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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Biomass carbon removal can help sustainable aviation fuels achieve on-time arrival

Biofuels, including sustainable aviation and marine fuels, and biomass carbon removal and storage (BiCRS) are often viewed as potentially competing pathways for advancing climate and energy goals. Their comparative economic, environmental, and temporal advantages remain debated. Rather than identifying a “best-use” for biomass, we show that the relative economic advantages of BiCRS versus biofuels exist along a continuum shaped by energy- and decarbonization-focused market conditions. These pathways need not be adversarial: BiCRS can enable, rather than displace, future biofuel deployment. While the lignocellulosic biofuel sector continues to face barriers associated with underdeveloped supply chains and technologies that have not yet been commercialized at scale, emerging BiCRS approaches are comparatively feedstock-flexible, rapidly deployable, and responsive to carbon removal markets. Early BiCRS deployment can help establish reliable biomass supply chains, reducing investment risk for future lignocellulosic biorefineries. By easing initial supply chain constraints, BiCRS can serve as a practical stepping stone toward meeting both near-term carbon removal needs and long-term sustainable fuel objectives under uncertain future market and policy conditions.

bioenvironmental engineering↗
DOE OSTI2023

Enhancing the EVI-X National Framework to Address Emerging Questions on Charging Infrastructure Deployment

As large national investments in EV charging continue to be made, this project seeks to improve the state-of-the-art in EV infrastructure analysis. New and improved quantitative analysis capabilities will position VTO to support EERE Leadership, assist the DOT/DOE Joint Office through timely analysis, and provide a strategy for the deployment of the national charging network. This project supports on-going development of NREL's EVI-X Suite of charging infrastructure analysis tools, including tools supporting large-scale network planning, local site design decisions, and comprehensive financial analysis. EVI-X development complements and leverages other VTO-funded efforts to ensure inputs to EVI-X and output produced by EVI-X are consistent with and well-integrated into the VTO portfolio (e.g., EV adoption scenarios from TEMPO, charging infrastructure design provided to EVs@Scale, etc.).

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2016

Differentiable McCormick relaxations

McCormick's classical relaxation technique constructs closed-form convex and concave relaxations of compositions of simple intrinsic functions. These relaxations have several properties which make them useful for lower bounding problems in global optimization: they can be evaluated automatically, accurately, and computationally inexpensively, and they converge rapidly to the relaxed function as the underlying domain is reduced in size. They may also be adapted to yield relaxations of certain implicit functions and differential equation solutions. However, McCormick's relaxations may be nonsmooth, and this nonsmoothness can create theoretical and computational obstacles when relaxations are to be deployed. This article presents a continuously differentiable variant of McCormick's original relaxations in the multivariate McCormick framework of Tsoukalas and Mitsos. Gradients of the new differentiable relaxations may be computed efficiently using the standard forward or reverse modes of automatic differentiation. Furthermore, extensions to differentiable relaxations of implicit functions and solutions of parametric ordinary differential equations are discussed. A C++ implementation based on the library MC++ is described and applied to a case study in nonsmooth nonconvex optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Unraveling the structural properties and dynamics of sulfonated solid acid carbon catalysts with neutron vibrational spectroscopy

Last year, nearly 1 billion waste tires were disposed of globally, a number that continues to grow with the deployment of more automobiles. Recycling this hazardous waste to produce useful products is paramount towards sustainability that has a direct impact on society. In an effort to alleviate the impact of this waste, we have shown that scrap tire crumb rubber can be turned into value-added sulfonated carbon catalysts that can be used for a number of applications. Here, we analyze the sulfonated carbon catalysts with several techniques in order to elucidate the structural properties as well as the impact of pre- and post-sulfonation on the surface functionalities. Most notably, we applied neutron vibrational spectroscopy in order to better understand the surface chemistry of carbon material and resolve the role of protons in tire-derived carbon. Our results suggest that tuning the surface chemistry and the content of sulfur and hydrogen will promote Lewis-acid catalysis, which allows for important heterogeneous reactions such as esterification.

esterification reaction↗
DOE OSTI2012

A $70/tCO2 greenhouse gas mitigation backstop for China’s industrial and electric power sectors: insights from a comprehensive CCS cost curve

