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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A genome-scale metabolic model for the denitrifying bacterium Thauera sp. MZ1T accurately predicts degradation of pollutants and production of polymers

The denitrifying bacterium Thauera sp . MZ1T, a common member of microbial communities in wastewater treatment facilities, can produce different compounds from a range of carbon (C) and nitrogen (N) sources under aerobic and anaerobic conditions. In these different conditions, Thauera modifies its metabolism to produce different compounds that influence the microbial community. In particular, Thauera sp . MZ1T produces different exopolysaccharides with floc-forming properties, impacting the physical disposition of wastewater consortia and the efficiency of nutrient assimilation by the microbial community. Under N-limiting conditions, Thauera sp . MZ1T decreases its growth rate and accelerates the accumulation of polyhydroxyalkanoate-related (PHA) compounds including polyhydroxybutyrate (PHB), which plays a fundamental role as C and energy storage in this β-proteobacterium. However, the metabolic mechanisms employed by Thauera sp . MZ1T to assimilate and catabolize many of the different C and N sources under aerobic and anaerobic conditions remain unknown. Systems biology approaches such as genome-scale metabolic modeling have been successfully used to unveil complex metabolic mechanisms for various microorganisms. Here, we developed a comprehensive metabolic model (M-model) for Thauera sp . MZ1T ( i Thauera861), consisting of 1,744 metabolites, 2,384 reactions, and 861 genes. We validated the model experimentally using over 70 different C and N sources under both aerobic and anaerobic conditions. i Thauera861 achieved a prediction accuracy of 95% for growth on various C and N sources and close to 85% for assimilation of aromatic compounds under denitrifying conditions. The M-model was subsequently deployed to determine the effects of substrates, oxygen presence, and the C:N ratio on the production of PHB and exopolysaccharides (EPS), showing the highest polymer yields are achieved with nucleotides and amino acids under aerobic conditions. This comprehensive M-model will help reveal the metabolic processes by which this ubiquitous species influences communities in wastewater treatment systems and natural environments.

Tec-Campos, Diego (ORCID:0000000188194150)↗
DOE OSTI2021

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003–2010. Nine isolates were identified as S . Typhimurium sequence type 313 while the other two were S . Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S . Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families

Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2—a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets—created using the redesigned network synthesis algorithm—which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.

42 ENGINEERING↗
DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗
DOE OSTI2021

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗
DOE OSTI2021

Critical Review of Platinum Group Metal-Free Materials for Water Electrolysis: Transition from the Laboratory to the Market : Earth-abundant borides and phosphides as catalysts for sustainable hydrogen production

To combat the global problem of carbon dioxide emissions, hydrogen is the desired energy vector for the transition to environmentally benign fuel cell power. Water electrolysis (WE) is the major technology for sustainable hydrogen production. Despite the use of renewable solar and wind power as sources of electricity, one of the main barriers for the widespread implementation of WE is the scarcity and high cost of platinum group metals (pgms) that are used to catalyse the cathodic hydrogen evolution reaction (HER) and the anodic oxygen evolution reaction (OER). Hence, the critical pgm-based catalysts must be replaced with more sustainable alternatives for WE technologies to become commercially viable. This critical review describes the state-of-the-art pgm-free materials used in the WE application, with a major focus on phosphides and borides. Several emerging classes of HER and OER catalysts are reviewed and detailed structure-property correlations are comprehensively summarised. The influence of the crystallographic and electronic structures, morphology and bulk and surface chemistry of the catalysts on the activity towards OER and HER is discussed.

