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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Evaluating performance of two-group interfacial area transport equation for vertical small and large diameter pipes

In the two-fluid transport model, the coupling of mass, momentum and energy transfer between phases is highly dependent on interfacial area transfer terms. Several research efforts in the past have been focused on the development of an interfacial area transport equation model (IATE), in order to eliminate the drawbacks of static flow regime maps currently used in best-estimate thermal-hydraulic system codes. The IATE attempts to model the dynamics that are involved in two phase flows by accounting for the different interaction mechanisms affecting bubble transport in the flow. The further development and validation of IATE models has been hindered by the lack of adequate experimental data in regions beyond the bubbly flow regime. At the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) experiments utilizing wire mesh sensors have been performed over all flow regimes, establishing a database of high-resolution (in space and time) data. Two sets of data from small and large diameter pipes fitted with wire mesh sensors is utilized in this work. Analysis of flow conditions in the bubbly, churn turbulent and annular flow regimes is presented. The performance of the Fu-Ishii two-group model is evaluated against small diameter database. Results indicate good performance (< 10% error) for small group 1 bubbles, and poor performance for large group 2 bubbles. The Smith two-group large diameter IATE model is evaluated for the large diameter database. In low void-fraction regimes, the Smith model performs well. In high void-fraction regimes, there is poor group-wise interfacial area prediction - however the total interfacial area is erroneously predicted well as group-wise errors compensate each other. Overall, the study suggests that further efforts and re-evaluation of closure terms are needed in order to extend the range of validity of the IATE models. (authors)

42 ENGINEERING↗
DOE OSTI2016

Cataloguing Past Incidents in Transporting Spent Nuclear Fuel

Shipments of spent nuclear fuel (SNF) and high level radioactive waste (HLW) have a history of more than 50 years, during which tens of thousands of tons of material have been transported in tens of thousands of shipments worldwide. The vast majority of these have been completed without incident. This safety record has been made possible by establishing robust regulatory requirements for the casks used in transport, studying past shipments and incidents, and improving equipment and procedures to lessen the probability and impacts of future events. The authors recently collected a wide array of publicly available information on transportation incidents involving SNF and HLW worldwide. This presented a challenge, as no international or US databases currently exist which are dedicated to SNF and HLW transportation incidents. Thus, sources for this research included national database reports from nations that publish them; technical reports and archival journal papers focused on the solutions to particular transportation problems; and news reports of SNF and HLW transportation incidents, including transportation accidents and protests of shipments. Based on the survey of past transportation incidents, of which several representative descriptions are included in this paper, the authors conclude that (1) the casks in which SNF and HLW are shipped are able to contain their radioactive cargoes in severe accidents because of their robust construction and their being in compliance with regulatory requirements; and (2) most incidents in transporting SNF and HLW have been minor ones, primarily resulting from procedural compliance deficiencies. Furthermore, recent incidents suggest that public information and engagement challenges outweigh technical challenges in SNF and HLW transportation, since the most significant challenges surrounding shipments in recent years have been the results of public demonstrations and protests. This paper discusses some SNF and HLW transportation incidents, as well as the process used in cataloguing them. In general, there have been few transportation incidents worldwide in the history of transporting SNF and HLW. The transportation of SNF and HLW has an excellent safety record; by learning from past incidents, shippers of SNF and HLW can continue to make safe shipments while avoiding mistakes made in the past. Despite the safe and successful record of SNF and HLW transportation, information on its record is not easy to find. Few incidents are detailed as thoroughly as the truck accident that occurred in 1971. Several anti-nuclear organizations publish pamphlets that make reference to transportation accidents involving radioactive material and imply that transporting SNF and HLW is an intrinsically dangerous activity whose history is fraught with accidents. The absence of a clear, complete, official record on transportation incidents allows these claims to continue to be unanswered and uncorrected. For these reasons, it would be beneficial to develop a database detailing incidents involving SNF and HLW internationally. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Nuclear Forensics for Irradiated Materials using Kernel Regression Models