As one of the world's fastest growing economies with abundant coal reserves, China's carbon dioxide (CO2) emissions have doubled in the last decade and are expected to continue growing for the foreseeable future. While the Central Government has been promoting development and growth of cleaner and more efficient energy systems, efforts to reduce carbon emissions from the heavily coal-based economy may require continued and increased development and deployment of carbon dioxide capture and storage (CCS) technologies. This paper presents the first detailed, national-scale assessment of CCS potential across the diverse geographic, geologic, and industrial landscape of China, through the lens of an integrated CCS cost curve. It summarizes the development of a cost curve representing the full chain of components necessary for the capture and geologic storage of CO2 from China's power generation and industrial sectors. Individual component cost estimates are described, along with the optimized source-sink matching of over 1,600 large stationary CO2 sources and 2300 gigatons of CO2 storage capacity within 90 major deep geologic onshore sedimentary sub-basins, to develop a cost curve incorporating CO2 capture, compression, transport, and storage. Results suggest that CCS can provide an important greenhouse gas mitigation option for most regions and industrial sectors in China, able to store more than 80% of emissions from these large CO2 sources (2900 million tons of CO2 annually) at costs less than $70/tCO2 for perhaps a century or more.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Catalyst and reactor design considerations for selective production of acids by oxidative cleavage of alkenes and unsaturated fatty acids with H 2 O 2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η 2 -O 2 ) complexes vs. H 2 O 2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H 2 O 2 concentrations. Semi-batch reactors with continuous introduction of H 2 O 2 solutions offer the means to maintain low H 2 O 2 concentrations while providing sufficient quantities of H 2 O 2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. Furthermore, this kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H 2 O 2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H 2 O 2 feed rate increases selectivity towards oxidative cleavage products and selective use of H 2 O 2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semibatch reactors with optimized molar feed rates of H 2 O 2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H 2 O 2 selectivity (3% to 30%). In addition, semibatch reaction conditions used avoid H 2 O 2 -mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H 2 O 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear-and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute time-scale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

irradiance↗
DOE OSTI2024

Field Testing of a Mixed Potential IoT Sensor Platform for Methane Quantification

Emissions of CH 4 from natural gas infrastructure must urgently be addressed to mitigate its effect on global climate. With hundreds of thousands of miles of pipeline in the US used to transport natural gas, current methods of surveying for leaks are inadequate. Mixed potential sensors are a low cost, field deployable technology for remote and continuous monitoring of natural gas infrastructure. We demonstrate for the first time a field trial of a mixed potential sensor device coupled with machine learning and internet-of-things platform at Colorado State University’s Methane Emissions Technology Evaluation Center (METEC). Emissions were detected from a simulated buried underground pipeline source. Sensor data was acquired and transmitted from the field test site to a remote cloud server. Quantification of concentration as a function of vertical distance is consistent with previously reported transport modelling efforts and experimental surveys of methane emissions by more sophisticated CH 4 analyzers.

03 NATURAL GAS↗
DOE OSTI2022

Data for Catalyst and Reactor Design Considerations for Selective Production of Acids by Oxidative Cleavage of Alkenes with H2O2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η2-O2) complexes vs. H2O2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H2O2 concentrations. Semi-batch reactors with continuous introduction of H2O2 solutions offer the means to maintain low H2O2 concentrations while providing sufficient quantities of H2O2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. This kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H2O2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H2O2 feed rate increases selectivity towards oxidative cleavage products and selective use of H2O2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semi-batch reactors with optimized molar feed rates of H2O2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H2O2 selectivity (3% to 30%). In addition, semi-batch reaction conditions used avoid H2O2-mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H2O2.

Catalysis↗
DOE OSTI2020

Outcomes of the DOE Workshop on Atmospheric Challenges for the Wind Energy Industry

