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DOE OSTI2025

Rapid characterization and failure analysis of 6276 rooftop-harvested photovoltaic connectors

Photovoltaic (PV) connectors, which link modules in series and connect PV strings in parallel, have increasingly been recognized as a primary contributor to PV system failures and a source of numerous fire incidents. However, publicly available data on the rates and types of connector failures are scarce, primarily due to the proprietary nature of the information and the need for comprehensive analysis. This study represents the first large-scale investigation of harvested PV connectors, drawing from a dataset of 6276 connectors from residential rooftop solar systems across the United States. The outcome of this work is twofold: 1) we have established a rapid characterization method for large populations of harvested connectors, incorporating visual inspection, resistance measurements, and X-ray imaging; and 2) the analysis made possible by our rapid-processing method has revealed, for a population of connector models provided by a single rooftop installer, failure statistics and insights for various connector makes and models, installation practices, operating currents, and internal component displacements. This research identifies common failure modes that could be considered in future connector designs standards, and operations and maintenance practices, to ultimately improve the reliability of this vital component of PV infrastructure.

MC4↗

DOE OSTI2025

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. Furthermore, we discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Basis sets↗

DOE OSTI2022

EdgeAI: Machine learning via direct attached accelerator for streaming data processing at high shot rate x-ray free-electron lasers

We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific user facilities such as the Linac Coherent Light Source-II x-ray Free-Electron Laser. We discuss how a low-latency inference model operating at the data acquisition edge can capitalize on the naturally stochastic nature of such sources. We simulate the method of attosecond angular streaking to produce representative results whereby simulated input data reproduce high-resolution ground truth probability distributions. By minimizing the mean-squared error between the decoded output of the latent representation and the ground truth distributions, we ensure that the encoding layers and resulting latent representation maintains full fidelity for any downstream task, be it classification or regression. We present throughput results for data-parallel inference of various batch sizes, some with throughput exceeding 100 k images per second. We also show in situ training below 10 s per epoch for the full encoder–decoder model as would be relevant for streaming and adaptive real-time data production at our nation’s scientific light sources.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗

DOE OSTI2020

Development and Characterization of 3D-Printed Cementitious Sytems for Innovative Nuclear Systems

The Transformational Challenge Reactor (TCR) is being developed to demonstrate a revolutionary approach to deploying new nuclear power systems by building and operating an additively manufactured microreactor. This initiative provides a unique opportunity to investigate the possibility of taking advantage of the recent development of the 3D-printed concrete system using the Sky Big Area Additive Manufacturing (SkyBAAM) printer at the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory. Two pathways have been pursued in parallel since the end of the second quarter of FY19: 1. Development of methods to characterize the performance of additive manufacturing concrete using traditional Portland-cement based solution, and 2. Investigation of the opportunity to develop innovation of printable materials with higher irradiation-resistance performance using nontraditional concrete solutions in favor of carbonated cementitious materials (CCMs). This report describes the results achieved to date for both pathways. The main results are listed below: 1. A test protocol has been established to characterize the fracture properties of 3D-printed concrete; this protocol will be used to assess the performance of printed traditional and nontraditional cementitious materials, with a focus on performance of the interfaces inherent to the additive manufacturing process. 2. A state-of-the-art review of the mechanisms, fabrication method, and performance of CCMs was conducted. CCMs appear to be a viable, highly innovative, more performant alternative to Portland-based cementitious solution for the erection of biological shield pending some materials development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Fuel Fabrication Capability Assessment in Support of Advanced Reactor Deployments