The ultimate purpose of nuclear forensics is to locate the origin of nuclear and other radioactive materials out of regulatory control used in nuclear security events such as classical forensics. For this purpose, some specific characteristics of interdicted materials (referred to as 'signatures') should be defined to compare the known sample database. In some cases, involved with irradiated material, the signatures could be specific amount of fission product inventory depending on reactor operational histories such as reactor type, initial enrichment, burn up rate of nuclear fuel and cooling period after irradiation in the reactor. In order to make inference model for irradiated material for nuclear forensics, we suggested 3 ways as follows; (i) analyzing ORIGEN produced nuclear substances for the fission product inventory, (ii) classifying the range of reactor type, (iii) predicting the operational history from the fission product inventory. In terms of nuclear substance analysis, the construction of spent fuel database has been internationally carried out since ITWG (Nuclear Smuggling International Technical Working Group) was established in 1995. However, enough sample data cannot be obtained in Korea to determine reactor type and operational histories because analyzing nuclear substances have been limited due to the international regulation. Thus, this study does not mention how to obtain mass or ratios of nuclides for the spent fuel. We just have generated simulation sample data as a fission product inventory using ORIGEN to construct spent fuel database. When unidentified radioactive materials are discovered, it is assumed that mass or ratios of the nuclides are analyzed by certain methods which are available in Korea as well as other countries. Then, a reactor type is determined, and finally, regression model can locate the origin or source of the radioactive materials by inferring operational histories using the fission product inventory. There are some studies on the classification of reactor type using statistical methods. As a part of predicting the operational history, this paper focuses on the development of spent fuel inference algorithm for nuclear forensics to estimate reactor operational histories that reflect characteristics of a reactor from the fission product inventory. The spent fuel inference algorithm for nuclear forensics has been developed on the basis of Kernel Regression (KR) which can conditionally generate the estimated output data by giving weight depending on geometric distance between sample data and input data. Also the KR which comprises Auto-Associative KR and Inferential KR have some benefits that can estimate only using data without assumption for specific physical model and re-learning process. Auto-associative KR (AAKR) was used to sort out outliers of input data and Inferential KR (IKR) was carried out to predict the operational histories for spent fuel. All of regression algorithms were performed in R programming tool. From the validation of both AAKR and IKR, it is expected that kernel regression has enough accuracy to be applied to nuclear forensics for spent fuel. Once the nuclear substance is measured to fill the fission product inventory with a certain reactor type, this kernel regression algorithm would predict the operational histories of spent fuel with high accuracy. Finally, this information is expected to be useful to find the origin of irradiated materials. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Characterization of Fresh Nuclear Fuel using Time-Of-Flight Neutrons