Chemistry↗
DOE OSTI2025

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗
DOE OSTI2023

Sulfur poisoning mechanism of LSCF cathode material in the presence of SO 2 : a computational and experimental study

Aiming at the comprehensive understanding of the single sulfur poisoning effect and, eventually, the multiple impurities poisoning phenomena on the SOFC (Solid Oxide Fuel Cell) cathode materials, the sulfur poisoning effect on the (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3 (LSCF-6428) has been investigated in the presence of 10 ppm SO 2 at 800, 900, and 1000°C, respectively, with a combined computational and experimental approach. The good agreement between the CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) simulations and the XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy), and TEM (Transmission Electron Microscopy) characterization results support the reliability of the CALPHAD approach in the SOFC field. Furthermore, comprehensive simulations were made to understand the impact of temperature, P(SO 2 ), P(O 2 ), and Sr concentration on the threshold of SrSO 4 stability. Results showed that the formation of SrSO4 is thermodynamically favored at lower temperatures, higher P(SO 2 ), higher P(O 2 ), and higher Sr concentration. Finally, comparisons were also made between LSCF-6428 and LSM20 (La 0.8 Sr 0.2 MnO 3 ) using simulations, which confirmed that LSCF-6428 is a poor sulfur-tolerant cathode, in agreement with the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Storage

This paper presents a prototype methodology to assess the possible transition of Class II carbon dioxide-enhanced oil recovery (CO2-EOR) wells to Class VI wells. The focus is on wellbore construction materials—casing, cement, tubing, and the packer—and includes comprehensive workflows to evaluate these materials, with primary emphasis on compliance with Environmental Protection Agency (EPA) Class VI well construction and conversion guidelines. These workflows systematically assess material properties and performance criteria to ensure regulatory compliance and optimize long-term wellbore integrity and functionality. Utilizing Python scripts and JavaScript Object Notation (JSON) representations, the study automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on workflow criteria. By emphasizing critical factors such as casing integrity, cementing techniques, tubing compatibility, and packer selection, the methodology helps well owners and operators prioritize wells for potential reuse as CO2 injection wells. Given limitations in digitized data, manual user verification is required in some sections. Future improvements include integrating non-digitized data through web scraping and machine learning techniques. This research serves as a practical guide for stakeholders, supporting environmental compliance and sustainable well operations.

geologic carbon sequestration↗
DOE OSTI2020

Dragonstone Strategy – State of Cybersecurity in the Oil & Natural Gas Sector

The oil & natural gas (ONG) system touches every corner of the nation and increased communications & control capabilities have not only allowed for greater efficiency of system operation, but have also created a massive target for adversaries to launch cyber-attacks. Like any other heavy industrial process, the ONG system relies on a complex system of information technology (IT) and operational technology (OT) devices. The current state of cyber-preparedness across the ONG industry varies from organization to organization. Among the most common challenges that ONG companies face are remote locations, longlived field assets, and lacking capabilities to find and track malware on their systems. ONG companies tend to be concerned with lack of cyber-awareness from employees, risk stemming from remote access for operations & maintenance, and software vulnerabilities within third-party equipment. Various industry and government organizations are performing research and development activities to address some of these challenges, but in many cases industry stakeholders are not aware of solutions that already exist. It is clear that a need exists for a coherent, comprehensive, multi-layered strategy for assuring the security and resilience of the nation's pipeline infrastructure against cyber threats. For a variety of reasons, the general consensus from stakeholders interviewed by LLNL is that the state of cyber-security within the electric grid is currently outpacing its ONG cousin. Existing strategies for the resilience and cyber-security of the electric grid can and should be leveraged to provide immediate benefits to the ONG system. In LLNL’s view, there are two key factors currently limiting the development of necessary cyber-practices within the ONG industry: The sheer number of differing regulatory bodies and trade groups offering both standards and best-practice recommendations for ONG cyber-security makes it difficult to create a comprehensive, directed, and coherent strategy that is applicable to all players within the ONG industry. The ONG industry is unaware of potentially useful technologies that have been developed for ensuring cyber-security of other infrastructure systems, such as the electric grid. Leveraging these technologies—and the science and engineering behind them—can provide some low-hanging fruit that can greatly improve cyber-security in the ONG industry without significant investments in terms of time and money. In the months following this report, LLNL will continue to perform outreach to key oil & gas industry stakeholders in a continual effort to identify the most pressing cyber-resilience issues in the industry. This outreach will be supplemented with LLNL’s threat intelligence capabilities to begin painting a clearer picture of the overall threat landscape faced by this sector. This assessment will be threat-informed and while the strategy itself will not be classified we will leverage intelligence analysis and adversary capabilities to identify gaps in current cybersecurity practices for oil & gas pipeline systems. Recommended efforts will be compiled into a cyber-resilience roadmap for the oil & gas pipeline sector, in which LLNL will highlight priority activities to immediately improve the state of cyber-resilience in the industry.

