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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗
DOE OSTI2021

History Matching and Performance Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope (ANS) is ongoing. After more than 2.5 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is economically attractive.

Wang, Xindan↗
DOE OSTI2023

Rapid Simulation of Unconventional Reservoirs by Multidomain Multiresolution Modeling Based on the Diffusive Time of Flight

Summary The fast marching method (FMM)-based rapid flow simulation has been shown to accelerate simulation efficiency by orders of magnitude by transforming 3D simulation to equivalent 1D simulation using the concept of the “diffusive time of flight” (DTOF). However, the 1D transformation does not directly apply to multiwell problems. In this paper, we propose a novel DTOF-based multidomain multiresolution discretization scheme to accelerate multiwell simulation of unconventional reservoirs. Our method formulates multiwell simulation problems based on the DTOF which displays the pressure front propagation in unconventional reservoirs. The DTOF contours are used to partition the reservoir into local and shared domains. A local domain is where the flow is dominated by a single well, and the shared domain is where the fluid flow is influenced by multiple wells. The DTOF contours expand independently in local domains and interfere in the shared domain. After the partitioning, each domain is discretized using a multiresolution scheme whereby the original 3D fine mesh is preserved near the wells to account for detailed physics including gravity, and the rest of the domain is discretized into 1D mesh based on the DTOF contours to alleviate the simulation workload. The power and efficacy of our approach are demonstrated using synthetic and field-scale simulation models with different degrees of geologic and well-completion complexity. The simulation results, number of active cells, and computation time for the proposed discretization scheme are compared with the original high-fidelity 3D model for each case. The results show that the proposed method is suitable for multiwell simulation problems in unconventional reservoirs and can accelerate flow simulations by orders of magnitude with minimal loss of accuracy. The novelty of this work is the creation of DTOF-derived multiresolution discretization with local and shared domains to simplify and accelerate the calculation of subsurface flow problems, especially in unconventional reservoirs. Our workflow can be easily interfaced with commercial simulators, making it suitable for large-scale field applications.

Engineering↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
DOE OSTI2020

Research three-dimensional hierarchical graphite architectures for anodes for fast charging

With current lithium ion batteries optimized for performance under relatively low charge rate conditions, implementation of XFC has been hindered by drawbacks including Li plating, kinetic polarization, and heat dissipation. This project will utilize model-informed design of 3-D hierarchical electrodes to tune key XFCrelated variables like 1) bulk porosity/tortuosity 2) vertical pore diameter, spacing, and lattice 3) crystallographic orientation of graphite particles relative to exposed surfaces 4) interfacial chemistry of the graphite surfaces through "artificial sEr' formation using ALD 5) current collector surface roughness (aspect ratio, roughness factor, etc.). A key aspect of implementing novel electrodes is characterizing them in relevant settings. For this project, ultimately led out of University of Michigan by Neil Dasgupta, that includes both coin cell and 2+ Ah pouch cell testing, as well as comparison testing against baselines. Sandia National Labs will be conducting detailed cell characterization on iterative versions/improvements of the model-based hierarchical electrodes, as well as COTS cells for baseline comparisons. Key metrics include performance under fast charge conditions, as well as the absence or degree of lithium plating. Sandia will use their unique high precision cycling and rapid EIS capabilities to accurately characterize performance and any lithium plating during 6C charging and beyond, coupling electrochemical observations with cell teardown. Sandia will also design custom fixturing to cool cells during rapid charge, to decouple any kinetic effects brought about by cell heating and allow comparisons between different cells and charge rates. Using these techniques, Sandia will assess HOH electrodes from the University of Michigan, as well as aiding in iterative model and electrode design.