More than 30 U.S. companies are designing a variety of advanced reactor concepts, and several companies are planning to demonstrate their reactor designs in the mid-2020s to late 2030s time frame. In 2020, the U.S. Department of Energy (DOE) announced a series of awards under the Advanced Reactor Demonstration Program (ARDP) to accelerate the successful deployment of 10 of these reactors under three pathways. TerraPower and X-energy were awarded grants under the Advanced Reactor Demonstration Program to deploy their respective Natrium reactor and Xe-100 reactor designs in the next 7–10 years. These demonstrations are in addition to several parallel programs, including the U.S. Department of Defense’s (DoD’s) interest in the development of microreactors, and interest of the National Aeronautics and Space Administration in space nuclear power and propulsion. The National Reactor Innovation Center’s (NRIC’s) mission is to accelerate the demonstration and deployment of advanced reactors; NRIC is partnering with several reactor developers and harnessing the world-class capabilities of the U.S. National Laboratory system to deliver on its mission. Several of these reactor designs will require advanced fuel forms that are not commercially available today, including metal fuel, molten salt fuel, TRi-structural ISOtropic (TRISO) particle fuel, and uranium nitride fuel. Recognizing that there may be potential gaps in the laboratory-scale process development and pilot-scale first-of-a-kind (FOAK) production of these fuel forms leading to delivery of the FOAK cores, NRIC commissioned this study to look at the challenges that need to be overcome for successful deliveries, including the evaluation of existing facilities and the potential need for a new fuel fabrication facility.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Numerical and experimental analysis of mechanically induced failure in electric vehicle battery modules

Mitigating thermal runaway and cell-to-cell propagation is essential for improving the safety of electric and hybrid vehicles. Enhancing digital twin capabilities to predict battery mechanical abuse is particularly critical for automotive and aerospace applications, where crashworthiness is a key concern. Understanding failure conditions and propagation in battery modules during mechanical abuse is complex due to interactions between structural deformation, heat transfer, electrochemical processes, exothermic reactions and mechanical fracture. While prior studies have focused on modeling cell-level behavior, extending these models to module or pack level is necessary for a system level understating of electric vehicle safety. This study develops coupled large deformation finite element models that simultaneously solve for electrochemistry, material failure, internal short circuit and thermal runaway propagation. The models account for mechanical and thermal interactions between lithium-ion cells and other battery components while the contact interfaces are evolving with time. Model-predicted voltage, temperature and force responses are compared with experimental data for validation. The results demonstrate that the approach captures key failure mechanisms, including thermal propagation through heat transfer, electrical propagation from short circuits in parallel-connected cells, and mechanical propagation via penetration and crack formation. These findings show that computational models are valuable tools for understanding battery module failure and providing insight that can reduce the need for extensive experimental testing.

25 ENERGY STORAGE↗

DOE OSTI2022

Fe Oxidation and Species Distribution at the Rock–Fluid Interface of Marcellus Shale Reacted with Hydraulic Fracturing Fluid

Hydraulic fracturing of shale reservoirs resulted in significant opportunity for increased oil and gas production in the United States. Rock-fluid interactions can cause mineral dissolution and precipitation reactions that lead to permeability changes in the shale matrix, which ultimately may affect transport pathways and hydrocarbon production. Understanding the distribution of secondary precipitates, such as barite and Fe(III) (hydro)oxides, and cation leaching at the rock-fluid interface is an important step to further investigate how these geochemical processes can change permeability and transport pathways. In this study, thin sections of the fracture-matrix interface were made from reacted Marcellus shale cores. The thin sections were characterized using synchrotron X-ray fluorescence imaging and synchrotron X-ray absorption spectroscopy. Fe species with different oxidation states were identified in the maps, together with barite and Ca distribution. The results show that ferrihydrite, as newly formed Fe(III)-bearing precipitates, aligned well with the border of the Ca (e.g., calcite) leaching region in the reaction front. Some Fe-containing clay also dissolved, but the dissolution region for the clay was not as deep as the calcite. Further, the reaction front is about three times deeper in the direction parallel to the shale bedding than that perpendicular to the bedding. The Ca leaching region can be an index for reaction front detection for Marcellus shale. Reactive transport modeling was conducted and the predicted Ca leaching boarder align well with ferrihydrite precipitation, consistent with the experimental observation. The carbonate mineral dissolution can be crucial to promote fluid access into the shale matrix. Together with our previous study on the shale reactive surface, this follow-up study showed similar Ca leaching region and Fe(III) precipitates distribution in the reaction front regardless of barite precipitation on the surface, indicating that the barite coatings on the surface may not pose a significant impact on reactive transport at the shale-fluid interface.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2021