Neutrons offer excellent characterization capabilities for nuclear fuels and can provide non-destructive insight on micro structure, chemistry and crystallographic phase. Measurements are possible at reactors or pulsed sources, but the inherent energy resolution implicit at pulsed sources offers unique opportunities. Recent advances in 2D neutron detection enabled new capabilities of material characterization using neutron imaging and tomography for nuclear materials. Moreover, time-of-flight (TOF) neutron measurements can enable isotope specific tomography by deriving isotope densities from transmission spectra exhibiting neutron resonances, which are recorded for each pixel. Tomographic algorithms allow 3D reconstructions of the spatial distribution of isotopes, density and features in typical fuel pellet samples. The ability to select radiographs for different energies allows characterizing samples which are opaque for thermal neutrons, such as enriched fuels or fuels containing plutonium, by selecting epi-thermal neutron energies and by knowledge of the total neutron cross sections of the constituents, isotopic enrichment levels can be determined. Nuclear cross sections are typically not calculated directly and databases such as the Evaluated Nuclear Data File (ENDF) database provide this information with cross sections determined by standardized experimental measurements, such as neutron transmission measurements for individual isotopes. Utilizing the information in the ENDF database, the 'inverse' problem can be solved by assuming cross section parameters to be known parameters and areal densities can be determined. This work presents recent advances at the Los Alamos Neutron Science Center (LANSCE) facility at Los Alamos National Laboratory (LANL), which provides the infrastructure to handle radioactive samples, in the development of fuel characterization with TOF neutrons. Examples include recent work on prototype accident tolerant nuclear fuels (ATF). The potential application of these techniques for nondestructive examination of irradiated fuel is under consideration. Non-destructive access to materials features for specimens embedded in containers, particularly for hazardous samples, such as a radioactive nuclear fuel, is indispensable to characterize and ultimately license new fuel forms. Energy-resolve neutron imaging is a new tool for this research field. The results reported here present a new imaging technique, setting a milestone in the capabilities of measuring non-destructively absolute quantities of physical properties. The enabling physics behind this new technique are nuclear resonances. We have demonstrated how absolute areal densities can be extracted from radiographs utilizing pulsed neutron sources. This technique provides information that is otherwise difficult and costly to obtain. In the case of nuclear fuels, the results from energy-dispersive neutron imaging may guide destructive examination of irradiated fuel. This summery does not describe recent analysis, which is ongoing. Particularly, the implementation of calibration standards has improved the determination of enrichment levels without additional calibration. The analysis of the samples was performed with full tomographic reconstructions for isotope specific data and presents a first approach in absolute isotope specific 3D reconstruction. This work was predominantly funded by and received substantial support from the Fuel Cycle R and D program at Los Alamos National Laboratory. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Development of Waste Inventory for Probabilistic Performance Assessment Modeling - 19361

Estimation of radioactive waste inventory is a key initial step in the development of an environmental fate and transport model for performance assessment (PA) of radioactive waste sites. PA model output is often sensitive to parameters that represent inventory as a source term, yet estimation is a difficult problem. Inventory estimation for a probabilistic performance assessment (PPA) is related to, but distinct from, that performed for waste excavation, characterization, and offsite disposal. The latter appropriately focuses on obtaining the most detailed information possible on specific hazards and locations; however, these questions cannot be fully answered without intrusive site characterization efforts. This type of characterization is often not feasible when assembling information regarding a source term in a PPA model. Development of waste inventory for a PPA is one piece of a larger hierarchical model. The physical process model represented by Goldsim computer code represents one level of the hierarchy, and the second level of the hierarchy involves estimation of inputs such as inventory, transport, and risk parameters. The estimation of inputs is not a straightforward problem. The parameters of a computer model often do not have an equivalence to the physical quantities they describe, and estimation of the physical quantities themselves can be difficult due to limitations of available information. Inventory information for the West Valley Site in upstate New York is based on data from historical shipping and disposal forms. In the 1990's, the West Valley Demonstration Project (WVDP) compiled information from existing databases and historical waste records into one complete modern database. A conceptual model was then applied and used with recorded information to characterize the waste mass and radionuclide composition for each waste burial. Information was ultimately aggregated over all waste records to estimate the mass of each radionuclide within each trench, hole, or caisson. Three decades later, we revisit the master database, make updates with newly-identified information, and incorporate the conceptual model previously used for inventory estimation in the hierarchical modeling framework. We characterize uncertainty using probability distributions for waste mass and radionuclide composition at the individual shipment or individual burial level. Uncertainty incorporated at the lowest level of the hierarchy is ultimately carried through to uncertainty in PPA model endpoints. Sensitivity analysis of early model results is then applied to identify influential inputs and guide subsequent efforts towards parameters that drive risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Fortifying Environmental Compliance Strategies at Hanford - 19541

