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This report contains a summary of highlights and top achievements from Los Alamos National Laboratory from December 2023, including Nuclear Security, Science Technology & Engineering, Mission Operations, and Community Relations.
Laboratory Directed Research and Development (LDRD) helps Los Alamos National Laboratory solve national security challenges through excellence in mission-focused science, technology, and engineering. The DOE Laboratory and Site-Directed Research and Development programs are among the most impactful sources of research and development for our Nation. The heart of the LDRD program is high-risk, high-reward research that creates innovative technical solutions for some of the Nation’s most difficult challenges. The LDRD programs follow strategic guidance derived from the missions of the U.S. Department of Energy, the National Nuclear Security Administration (NNSA), and the Laboratory.
This report summarizes the international collaborations conducted by Sandia funded by the US Department of Energy Office (DOE) of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) as part of the Sandia National Laboratories Salt R&D and Salt International work packages. This report satisfies the level-three milestone M3SF-24SN010303063. Several stand-alone sections make up this summary report, each completed by the participants. The sections discuss granular salt reconsolidation (KOMPASS/MEASURES), engineered barriers (RANGERS), numerical model comparison (DECOVALEX), an NEA Salt Club working group on the development of scenarios as part of the performance assessment development process, and progress on seal percolation experiments with German colleagues at Gesellschaft für Anlagen- und Reaktorsicherheit (GRS). Finally, we summarize events related to the US/German Workshop on Repository Research, Design and Operations.
Sandia is a federally funded research and development center (FFRDC) focused on developing and applying advanced science and engineering capabilities to mitigate national security threats. This is accomplished through the exceptional staff leading research at the Labs and partnering with universities and companies. Sandia’s LDRD program aims to maintain the scientific and technical vitality of the Labs and to enhance the Labs’ ability to address future national security needs. The program funds foundational, leading-edge discretionary research projects that cultivate and utilize core science, technology, and engineering (ST&E) capabilities. Per Congressional intent (P.L. 101-510) and Department of Energy (DOE) guidance (DOE Order 413.2C, Chg 1), Sandia’s LDRD program is crucial to maintaining the nation’s scientific and technical vitality
This report summarizes the international collaborations conducted by Sandia funded by the US Department of Energy Office (DOE) of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) as part of the Sandia National Laboratories Salt R&D and Salt International work packages. This report satisfies the level-three milestone M3SF-23SN010303062. Several stand-alone sections make up this summary report, each completed by the participants. The sections discuss granular salt reconsolidation (KOMPASS), engineered barriers (RANGERS), numerical model comparison (DECOVALEX) and an NEA Salt Club working group on the development of scenarios as part of the performance assessment development process. Finally, we summarize events related to the US/German Workshop on Repository Research, Design and Operations.
Sandia is a federally funded research and development center (FFRDC) focused on developing and applying advanced science and engineering capabilities to mitigate national security threats. This is accomplished through the exceptional staff leading research at the Labs and partnering with universities and companies. Sandia’s LDRD program aims to maintain the scientific and technical vitality of the Labs and to enhance the Labs’ ability to address future national security needs. The program funds foundational, leading-edge discretionary research projects that cultivate and utilize core science, technology, and engineering (ST&E) capabilities. Per Congressional intent (P.L. 101-510) and Department of Energy (DOE) guidance (DOE Order 413.2C, Chg 1), Sandia’s LDRD program is crucial to maintaining the nation’s scientific and technical vitality.
The importance of actinides for science, technology, and medicine is widely recognized and does not require a lengthy introduction. However, the fundamental understanding of actinides and their chemical and physical properties lags behind the knowledge of most other elements in the periodic table. Most actinides (89 ≤ Z ≤ 103) are man-made and were produced in particle accelerators or nuclear reactors in the second half of the 20th century. Although trends in bonding and electronic structure are well characterized and documented across the periodic table, fundamental questions remain regarding the chemistry and physics of the actinides. This lack of knowledge is largely because most isotopes of actinides are intensely radioactive, which greatly increases the difficultly in handling them.
