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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Optical and Durability Evaluation for Silvered Polymeric Mirrors and Reflectors: Cooperative Research and Development Final Report, CRADA Number, CRD-08-316

3M is currently developing silvered polymeric mirror reflectors as low-cost replacements for glass mirrors in concentrating solar power (CSP) systems. This effort is focused on development of reflectors comprising both metallized polymeric mirror films based on improved versions of ECP-305+ or other durable mirror film concepts and appropriate mechanically robust substrates. The objectives for this project are to reduce the system capital and operating costs and to lower the levelized cost of energy for CSP installations. The development of mirror reflectors involves work on both full reflectors and mirror films with and without coatings. Mirror reflectors must meet rigid optical specifications in terms of radius of curvature, slope errors and specularity. Mirror films must demonstrate long-term durability and maintain high reflectivity. 3M would like to augment internal capabilities to validate product performance with methods and tools developed at NREL to address these areas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Fast Dynamic Simulation-Based Small Signal Stability Assessment and Control

Power grid planning and operation decisions are made based on simulation of the dynamic behavior of the system. Enabling substantial energy savings while increasing the reliability of the aging North American power grid through improved utilization of existing transmission assets hinges on the adoption of wide-area measurement systems (WAMS) for power system stabilization. However, adoption of WAMS alone will not suffice if the power system is to reach its full entitlement in stability and reliability. It is necessary to enhance predictability with "faster than real-time" dynamic simulations that will enable the dynamic stability margins, proactive real-time control, and improve grid resiliency to fast time-scale phenomena such as cascading network failures. Present-day dynamic simulations are performed only during offline planning studies, considering only worst case conditions such as summer peak, winter peak days, etc. With widespread deployment of renewable generation, controllable loads, energy storage devices and plug-in hybrid electric vehicles expected in the near future and greater integration of cyber infrastructure (communications, computation and control), monitoring and controlling the dynamic performance of the grid in real-time would become increasingly important. The state-of-the-art dynamic simulation tools have limited computational speed and are not suitable for real-time applications, given the large set of contingency conditions to be evaluated. These tools are optimized for best performance of single-processor computers, but the simulation is still several times slower than real-time due to its computational complexity. With recent significant advances in numerical methods and computational hardware, the expectations have been rising towards more efficient and faster techniques to be implemented in power system simulators. This is a natural expectation, given that the core solution algorithms of most commercial simulators were developed decades ago, when High Performance Computing (HPC) resources were not commonly available.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

A Review of the American Recovery and Reinvestment Act Smart Grid Projects and Their Implications for China

The Chinese government has paid growing attention to renewable energy development and has set ambitious goals for carbon dioxide (CO2) emissions reduction and energy savings. Smart grid (SG) technologies have been regarded as emerging ways to integrate renewable energy and to help achieve these climate and energy goals. This report first reviews completed SG demonstrations under the U.S. American Recovery and Reinvestment Act (ARRA); especially two key programs: the SG Investment Grant (SGIG) and the SG Demonstration Project (SGDP). Under the SGIG, the larger of the two programs, over $3.4 billion was used to help industry deploy existing advanced SG technologies and tools to improve grid performance and reduce costs. Including industry investment, a total of $8 billion was spent on 99 cost-shared projects, which involved more than 200 participating electric utilities and other organizations. These projects aimed to modernize the electric grid, strengthen cyber security, improve interoperability, and collect comprehensive data on SG operations and benefits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Identification and Characterization of Thermal Fluid Phenomena Associated with Selected Operating/Accident Scenarios in Modular High Temperature Gas-cooled Reactors

