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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
NASA NTRS2000

Orbiter Capability for Providing Water to the International Space Station according to the Most Probable Flight Attitudes

Water to be generated by, delivered to, and processed by the International Space Station (ISS) is a critical Environmental Control and Life Support (ECLS) element, especially for the early ISS missions. A significant portion of the water required by the ISS shall be provided by the Shuttle Transportation System (STS) Orbiter. The balance of water generated by the Orbiter Fuel Cells (FC), minus that water consumed by the Orbiter Flash Evaporator System (FES) and crew, is available for transfer to the ISS. During later missions, crew respired and perspired water, as well as effluent water from the Orbiter LiOH canisters, will be collected as condensate and available for transfer to the ISS. Orbiter radiator performance provides the most variance in determining the amount of net Orbiter water available for transfer to the ISS. As radiator performance decreases, the dependence upon the FES (and FC water) increases for rejecting Orbiter waste heat. Generally, radiator performance decreases as the ISS assembly size increases (especially as solar arrays are added), and also as beta angle increases. ISS solar array deployment necessitates the use of models with articulating solar arrays (for Earth local-vertical attitudes), as array position dramatically affects Orbiter radiator performance. Recent developments in the relaxation of beta angle limitations have also increased the complexity and difficulty of providing water to the ISS. Other factors that may hinder the ability to transfer water are the number of empty Contingency Water Containers (CWCs) available, duration of open-hatch time, crew activity timeline, and full CWC storage capability. A parametric study has been accomplished that provides a quick-reference table for determining expected water generation rates for ISS missions 2A.2 through 7A.1. An hourly Orbiter water generation rate is reported according to a matrix that consists of: (1) (six) significant changes in ISS assembly configuration; (2) (four) beta angles (0 deg. , +37 deg., +53 deg. , and +75 deg.); (3) the (three) most representative ISS attitudes (XPOP-O, XPOP-180 and +XVV); (4) (four) Orbiter radiator configurations (both stowed, starboard deployed, port deployed, and both deployed) and (5) the (two) conditions (radiator inlet temperatures and fuel cell power) most consistent with sleep and wake periods. Those permutations of higher probability of occurrence than others have been identified. Another parametric study has been accomplished that provides a quick-reference table for determining expected water generation rates for ISS assembly complete missions. An hourly Orbiter water generation rate is reported according to a matrix that consists of: (1) (seven) beta angles (-75 deg., -60 deg., -30 deg., 0 deg., +30 deg., +60 deg., and +75 deg.); (2) the (nine) PYR angles that define the corners of the envelope; (3) (four) Orbiter radiator configurations (both stowed, starboard deployed, port deployed, and both deployed) and (4) the (two) conditions (radiator inlet temperatures and fuel cell power) most consistent with sleep and wake periods.

Dunaway, Brian↗
DOE OSTI2019

Virtual Excited State Reference for the Discovery of Electronic Materials Database: An Open-Access Resource for Ground and Excited State Properties of Organic Molecules

This letter announces the Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE materials DB), the first database to include downloadable excited-state structures (S 0 , S 1 , T 1 ) and photophysical properties. Furthermore, VERDE materials DB is searchable, open-access via www.verdedb.org , and focused on light-responsive π-conjugated organic molecules with applications in green chemistry, organic solar cells, and organic redox flow batteries. It includes results of our active and past virtual screening studies; to date, more than 13 000 density functional theory (DFT) calculations have been performed on 1 500 molecules to obtain frontier molecular orbitals and photophysical properties, including excitation energies, dipole moments, and redox potentials. To improve community access, we have made VERDE materials DB available via an integration with the Materials Data Facility. We are leveraging VERDE materials DB to train machine learning algorithms to identify new materials and structure–property relationships between molecular ground- and excited-states. We present a case-study involving photoaffinity labels, including predictions of new diazirine-based photoaffinity labels anticipated to have high photostabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Application of Spatial Data Modeling and Geographical Information Systems (GIS) for Identification of Potential Siting Options for Various Electrical Generation Sources

