Seismically Informed High-Resolution Geometric Gravity Inversion and Forward Modeling of Paleozoic Basement in Rock Valley, NV
A gravity inversion of relative gravity data in southern Nevada.
Bodmer, Miles Arnold [Sandia National Laboratories↗
SEARCH · Engineering Papers
Results for “nevada”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
KRUSTY: Advancing Space Nuclear Power for Future Missions [Slides]
For more than 70 years, LANL has conducted subcritical and critical experiments in support of space reactors, small modular reactors (SMRs), and criticality safety programs. These experiments were performed first at Los Alamos Critical Experiments Facility (LACEF) at TA-18 and in more recent years at the National Criticality Experiments Research Center (NCERC) in Nevada.
LACEF↗
Evaluation of Technologies to Mitigate the Presence of Gaseous Elemental Mercury in Waste Disposal Containers
A study was conducted to evaluate sorbent technologies that can mitigate the presence of elemental mercury (Hg⁰) in waste containers for mercury-contaminated debris (MCD). Decontamination and demolition (D&D) activities at the Y-12 National Security Complex (Y-12) and other U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) facilities generate MCD requiring offsite disposal. The debris is packaged in appropriate waste containers and may be temporarily stored onsite prior to transport for treatment and/or disposal. During transportation of loads that had no visible liquid Hg at the point of origin, temperature changes can cause Hg⁰ to evaporate, condense, and form droplets on container walls. Furthermore, vibration during transportation could cause beads of Hg to be released from the debris, container walls, and ceiling, resulting in pools of liquid Hg⁰ on the container floor. Waste acceptance criteria (WAC) limitations for commercial disposal facilities, the Nevada National Security Site (NNSS), and ORR mixed low-level waste landfills prohibit the presence of any free liquids in containers identified as a solid waste form. Potential solutions to mitigate the presence of residual liquids that could be formed through vapor condensation include the use of sorbents or similar materials to capture and stabilize volatile Hg⁰ vapors and thus ensure compliance with landfill WAC requirements. This report summarizes data from small-scale laboratory experiments conducted to evaluate sorbent materials for Hg⁰ vapor suppression and sorption of liquid Hg⁰ that could form under relevant transportation and disposal conditions. A series of experiments was conducted to evaluate commercial sorbent materials and their effectiveness for Hg⁰ sorption across a temperature range from 19.4°C to 60°C. The impact of residual moisture on sorption was investigated under relevant conditions, and leaching tests were performed to assess the stability of Hg⁰ captured sorbent materials. The results provide estimates for sorbent quantities needed for a given Hg⁰ mass loading based on experimental results exposing sorbents to gaseous and liquid Hg⁰ at various mass ratios. Overall, sorbents that were most effective for Hg⁰ vapor suppression were brominated activated carbons, mackinawite-based sorbents coated on vermiculite, and sulfur-modified granular activated carbon. Elevated temperatures and moisture conditions did not result in significant increases of Hg⁰ headspace concentrations, and the materials also demonstrated high sorption capacities for the sorption of liquid Hg⁰.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Final Calendar Year 2024 Post-Closure Monitoring Letter, Revision 1 with ROTC-1
This letter serves as the annual post-closure letter for Corrective Action Unit (CAU) 98, Frenchman Flat (FF); CAU 97, Yucca Flat/Climax Mine (YF/CM); and CAU 99, Rainier Mesa/Shoshone Mountain (RM/SM) for calendar year (CY) 2024. This letter will discuss the post-closure monitoring activities that occurred during CY 2024, identify any triggers reached, and summarize water usage on the Nevada National Security Site (NNSS) and surrounding hydrographic basins at the three CAUs.
54 ENVIRONMENTAL SCIENCES↗
Evaluation of Three Types of Electric Field Sensors
On June 3-4, 2025, we evaluated three types of electric-field (E-field) sensors: capacitive electrodes, stainless-steel stakes, and porous pots - at two electromagnetic (EM) stations (PWBVI and PWAOF) on Aqueduct Mesa at the Nevada National Security Site. We compared calibrated time series and derived metrics including power spectral density, root-mean-square (RMS) amplitude, signal-to-noise ratio (SNR), and detectability of power line harmonics and Schumann resonance. The objective was to identify an alternative E field sensor with higher SNR than the existing capacitive electrodes. Our data demonstrates that stainless-steel electrodes perform best, with the highest SNR and the most consistent detection of power-line harmonics and Schumann resonance among the three sensor types; they may be used as a supplement to, or replacement for, the existing capacitive electrodes.
58 GEOSCIENCES↗
Compliance of NNSS Activities with P322-4 Issues Management and NNSSWAC Requirements
The Institutional Quality and Performance Assurance Division's Quality Support Services Group conducted a surveillance of the compliance of Waste Management Program activities to Issues Management/Corrective Action requirements communicated in P322-4 and the Nevada National Security Site Waste Acceptance criteria (NNSSWAC). All corrective actions reviewed and records examined were found to be compliant with appropriate and relevant procedures. There were no Findings or Opportunities for Improvement noted.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network
This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.