GPU acceleration of rank-reduced coupled-cluster singles and doubles

Here, we have developed a graphical processing unit (GPU) accelerated implementation of our recently introduced rank-reduced coupled-cluster singles and doubles (RR-CCSD) method. RR-CCSD introduces a low-rank approximation of the doubles amplitudes. This is combined with a low-rank approximation of the electron repulsion integrals via Cholesky decomposition. The result of these two low-rank approximations is the replacement of the usual fourth-order CCSD tensors with products of second- and third-order tensors. In our implementation, only a single fourth-order tensor must be constructed as an intermediate during the solution of the amplitude equations. Owing in large part to the compression of the doubles amplitudes, the GPU-accelerated implementation shows excellent parallel efficiency (95% on eight GPUs). Our implementation can solve the RR-CCSD equations for up to 400 electrons and 1550 basis functions—roughly 50% larger than the largest canonical CCSD computations that have been performed on any hardware. In addition to increased scalability, the RR-CCSD computations are faster than the corresponding CCSD computations for all but the smallest molecules. We test the accuracy of RR-CCSD for a variety of chemical systems including up to 1000 basis functions and determine that accuracy to better than 0.1% error in the correlation energy can be achieved with roughly 95% compression of the ov space for the largest systems considered. We also demonstrate that conformational energies can be predicted to be within 0.1 kcal mol -1 with efficient compression applied to the wavefunction. Finally, we find that low-rank approximations of the CCSD doubles amplitudes used in the similarity transformation of the Hamiltonian prior to a conventional equation-of-motion CCSD computation will not introduce significant errors (on the order of a few hundredths of an electronvolt) into the resulting excitation energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

OpenPATH and Itinerum Integration: A Case Study of Merging Open-Source Projects: Preprint

Throughout the transportation sector, multiple mobility tracking platforms have been developed independently, in parallel, with similar use cases and infrastructure. Maintaining such platforms on an individual level can result in duplicated effort. Innovation within the field could be slowed by the limited resource of people working on extremely similar projects. We provide a case study in how such platforms can be combined with low effort and provide an example in the mobility domain of what the resulting integration points, modules and ownership may look like. OpenPATH (formerly e-mission) and Itinerum are two examples of similar independently developed human mobility tracking platforms that extend beyond standard traffic data collection. Due to the open source nature of the projects, members from both teams decided to merge the functionality, thereby only hosting a single data collection process and limiting maintenance of separate intake platforms. On the front-end, specific questionnaire functionality from Itinerum, mainly the ability to display and return questions and results focused on sociodemographic attributes, was integrated into the OpenPATH user interface. On the back-end, an export pipeline stage was created to transport collected data back to the Itinerum database. Upon completion, the OpenPATH application retained its original functionality while adding the ability to export data for future data sharing and creating an avenue to incorporate Itinerum hosted questions and answers. Itinerum benefits from the rich feature set and infrastructure of OpenPATH without losing needed elements such as the questionnaire component. This case study, within the transportation sector, illustrates the various configurations in which open source software can be developed, maintained and deployed.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Computational Modeling of Graphite Degradation due to Molten Salt Infiltration and Wear