Oak Ridge National Laboratory (ORNL) initiated an internal National Electric Generation Siting Study, which is an ongoing multiphase study addressing several key questions related to our national electrical energy supply. This effort has led to the development of a tool, OR-SAGE (Oak Ridge Siting Analysis for power Generation Expansion), to support siting evaluations. The objective in developing OR-SAGE was to use industry-accepted approaches and/or develop appropriate criteria for screening sites and employ an array of Geographic Information Systems (GIS) data sources at ORNL to identify candidate areas for a power generation technology application. The initial phase of the study examined nuclear power generation. These early nuclear phase results were shared with staff from the Electric Power Research Institute (EPRI), which formed the genesis and support for an expansion of the work to several other power generation forms, including advanced coal with carbon capture and storage (CCS), solar, and compressed air energy storage (CAES). Wind generation was not included in this scope of work for EPRI. The OR-SAGE tool is essentially a dynamic visualization database. The results shown in this report represent a single static set of results using a specific set of input parameters. In this case, the GIS input parameters were optimized to support an economic study conducted by EPRI. A single set of individual results should not be construed as an ultimate energy solution, since US energy policy is very complex. However, the strength of the OR-SAGE tool is that numerous alternative scenarios can be quickly generated to provide additional insight into electrical generation or other GIS-based applications. The screening process divides the contiguous United States into 100 x 100 m (1-hectare) squares (cells), applying successive power generation-appropriate site selection and evaluation criteria (SSEC) to each cell. There are just under 700 million cells representing the contiguous United States. If a cell meets the requirements of each criterion, the cell is deemed a candidate area for siting a specific power generation form relative to a reference plant for that power type. Some SSEC parameters preclude siting a power plant because of an environmental, regulatory, or land-use constraint. Other SSEC assist in identifying less favorable areas, such as proximity to hazardous operations. All of the selected SSEC tend to recommend against sites. The focus of the ORNL electrical generation source siting study is on identifying candidate areas from which potential sites might be selected, stopping short of performing any detailed site evaluations or comparisons. This approach is designed to quickly screen for and characterize candidate areas. Critical assumptions supporting this work include the supply of cooling water to thermoelectric power generation; a methodology to provide an adequate siting footprint for typical power plant applications; a methodology to estimate thermoelectric plant capacity while accounting for available cooling water; and a methodology to account for future ({approx}2035) siting limitations as population increases and demands on freshwater sources change. OR-SAGE algorithms were built to account for these critical assumptions. Stream flow is the primary thermoelectric plant cooling source evaluated in this study. All cooling was assumed to be provided by a closed-cycle cooling (CCC) system requiring makeup water to account for evaporation and blowdown. Limited evaluations of shoreline cooling and the use of municipal processed water (gray) cooling were performed. Using a representative set of SSEC as input to the OR-SAGE tool and employing the accompanying critical assumptions, independent results for the various power generation sources studied were calculated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Demonstration of Electroreduction Technology to Convert GNF Uranium Oxide Powder to Metal

Global Nuclear Fuel – Americas LLC (GNF) has partnered with Argonne National Laboratory to demonstrate electroreduction of uranium oxides produced by deconversion of UF 6 to uranium metal through the Gateway for Accelerated Innovation in Nuclear (GAIN) program under the U.S. Department of Energy to accelerate the domestic production of metallic advanced reactor fuels. Electroreduction of uranium oxide was first demonstrated and patented by Argonne in the early 2000s as a technology to convert used oxide nuclear fuel from light water reactors to metal for further fuel reprocessing. More recently, electroreduction has been proposed as a front-end technology for metallization of uranium oxides produced by deconversion of UF 6 and for scrap recovery of oxide materials. During the electroreduction process, UO 2 powder is contained in a stainless-steel mesh basket with a cathode lead located in the center of the UO 2 bed. The basket is immersed in lithium chloride molten salt electrolyte containing 1 wt% lithium oxide along with a platinum anode and a nickel/nickel oxide (Ni/NiO) reference electrode. Current is applied to the cell between the cathode and anode to reduce the UO 2 to metallic uranium via a solid-state reduction reaction. Oxide ions released from the UO 2 during reduction are transported through the salt to the anode where oxygen gas is evolved. Once reduction is complete, the basket containing the metallicized uranium is removed from the salt and can be processed to remove the salt and consolidate the uranium into an ingot for use in metallic fuel fabrication. This project was performed to provide evidence of the electroreduction technology readiness level for metallization of UO 2 powder, identify and retire technical risks for industrialization of electroreduction, and accelerate the path to commercialization for metallic fast reactor fuel production. To that end, five electroreduction tests were performed with UO 2 provided by GNF and the resulting product was analyzed for the extent of conversion to metal and for impurity contents of the metal product to verify that electroreduction does not introduce impurities that would prevent use of the product in metallic fuel fabrication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Dose, LET, time and strain dependence of radiation-induced 53BP1 foci in 15 mouse strains ex vivo and associations to in vivo radiation susceptibility