15 GEOTHERMAL ENERGY↗
Surveillance LANL-ASMT-2026-0059 Procurement – NNSS Supplier Review
The Institutional Quality and Performance Assurance Division's Quality Support Services Group conducted a surveillance of IQPA-IQ Supplier Evaluation group's required assessments of suppliers providing items and services relevant to the Nevada National Security Site. Based upon records examined, the surveillance team has determined that all supplier evaluation/oversight requirements are being met, and no Findings or Opportunities for Improvement are noted.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
IER 519 Experiment Execution Report: TEX Hanford
The TEX-Hanford experiments were performed at the National Criticality Experiments Research Center (NCERC) at the Device Assembly Facility (DAF) at the Nevada Nuclear Security Site (NNSS). Three configurations were measured, with the measurements occurring in December 2025 and January 2026. The Fe-14 configuration was executed in December 2025; the Fe-11 configuration began its handstack on the Planet critical assembly machine in December 2025, but was taken critical in January 2026; the Fe-16 configuration was executed entirely in January 2026. The TEX-Hanford experiments were performed on the Planet critical assembly machine utilizing using PANN (Plutonium Aluminum No Nickel) ZPPR (Zero Power Physics Reactor) plutonium plates as fuel. The configurations were moderated with varying thicknesses of HDPE and iron absorber. This document details the configurations that were measured, preliminary reactivity measurements of the measured configurations, data files from the neutron detection systems, and results from the coordinate-measuring machine (CMM) measurements of the final stack height measurements each configuration.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
VIC-Global Parameter Dataset Sensitivity with the Variable Infiltration Capacity Model: Evaluating the importance of dynamic land surface parameters when using the VIC-Global parameter dataset
Accurate prediction of runoff is essential to water resources management, flood risk assessment, and ecosystem protection. However, many hydrological models still have relatively substantial limitations when representing the influence of land use and land cover (LULC) on runoff generation and routing. Changes in LULC, such as deforestation, urban expansion, agricultural intensification, and wetland loss, have been shown to alter the water balance at the land surface through fundamental hydrologic processes (e.g., interception, infiltration, evapotranspiration, and soil storage). However, it remains an open question what the exact magnitude and timing of these impacts are for the spatial and temporal scales commonly used in engineering applications. In this analysis we focus on one aspect of recent LULC change for assessing human impacts, which is urbanization. Specifically we seek to determine the impacts of urbanization on the magnitude and timing of surface runoff and baseflow in HUC-12 basins in Clark County, Nevada which has experienced rapid urbanization. We use the Variable Infiltration Capacity (VIC) hydrology model with a widely used off-the-shelf dataset of land surface parameters, VIC-Global, both of which have been commonly used in the past for water and energy balance modeling for large scale hydrologic studies. We examine two scenarios where the first scenario removes all urbanized land cover and parameterizes those areas of the basins as barren or open shrubland. The second scenario tests the opposite case where all areas of the basins are classified as urban regardless of their present classification. The results from the VIC model show there is a low sensitivity for daily surface runoff between scenarios. The daily baseflow values indicate similar low sensitivity to the classification change during specific periods, but then have substantial differences during other period when large precipitation events are occurring. This is likely due to the assumed parameter values for the urban land cover classification made by the VIC-Global dataset. Using a static land cover parameterization is reasonable for large domain hydrology models that are being used for near-term planning horizons (<30 years). However, longer planning horizons where feedbacks between the atmosphere and land surface are important, especially in transient climate situations, considerations for how to update land surface parameters should be incorporated.
42 ENGINEERING↗
Integral Experiment Execution of Thermal or Epithermal eXperiments using Plutonium with Polyethylene and Iron, IER 519, TEX-Hanford (-Iron), CED-3b
This report documents the execution of experiments and measurements for IER 519, Thermal/Epithermal eXperiments (TEX) for Hanford applications, using plutonium Zero Power Physics Reactor (ZPPR) plates moderated by interstitial polyethylene and iron (Fe) absorber plates. Initial hand stack, mass, and dimensional measurements were performed in July 2025. The experiments were completed over three weeks from December 2025 to January 2026 at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Sites (NNSS). All photos and critical data were provided by NCERC and experimenters in LANL’s NEN-2.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Assessing turbulence and mixing parameterizations in the gray-zone of multiscale simulations over mountainous terrain during the METEX21 field experiment
Multiscale numerical weather prediction models transition from mesoscale, where turbulence is fully parameterized, to microscale, where the majority of highly energetic scales of turbulence are resolved. The turbulence gray-zone is situated between these two regimes and multiscale models must downscale through these resolutions. Here, we compare three multiscale simulations which vary by the parameterization used for turbulence and mixing within the gray-zone. The three parameterizations analyzed are the Mellor-Yamada Nakanishi and Niino (MYNN) Level 2.5 planetary boundary layer scheme, the TKE-1.5 large eddy simulation (LES) closure scheme, and a recently developed three-dimensional planetary boundary layer scheme based on the Mellor-Yamada model. The simulation domain includes complex (i.e., mountainous) terrain in Nevada that was instrumented with meteorological towers, profiling and scanning lidars, a tethered balloon, and a surface flux tower. Simulations are compared to each other and to observations, with assessment of model skill at predicting wind speed, wind direction and TKE, and qualitative evaluations of transport and dispersion of smoke from controlled releases. This analysis demonstrates that microscale predictions of transport and dispersion can be significantly influenced by the choice of turbulence and mixing parameterization in the terra incognita , particularly over regions of complex terrain and with strong local forcing. This influence may not be apparent in the analysis of model skill, and motivates future field campaigns involving controlled tracer releases and corresponding modeling studies of the turbulence gray-zone.