Dominant phenomena are identified and characterized for the loss-of-forced-convection (LOFC) scenario, the depressurized loss-of-forced-convection (DLOFC) scenario, and the moisture ingress scenario with relief valves available scenario. These scenarios are considered for the modular high temperature gas-cooled reactor (MHTGR) baseline design—with both a prismatic core and a pebble-bed core. The objectives of this effort, described in the above paragraph, were achieved by following a methodology identified by the U.S. Nuclear Regulatory Commission (NRC) and recommended in their Regulatory Guide 1.203. The methodology employed is described. For the above scenarios, baseline phenomena identification and ranking tables (PIRTs) generated by a NRC-sponsored effort in 2008 for the LOFC and DLOFC scenarios and a baseline PIRT generated by a Department of Energy-sponsored effort in 2011 by their Next Generation Nuclear Plant (NGNP) Moisture Ingress Assessment Committee were used to identify the dominant phenomena and existing levels-of-knowledge. Ten dominant phenomena (with only medium or low levels-of-knowledge) were identified for the LOFC and DLOFC scenarios including: (1) Inlet plenum stratification and plumes, (2) core coolant flow distribution, (3) radiant heat transfer from the top of the core to the upper vessel head, (4) reactor cavity air circulation and heat transfer, (5) reactor cavity cooling system behavior, (6) decay heat distributions, (7) core effective thermal conductivity, (8) molecular diffusion in air ingress DLOFC, (9) duct exchange flow, (10) phenomena that affect cavity gas composition for air-ingress. Five dominant phenomena, with high levels of knowledge, were identified for the moisture-ingress scenario with relief valves available including: (1) flow through break, (2) moisture level in the primary, (3) transport to moisture monitor, (4) moisture monitor instrument response, and (5) heat removal by shutdown cooling system. These phenomena are discussed and characterized. A listing of experiments—both completed and ongoing—is given with a view toward including data useful for further more detailed examination of the dominant phenomena listed in the previous paragraph. Note that only data for the LOFC and DLOFC scenarios are listed—since the moisture ingress scenario with relief valves available –have been identified as having adequate levels-of-knowledge by the PIRT committee. Finally, a preliminary computational fluid dynamics (CFD) calculation of inlet plenum stratification and plumes is described. Techniques employed for this calculation are typical for preliminary scoping calculations performed to validate numeric tools.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Solar Bankability Data to Advance Transactions and Access (SB-DATA) Final Technical Report

The DOE project “Solar Bankability Data to Advance Transactions and Access”, known in the solar industry and referred to in this report as “Orange Button”, had project objectives of convening key stakeholder participants in the solar project lifecycle to develop a data taxonomy that meets to the solar industry’s needs for standardized data types for use in solar projects. Additional Orange Button deliverables included the development of an online data exchange to act as a clearinghouse of data that conformed to the data standard and additional solar industry data, and a Solar Data Translation Platform that could transform legacy solar project data to conform to the Orange Button data standard. All of these objectives were achieved. The Smart Electric Power Alliance (SEPA) provided program management, industry participant recruiting and convening, worked with the solar industry to define the scope of the Orange Button data taxonomy, and documented and delivered the taxonomy data requirements to funded project partners to develop both the taxonomy and the data conversion tools. Further efforts included performing extensive industry outreach and awareness to encourage adoption of the Orange Button taxonomy by the solar industry by enumerating the cost saving benefits of using the taxonomy and the public benefit of the increased use of solar energy due to increased bankability and viability of solar development projects. Solar PV panel and component prices have fallen in the last decade, while soft costs have remained stubbornly high and can account for as much as 64% of the total cost of a new solar system. Part of the U.S. Department of Energy SunShot Initiative, Orange Button enabled the creation and adoption of industry-led open data standards for rapid and seamless information exchange across the solar value chain, from origination to decommissioning. Standardizing data will reduce soft costs by making it easier to share solar data and speeding up processes. The taxonomy is a product of solar industry participants convening to identify the pain points caused by incompatible data, and to agree on and standardize data types to be used by the actors in the solar project lifecycle. This report focuses on the SEPA led first phase of Orange Button project that included industry outreach and recruiting participants for five industry working groups, widespread industry outreach to increase awareness and encourage eventual adoption of the taxonomy, and the definition of the scope, use cases, and supporting data types of the Orange Button taxonomy. The solar industry has been receptive of the completed Orange Button taxonomy. In SEPA’s work, 401 solar industry participants facilitated by SEPA defined the scope, use cases, and requirements for the taxonomy leading to over 150 taxonomy early adopters incorporating the taxonomy into their software products serving the solar industry, and several large investors and banks have started projects to enable them to utilize the taxonomy to gain back-office efficiencies. Moving forward, as the solar industry more widely embraces the Orange Button taxonomy and begins realizing the tangible benefits of adoption at scale, we expect further pressure on solar soft costs and increases in the bankability of solar projects.