We present a comparative analysis on the repair of radiation-induced DNA damage ex vivo in 15 strains of mice, including 5 inbred reference strains and 10 collaborative-cross strains, of both sexes. Non-immortalized primary skin fibroblasts derived from 76 mice were subjected to both low- and high-LET radiation (0.1, 1 and 4 Gy of X rays; 1.1 and 3 particles/100μm2 of 350 MeV/n 40Ar and 600 MeV/n 56Fe). Automated image quantification of 53BP1 radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET. Similarly to what we had previously reported for immortalized human cell lines [1], we observed a saturation of RIF number with dose at 4h post-irradiation, with more RIF/Gy for lower LET (X rays and 40Ar) compared to 56Fe. However at later time points (24h and above), the trend was inverted with more RIF/Gy for higher LET. Our data suggest that multiple DSBs cluster into RIF: as the linear density of DSBs increases with LET, so does the probability of having more DSBs per RIF, which makes it more difficult for cells to fully resolve high-LET-induced RIF, explaining the hypersensitivity to high-LET radiation despite a low number of RIF. Taking into account the amount of clustering at a given dose and LET, but also the kinetics of DNA damage repair, we introduced a novel mathematical formalism to evaluate the number of remaining RIF over time. We showed that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the repairable fraction of RIF measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk. In addition to the efficacy of repair and persistent RIF levels, even the amount of spontaneous foci without irradiation was shown to be strain dependent, indicating that these phenotypes are at least partially driven by genetics, and supporting their potential as indicators of individual radiation sensitivity. [1] Neumaier, T., et al., PNAS, 2012 (8) 109:443

Radiation, DNA damage, repair kinetics↗
DOE OSTI2014

Lesson Learned from Technical and Economic Performance Assessment and Benefit Evaluation of CHP-FCS

Recent efforts and interest in combined heat and power (CHP) have increased with the momentum provided by the federal government support for penetration of CHP systems. Combined heat and power fuel cell systems (CHP-FCSs) provide consistent electrical power and utilize the heat normally wasted in power generation for useful heating or cooling with lower emissions compared to alternative sources. A recent study investigated the utilization of CHP-FCSs in the range of 5 to 50KWe in various commercial building types and geographic locations. Electricity, heating, and water heating demands were obtained from simulation of the U.S. Department of Energy (DOE) commercial reference building models for various building types. Utility rates, cost of equipment, and system efficiency were used to examine economic payback in different scenarios. As a new technology in the early stages of adoption, CHP-FCSs are more expensive than alternative technologies, and the high capital cost of the CHP-FCSs results in a longer payback period than is typically acceptable for all but early-adopter market segments. However, the installation of these units as on-site power generators also provide several other benefits that make them attractive to building owners and operators. The business case for CHP-FCSs can be made more financially attractive through the provision of government incentives and when installed to support strategic infrastructure, such as military installations or data centers. The results presented in this paper intend to provide policy makers with information to define more customized incentives and tax credits based on a sample of building types and geographic locations in order to attract more business investment in this new technology.

Makhmalbaf, Atefe↗
DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2010

ANALYSIS OF A HIGH TEMPERATURE GAS-COOLED REACTOR POWERED HIGH TEMPERATURE ELECTROLYSIS HYDROGEN PLANT

An updated reference design for a commercial-scale high-temperature electrolysis (HTE) plant for hydrogen production has been developed. The HTE plant is powered by a high-temperature gas-cooled reactor (HTGR) whose configuration and operating conditions are based on the latest design parameters planned for the Next Generation Nuclear Plant (NGNP). The current HTGR reference design specifies a reactor power of 600 MWt, with a primary system pressure of 7.0 MPa, and reactor inlet and outlet fluid temperatures of 322°C and 750°C, respectively. The reactor heat is used to produce heat and electric power to the HTE plant. A Rankine steam cycle with a power conversion efficiency of 44.4% was used to provide the electric power. The electrolysis unit used to produce hydrogen includes 1.1 million cells with a per-cell active area of 225 cm2. The reference hydrogen production plant operates at a system pressure of 5.0 MPa, and utilizes a steam-sweep system to remove the excess oxygen that is evolved on the anode (oxygen) side of the electrolyzer. The overall system thermal-to-hydrogen production efficiency (based on the higher heating value of the produced hydrogen) is 42.8% at a hydrogen production rate of 1.85 kg/s (66 million SCFD) and an oxygen production rate of 14.6 kg/s (33 million SCFD). An economic analysis of this plant was performed with realistic financial and cost estimating The results of the economic analysis demonstrated that the HTE hydrogen production plant driven by a high-temperature helium-cooled nuclear power plant can deliver hydrogen at a competitive cost. A cost of $3.03/kg of hydrogen was calculated assuming an internal rate of return of 10% and a debt to equity ratio of 80%/20% for a reactor cost of $2000/kWt and $2.41/kg of hydrogen for a reactor cost of $1400/kWt.