54 ENVIRONMENTAL SCIENCES↗
The National Criticality Experiments Research Center and its role in support of advanced reactor design
The National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site (NNSS) in the Device Assembly Facility (DAF) and operated by Los Alamos National Laboratory (LANL) is the only general purpose critical experiments facility in the United States. Experiments from subcritical to critical and above prompt critical are carried out at NCERC on a regular basis. In recent years, NCERC has become more involved in experiments related to nuclear energy, including the Kilopower/KRUSTY demonstration and the recent Hypatia experiment. Multiple nuclear energy related projects are currently ongoing at NCERC. This paper discusses NCERC’s role in advanced reactor design and how that role may change in the future.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Seismic Observations of the OSIRIS-REx Sample Return Capsule Reentry: Deployment, Signal Characteristics, and Wavefield Phenomenology
Controlled spacecraft reentries from interplanetary trajectories provide rare, well-characterized hypersonic sources for advancing seismoacoustic observation techniques. Here we present seismic observations of the OSIRIS-REx sample return capsule (SRC) reentry on 24 September 2023, recorded by 16 three-component nodal seismometers deployed near Eureka, Nevada, at ground distances of 7–20 km from the capsule trajectory. Air-to-ground coupled signals are detected at all stations, exhibiting impulsive onsets consistent with ballistic shock arrivals from the descending Mach cone. We characterize the seismic wavefield through signal amplitude, period, waveform cross-correlation, and array processing. Signal periods decrease systematically with increasing distance from the trajectory within the airport array, indicating that higher-frequency content becomes more prominent at greater offsets, opposite to expectations from geometric spreading and atmospheric absorption. Seismic array processing identifies frequency-dependent back-azimuth variations whose origin remains unresolved; possible contributing factors include source geometry, scattering by fine-scale layered structure in the stratosphere, and near-surface effects. These observations document a spatially complex seismic wavefield from a well-characterized hypersonic line source and provide constraints for future modeling of atmospheric propagation and air-to-ground coupling.
OSIRIS-REx↗
Modeling Subsurface Performance of a Geothermal Reservoir Using Machine Learning
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells—increasing or decreasing the fluid flow rates across the wells—and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy, and second, to find optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an “open-source” reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 h, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 s. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.
15 GEOTHERMAL ENERGY↗
Seismic Characterization of the Blue Mountain Geothermal Field
Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.
58 GEOSCIENCES↗
Long-Term Persistence of Three Microbial Wildfire Biomarkers in Forest Soils
Long-term monitoring of microbial communities in the rhizosphere of post-fire forests is currently one of the key knowledge gaps. Knowing the time scale of the effects is indispensable to aiding post-fire recovery in vulnerable woodlands, including holm oak forests, that are subjected to a Mediterranean climate, as is the case with forests that are found in protected areas such as the Sierra Nevada National and Natural Park in southeastern Spain. We took rhizosphere soil samples from burned and unburned holm oak trees approximately 3, 6, and 9 years after the 2005 fire that devastated almost 3500 ha in southeastern Spain. We observed that the prokaryotic communities are recovering but have not yet reached the conditions observed in the unburned forest. A common denominator between this fire and other fires is the long-term persistence of three ecosystem recovery biomarkers—specifically, higher proportions of the genera Arthrobacter, Blastococcus, and Massilia in soil microbial communities after a forest fire. These pyrophilous microbes possess remarkable resilience against adverse conditions, exhibiting traits such as xerotolerance, nitrogen mineralization, degradation of aromatic compounds, and copiotrophy in favorable conditions. Furthermore, these biomarkers thrive in alkaline environments, which persist over the long term following forest fires. The relative abundance of these biomarkers showed a decreasing trend over time, but they were still far from the values of the control condition. In conclusion, a decade does not seem to be enough for the complete recovery of the prokaryotic communities in this Mediterranean ecosystem.
54 ENVIRONMENTAL SCIENCES↗
Multiscale Interactions between Local Short- and Long-Term Spatio-Temporal Mechanisms and Their Impact on California Wildfire Dynamics
California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes; the interplay between fire weather index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks; and geographical variations in the relationship between the FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. The findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r > 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).
54 ENVIRONMENTAL SCIENCES↗