This progress report (Level 3 Milestone Number M3SF-24LL010301062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite International Collaborations Work Package SF-24LL01030106. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. The focus of this milestone is the establishment of international collaborations for sorption modeling and the associated impacts of unlocking larger, community-based datasets. More specifically, we are developing a database framework for Spent Fuel and Waste and Science Technology (SFWST) that is aligned with the Helmholtz Zentrum Dresden Rossendorf (HZDR) and other international sorption database development groups in support of the database needs of the SFWST program.
This report summarizes the findings of a four months FY24 Advanced Science & Technology (AS&T) LDRD Quick Targeted Investigation (QTI) project focused on the exploration of supervised dimension reduction approaches based on autoencoders. Autoencoders have been extensively employed in literature for unsupervised learning tasks, however, their use for supervised regression tasks, which are common within scientific applications, has been limited. Motivated by linear dimension reduction strategies like Active Subspaces and Adaptive Basis, we explored the possibility of employing autoencoders to discover a non-linear manifold able to represent the original function in fewer dimensions. In this report, we discuss a neural network architecture and we perform a numerical campaign on several problems ranging from simple two-dimensional functions to a model problem for magnetohydrodynamics in five dimensions. In our preliminary results, we show that the proposed approach is found to be superior to linear dimension reduction strategies in representing the target function even with a single latent variable.
Sandia is a federally funded research and development center (FFRDC) focused on developing and applying advanced science and engineering capabilities to mitigate national security threats. This is accomplished through the exceptional staff leading research at the Labs and partnering with universities and companies. Sandia’s LDRD program aims to maintain the scientific and technical vitality of the Labs and to enhance the Labs’ ability to address future national security needs. The program funds foundational, leading-edge discretionary research projects that cultivate and utilize core science, technology, and engineering (ST&E) capabilities. Per Congressional intent (P.L. 101-510) and Department of Energy (DOE) guidance (DOE Order 413.2C, Chg 1), Sandia’s LDRD program is crucial to maintaining the nation’s scientific and technical vitality.
The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) research program is guided by the high-level goal of closing prioritized knowledge gaps related to spent nuclear fuel (SNF) storage and transportation, which are summarized by Saltzstein et al. (2020). One of the high-priority knowledge gaps is the identification and quantification of mechanical loads that are expected to affect SNF during normal conditions of transportation and storage to inform the range of physical SNF test programs. This report uses modeling and analysis methods to estimate the mechanical loads on spent nuclear fuel (SNF) in the general 30 cm package drop scenario. The drop scenario assumes impact limiters are in place in the transportation configuration and the impact surface is perfectly rigid. The goal of this analysis is to consider the universe of potential mechanical loading conditions that can happen to SNF and present the results in a manner that is useful for materials testing, decision making, and regulatory rule making purposes. This study uses validated finite element models and methods to perform a broad parametric study of key variables that can affect the mechanical loads on SNF during a hypothetical package free drop scenario. Physical drop test data from a cask and fuel assembly drop test campaign is the basis for model validation. Additionally, the results of the parametric study are used to inform a damage model, which uses multiple nonlinear regression to estimate the relationships between input variables and output response. The parametric finite element analyses consider thousands of input variable combinations, while the damage model estimates millions of combinations. The breadth of this study provides confidence that the potential range of mechanical loads that SNF might experience during the general 30 cm package drop scenario are characterized well enough to consider this knowledge gap closed. While this report documents the overall peak values calculated in this study, the 95 th percentile values, the histograms, and the observed trends are equally important. This study covered a large range of SNF temperatures, room temperature to 300°C, and burnups, 10 GWd/MTU to 62 GWd/MTU. Each temperature and burnup combination has a different cladding yield strain, so it is more meaningful to summarize the calculated cladding strain response as its factor of safety, which is defined relative to the yield strain. The factor of safety is calculated as the yield strain divided by the peak cladding strain. A factor of safety greater than unity indicates that the cladding remains below yield, whereas a value less than unity is indicative of plastic deformation. In all cases of this study a safety factor over 1.0 was calculated, although in the most limiting case at 300°C the safety factor was only 1.01, which suggests that yielding could occur when additional loads like rod internal pressure are included. When the temperature is restricted to 200°C the limiting safety factor increases to 1.28, which has significant margin to accommodate internal pressure and potential local cladding defects that could cause a local stress concentration. An important trend in the calculated fuel rod mechanical loads is that the 2 nd highest loaded fuel rod in an assembly tends to be significantly lower than the highest loaded rod. The implication is that even if one rod in an assembly experiences a failure the loads would have to be significantly higher to cause two or more rods to fail.