25 ENERGY STORAGE↗
DOE OSTI2020

Innovations in Sensors and Controls for Building Energy Management: Research and Development Opportunities Report for Emerging Technologies

Sensors, actuators, and controllers, which collectively serve as the backbone of cyberphysical systems for building energy management, are one of the core technical areas of investment for achieving the U.S. Department of Energy (DOE) Building Technologies Office's (BTO's) goals for energy affordability in the national building stock - both commercial and residential. In fact, an aggregated annual energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms. energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Evaluation of the Dissolution Behavior of L-Bundle End Caps and HFIR Fuel Carriers

The H-Canyon facility is currently using the 6.1D dissolver for the dissolution of Material Test Reactor (MTR) fuel and the 6.4D dissolver for the dissolution of High Flux Isotope Reactor (HFIR) fuel using mercury-catalyzed HNO₃ dissolution flowsheets. The processing strategy for both dissolvers involves the dissolution of multiple charges of fuel per batch. After the designated heating cycle, the dissolvers are opened, and the charging wells are probed to determine if the MTR or HFIR fuel has dissolved. If undissolved fuel fragments are beyond a certain height, the dissolver must be closed and heated for an additional amount of time to dissolve the remaining material. In recent MTR fuel dissolutions, “high probes” (i.e., excessive undissolved material) were frequently observed, which resulted in extended dissolution times. The suspected cause of the high probes was the incomplete dissolution of the L-Bundle End Cap, rather than the fuel or fuel bundles. The End Cap is hypothesized to be binding in the insert well and not dropping into the acid as the L-Bundle and fuel dissolve. Once the End Cap is dislodged by the probe and drops into the acid, the dissolution rate of the End Cap appears to be significantly reduced compared to the dissolution rate of the fuel and other parts of the L-Bundle. A similar issue has also been observed with the lifting bail on the HFIR fuel carriers. During HFIR fuel dissolutions, the lifting bail on the outer carrier has resulted in high probes due to incomplete dissolution. In one case, a partially dissolved bail was caught in one of the insert well holes which prevented the probe from going to the bottom of the well.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Quantum Nature and Mass of the Neutrino. FY20 Annual Laboratory Continuation Progress Report

Over the last 100 years we have learned a much about the neutrino, but there remain interesting questions about this weakly interacting particle. In particular, at LLNL we are developing experiments to measure the mass and the quantum nature of the neutrino. The 2015 long range plan recommended tonne-scale neutrinoless double beta decay experiments as the top new project priority and this experiment will target the quantum nature of the neutrino. The LLNL team is motivated and focused on developing the best technology for this experiment which is a liquid xenon time project chamber called nEXO. On a longer time scale, LLNL is also developing technology to measure the neutrino mass with tritium decay experiments. Work on nEXO at LLNL started in 2015 with an LDRD and program development funds to develop the nEXO concept, publish sensitivity predictions, explore alternatives and risks, and to build a credible project team and this effort is on going. In addition, we received research funding from DOE-SC NP and LLNL manages pre-conceptual R&D for the nEXO collaboration a portion of which is executed at LLNL. The Project 8 effort is solely funded by LLNL LDRD, and ends this year. A second LDRD effort is focused on repurposing cyclotron radiation emission spectroscopy for eV-scale X-ray detection. This second effort, while separated from Project 8, still has scientific and technical commonalities with Project 8. The funding for this X-ray detection effort will continue for one more year. LLNL has a long history of building large projects, science projects and time projection chambers, but nEXO is in fact the first project of this scale that LLNL is prepared to lead for DOE-SC NP.We have the tools, skills, people and motivation to make nEXO a reality. The current program development dollars are used to prepare the nEXO concept for down select and CD1. These internal LLNL dollars pay for a number of things including project staff to organize the nEXO collaboration for the various reviews that lie ahead, to develop the draft plans and structure to manage the project as well as setting up an external advisory committee. The current LDRD is exploring alternatives that effect the risk profile as well as possible performance improvements. The DOE-SC NP base funding is targeted at simulation and analysis of the nEXO concept in preparation for the down select and refinement of the understanding of the detector as well as scientific effort on the large xenon test stand (LXTS) that will burn down one of the largest risks to the nEXO project. Lastly, LLNL is leading the pre-conceptual R&D effort and managing the funds for the nEXO collaboration. The results of this effort are reported elsewhere, but the scope of this executed at LLNL will be reported here and is primarily the engineering and construction of the LXTS experiment. The primary technical contribution of LLNL to the Project 8 concept is the formation and study of atomic tritium. Atomic tritium is necessary for Project 8 to reach the ultimate sensitivity. LLNL has considerable experience with tritium and is well suited for this crucial work. Although the focus of this work is strictly fundamental science, there has already been one significant spinoff to develop a new means to measure radio xenon in the air

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Horn Mountain Offshore Oil Field Case Study

This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Horn Mountain oil field NFB M Sand, in the field's North fault block, using three pairs of wells. Each pair of wells is a line drive pattern design (one CO 2 injector and one production well). Four 20-year injection scenarios were assessed, varying CO 2 injector well placements. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.

