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At least 73 records · Page 4

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗

Direct numerical simulation of a turbulent methane/air flame impinged by a sub-breakdown electric field

Here, the effects of an external electric field on a turbulent methane/air diffusion flame are analyzed in this work using direct numerical simulations. The analyzed configuration consists of a temporally evolving mixing layer of air and a mixture of methane and nitrogen at 1 atm that is impinged by an electric field in the direction normal to the mean mixing plane. The combustion and chemi-ionization reactions involved in the flow are modeled using finite-rate chemistry and a reduced reaction scheme consisting of 26 species and 134 reactions. The mass diffusion and ion-wind effects are modeled using a detailed description of the diffusion coefficients and electric mobilities based on kinetic theory. The presented calculations show that the turbulence generated within the mixing layer is mostly unaffected by the applied electric field for the configuration under exam. In fact, the electric body force is developed away from the mixing region where the flow is uniform. Conversely, the turbulence is able to introduce very high intermittency in the electrically charged species concentration and, consequently, in the electric body force. Such intermittency will constitute a challenge in the future formulation of combustion models that take into account ion-wind effects.

09 BIOMASS FUELS↗

A comparative analysis of numerical approaches for the description of gas flow in clay-based repository systems: From a laboratory to a large-scale gas injection test

There is nowadays a consensus among many countries that geological disposal is a favourable solution for the long-term management. Although different host formations and different barrier systems are under consideration around the world, clay-based materials form an important component for waste isolation in most national programmes. Hence, a good comprehension of the effect of gas flow on the hydro-mechanical behaviour of clay-based soils is essential, both at laboratory and field scale. Task B under the international cooperative project DECOVALEX-2023 has recently shown that, after some enhancement, models can be employed to reproduce laboratory scale tests, even with different sample geometries 37 . However, further work is required to understand whether they can be applied to simulate a large-scale experiment. Up-scaling of models for the advective transport of gas through clay-based low permeable material presents a number of problems related to the difficulty in obtaining consistent hydrogeological parameters and constitutive relationships at both laboratory and field scale. Based on a unique dataset from a large-scale gas injection test (Lasgit) performed at the Äspö Hard Rock Laboratory (Sweden), Task B within DECOVALEX-2023 has explored the refinement of these numerical strategies applied to the simulation of gas flow. Work performed within the task reveals that codes do not need to be substantially modified from the laboratory models to reproduce full-scale tests: indeed, model parameters calibrated and validated at laboratory scale have been applied to predict field scale gas flow at Lasgit, including peak gas pressure and injected cumulative gas volume. By means of (1) the introduction of interfaces between blocks to reflect the experimental configuration and the (2) adjustment of some parameters (e.g., higher permeability), the updated models are able to represent most of the key features observed in the experimental data, even at a large scale.

Tamayo-Mas, E↗

Constitutive behavior and processing maps of a new wrought magnesium alloy ZE20 (Mg-2Zn-0.2Ce)

ZE20 (Mg-2Zn-0.2Ce) 2 is a new wrought magnesium alloy with improved extrudability and mechanical properties [1]. To understand the constitutive behavior and workability of this new alloy, Gleeble thermomechanical testing has been carried out in this study. The flow stress behavior of ZE20 was investigated between 250 °C–450 °C and 10 –3 s –1 –1.0 s –1 in isothermal compression. Constitutive descriptions of the flow stress are provided. A new general approach at application of the extended Ludwik equation is demonstrated and was found to be more accurate than the hyperbolic sine Arrhenius model while having a similar number of model constants. Processing maps were developed based on the experimental results and are verified with microstructural investigation. A region of safe processing with non-basal texture and high activity of dynamic recrystallization (DRX) was found between 375 °C and 450 °C, from 10 –1 s –1 to 10–2.5 s –1 . A region of potentially safe processing with annealing that is associated with shear band nucleation of non-basal grains was identified for temperatures as low as 300 °C and rates as high as 10 –1 s –1 .