The U.S. Department of Energy-funded Mesoscale-to-Microscale Coupling (MMC) project team planned and conducted a virtual Workshop on Atmospheric Challenges for the Wind Energy Industry on October 19 and 20, 2020. The goal of the workshop was to forge a dialog with the community, including industry representatives, on how modeling tools are currently being used, the present active atmospheric modeling research in support of wind energy, and required advancements in capabilities and technology to continue to advance wind energy deployment. The workshop was planned in collaboration with an industry advisory panel that included representatives from wind power plant developers, turbine manufacturers, and companies that provide resource assessment and forecasting services. The format of the workshop included panels from government research sponsors, visionaries from industry, and mixed panels of researchers discussing research status and needs. A shared keynote presentation from the Technical University of Denmark experts anchored the second day of the workshop. An emphasis was placed on understanding the research needs in the offshore environment. In addition, breakout opportunities were provided each day. On the first day, the breakout discussions addressed predesigned questions configured to elicit participants’ thoughts on needed research directions. The second-day breakouts treated three important technical topics through a combination of presentations and group conversations. Each workshop participant chose their breakout preference from among downscaling details, modeling for turbines, and using artificial intelligence for atmospheric modeling. The discussions were robust and productive. The outcomes of the workshop include archiving a series of recommendations from industry and the research community on research directions required to further advance wind energy deployment. Discussions confirmed the need for high-fidelity modeling but that there are specific areas of applicability and other areas where the time and cost of computation is prohibitive. In those cases, the high-fidelity models can inform low-order models that are more practical for real-time or widely deployed applications. Industry must consider the financial cost of performing more expensive modeling approaches, but industry engineers and researchers are using these approaches where there appears to be a return on investment. An emerging type of low-order model is based on machine learning (ML). Participants confirmed that there are many atmospheric phenomena that need to be modeled better, including low-level jets, cold air outbreaks, land-sea induced circulations, diurnal variability, thin stable boundary layers, dynamic changes such as from frontal passage, interaction of wakes and blockage, and more. For the offshore environment, there is wide agreement that some level of ocean-wave-atmospheric coupling is necessary to capture variations in rotor-level winds needed to plan and operate offshore wind plants. Another recurring recommendation is that more observations are needed, particularly for the offshore environment. Those observations should consider the needs for model improvement, both for physically based models and for ML models. Observations must capture atmospheric profiles of variables that are important to understanding and modeling atmospheric and oceanic phenomena that impact boundary layer winds. Models must be validated with data and the uncertainty quantified, particularly those that are sensitive to initial and boundary conditions. Finally, a repeated request was to consider the holistic needs of hybrid plants of wind, solar, and storage resources because those types of plants are likely to be the wave of the future. In addition, industry wishes to understand impacts of the resource under a changing climate for long-term planning.

17 WIND ENERGY↗
DOE OSTI2024

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ascorbic Acid Stability and pH Testing to Support RWM-018 Pilot Scale Wellhead Treatment System Feasibility Determination

A multitude of groundwater remediation techniques for chlorinated volatile organic compounds (cVOCs) have been conducted at the A/M-Areas of the Savannah River Site (SRS). Historical in-situ chemical oxidation (ISCO) injections of potassium permanganate and sodium persulfate conducted in 2018 and 2020, have left residual oxidant concentrations in the A/M-Area groundwater system. ISCO events targeted dense non-aqueous phase liquids (DNAPLs) through the injection of strong oxidants within plume zones upgradient of current groundwater recovery wells RWM-008 and RWM-018. These residual oxidants could significantly impede the operation of the mercury removal system needed to meet National Pollutant Discharge Elimination System (NPDES) permit requirements for the ongoing pump-and-treat system that hydraulically controls potions of the A/M-Area plume. Effluent treated groundwater from this system is discharged to surface water at the receiving outfall of the M-1 Air Stripper. To prevent interference of the M-1 Air Stripper system by residual oxidants, groundwater recovery has been ceased at well RWM-018. Modeling of oxidant transport in A/M-Area from ISCO estimated that the potential oxidant load contributed by RWM-018 could be as high as 120 mg/L. It is also possible that oxidants may be contributed via pumping at well RWM-008 in the near future as residual oxidants within the aquifer migrate toward its zone of influence. Savannah River National Laboratory (SRNL) has conducted research to investigate potential pre-treatment chemicals to neutralize these residual oxidants, before reaching the M-1 Air Stripper, to allow for resumed groundwater recovery at RWM-018 and continued pumping at RWM-008. Deployment of ascorbic acid for neutralization of residual oxidants at RWM-018 (and possibly RWM-008) is recommended based on results from previous reductant testing (SRNL, 2021). For a maximum estimated oxidant load at RWM-0018, a well-head treatment system would need to dose about 400 gallons of ascorbic acid each month to ensure complete neutralization. A second system with additional reagent should also be considered for deployment at RWM-008.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Progress Towards Synthesis of Uranium Chloride Fuel Salts Using Zinc Chloride

Reliable, scalable methods for producing high-purity actinide chloride salts are needed to support molten salt reactor fuel development and deployment. This report describes the continued development and demonstration of a bench-scale chlorination and purification apparatus using a zinc chloride-based method for synthesizing uranium chloride fuel salts. In this approach, uranium metal is chlorinated by ZnCl2 to produce LiCl-KCl-UCl3. Reaction with three aliquots of added uranium metal was used to generate a target uranium concentration of 30 wt %. While this concentration was chosen for initial testing of the apparatus and method, the final uranium concentration is not limited to 30 wt %. The zinc metal generated in the reaction forms an immiscible layer that was removed by volatilization at moderately high temperatures. Electrochemical measurements confirmed the removal of zinc and applied sensing methods indicated the uranium concentration to be approximately 25 wt %. These initial results demonstrate that the bench-scale chlorination apparatus is an effective platform for the synthesis and purification of uranium chloride salts using ZnCl2. This method shows promise for application to industry-relevant salt systems such as NaCl-UCl3. Further development is recommended to optimize reagent loading, zinc removal, and avoid possible U-Zn alloy formation.