08 HYDROGEN↗
NASA NTRS2011

GLM Proxy Data Generation: Methods for Stroke/Pulse Level Inter-Comparison of Ground-Based Lightning Reference Networks

In order to produce useful proxy data for the GOES-R Geostationary Lightning Mapper (GLM) in regions not covered by VLF lightning mapping systems, we intend to employ data produced by ground-based (regional or global) VLF/LF lightning detection networks. Before using these data in GLM Risk Reduction tasks, it is necessary to have a quantitative understanding of the performance of these networks, in terms of CG flash/stroke DE, cloud flash/pulse DE, location accuracy, and CLD/CG classification error. This information is being obtained through inter-comparison with LMAs and well-quantified VLF/LF lightning networks. One of our approaches is to compare "bulk" counting statistics on the spatial scale of convective cells, in order to both quantify relative performance and observe variations in cell-based temporal trends provided by each network. In addition, we are using microsecond-level stroke/pulse time correlation to facilitate detailed inter-comparisons at a more-fundamental level. The current development status of our ground-based inter-comparison and evaluation tools will be presented, and performance metrics will be discussed through a comparison of Vaisala s Global Lightning Dataset (GLD360) with the NLDN at locations within and outside the U.S.

Cummins, Kenneth L.↗
DOE OSTI2021

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Investigation of Supercells for Preparation of Homogenized Cross Sections for Prismatic Deep Burn VHTR Calculations

In Very High Temperature Reactors (VHTRs), the long mean-free-path and large migration area of neutrons leads to spectral influences between fuel and reflector zones over long distances. This presents significant challenges to the validity of the classic two-step approach of cross section preparation wherein infinite lattice transport calculations are performed on relatively small physical domains (e.g. single assembly) in order to compute homogenized few-group cross sections for whole core analysis. Effects of the inner and outer reflectors render infinite lattice calculations on a single peripheral fuel assembly quite inaccurate, while burnable poison locations affect neighboring assemblies as well. Use of transuranics-only (TRU) Deep Burn fuel in a prismatic VHTR (DB-VHTR) presents the additional challenge of producing vastly different neutron spectra between fresh and burned fuel. ?This paper presents the progress in seeking a systematic method for generation of diffusion theory data in optically thin, multiply-heterogeneous reactors in a production context. A companion paper presents the underlying theory and systematic development of the methodology. In the context of this work, a supercell refers to an extended domain surrounding a region of interest. The extended domain is used to decouple the solution in this region of interest from the boundary conditions of the problem. This is an extension of the concept of color set, which was demonstrated to work very well for light water reactors (LWR). However, a half-assembly in an LWR presents a greater neutronic depth (in mean free paths) than in a VHTR. ??In order to make the supercell calculations more computationally manageable, an initial calculation is performed on a small domain and individual cells (individual compacts or coolant channels with graphite surrounding) are homogenized then used in the supercell calculations. This allows faster computation on the larger domain while retaining the overall hexagonal geometry of the fuel blocks. An application of this supercell concept using the DRAGON transport code is evaluated in this work for its effectiveness and practicality as part of an overall cross section preparation scheme for prismatic DB-VHTR reactors. The sizes of supercells for a peripheral fuel block are evaluated using independence from boundary conditions as an indicator.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Energy management systems for forecasted demand error compensation using hybrid energy storage system in nanogrid

This paper proposes an energy management system (EMS) for nanogrids to balance the power supply and forecasted demand in consideration of forecasting errors arising from high instantaneous demand. The proposed EMS employs a power-balancing optimization process for forecasted demand and a reference power modulation strategy for forecasting errors. This power-balancing optimization utilizes nanogrid sources, such as photovoltaics, fuel cells, and batteries, to meet forecasted demand and a supercapacitor charging process to overcome issues with a low energy density. The proposed reference power modulation strategy is utilized to allocate power from a hybrid energy storage system consisting of a battery and supercapacitor in order to compensate for forecasting errors. In addition, this proposed strategy considers battery and supercapacitor constraints such as the power changing rate and total power limitations. Further, the power-balancing optimization process also operates at faster sampling rate than the reference power modulation process in order to improve the computational efficiency. The performance of the proposed EMS is evaluated using real data obtained from the Korea Electric Power Exchange.