At the Hanford Site, located near Richland, Washington, the Department of Energy is cleaning up legacy radioactive and mixed-waste generated from the Manhattan Project in the 1940's. A major component of cleaning up the waste is maintaining compliance with federal and state environmental regulations. Environmental compliance is also determined through permits, agreements, and consent orders issued by regulating agencies such as the Washington State Department of Health: Office of Radiation Protection, Washington State Department of Ecology Nuclear Waste Program, and the Environmental Protection Agency. Maintaining compliance at Hanford reduces environmental impacts and addresses violations, or non-compliances. The following strategies improve compliance and support the avoidance of enforcement actions. At Hanford, regulatory agency environmental enforcement actions, and their corrective actions, are tracked to completion using databases maintained by inspection subject matter experts. The databases are used to provide the Department of Energy and contractor management with up-to-date status of regulatory agency activity and the required corrective actions. Trending enforcement actions helps target compliance vulnerabilities. Findings and corrective actions that are entered into the databases are then trended by date, location, responsible contractor, agency, and type of compliance issue. The ability to review previous non-compliances in certain locations of the Site, or by general alleged violation, provides the project's environmental contacts with information on what types of issues to look for on pre-inspection walk downs. Finding non-compliances during pre-inspection walk downs allows the contractor to correct the issue and avoid potential fines from regulating agencies. The walk downs are conducted by environmental specialists and project personnel looking for issues that may be viewed as a compliance problem. Using agency checklists and previous inspection correspondence can help to provide valuable information during pre-inspection activities. Training regulatory agency inspectors on Site security requirements, cultural and ecological standards, and inspection protocols allows for increased efficiency and reduces potential miscommunication between regulatory agencies and the regulated contractors. The training also allows the contractors to give the regulating agencies the up-to-date policies and procedures that will be addressed during the inspection. Hanford has pre-identified inspection coordinators within each contractor to assist in coordinating with Department of Energy personnel, projects, and management prior to the inspections. These inspection coordinators notify affected management, accommodate and escort the regulators to locations they ask to inspect, set up requested interviews, and gather requested information that will need to be cleared for public release. These practices make for positive experiences and interactions with the regulating agency personnel and help reduce and eliminate environmental non-compliances, findings, violations, and fines. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Experimental validation of the Cristal V2.0 French criticality calculation package - 14587

A new version of the CRISTAL criticality calculation package, named CRISTAL V2.0 [1], has been developed by IRSN and CEA, in collaboration with AREVA and EDF. Four calculation routes are now available, using nuclear data issued from the JEFF-3.1.1 evaluation: two multigroup routes based on 281 groups cross-sections (APOLLO2 - MORET 5 or APOLLO2-Sn calculations), a pointwise Monte Carlo route (TRIPOLI-4{sup R}) and a criticality standard calculation route. The CRISTAL V2.0 package, which will be delivered soon to OECD/NEA data bank, benefits from a broad validation database covering almost all areas of criticality-safety applications, from fuel fabrication to reprocessing, including transportation. 3,127 critical experiments, corresponding to 342 series, either issued from the OECD/ICSBEP Handbook or performed in French facilities (confidential data) were selected for the CRISTAL V2.0 validation database. Currently, more than 2,300 experiments are already part of the validation database. This validation work highlights an overall consistency to experimental data and inter-comparisons between the different calculation routes mainly show good agreements on a large set of common experiments. (authors)

42 ENGINEERING↗
DOE OSTI2024

The 2022 Russian Invasion of Ukraine: Nuclear Supply Chains vs. Sanctions

The United States and European countries are unlikely to collectively approve of sanctions against Russian exports of nuclear fuel assemblies and uranium in the near term despite the 2022 invasion of Ukraine. Rather than bearing the costs that cutting off Russian imports would have on domestic nuclear energy production, the United States and European countries are more likely to prefer developing alternative supply chains of nuclear fuel and enriched uranium to reduce dependence on Russian resources. This outlook is primarily based on two areas of evaluation: (1) comparison of the Russian-made reactor fuel supply chain within the European Union (EU) in 2014 following the annexation of Crimea and in 2022 following the invasion of Ukraine, and (2) the dependence of France and the United States on Russia’s exports of enriched uranium. Additionally, the potential impacts to Kazakh uranium exports if trade routes for nuclear resources through Russia became unavailable were considered as an additional factor in the push for disentanglement from Russian nuclear resources. This work utilized BACI, a database of harmonized international trade data at the product level drawn from the United Nations Comtrade Database and created by the French international economics research institute CEPII.1 Comparisons of imports and exports were based on the trade value in U.S. dollars as reported in BACI instead of the quantity of the traded product. This evaluation only considers import and export data up until 2021, since the trade data for 2022 is incomplete within the Comtrade Database for several of the key countries presented in this work, including Australia, Canada, Namibia, Niger, and Russia.