14 SOLAR ENERGY↗
DOE OSTI2019

Application of Next-Generation Sequencing to Engineering mRNA Turnover in Cyanobacteria

This early career project began on July 15th, 2013, and concluded on July 14th, 2018. The project was staffed by three post-doctoral fellows and two graduate students. Three rotation students, one undergraduate, one high school student, and two summer REU have also worked on the project. The chief objective of the project was to develop a deeper understanding of how messenger RNA molecules are recycled in two bacterial species 1.) Escherichia coli and 2.) cyanobacteria Synechococcus sp. PCC7002 by applying next generation nucleic acid sequencing technologies. We succeeded in developing tools and approaches for performing these experiments and developed a better understanding of RNA turnover in each organism. We now have a better understanding of RNA molecules cut by RNase III, a common class of endonuclease, in both organisms and a global map of RNA turnover in cyanobacteria – the first of its kind for this class of microbe. To disseminate our findings, we published six primary research manuscripts as of the deposition of this report and expect to publish two others in 2019. We have deposited two sets of RNA sequencing data into a public database in support of our manuscripts. We have also published three reviews and commentaries of related topics. Dr. Gina Gordon, a funded graduate student defended her thesis in 2018 based on work performed in the course of the project. Dr. Travis Korosh defended his thesis in 2018 based in part on work performed in the course of the project. Dr. Jeffrey Cameron, now an Assistant Professor at CU-Boulder, Dr. Andrew Markley, and Dr. Michael Engstrom also worked on the project as post-doctoral researchers. In summary, the project has discovered new molecular biology information, trained five full-time researchers, deposited novel datasets in a public repository, and published research articles and presentations to disseminate our findings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Overview of Energy LCA at NETL: LCA at DOE Special Session

Evaluating the advantages and disadvantages of energy technology and policy options requires the comparison of those options on a common basis, which includes not only the impacts of converting fuel to useful energy, but of infrastructure construction, extraction and transportation of fuel, and transport of the final energy product to the end user. Further, environmental costs and benefits must be weighed against economic analyses with identical boundaries. At the Department of Energy’s National Energy Technology Laboratory, life cycle analysis (LCA) is used as tool and framework for performing these types of evaluations. This overview will describe the LCA process at NETL, including unique application of stochastic methods to environmental and economic analyses, and show highlights from several recent studies such as a complete inventory of natural gas extraction, and a comparison of advanced power technology options.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Detailed Statistical Models of Host-Based Data for Detection of Malicious Activity

The cybersecurity research community has focused primarily on the analysis and automation of intrusion detection systems by examining network traffic behaviors. Expanding on this expertise, advanced cyber defense analysis is turning to host-based data to use in research and development to produce the next generation network defense tools. The ability to perform deep packet inspection of network traffic is increasingly harder with most boundary network traffic moving to HTTPS. Additionally, network data alone does not provide a full picture of end-to-end activity. These are some of the reasons that necessitate looking at other data sources such as host data. We outline our investigation into the processing, formatting, and storing of the data along with the preliminary results from our exploratory data analysis. In writing this report, it is our goal to aid in guiding future research by providing foundational understanding for an area of cybersecurity that is rich with a variety of complex, categorical, and sparse data, with a strong human influence component. Including suggestions for guiding potential directions for future research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Risk Assessment and Ventilation Modeling for Hydrogen Release in Vehicle Repair Garages

The availability of repair garage infrastructure for hydrogen fuel cell vehicles is becoming increasingly important for future industry growth. Ventilation requirements for hydrogen fuel cell vehicles can affect both retrofitted and purpose-built repair garages and the costs associated with these requirements can be significant. A hazard and operability study (HAZOP) was performed to identify key risk-significant scenarios related to hydrogen vehicles in a repair garage. Detailed simulations and modeling were performed using appropriate computational tools to estimate the location, behavior, and severity of hydrogen release based on key HAZOP scenarios. This work compares current fire code requirements to an alternate ventilation strategy to further reduce potentially hazardous conditions. Overall, the amount of flammable mass of hydrogen at any one time in the simulation is low compared to the total mass of hydrogen released, due to the low flow rate of a low pressure release. It is shown that position, direction, and velocity of ventilation have a significant impact on the amount of instantaneous flammable mass in the domain.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

An Overview of Non-LWR Vessel Cooling Systems for Passive Decay Heat Removal (Technical Letter Final Report)