Weapons research, development, and production operations at the former Pinellas Plant, which includes the Building 100 area, released chlorinated organic solvents into the subsurface, contaminating the underlying soil and groundwater. The site was sold to Pinellas County and is now home to a thriving industrial park known as the Young - Rainey Science, Technology, and Research (STAR) Center. The US Department of Energy (DOE) has applied bioremediation at the Building 100 Area as a key technology to clean up the chlorinated volatile organic compound (cVOC) contamination in soil and groundwater. The monitoring data indicate significant progress toward remedial objectives over the past two decades. Starting conditions in the 1980s-1990s included areas containing residual undissolved dense nonaqueous phase liquids (DNAPLs) and the associated presence of an extensive high concentration plume in the groundwater. The original parent cVOCs were primarily tetrachloroethene (PCE) and trichloroethene (TCE). After several informative pilot studies, bioremediation was implemented at the Building 100 Area of the site and relies on reductive biological pathways and the sequential removal of chlorine from the parent cVOCs forming dichloroethane (DCE) and chloroethene (vinyl chloride, VC). As bioremediation sites evolve toward cleanup, the trends in VC concentrations often serve as a critical indicator for progress and remediation timeframe because VC typically has a lower concentration target remedial objective (nominally 1 to 2 μg/L) compared to PCE and TCE (nominally 3 to 5 μg/L).
Presentation for the 2025 Materials Science & Technology Conference summarizing NETL work involving development and testing of environmental barrier coatings for protecting ceramic matrix composites in high efficiency gas turbines.
Laboratory Directed Research and Development (LDRD) helps Los Alamos National Laboratory solve national security challenges through excellence in mission-focused science, technology, and engineering (ST&E). The Department of Energy (DOE) Laboratory and Site-Directed Research and Development programs are among the most impactful sources of research and development for our Nation. The heart of the LDRD program is high-risk, high-reward research that creates innovative technical solutions for some of the Nation’s most difficult challenges. The LDRD programs follow strategic guidance derived from the missions of the U.S. Department of Energy, the National Nuclear Security Administration (NNSA), and the Laboratory.
This dataset contains daily aggregated measurements of daily PM2.5 from ambient wildfire smoke in the contiguous United States, spanning from 2006 to 2016. The data is sourced from a study by Childs et al. (2022), titled "Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US" published in Environmental Science & Technology. To compute the standardized weight across different zip codes, we computed the weight calculation on a 10km grids. To compute the weight, we obtain area-weights that add up to 1 in each polygon of zipcodes. This enabled us to calculate the smoke values per zipcode for the aforementioned period. Those interested in replicating our data processing pipeline can access it at https://github.com/NSAPH-Data-Processing/smoke_aggregation.
This dataset contains the code and data files needed for implementation of a Multivariate Bayesian Regression model, described in Jin et al. (2025), for the historical prediction of the chemical composition of disposed coal ash at U.S. coal fired power plants as a function of annualized coal purchase data. The integrated coal supply data file (CoalSupplyDataset.csv) represents a compilation of monthly fuel purchase records for the period 1973-2022 at major U.S. power stations. These records were obtained from the U.S. Energy Information Administration. The CSV file also contains, for each coal purchase record, the coal region of the mine as defined by the U.S. Geological Survey. Data entry errors and data gaps in the EIA records were corrected as described in Jin et al. This CSV file represents the integrated coal supply data after corrections were made. The model structure and fitting parameters are encoded in pickle file format (Bayesian.pkl). The model was developed with the coal supply data and coal ash composition data, apportioned according to the Stratified Shuffle Split for training and testing subsets. The model was built using Python and the PyMC library. Reference Publication: Jin, Z.; Huang, J.; Hower, J.C.; Hsu-Kim, H.(2025). Predictive Assessment of the Chemical Composition of Coal Ash in Reserve at U.S. Disposal Sites. Environmental Science & Technology.
Presented at Materials Science & Technology (MS&T) 2020
Monthly highlights for February for the Nuclear Science & Technology directorate