Political science↗
DOE OSTI2025

Recent Metallic Fuel Data Recovery in FIPD

The Metallic Fuels Irradiation and Physics Database (FIPD) [1] is an organized collection of metallic fuel test pin data (U-xPu-yZr, = 0 ~ 28; y = 2 ~ 10) and documentation available to industry. FIPD mainly contains three types of data: (1) Fuel pin fabrication data, including fuel slug diameter, fuel slug length, cladding diameter, smear density, etc. (2) Fuel pin operation conditions, including axial distributions for power, temperatures, fluences, burnup, and isotopic densities, etc. and (3) Fuel pin post-irradiation examination (PIE) data, including fission gas release and gas chemistry, profilometry, and neutron radiography, etc. The operating conditions for pins with PIE data available in FIPD span significant ranges across key parameters. The fuel peak burnup extends from less than 5% up to 20 at%. The cladding peak temperature varies from about 490°C to 660°C. Finally, the cladding peak DPA shows a wide range from less than 5 to 120. These broad ranges reflect the diverse testing conditions and operational parameters captured in the available PIE data. More detail about FIPD can be found in ref. [2]. The database development is an ongoing effort covering metallic fuel experiments from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). As reported in the ref. [3, 4], most of the PIE data generated during the IFR program [5] has been collected, reviewed, processed, and integrated into FIPD. The most recently added PIE data can be found in ref. [4], which shows the collection of over 95% of the PIE data by the time of this paper. The recent improvements to the database are summarized in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Intern Poster: STIG Shouldn't Drop ACID

STIG (Structured Threat Intelligence Graph) is an open-source graph database tool from INL. It’s used to create and process cyber intelligence graphs, which are shared in the cyber threat intelligence community and used to train INL machine learning products like @DisCo. For quality machine learning and critical infrastructure defense, STIG’s database must be ACID: Atomic, Consistent, Isolated, Durable. Various ACID tests were designed and applied to STIG to ensure its behavior follows these properties.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

Abstract The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties ( EFP s). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity ( GPP ) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFP s and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site‐years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R 2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra‐ and interspecific trait variation on ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Do we have globally representative data to understand soil processes?

Understanding and modeling soils and soil organic matter (SOM) are central to a variety of human needs, from food production to ecosystem management. Soil data have been collected for over a century, but the global spatial and process representativeness of soil data remains unclear. We assessed the representativeness of currently available soil data that could be used to understand a variety of SOM processes. We used 16 open-source soil databases and data from over 281,000 unique locations globally, categorizing the databases into three main data types necessary to understand SOM processes: soil carbon stocks and fluxes, mechanistic drivers of these stocks and fluxes, and soil carbon gain or loss potential. We found that stock and driver data have extensive global coverage. However, data on soil carbon gain or loss potential, particularly data describing change in soils over time such as time series data, are severely limited in their global coverage. We conclude that while significant strides have been made in measuring soil carbon stocks and fluxes, and their drivers, we are limited in global data related to changes in soils over time. Our recommendations for soil data generators are to ensure precise metadata reporting and prioritizing sampling in underrepresented areas like tropical, arctic, mountainous, wetland and arid regions. We also encourage designing revisit schemes that explicitly support change detection and reporting multi-modal datasets that can aid in model development. Targeted measurement of low coverage soil data types and regions is necessary for a range of applications including current and future biogeochemical predictions, and their management and policy implications.