36 MATERIALS SCIENCE↗

Immersion Freezing in Particle-Based Aerosol-Cloud Microphysics: A Probabilistic Perspective on Singular and Time-Dependent Models

Cloud droplets containing immersed ice-nucleating particles (INPs) may freeze at temperatures above the homogeneous freezing threshold temperature in a process referred to as immersion freezing. In modeling studies, immersion freezing is often described using either so-called “singular” or “time-dependent” parameterizations. Here, we compare both approaches and discuss them in the context of probabilistic particle-based (super-droplet) cloud microphysics modeling. First, using a box model, we contrast how both parameterizations respond to idealized ambient cooling rate profiles and quantify the impact of the polydispersity of the immersed surface spectrum on the frozen fraction evolution. Presented simulations highlight that the singular approach, constituting a time-integrated form of a more general time-dependent approach, is only accurate under a limited range of ambient cooling rates. The time-dependent approach is free from this limitation. Second, using a prescribed-flow two-dimensional cloud model, we illustrate the macroscopic differences in the evolution in time of ice particle concentrations in simulations with flow regimes relevant to ambient cloud conditions. The flow-coupled aerosol-budget-resolving simulations highlight the benefits and challenges of modeling cloud condensation nuclei activation and immersion freezing on insoluble ice nuclei with super-particle methods. The challenges stem, on the one hand, from heterogeneous ice nucleation being contingent on the presence of relatively sparse immersed INPs, and on the other hand, from the need to represent a vast population of particles with relatively few so-called super particles (each representing a multiplicity of real particles). We discuss the critical role of the sampling strategy for particle attributes, including the INP size, the freezing temperature (for singular scheme) and the multiplicity.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning Aided Modeling of Granular Materials: A Review

Artificial intelligence (AI) has become a buzzy word since Google’s AlphaGo beat a world champion in 2017. In the past five years, machine learning as a subset of the broader category of AI has obtained considerable attention in the research community of granular materials. This work offers a detailed review of the recent advances in machine learning-aided studies of granular materials from the particle-particle interaction at the grain level to the macroscopic simulations of granular flow. This work will start with the application of machine learning in the microscopic particle-particle interaction and associated contact models. Then, different neural networks for learning the constitutive behaviour of granular materials will be reviewed and compared. Finally, the macroscopic simulations of practical engineering or boundary value problems based on the combination of neural networks and numerical methods are discussed. We hope readers will have a clear idea of the development of machine learning-aided modelling of granular materials via this comprehensive review work.

42 ENGINEERING↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

An experimental, theoretical, and kinetic modeling study of post-flame oxidation of ammonia

The post -flame oxidation rate of ammonia was investigated in a novel atmospheric pressure flow reactor at temperatures of 1280 ± 16 K and as a function of residence time and mixture composition (1-10% O 2 , dry and moist). The experimental results, as well as selected data from literature, were analyzed using an updated detailed chemical kinetic model. The medium temperature, very lean conditions enhance the importance of reactions of the nitroxyl (HNO) intermediate. High-level theory was used to calculate the rate constant for HNO + NH 2 , indicating that this step is significantly faster than values used in literature. Furthermore, a trajectory based approach was used to determine collision efficiencies for selected bath gases for HNO + M. The experimental results show that the NH 3 oxidation rate increases with temperature and O 2 concentration, while the presence of water vapor slightly inhibits reaction. Formation of NO and N 2 O was strongly promoted at higher levels of O 2 . Modeling results agreed well with the measurements, except at the lowest level of O 2 . The predicted oxidation rate of NH 3 was shown to result from a delicate balance between chain branching and terminating steps involving NH 2 , H 2 NO, and HNO. Recent theoretical work on reactions of these species by Klippenstein and coworkers and Stagni et al. was instrumental in improving modeling predictions. After initiation, NO reached a pseudo -steady-state level, where the pathways to NO were largely balanced by the NH 2 + NO reaction. Nitric oxide was partly oxidized to NO 2 , with the NH 2 + NO 2 reaction responsible for most of the N 2 O formation. Novelty and significance statement: This study provides the first detailed kinetic analysis of the lean postflame oxidation of ammonia, based on time -resolved flow reactor data in a novel reactor. In addition to the post -flame oxidation rate of ammonia, data for formation of NO and N 2 O were compared with modeling predictions. The medium temperature, very lean conditions enhance the importance of reactions of the HNO and H 2 NO intermediates. Inclusion in the model of results from recent high-level theoretical work, including present calculations for HNO + NH 2 and HNO + M, was crucial for capturing the observed behavior. It is argued that the post -initiation steady-state NH 3 oxidation rates constitute important data for model validation, along with ignition delays and laminar flame speeds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Time-Lapse Full-Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion (FWI), subsurface flow processes, and rock physics models. For the inverse modeling, we handle the back propagation of gradients by an intrusive automatic differentiation strategy that offers three levels of user control: (1) At the wave physics level, we adopted the discrete adjoint method in order to use our existing high-performance FWI code; (2) at the rock physics level, we used built-in automatic differentiation operators from the TensorFlow backend; (3) at the flow physics level, we implemented customized partial differential equation (PDE) operators for the multiphase flow equations. The three-level coupled inversion strategy strikes a good balance between computational efficiency and programming efforts, and when the gradients are chained together, it constitutes a coupled inverse system. Our numerical experiments demonstrate that the three-level coupled inverse problem is superior in terms of accuracy to a traditional decoupled inversion strategy. Additionally, our method is able to simultaneously invert for parameters in empirical relationships such as the rock physics models. Our proposed inverted model can be used for reservoir performance prediction and reservoir management/optimization purposes.