Molten-salt reactors (MSRs) represent a promising next-generation reactor design, with graphite serving as a moderator and/or reflector in several designs. However, due to limited experimental data and operational experience, a technical understanding of the structural integrity of graphite in molten salt environments remains incomplete. This report presents a modeling-based evaluation of graphite degradation in MSR environments, focusing on the effects of salt infiltration in fuel salt-based designs and surface wear in pebble bed reactor designs. The objective of this study is to enhance understanding of the structural integrity challenges posed by these degradation mechanisms and to provide a framework for assessing graphite behavior in MSRs. The first part of the report investigates the phenomenon of molten salt infiltration into graphite. This infiltration occurs when molten salt permeates the interconnected pore structure of the graphite moderator, driven by factors such as pressure differentials and the physical properties of both the salt and graphite. The infiltration process is influenced by characteristics of the pore structure, viscosity of the molten salt, and the interfacial energies between the graphite, salt, and the atmosphere within the graphite pore. Utilizing a coupled multiphysics modeling approach with Grizzly software, the study evaluates the stress induced by internal heat sources due to infiltration, which can lead to structural concerns. This evaluation is crucial for understanding how infiltration affects the mechanical integrity of graphite components in MSRs. The study considers the Molten-Salt Reactor Experiment (MSRE) graphite stringer geometry due to the availability of relevant data. Through detailed finite element analysis, the study examines stress distributions at varying infiltration percentages, revealing that stress levels increase with higher amounts of infiltration. Rare-event simulations, using the parallel subset simulation (PSS) framework, further quantify the failure probabilities under input uncertainties, with a user-specified failure metric. The PSS framework also identifies critical input parameters that significantly affect the stress values, including infiltration amount, thermal conductivity, and power density. Additionally, considering realistic reactor scenarios, the analysis was performed to account for the combined effects of radiation and infiltration, and modeling strategies on how to analyze new reactor designs or new graphite grades are discussed. The second part of the report focuses on wear mechanisms in pebble bed-based MSRs. As graphite fuel pebbles interact with the graphite reflector block, wear can result in material loss and the formation of surface defects, which may act as stress concentrators. A similar multiphysics modeling framework is employed to assess the impact of wear on the structural integrity of graphite components. This study considers a generic fluoride-cooled high-temperature reactor (gFHR) design due to the availability of comprehensive data. Worst-case scenario dimensions of the reflector blocks were analyzed under thermal and radiation conditions. Subsequently, wear in the form of idealized pits and grooves is modeled on the inner surface of the graphite block, with the maximum stress from previous simulations. The simulations show that groove-type defects are more detrimental than pits, leading to higher stress concentrations. Considering worst-case simulation scenarios and experimental wear rates, it was determined that the formation of a surface defect critical enough to affect the stress may not be possible in a gFHR design. Overall, the findings of this research contribute to the development of robust modeling tools for predicting graphite behavior under various operational conditions in MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Multiphase Modeling in a Parallel Plate Fluidized Bed Receiver for Concentrating Solar Power

A novel high temperature particle solar receiver is developed by using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a packed bed at the lower end, leaving the system from the bottom at a constant flow rate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built and a near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2K.

CSP↗

DOE OSTI2022

13 C-metabolic flux analysis of Clostridium ljungdahlii illuminates its core metabolism under mixotrophic culture conditions

Carbon dioxide-fixing acetogenic bacteria (acetogens) utilizing the Wood-Ljungdahl Pathway (WLP) play an important role in CO 2 fixation in the biosphere and in the development of biological processes – alone or in cocultures, under both autotrophic and mixotrophic conditions – for production of chemicals and fuels. To date, limited work has been reported in experimentally validating and quantifying reaction fluxes of their core metabolic pathways. Here, the core metabolic model of the acetogen Clostridium ljungdahlii was interrogated using 13 C-metabolic flux analysis ( 13 C-MFA), which required the development of a new defined culture medium. Autotrophic, heterotrophic, and mixotrophic growth in defined medium was possible by adding 1 mM methionine to replace yeast extract. Our 13 C-MFA found an incomplete TCA cycle and inactive core pathways/reactions, notably those of the oxidative pentose phosphate pathway, Entner-Doudoroff pathway, and malate dehydrogenase. 13 C-MFA during mixotrophic growth using the parallel tracers [1– 13 C]fructose, [1,2– 13 C]fructose, [1,2,3– 13 C]fructose, and [U– 13 C]asparagine found that externally supplied CO 2 contributed the majority of carbon consumed. All internally-produced CO 2 from the catabolism of asparagine and fructose was consumed by the WLP. While glycolysis of fructose was active, it was not a major contributor to overall production of ATP, NADH, and acetyl-CoA. Gluconeogenic reactions were active despite the availability of organic carbon. Asparagine was catabolized equally via conversion to threonine and subsequent cleavage to produce acetaldehyde and glycine, and via deamination to fumarate and then the anaplerotic conversion of malate to pyruvate. Both pathways for asparagine catabolism produced acetyl-CoA, either directly via pyruvate or indirectly via the WLP. Cofactor stoichiometry based on our data predicted an essentially zero flux through the ferredoxin-dependent transhydrogenase (Nfn) reaction. Instead, nearly all of NADPH generated from the hydrogenase reaction was consumed by the WLP. Reduced ferredoxin produced by the hydrogenase reaction and glycolysis was mostly used for ATP generation via the RNF/ATPase system, with the remainder consumed by the WLP. NADH produced by RNF/ATPase was entirely consumed via the WLP.