02 PETROLEUM↗
DOE OSTI2020

AWCC Simulations

Neutron well counters provide a means to measure fissile mass by detecting coincident neutrons, which is a unique signature to fission. For coincidence counting, mass is determined using a calibration curve established with items that have the same material characteristics. Multiplicity analysis solves the point model equations for mass using known detector parameters. In both cases, mass measurements may exhibit a bias due to item characteristics and should be corrected for. Experiments can be done to estimate bias and material effects, but they require having both the well counter and the material well defined. In pursuit of estimating measurement bias and uncertainty in a High Efficiency Neutron Counter (HENC), an MCNP simulation was matched to measurements performed with an Active Well Coincidence Counter (AWCC) to de ne a neutron source term. The neutron source term will be used to predict measurement performance of similar material types in a HENC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica

Numerical simulations of Greenland and Antarctic ice sheets involve the solution of large-scale highly nonlinear systems of equations on complex shallow geometries. This work is concerned with the construction of Schwarz preconditioners for the solution of the associated tangent problems, which are challenging for solvers mainly because of the strong anisotropy of the meshes and wildly changing boundary conditions that can lead to poorly constrained problems on large portions of the domain. Here, two-level GDSW (Generalized Dryja–Smith–Widlund) type Schwarz preconditioners are applied to different land ice problems, i.e., a velocity problem, a temperature problem, as well as the coupling of the former two problems. We employ the MPI-parallel implementation of multi-level Schwarz preconditioners provided by the package FROSch (Fast and Robust Schwarz)from the Trilinos library. The strength of the proposed preconditioner is that it yields out-of-the-box scalable and robust preconditioners for the single physics problems. To our knowledge, this is the first time two-level Schwarz preconditioners are applied to the ice sheet problem and a scalable preconditioner has been used for the coupled problem. The pre-conditioner for the coupled problem differs from previous monolithic GDSW preconditioners in the sense that decoupled extension operators are used to compute the values in the interior of the sub-domains. Several approaches for improving the performance, such as reuse strategies and shared memory OpenMP parallelization, are explored as well. In our numerical study we target both uniform meshes of varying resolution for the Antarctic ice sheet as well as non uniform meshes for the Greenland ice sheet are considered. We present several weak and strong scaling studies confirming the robustness of the approach and the parallel scalability of the FROSch implementation. Among the highlights of the numerical results are a weak scaling study for up to 32 K processor cores (8 K MPI-ranks and 4 OpenMP threads) and 566 M degrees of freedom for the velocity problem as well as a strong scaling study for up to 4 K processor cores (and MPI-ranks) and 68 M degrees of freedom for the coupled problem.

58 GEOSCIENCES↗
DOE OSTI2020

Technical Issues in the Comprehensive Nuclear Test Ban Treaty (CTBT) Ratification Debate: A 20 Year Retrospective