The following report provides a technical review of various reactor vessel cooling system (VCS) concepts under consideration for decay heat removal (DHR) in non-light water advanced reactor designs. This review focuses on ex-vessel designs, including the Reactor Cavity Cooling System (RCCS), the Reactor Vessel Auxiliary Cooling System (RVACS), and hybrid iterations, using both air and water cooling to achieve their heat removal function. Based on a literature review of publicly available sources published between 1979 and 2021, a technical summary is presented detailing existing and planned VCS design options, their applicability to specific reactor type, and review of authored research and development studies. Following an assessment of the availability of data and modeling tools, an evaluation was performed analyzing their likely performance during normal, degraded, and accident conditions, including reliability, stability, and longevity. With renewed consideration of air-based DHR systems by some US vendors, there is a need to fully understand the complexities inherent to natural circulation systems, and more importantly, how they may influence safety-related heat removal functions and system performance. For DHR systems that rely on air-based mode of cooling, this entails quantification of the impacts of low flow conditions during start-up, relative elevations of inlet and outlet ducts for below-grade installations, effects of the use of multiple parallel chimneys for redundancy, and impact of weather conditions at the plant site. For systems relying on water-based mode cooling, reliance on limited coolant inventory in an event of pipe break or extended duration accident scenarios, sensitivities related to stability of boiling flow and heat transfer conditions, and quantification of full-scale structural vibrations on balance of plant structures are among the complicating factors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

MOOSE Framework Meshing Enhancements to Support Reactor Analysis

MOOSE-based physics codes require an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The use of difficult-touse, external licensed software is often required to generate high quality meshes for reactor geometries. High-fidelity geometry modeling also requires elaborate tracking of groups of elements for material property assignment and output reporting which can be considerably complex for the user to identify and maintain. Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, several meshingrelated enhancements have been developed for the MOOSE framework to address user challenges in creating finite element meshes for advanced reactor geometries. MOOSE mesh generators have been developed to mesh hexagonal geometries (pins, ducted assemblies, and cores) commonly found in liquid-metal cooled fast reactor concepts. The mesh generator used for hexagonal pin cells is generic for regular polygons and therefore may also be used for Cartesian pin cells. Hexagonal pin cells can be stitched into ducted assemblies, and assemblies can be stitched together into a core. The user may specify region ids, region names, and other preferences on the mesh. This control is useful for later material mapping in the MOOSE-based physics codes input. A capability was also developed for meshing rotating control drums including determination of material volume fractions in each mesh element as a function of time. Control drum meshes may be stitched to other hexagonal assemblies to create a core configuration. Additional mesh generators were developed that wrap around the hexagonal meshing capabilities and utilize “extra element integer” ID values on each element. In regular Cartesian or hexagonal assemblies or cores, the bookkeeping of element groups for both material assignment and output reporting can now be automated through assignment of pin, assembly, core, axial and depletion id values stored as extra element integers. The extra element tags on the mesh greatly speed the reactor analyst’s efforts to map materials to meshes, track depletion zones, and parse output such as axial pin power distributions. At the highest level, pin, assembly, and core mesh generators (with this reactor terminology) have also been developed to easily generate regular Cartesian and hexagonal cores, including axial extrusion. These reactor geometry builders call upon the previously mentioned capabilities to produce analysis-ready 3D meshes including material assignments. Open source mesh triangulation capabilities were also investigated for integration into the MOOSE framework to address the need for meshing the core periphery region which extends from the irregular outer assembly border to a cylindrical boundary. Options are limited due to licensing constraints, and the recommendation is pursue building a native MOOSE Delaunay triangulator routine with full functionality. Finally, a series of verification problems were performed with NEAMS physics tools. All developed capabilities will be available in the new open-source “Reactor” module of the MOOSE framework, which is accessible to any MOOSE-based NEAMS physics tool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Tailoring EVMS Tools for Projects under $50M

The Earned Value Management System (EVMS) Tailoring Guide for Projects Under $\$$50M is designed for U.S. Department of Energy (DOE) cost-reimbursed projects less than $50M where full EVMS is not required per DOE Order 413.3B but is applicable to all projects below a mandated compliant EVMS requirement. The guide provides an inventory of tools and rules typically used as part of a fully compliant EVMS. The ranking employed in this guide identifies key foundational tools, as well as identifying opportunities for tailoring based upon project size or risk. The goal is to provide guidance for companies to establish enterprise level tools that provide meaningful performance data as efficiently as possible.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Residential Facade Retrofits Modeling: Results and Documentation

Utilizing NREL's ResStock analysis tool and datasets, we performed an economic analysis for various facade upgrade combinations and strategies. This analysis considers the combined life-cycle cost of re-siding and window and insulation upgrades including both home value impacts and recurring bill savings estimates from a ResStock analysis, for varying years of home ownership.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Small arms suppression project (LLNL final report)