02 PETROLEUM↗
DOE OSTI2020

Heat Integration Optimization and Dynamic Modeling Investigation for Advancing the Coal-Direct Chemical Looping Process

The purpose of the project is to address the optimization and startup operation of a modular coal direct chemical looping (CDCL) combustion system integrated with a steam cycle for power generation to reduce the risks involved in further scale-up of the technology. The modular reactor design of the CDCL process provides flexibility in the fabrication of the reactor and in its operating capacity (i.e. turndown ratio) at the cost of a more complex heat exchange network (HEN) design and integration. To address the technology gaps and advance the efficiency and economic feasibility of the CDCL technology, the project will perform a detailed and comprehensive analysis of the integration of a modular CDCL reactor system and a steam cycle system under both static and transient conditions via HEN process performance simulations and system dynamic modeling, respectively. The scope of work consists of 1) Experimental and computational studies of the CDCL combustor reactor 2) Comprehensive static (i.e. steady-state) system HEN design analysis in CDCL 550 MWe commercial unit for power generation and 3) Dynamic modeling of site specific design of 10MWe CDCL large pilot plant. The project team has successfully developed and validated a kinetic model for the oxidation of oxygen carriers in the combustor using the unreacted shrinking core model (UCSM). The model is capable of capturing the oxidation kinetics of fully or partially reduced oxygen carrier particles. A computational fluid dynamics (CFD) model is developed to simulate the hydrodynamics, heat transfer, and chemical reaction occurring in the CDCL combustor. The model is developed in MFIX and ANSYS Fluent. Key aspects of CDCL combustor operation, including heat transfer, oxygen carrier oxidation, and the transport of oxygen carrier particles, are simulated using this CFD model. The HEN for a commercial scale 550 MWe CDCL power plant is simulated and optimized using ASPEN Plus. Practical design considerations are incorporated based on industrial experiences. The performance and cost for the commercial CDCL plant is updated based on these analyses. A dynamic model for the 10 MWe CDCL pilot plant is developed in ProTRAX simulation software. The model is based on the pilot plant design developed in project DE-FE0027654 “10 MWe CDCL Large Pilot Plang – Pre-FEED Study” and the steam cycle data obtained from Dover Light & Power plant. The transient behaviors during pilot plant load variation are simulated using the dynamic model.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

2020 Review Panel Workshop on Energy Intensity Indicators: Summary Findings and Meeting Notes

On January 28-29, 2020, the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), in coordination with Pacific Northwest National Laboratory (PNNL), sponsored an expert workshop focused on energy intensity indicators. The intent of the workshop was to support a comprehensive review of the EERE Energy Intensity Indicators (EII), a national system of indicators used to track changes in the energy intensity of economic sectors. One goal of the workshop was to gather input from a panel of experts who have experience and knowledge related to the EII methodological approach and key data sources used to calculate indicators for each of the end-use sectors of the economy—transportation, residential, commercial, industrial, and electricity. The current EERE EII methodology is documented in a 2017 PNNL report, A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends, which is available online. The workshop also included a presentation by Dr. Beng Ang, who discussed the Log Mean Divisia index (LMDI) approach to decomposition analysis, which was followed by a discussion concerning the methodological approaches that could be applied to future EII efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Development of an In-Situ Method for Cable Condition Monitoring in Nuclear Power Plants (SBIR Phase IIB Final Report)