25 ENERGY STORAGE↗
DOE OSTI2016

Electrode behavior RE-visited: Monitoring potential windows, capacity loss, and impedance changes in Li 1.03 (Ni 0.5 Co 0.2 Mn 0.3 ) 0.97 O 2 /silicon-graphite full cells

Here, the capacity and power performance of lithium-ion battery cells evolve over time. The mechanisms leading to these changes can often be identified through knowledge of electrode potentials, which contain information about electrochemical processes at the electrode-electrolyte interfaces. In this study we monitor electrode potentials within full cells containing a Li 1.03 (Ni 0.5 Co 0.2 Mn 0.3 ) 0.97 O 2 –based (NCM523) positive electrode, a silicon-graphite negative electrode, and an LiPF6-bearing electrolyte, with and without fluoroethylene carbonate (FEC) or vinylene carbonate (VC) additives. The electrode potentials are monitored with a Li-metal reference electrode (RE) positioned besides the electrode stack; changes in these potentials are used to examine electrode state-of-charge (SOC) shifts, material utilization, and loss of electrochemically active material. Electrode impedances are obtained with a Li x Sn RE located within the stack; the data display the effect of cell voltage and electrode SOC changes on the measured values after formation cycling and after aging. Our measurements confirm the beneficial effect of FEC and VC electrolyte additives in reducing full cell capacity loss and impedance rise after cycling in a 3.0–4.2 V range. Comparisons with data from a full cell containing a graphite-based negative highlight the consequences of including silicon in the electrode. Our observations on electrode potentials, capacity, and impedance changes on cycling are crucial to designing long-lasting, silicon-bearing, lithium-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assessment of Low-Level Pu Isotope Ratio Measurements Using Multicollector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS/MS) Equipped with a Pre-Mass Filter

We present an initial investigation into the performance of a multicollector inductively coupled plasmamass spectrometer equipped with a pre-mass filter (Neoma MC-ICP-MS/MS) for making plutonium (Pu) isotope ratio measurements on solutions containing low level (i.e., pg mL –1 ) Pu concentrations. This assessment was achieved by comparison of the 240 Pu/ 239 Pu, 241 Pu/ 239 Pu, and 242 Pu/ 239 Pu ratios attained over a one month period on the MC-ICP-MS/MS with the long-term (∼1 year) performance observed on the predecessor MC-ICP-MS (Neptune Plus) instrument each equipped with an equipped with an APEXΩ desolvating nebulizer for repeated measurements of certified reference materials from New Brunswick Program Office (NBL PO) CRM 136a and CRM 137. The MC-ICP-MS/MS performance of repeated measurement of CRM 136a (n = 20) resulted in mean values of 240 Pu/ 239 Pu = 0.1448 ± 0.0006, 241 Pu/ 239 Pu = 0.00371 ± 0.00006, and 242 Pu/ 239 Pu = 0.00682 ± 0.00006 (k = 2). The CRM 137 (n = 20), analyzed during the same analytical sessions, produced mean values for 240 Pu/ 239 Pu = 0.2414 ± 0.0006, 241 Pu/ 239 Pu = 0.00464 ± 0.00007, and 242 Pu/ 239 Pu = 0.0157 ± 0.0001 (k = 2). These results closely align with the certificate values for CRM 136a and CRM 137 and are within the k = 2 envelopes defined by the long-term performance of the traditional MC-ICP-MS approach (Neptune Plus). Examination of the performance of the various Pu isotope ratios as a function of total Pu content revealed accurate results (<3% relative difference, or RD) above ∼50 fg total Pu. The results presented here demonstrate the capability of the MC-ICP-MS/MS making accurate and precise low level Pu isotopic measurements. While the intent of this work was not to investigate the functionality of the collision cell, the pre-mass filter was employed. Future studies are warranted to investigate the entire capability of the MC-ICP-MS/MS collision cell and pre-cell mass filter optimization for performing low level Pu isotope measurements, even in mixed matrix samples.

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