13C metabolic flux analysis↗

DOE OSTI2025

Modification of Ni-20Cr corrosion dealloying behavior in molten fluorides via cold work induced plastic deformation

The corrosion dealloying behavior of cold-worked (CW) Ni20Cr alloy (wt%) was studied in molten LiF-NaF-KF (or FLiNaK) salts at 600 °C, equal to a homologous temperature (TH) of 0.52. Alloys were cold-rolled to achieve reductions of thickness of 10%, 30%, and 50% introducing plastic deformation and a high density of dislocations. Potentiostatic holds (Eapplied) were applied in two different electrode potential regimes. At 1.75VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, Cr dealloying to Cr(II) and Cr(III) is predominant, while at 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, both Ni and Cr are oxidized in molten FLiNaK at 600 °C. In these potential regimes, dealloyed Ni20Cr displayed bicontinuous porosity within the grain interior and at grain boundaries, driven by the high driving force for Cr dissolution and sustained by defect mediated outward solid state diffusion of Cr in parallel with surface diffusion of Ni. The bicontinuous porous structure developed was observed to undergo further coarsening and densification of the Ni-rich ligaments at a higher electrode potential. The main effect of CW observed is the introduction of plastic deformation and dislocation substructures that serve as short-circuit paths for Cr solid state diffusion to surfaces exposed to FLiNaK. This modified the evolution of the bicontinuous porous structure which increased with CW substantially. Kinetic analysis reveals that the Cr dealloying at +1.75 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$ and 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$ is initially charge transfer controlled, except for the 50% CW condition at 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, where the process becomes limited by slow Cr defect mediated bulk diffusion. The rate determining factors are explored and compared to experimental results.

Chan, Ho Lun↗

DOE OSTI2023

Scaling Automatic Vector Data Alignment to Satellite Imagery

Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly processing large-scale EO data using high performance computing resources. Accurate mapping of the built environment from remote sensing (RS) imagery has been one of the crucial components in GeoAI workflows for a wide spectrum of humanitarian applications. Derived vector data of built environment is often leveraged for disaster preparedness and response activities. However, factors such as differences in ortho-rectification, atmospheric conditions and human error, results in spatial misalignment between vector data and the timely available RS imagery. Model training for downstream tasks such as object detection, change analysis, etc., is negatively impacted due to such spatial misalignment. Although there has been progress towards automatic alignment of vector data, the lack of scalability remains an open research challenge. This paper proposes to leverage parallel computing to optimize an automatic vector data alignment workflow. It further employs CPU-level multi-core parallelism for improving the performance of the workflow for scalable built environment mapping. We report observations and discuss findings from the preliminary experiments performed on the Summit Supercomputer.