This is the final report of a Small Business Innovation Research (SBIR) project that Analysis and Measurement Services Corporation (AMS) has conducted for the U.S. Department of Energy (DOE) over a seven-and-a-half year period (February 2013 through April 2020 with the awards of Phase I, Phase II and Phase IIB projects). The goal of the project was to design, develop, validate, and demonstrate a technique for in-situ testing of cable insulation polymers that will identify, locate, and provide the degree of aging for cables commonly used in nuclear power plants. During the Phase I project, AMS established that the frequency domain reflectometry (FDR) technique can successfully identify and measure cable insulation degradation that can be trended with aging. In Phase II, AMS performed extensive cable aging studies to correlate FDR measurements with other laboratory condition monitoring techniques and developed aging condition categories to quantify the severity of insulation degradation. In Phase IIB, the project expanded the research to include a wider variety of cable polymers that are used in the commercial nuclear power industry. This work also involved developing acceptance criteria to objectively assess age-related cable degradation while sharing the results of this research with industry, academia, and national laboratories to advance the state of the art in cable aging management technologies. The products developed under this research project provide the nuclear industry with an effective condition monitoring tool to support safe and long-term plant operation. Throughout the project, collaborations and support were received from a variety of industry organizations and individuals including DOE National Laboratories as well as nuclear plant utilities and several other industry experts and cable manufacturers. Contributions from these organizations included the donation of new cables, naturally aged cables, and research collaboration. The validation and commercialization of the products of this project were achieved through opportunities to test and demonstrate the technologies’ capabilities on-site at nuclear power generation and research facilities as well as in the laboratory alongside industry peers and cable testing service companies. The research resulted in a technology that can be used to identify, locate, and quantify age-related degradation in several types of cable polymers. This included developing software and hardware as well as the methodology for using the FDR technique to assess age-related degradation of installed cables. The technology developed under this project can provide nuclear plant management, engineers, and technicians with an in-situ electrical test method to determine if in-service cables need to be replaced, monitored on a periodic basis, or show no evidence of significant age-related degradation that may require action. Near the end of this Phase IIB project, the FDR product was sold to a nuclear power utility in South Korea. This sale of a dedicated aging assessment tool is the beginning of a comprehensive contract with the expectation of twelve (12) units sold to that country. Additionally, the FDR technology has been sold to several industry organizations including a nuclear research institute and the Diablo Canyon nuclear power plant. This technology is also being leased by other nuclear industry service companies for incorporation into aging management programs. The cable testing technology that was developed under this project was also integrated into a comprehensive cable aging assessment service that is being offered to the nuclear industry at the request of U.S. nuclear utilities and is currently part of onsite testing services provided by AMS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

The Scientific Justification for a U.S. Domestic High-Performance Reactor-Based Research Facility

The Basic Energy Science Advisory Committee (BESAC) was charged with forming a subcommittee to assess the scientific justification for a U.S. domestic high-performance reactor-based research facility in order to continue providing the U.S scientific community with leading neutron capabilities in support of DOE's missions in science, energy, environment, and national security. The assessment included consideration of current international plans and existing domestic facility infrastructure. The subcommittee held a series of meetings from August 19, 2019 to April 24, 2020 that included DOE senior officials, leaders of national and international neutron facilities (SNS, HFIR, NIST, ILL, FRM-II), chairs of the NAS and POPA HEU-LEU committees, and outside experts on important areas of science, technology, and industry where high flux nuclear reactor facilities make important contributions. Also included were tours of neutron facilities (SNS, HFIR, NIST, BR2 reactor, and the planned Jules Horowitz Reactor). This July 2020 (revised 10-28-2020) report describes scientific use cases, brief summaries of existing and planned neutron facilities in the US and Europe, a comprehensive review of HFIR, a comprehensive discussion of the current state of progress on HEU-LEU conversion, user information from NIST and ORNL, and three recommendations to DOE for moving forward.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experimental Testing of Particle Erosion and Attrition in CSP Systems