US Special Operations Command (USSOCOM) was seeking a technological leap in small firearms weapon suppressor technology, because anticipated enemy capabilities are requiring the operators to have smaller detection cross sections to ensure the safe execution of missions. Suppressors have been developed almost exclusively through trial-and-error methods since the time of the original design by Hiram Maxim over one hundred years ago. Consequently USSOCOM deemed it prudent to perform a physicsbased study of weapon suppression to understand performance limits and possibly identify breakthrough technologies. Lawrence Livermore National Laboratory’s (LLNL’s) high performance production level computational tool called ALE3D (Arbitrary Lagrangian-Eulerian 3D and 2D) has unique physics models and numerical algorithms for modeling suppressor dynamics. The flexible and extendable code framework supports fully integrated hydrodynamics, heat transfer, solid and fluid dynamics, and chemistry that can be applied to simulating propellant-driven motion of a bullet down a gun barrel, the transfer of heat from the burning propellant to the barrel and suppressor, the chemistry of muzzle flash, and the shock/acoustic/optical signatures in the near-field. LLNL’s originally anticipated role was to augment ALE3D for this task, by developing the software and analysis methodologies specific to the simulation of blast and muzzle flash phenomena. It was believed that insights provided by our ALE3D simulations in tandem with a coordinated experimental component by our other team members from Oak Ridge National Laboratory (ORNL) and the U. S. Army Armament, Research, Development and Engineering Center (ARDEC), would have excellent prospects of yielding useful suppressor design improvements that could be transitioned to industry and utilized by US Special Operations Command. The three year effort has come to fruition with the development of revolutionary suppressor designs that far outperform any previous or current design by anyone outside this multi-lab team.

42 ENGINEERING↗
DOE OSTI2020

Transfer Factors for the FRMAC Assessment Manual and Turbo FRMAC to Improve Radiological Dose Assessment

The Turbo FRMAC analysis tool is used to perform complex calculations to quickly evaluate radiological consequences and aid in decision making during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment Center (FRMAC). To be able to assess impacts, input data called transfer factors that describe radionuclide uptake by local plants and animals are required. During the code application exercises in late 2016, identifying, finding, and validating nonstandard transfer factors proved to be time consuming and diverted the teams’ activity away from other critical tasks. As a result, a task was undertaken to dramatically expand the list of available transfer factors (food and non-food) and incorporate these factors into Turbo FRMAC. This will ultimately result in improved efficiency of the assessment team to perform calculations during times when the FRMAC is activated and provide more defensible, vetted data from which to calculate results. As a result of these and subsequent exercises, transfer factors were needed for the following items: bell peppers, Christmas tree, deer, flowers, fresh cucumbers, tomatoes, grapefruit, lichens, mushrooms, oranges, snap beans, squash, strawberries, sugarcane for sugar and seed, sweet corn, tea, tobacco, tree bark, and watermelon. To expand the applicability of the information tables, generic transfer data were also provided for common categories and recommendations were made for expanding the list of chemicals based on chemical similarity. The data presented in this report were compiled from recent literature with most of the data encompassing the period from 2000 to 2018. The following radionuclides were targeted during the literature search: elements associated with reactor accidents or nuclear detonations (Sr 89/90, Cs 134/137, Ce 141/144, Ru 103/106, I 129/131/133, Pu 238/239, Am 241, Zr 95, and Nb 95) and elements associated with industrial accidents or dirty bombs (Ir 192 and Co 60). Data from other elements were evaluated if they were identified during the literature search. In addition, reports were evaluated that were recommended by the research consultants. For each plant or animal transfer factor, the goal was to determine the geometric mean, the geometric standard deviation, the minimum, the maximum, and the number of measurements used. If only one measurement was available that was presented as the mean. Concentration ratios with large geometric standard deviations (GSDs) were generally the result of a paucity of measurements or a few disparate measurements. Measurement disparity was observed for data from different soil types. The geometric mean (GM) is a good reference value for planning and responses purposes, but the location-specific concentrations are unlikely to be similar to the model results. Recommendations for further work include: segregating the data to reflect the influence of soil type, developing approaches to incorporate animal data based on aggregated transfer measurements, and including data for foliar deposition on plants.

61 RADIATION PROTECTION AND DOSIMETRY↗