54 ENVIRONMENTAL SCIENCES↗

Augmented reduced order models for turbulence

The authors introduce an augmented-basis method (ABM) to stabilize reduced-order models (ROMs) of turbulent incompressible flows. The method begins with standard basis functions derived from proper orthogonal decomposition (POD) of snapshot sets taken from a full-order model. These are then augmented with divergence-free projections of a subset of the nonlinear interaction terms that constitute a significant fraction of the time-derivative of the solution. The augmenting bases, which are rich in localized high wavenumber content, are better able to dissipate turbulent kinetic energy than the standard POD bases. Several examples illustrate that the ABM significantly out-performs L 2 -, H 1 - and Leray-stabilized POD ROM approaches. The ABM yields accuracy that is comparable to constraint-based stabilization approaches yet is suitable for parametric model-order reduction in which one uses the ROM to evaluate quantities of interests at parameter values that differ from those used to generate the full-order model snapshots. Several numerical experiments point to the importance of localized high wavenumber content in the generation of stable, accurate, and efficient ROMs for turbulent flows.

Kaneko, Kento↗

1D Modeling for the Development of a Digital Twin for Hydropower Systems with Applications for a Testing Rig

Modeling and simulation constitute two important parts in constructing a sensible digital twin to mimic the dynamics of hydropower systems. Because of the physical nature of a hydropower system, the basic modeling should cover the water flow systems from the reservoir to the penstock (inlet water pipes), penstock to hydro turbine, and hydro turbine to generator and from the linkage of the hydropower systems to the grid. This report describes initial attempts to model these dynamic components, including the formulation of the linearized state space model for hydro turbine systems using the well-known six-coefficients linearization method and the formulation of the voltage and power dynamical models of a synchronous generator. To validate the accuracy of the proposed model, data collected from Norwegian University of Science and Technology were used to obtain relevant parameters for the model, and the desired simulation results were obtained. Additionally, neural network modeling and learning were also developed and applied to model the generation torque and water flow rate subsystems to demonstrate a potential learning scheme, which can be used in the development of a digital twin.

13 HYDRO ENERGY↗

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗

EBS Task Force: Task 9/FEBEX Modeling Final Report: Thermo-Hydrological Modeling with PFLOTRAN

This report outlines Sandia National Laboratories modeling studies applied to Stage 1 and Stage 2 of the Full-scale Engineered Barriers Experiment in Crystalline Host Rock (FEBEX) in situ test for the SKB EBS Task Force Task 9. The FEBEX test was a full-scale test conducted over ~18 years at the Grimsel, Switzerland Underground Research Laboratory (URL) managed by NAGRA. It involved emplacing simulated waste packages, in the form of welded cylindrical heaters, inside a tunnel in crystalline granitic rock and surrounded by a bentonite barrier and cement plug. Sensors emplaced within the bentonite monitored the wetting-up, heating, and drying out of the bentonite barrier, and the large resulting data set provides an excellent opportunity for validation of multiphysics Thermal-Hydrological (TH), Thermal-Hydrologic-Chemical (THC), and Thermal-Hydrological-Mechanical (THM) modeling approaches for underground nuclear waste storage and the performance of engineered bentonite barriers. The present status of the EBS Task Force is finalizing Task 9, which follows years of modeling studies of the FEBEX test, by many notable modeling teams (Gens et al., 2009; Sanchez et al. 2010; 2012; Samper et al., 2018). These modeling studies generally use two-dimensional axisymmetric meshes, ignoring threedimensional effects, gravity and asymmetric wetting and dry out of the bentonite engineered barrier. This study investigates these effects with use of the PFLOTRAN THC code with massively parallel computational methods in modeling FEBEX Stage 1 and Stage 2 results. The PFLOTRAN numerical code is an open source, state-of-the-art, massively parallel subsurface flow and reactive transport code operating in a high-performance computing environment (Hammond et al., 2014). Section 2 describes the applied partial differential equations describing mass, momentum and energy balance used in this study, considerations derived by assuming phase equilibrium between gas and liquid phases, constitutive equations for granite, cement plug, and bentonite domains, and specific approaches for use inthe PFLOTRAN code. Section 3 describes the geometry, meshing, and model set-up. Section 4 describes modeling results, Section 5 compares modeling results to field testing data, and Section 6 gives conclusions. The Appendix provides detailed information required by the EBSTask Force for final reporting.