In CSP systems using solid particles for heat transfer, erosion from the falling particles can damage the system components upon impact, and from sliding against the component walls. Furthermore, the resulting attrition of particles can change the thermal performance due to alterations in particle morphology. The research on these issues has been limited to industrial applications, and don’t necessarily coincide with the operating conditions in CSP systems. In this work, we investigated the durability of the particles selected as the heat transfer media, as well as special substrate materials that are of interest as lining materials to the particle storage tanks and hoppers. Three different erosion phenomena were studied: impact, abrasion, and attrition erosion. The low-temperature experiments revealed negligible losses from attrition and abrasion erosion. Although the substrates indicated visible surface damage from impact erosion, the actual material mass loss was small even after a throughput of 500kg of particles 63 days of 1MW CSP plant operation assuming 14 hours per day of operation. Erosion is typically classified as impact, abrasion, or attrition erosion. For example, the CSP systems utilizing solid particles as heat transfer media will likely experience impact erosion on the receiver hopper and heat exchanger walls as the solid particles fall from the reservoir. Additionally, there will be sliding erosion along the receiver walls as particles move through the hopper, and lastly, there will also be attrition erosion as the particles rub against each other. The extent of erosion depends on many factors including but not limited to particle shape and size, material hardness/brittleness and ductility, and particle impact speed and angle. Mechanistic erosion equations that are available in the literature are mostly derived from data pertaining to specific experiments and therefore can’t be applied to all applications without suitable adjustments. Survey of the literature relating to particle-based receivers revealed that the most prevalent approach has been to choose low velocities to limit erosion, but to our knowledge, little effort has been put in to fully characterize erosion at the expected operating conditions. A relatively recent work investigated the erosion of wire mesh proposed for use in a particle receiver, where the results actually showed an increase in mass as oxidation occurred on the mesh surface but the work did not investigate the particle attrition rate, and the erosion rate of a solid substrate. The end goal of this work is to develop a comprehensive particle and substrate durability model that will allow a comprehensive understanding of particle-based CSP operating conditions on component durability.

14 SOLAR ENERGY↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Securing Vehicle Charging Infrastructure

As the US electrifies the transportation sector, cyber attacks targeting vehicle charging could bring consequences to electrical system infrastructure. This is a growing area of concern as charging stations increase power delivery and must communicate to a range of entities to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and are complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid communication system cybersecurity could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks - or public perception of such - ripples across the industry and has lasting and devastating effects. Unfortunately, there is no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured interfaces. Thus, comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project is providing the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team is creating a cybersecurity threat model and performing a technical risk assessment of EVSE assets, so that automotive, charging, and utility stakeholders can better protect customers, vehicles, and power systems in the face of new cyber threats.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Guidelines for Broadband Seismometer Testing

The Comprehensive Nuclear-Test-Ban Treaty mandates the four verification technologies to be used by the International Monitoring System (IMS) to monitor compliance to the Treaty. These technologies are seismic, hydroacoustic, infrasound, and radionuclide. Operational manuals for each of these technologies specify the requirements that equipment installed at IMS stations must meet for data from said stations to be accepted by the International Data Center. Following a model in which a revised set of infrasound sensor specifications and accompanying test procedures were developed in an international collaboration overseen by the Comprehensive Nuclear-Test-Ban Treaty Organization, the same process was recently followed for seismometers potentially of use by the IMS. This document, a product of that collaboration, defines key concepts and recommends test procedures to be followed to characterize broadband seismometers in a consistent and standardized way. Results from these test procedures can be used to verify that a seismometer meets the manufacturers stated specifications and IMS requirements. ACKNOWLEDGEMENTS The writers of this document would like to acknowledge Charles R. Hutt, John R. Evans, Fred Followill, Robert L. Nigbor, and Erhard Wielandt, the authors of the 2009 Guidelines for Standardized Testing of Broadband Seismometers and Accelerometers funded by the U.S. Department of Interior, on which this document is based. Although this document is limited in scope to seismometers and much of the document has been updated, the structure remains essentially the same.

58 GEOSCIENCES↗