The functions of the majority of genes regulated by σ E1 remain undefined. We present a functional/structural analysis of a conserved putative membrane transport system (YehZYXW) whose expression is strongly activated by σ E1 . Though annotated as a quaternary ammonium osmolyte uptake system, experimental physiological studies and measured ligand-binding properties of the periplasmic binding protein (PBP), YehZ, are inconsistent with this function. A crystal structure of B. abortus YehZ provides molecular insight into differences between bona fide quaternary ammonium osmolyte importers and YehZ-related proteins, which form a distinct phylogenetic and functional group of PBPs.

ABC transporter↗
DOE OSTI2022

Clean Energy Transition for Transportation Systems: Modeling Implications

Transportation is currently the least-diversified energy demand sector, with over 90% of energy use coming from petroleum. As a result, transportation recently became the largest source of GHG emissions in the U.S. and mobility needs for passenger and freight are growing rapidly. However, after over a century of petroleum dominance, new disruptive technologies and business models offer a pathway to decarbonize the sector. Transportation is at a turning point. On the horizon lies a future where affordable and abundant renewable electricity can be used to power cost-competitive battery electric vehicles (EVs) and produce energy-dense low-carbon fuels enabling to fully decarbonize transportation systems across all modes. Exploring the clean energy transition for the multitude of different transportation systems requires new analytical modeling and approaches. This talk reviewed current work at the National Renewable Energy Laboratory (NREL) to develop and use innovative tools and analytics approaches to inform the transformation to a sustainable mobility future and the integration of transportation systems with the broader energy sector.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Immobilized Low-Activity Waste Transportation System - 18496

The transportation of radioactive immobilized low-activity waste (ILAW) containers at the United States Department of Energy's (DOE) Hanford site is planned with a new ILAW transporter system. A project will design, procure, and fabricate components to support the safe and efficient transport of the radioactive ILAW containers, generated at the Hanford Tank Waste Treatment and Immobilization Plant (WTP), Low-Activity Waste (LAW) production facility, to the Integrated Disposal Facility (IDF) final disposal site. Prototype design was completed in fiscal year (FY) 2017. Fabrication of the transportation trailer/pallet system is occurring in FY2018, with testing to be completed in early FY2019. Any design modification will be incorporated into the design, and procurement of additional systems will then occur, to support WTP LAW hot commissioning, as soon as 2022. This project is implemented by the DOE tank farm contractor, Washington River Protection Solutions LLC (WRPS), with primary prototype design and fabrication being performed by SNC-Lavalin (Atkins). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Impact of Advanced Vehicle Technologies on Energy Consumption for the City of Detroit Using Transportation System Simulations

In developing a transportation system model, the energy impact of the model is extremely important for sustainability and validation. One approach to evaluating the energy impact is to consider the amount of fuel consumed by transportation in the model for different scenarios and technologies. Argonne National Laboratory has collaborated with the Southeast Michigan Council of Governments (SEMCOG) and the Detroit Department of Transportation to develop and validate a transportation system model for Southeast Michigan, focusing on the city of Detroit. The objective of this paper is to analyze the vehicle energy consumption in the Detroit Transportation System model. The focus is on evaluating the SEMCOG road network drive cycles as performed with current and future vehicle technologies.

Islam, Ehsan↗
DOE OSTI2021

Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

33 ADVANCED PROPULSION SYSTEMS↗