carbon fluxes↗
DOE OSTI2016

Evolving landscape of low-energy nuclear physics publications

Evolution of low-energy nuclear physics publications over the last 120 years has been analyzed using nuclear physics databases. An extensive study of Nuclear Science References, Experimental Nuclear Reaction Data (EXFOR), and Evaluated Nuclear Structure Data File (ENSDF) contents provides a unique picture of refereed and non-refereed nuclear physics references. Significant fractional contributions of non-refereed reports, private communications and conference proceedings in EXFOR and ENSDF databases in the 1970’s reflect extensive experimental campaigns and an insufficient number of research journals. This trend has been reversed in recent years because the number of measurements is much lower, while number of journals is higher. In addition, nuclear physics results are mainly published in a limited number of journals, such as Physical Review C and Nuclear Physics A. In the present work, historic publication trends and averages have been extracted and analyzed using nuclear data mining techniques. Lastly, the results of this study and implications are discussed and conclusions presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A centralized resource for bacterial–fungal interactions research

Research on bacterial-fungal interactions (BFIs) has revealed that fungi and bacteria frequently interact with one another within diverse ecosystems and microbiomes. Assessing the current state of knowledge within the field of BFI research, particularly with respect to what interactions between bacteria and fungi have been previously described, is very challenging and time consuming. This is largely due to a lack of any centralized resource, with reports of BFIs being spread across publications in numerous journals using non-standardized text to describe the relationships. To address this issue, we have developed the BFI Research Portal, a publicly accessible database of previously reported interactions between bacterial and fungal taxa to serve as a centralized resource for the field. Users can query bacterial or fungal taxa to see what members from the other kingdom have been observed as interaction partners. Search results are accompanied by interactive and intuitive visual outputs, and the database is a dynamic resource that will be updated as new BFIs are reported.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

An Implementation of ICME in Materials Information Exchanging Interfaces

The Integrated Computational Materials Engineering (ICME) approach provides a new paradigm for improving the performance of existing materials or discovering and developing new materials. It focuses on developing effective connections between isolated engineering fields, to bring quantitative processing-structure-property relationships and abundant validated data that populate the knowledge base for accelerating the research of new materials while reducing the cost of development. The data exchanging interfaces play a key role in building such ICME connections among different materials models, simulation tools and individual organizations. With implementations of information exchanging interface between different materials database, and interface between database and applications, this paper concludes that in building effective ICME applications, 1) standards-compliant interface can improve the exchange efficiency; 2) popular web service enables automated online materials data transfer; 3) customized data interoperation scripts can provide flexibility and productivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Applying U.S. metal fuel experience to new fuel designs for fast reactors

With the increasing interest in small modular reactors or microreactors, developers are working to design and submit licensing approval requests of U–10Zr-fueled fast reactors. The developers and their proponents cite prior metal fuel experience (worldwide, but U.S. experience in particular for many developers) as the motivation and justification for their reactor concepts. The experience with metal fuel deployment in sodium-cooled fast reactors as well as the underlying irradiation testing database, provide a suitable basis for analytically justifying the use of metal fuel in new reactors. The evolution of metal fuel design and capability illustrates the importance of key fuel design parameters to consider in new applications of the prior experience: fuel smeared density, plenum-to-fuel volume ratio, the ratio of cladding radius to thickness, fuel composition, and cladding and duct materials. In-service operating and deployment conditions to be considered include fuel linear heat generation rate, fuel temperature, cladding temperature, peak burnup and peak fast fluence. Fuel designs and in-service conditions that are bounded by the database and experience are most easily addressed, but deviations from those previous parameters and conditions can be addressed by considering impacts on previously established behavior and applying other mitigating conservatisms, as appropriate. Here, the authors recommend any new deployment proceed with fuel surveillance and monitoring to mitigate risk, application of conservative measures to address uncertainties, and a fuel qualification program that addresses a range of in-service operating conditions with production fuel. The work reported should be of interest to students and regulators unfamiliar with metal fuel in fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