42 ENGINEERING↗

High salt-induced PSI-supercomplex is associated with high CEF and attenuation of state transitions

Abstract While PSI-driven cyclic electron flow (CEF) and assembly of thylakoid supercomplexes have been described in model organisms like Chlamydomonas reinhardtii , open questions remain regarding their contributions to survival under long-term stress. The Antarctic halophyte, C. priscuii UWO241 (UWO241), possesses constitutive high CEF rates and a stable PSI-supercomplex as a consequence of adaptation to permanent low temperatures and high salinity. To understand whether CEF represents a broader acclimation strategy to short- and long-term stress, we compared high salt acclimation between the halotolerant UWO241, the salt-sensitive model, C. reinhardtii , and a moderately halotolerant Antarctic green alga, C. sp. ICE-MDV (ICE-MDV). CEF was activated under high salt and associated with increased non-photochemical quenching in all three Chlamydomonas species. Furthermore, high salt-acclimated cells of either strain formed a PSI-supercomplex, while state transition capacity was attenuated. How the CEF-associated PSI-supercomplex interferes with state transition response is not yet known. We present a model for interaction between PSI-supercomplex formation, state transitions, and the important role of CEF for survival during long-term exposure to high salt.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal plasticity modeling of strain-induced martensitic transformations to predict strain rate and temperature sensitive behavior of 304 L steels: Applications to tension, compression, torsion, and impact

This paper advances crystallographically-based Olson-Cohen (direct γ → α’) and deformation mechanism (indirect γ→ε→α’) phase transformation models for predicting strain-induced austenite to martensite transformation. Here, the advanced transformation models enable predictions of not only strain-path sensitive, but also of strain-rate and temperature sensitive deformation of polycrystalline stainless steels (SSs). The deformation of constituent grains in SSs is modeled as a combination of anisotropic elasticity, crystallographic slip, and phase transformation, while the hardening is based on the evolution of dislocation density and explicit shifts in phase fractions. Such grain-scale deformation is implemented within the meso-scale elasto-plastic self-consistent (EPSC) homogenization model, which is coupled with the implicit finite element (FE) method to provide a constitutive response at each FE integration point for solving boundary value problems at the macro-scale. Parameters pertaining to the hardening and transformation models within FEEPSC are calibrated and validated on a suite of data including flow curves and phase fractions for monotonic compression, tension, and torsion as a function of strain-rate and temperature for wrought and additively manufactured (AM) SS304L. To illustrate the potential and accuracy of the integrated multi-level FE-EPSC simulation framework, geometry, mechanical response, phase fractions, and texture evolution are simulated during gas-gun impact deformation of a cylinder and quasi-static tension of a notched specimen made of AM SS304L. Details of the simulation framework, comparison between experimental and simulation results, and insights from the results are presented and discussed.

304L steels↗

Unclassified Source Term and Radionuclide Data for the Groundwater Flow and Contaminant Transport Model for Corrective Action Units 101 and 102: Central and Western Pahute Mesa, Nye County, Nevada, Revision 1

This report documents the evaluation of information and data available on the unclassified source term and radionuclide (RN) contamination for Central and Western Pahute Mesa (PM): Corrective Action Units (CAUs) 101 and 102. The Central and Western PM CAUs constitute two areas of the Nevada National Security Site (NNSS) used for underground nuclear testing (Figure 1-1). Eighty-five underground nuclear tests were conducted at the PM CAUs between 1965 and 1992 (NNSA/NFO, 2015b). Underground nuclear tests deposit radioactive elements in the subsurface, resulting in groundwater contamination in the vicinity of the underground test locations. At the PM CAUs, the testing resulted in more than 2.68 × 10 7 curies (Ci) of radioactivity (decay-corrected to September 30, 2012) remaining underground (Finnegan et al., 2016). Of the 85 underground nuclear tests conducted at the PM CAUs, three were shallow tests detonated within 200 meters (m) of the surface and referred to as the “near-surface tests”; the remaining 82 were detonated deeper than 200 m below ground surface (bgs) and are referred to as the “deep underground tests” in this document.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