Potnis, Abhishek↗

DOE OSTI2023

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗

DOE OSTI2020

Vadose Zone Model for B-63 Area for Composite Analysis

The objectives of the vadose modeling for the updated Hanford Site composite analysis (CA) are to simulate the flow and transport of water and radionuclide releases from the surface to the water table and to provide radionuclide transfer rates for the plateau to river (P2R) model, version 8.3 (CP-57037, Model Package Report: Plateau to River Groundwater Model, Version 8.3). Water additions include natural recharge and water discharged to the ground as a result of industrial processes associated with Hanford Site operations. Contaminant sources include radionuclides in water discharged to the ground during operations and radionuclides disposed “dry” in solid waste burial grounds or other means. The following 16 radionuclides were selected for this modeling effort; carbon-14 (C-14), chlorine-36 (Cl-36), tritium (H-3), iodine-129 (I-129), neptunium-237 (Np-237), rhenium-187 (Re-187), strontium-90 (Sr-90), technetium-99 (Tc-99), uranium-232 (U-232), uranium-233 (U-233), uranium-234 (U-234), uranium-235 (U-235), uranium-236 (U-236), uranium-238 (U-238), radium-226 (Ra-226), and thorium-230 (Th-230). The simulation time starts in 1943 and ends at 12070, which is 10,000 years after assumed Hanford Site closure in 2070. The parallel version of the Subsurface Transport Over Multiple Phases (STOMP1) simulator, officially named the exascale Subsurface Transport Over Multiple Phases (eSTOMP), is used to simulate flow and transport for the vadose models. The documentation for the STOMP code is comprehensive. The theoretical and numerical approaches applied in the STOMP code are documented in a published theory guide (PNNL-12030, STOMP Subsurface Transport Over Multiple Phases Version 2.0 Theory Guide). The code has undergone a rigorous verification procedure against analytical solutions, laboratory-scale experiments, and field-scale demonstrations. The application guide (PNNL-11216, STOMP Subsurface Transport Over Multiple Phases Application Guide) provides instructive examples in the application of the code to classical groundwater problems. The user’s guide (PNNL-15782, STOMP: Subsurface Transport Over Multiple Phases Version 4.0: User’s Guide) describes the general use, input file formatting, compilation, and execution of the code. The primary output of the vadose zone modeling is radionuclide transfer rates to the groundwater for input into the P2R model. The rates will be summed over the 100 by 100 m P2R grid cells that fall within the vadose zone model source domain.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Vadose Zone Model for REDOX Area for Composite Analysis

The objectives of the vadose modeling for the updated Hanford Site composite analysis (CA) are to simulate the flow and transport of water and radionuclide releases from the surface to the water table and to provide radionuclide transfer rates for the plateau to river (P2R) model, version 8.3 (CP-57037, Model Package Report: Plateau to River Groundwater Model, Version 8.3). Water additions include natural recharge and water discharged to the ground as a result of industrial processes associated with Hanford Site operations. Contaminant sources include radionuclides in water discharged to the ground during operations and radionuclides disposed “dry” in solid waste burial grounds or other means. The following 16 radionuclides were selected for this modeling effort: carbon-14 (C-14), chlorine-36 (Cl-36), tritium (H-3), iodine-129 (I-129), neptunium-237 (Np-237), rhenium-187 (Re-187), strontium-90 (Sr-90), technetium-99 (Tc-99), uranium-232 (U-232), uranium-233 (U-233), uranium-234 (U-234), uranium-235 (U-235), uranium-236 (U-236), uranium-238 (U-238), radium-226 (Ra-226), and thorium-230 (Th-230). The simulation time starts in 1943 and ends at 12070, which is 10,000 years after assumed Hanford Site closure in 2070. The parallel version of the Subsurface Transport Over Multiple Phases (STOMP1) simulator, officially named the exascale Subsurface Transport Over Multiple Phases (eSTOMP), is used to simulate flow and transport for the vadose models. The documentation for the STOMP code is comprehensive. The theoretical and numerical approaches applied in the STOMP code are documented in a published theory guide (PNNL-12030, STOMP Subsurface Transport Over Multiple Phases Version 2.0 Theory Guide). The code has undergone a rigorous verification procedure against analytical solutions, laboratory-scale experiments, and field-scale demonstrations. The application guide (PNNL-11216, STOMP Subsurface Transport Over Multiple Phases Application Guide) provides instructive examples in the application of the code to classical groundwater problems. The user’s guide (PNNL-15782, STOMP: Subsurface Transport Over Multiple Phases Version 4.0: User’s Guide) describes the general use, input file formatting, compilation, and execution of the code. The primary output of the vadose zone modeling is radionuclide transfer rates to the groundwater for input into the P2R model. The rates will be summed over the 100 by 100 m P2R grid cells that fall within the vadose zone model source domain.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