Dulovic, Stephanie↗
DOE OSTI2017

Qualification Testing Versus Quantitative Reliability Testing of PV - Gaining Confidence in a Rapidly Changing Technology: Preprint

Continued growth of PV system deployment would be enhanced by quantitative, low-uncertainty predictions of the degradation and failure rates of PV modules and systems. The intended product lifetime (decades) far exceeds the product development cycle (months), limiting our ability to reduce the uncertainty of the predictions for this rapidly changing technology. Yet, business decisions (setting insurance rates, analyzing return on investment, etc.) require quantitative risk assessment. Moving toward more quantitative assessments requires consideration of many factors, including the intended application, consequence of a possible failure, variability in the manufacturing, installation, and operation, as well as uncertainty in the measured acceleration factors, which provide the basis for predictions based on accelerated tests. As the industry matures, it is useful to periodically assess the overall strategy for standards development and prioritization of research to provide a technical basis both for the standards and the analysis related to the application of those. To this end, this paper suggests a tiered approach to creating risk assessments. Recent and planned potential improvements in international standards are also summarized.

14 SOLAR ENERGY↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size: Preprint

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear- and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute timescale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2023

Task 2.3: Continuous Counter-Current Chromatography

This task in the Separations Consortium focuses on the development of counter-current chromatography (CCC), which is an advanced liquid-liquid chromatography method. Today, CCC is primarily practiced in batch mode operation, but continuous operation will be required for at-scale deployment in a biorefinery setting. In this task, we are developing a continuous CCC process in collaboration with a company that builds CCC units. This work will be demonstrated on the biorefining challenge of lignin valorization. Specifically, we demonstrate use of continuous CCC for both monomer-monomer and monomer-oligomer separations in multiple lignin streams of relevance to the biorefining industry. Breakthroughs in this area would be useful for BETO goals in both sustainable aviation fuel and biochemicals production, including directly contributing to BETO's 2030 lignin valorization goal. Our approach includes developing new computational modeling approaches to optimize both batch and continuous CCC processes, experimental work to determine optimal solvent systems for multiple lignin streams sourced from BETO-funded projects and industrial collaborators, and techno-economic analysis and life cycle assessment to identify the most impactful areas to ultimately enable this approach in the biorefinery. This task overall will enable high-resolution, multi-component, continuous separations at scale, demonstrated on a grand challenge biorefining problem.

BIOMASS FUELS↗
DOE OSTI2025

Fusing Edge Computing with Transport Security by Leveraging the Controller Area Network Transport Security Tracking and Reporting (C-STAR) Unit

Rapid advances in embedded system complexity and capability provides exciting opportunities for transportation security deployment. Manufacturers and developers of these embedded systems continue to provide lower cost and more powerful solutions that can be leveraged by researchers and engineers. Furthermore, deploying these devices at the “edge” of the Internet-of-Things (IoT) infrastructure provides opportunities for highly capable applications in transport security. In an edge computation architecture, the device is co-located at the source of the data in the larger IoT structure – this provides computational capability at the location directly where the data is collected. For shipment transport security, this provides a direct compute node for digestion of data and mitigation actions in real-time. In our application, the vehicle provides a significant amount of this data that can be processed in real-time via the Controller Area Network Transport Security Tracking and Reporting (C-STAR) edge device. Utilization of a computational node located on the vehicle, such as the C-STAR, capitalizes on previously discussed opportunities of edge architectures. In this paper, we will discuss this security solution’s usability, current deployments, and scalability to further applications in transport security. First, we will cover the supported vehicle platforms that can leverage the C-STAR technology. This will be particularly relevant to medium- and heavy-duty vehicles transporting high-risk shipments. Second, we will speak to current deployments of the C-STAR that are ongoing. Finally, we will discuss additional areas for expansion such as maturing the onboard algorithms through continuing collaborations.

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