Two decades after the U.S. Senate declined in 1999 to give its consent to ratification of the Comprehensive Nuclear Test Ban Treaty (CTBT), the treaty remains in legal and political limbo. Legally, the treaty cannot enter into force without U.S. ratification. However, the Senate’s rejection does not strip the treaty of its force as an element of customary international law or alter the will of other signatories to see it enter into force. Politically, the debate over the virtues and flaws of the treaty remains as strong as ever, with some CTBT advocates pushing energetically for U.S. re-review while some opponents seek ways to “un-sign” the treaty. Meanwhile, despite the Senate’s rejection of the treaty, the United States acts in a manner consistent with its main obligations by maintaining a moratorium on explosive nuclear testing and providing financial support (as well as technical expertise) to the CTBT Organization (CTBTO)—in particular the CTBTO’s International Monitoring System (IMS). The CTBT may well remain in such limbo for a long time to come, unless some catalytic event comes along to re-shape national perceptions and priorities, one way or the other. The treaty’s future, whatever it might be, will be determined in part by how much perspectives might have changed in light of interim developments. Our purpose is to shed light on some of those developments and to assess their relevance. The 1999 ratification debate addressed a large number of issues. Rejection was driven by various policy and technical judgments. The purpose of this paper is to re-examine those technical judgments in light of what has been learned over the following two decades. On some technical matters, there was explicit recognition of extant uncertainties, as well as a conviction and hope that time would dispel them. To be doubly clear, our purpose is not to recommend a way forward on CTBT ratification. The policy judgments of 1999 and 2020 are beyond the scope of this paper. This technical re-examination proceeds as follows. It begins with a short background section to introduce the key technical matters in discussion in the U.S. ratification process. Then it moves systematically through each of those topics with a review of relevant background information, a discussion of key points in debate, an analysis of subsequent experience, and a current assessment. The historical analysis draws on many sources including the primary documents of the Congressional debate, the official article-by-article interpretation by the Department of State, and the statements of key players in the process. We also relied on key technical reports and publications by subject matter experts that have addressed in more detail many of the issues in our focus. These sources include the 2002 and 2012 reports of the National Academy of Sciences as well as publications by senior technical staff of Lawrence Livermore National Laboratory (LLNL) who were actively involved in the ratification debate, including then-Laboratory Director Bruce Tarter. We also conducted several interviews with government officials from the 1990s, past laboratory directors, and other members of the scientific community. But, except where individuals are specifically cited by name, the judgments offered here are our own and should not be attributed to any other individual or to LLNL as such.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Thermocatalytic Heat Pipes for Geothermal Resource Recovery

Heat pipes are an important technology that allow orders of magnitude faster heat transfer than simple conduction. However, operating principles in heat pipes place fundamental bounds on their performance (critical heat flux and efficiency). Conventional heat pipe functionality is inherently tied to vaporization and condensation of the working fluid charged in the heat pipe. These fluids each have different operating temperature ranges based on the capillary, entrainment, sonic, and boiling limits of the heat pipe design. These limits, typically the capillary limit, dictate the maximum heat flux a heat pipe can carry, and most importantly for geothermal systems, the distance over which the pipes can operate (100 to 200 m maximum under optimum conditions). A thermocatalytic heat pipe breaks the inherent limitations of phase change thermo- and hydrodynamics and can transform heat pipe technology as a potentially more efficient means of extracting heat from a geothermal resource. The thermocatalytic heat pipe uses a working fluid to transport both sensible and chemical heat. An endothermic chemical reaction at depth removes heat from the reservoir and produces reactive intermediates, which are transported to the surface and used to run a reverse exothermic reaction that releases heat for use in power generation or other useful purposes. This technology offers two distinct advantages over conventional geothermal heat recovery technologies: (1) lower heat loss to the rock outside of the geothermal reservoir, and (2) higher heat transfer rates to the well field within the geothermal reservoir. Both advantages offer opportunity to reduce risks and lower costs of geothermal energy recovery. In this report, we discuss an initial effort to assess the efficacy and limitations of this technology for extracting heat from both porous/permeable and nominally impermeable geothermal reservoirs. Numerical simulation capabilities of the STOMP-GT code were enhanced to enable simulations of thermochemical heat pipes traversing geothermal reservoirs. An array of potential thermochemical reaction systems was evaluated and screened. Of these, an ethanol dehydration reaction was most promising in the vapor-liquid reaction set. A solid-phase dehydration reaction (CuSO4·5H2O) showed the highest reaction enthalpy per unit volume but would require development of a nonaqueous carrier fluid to implement it in a heat pipe. Subsurface reservoir simulations predicted long-term performance of the heat pipes for each geothermal reservoir type. The performance of U-shaped wells and coaxial wells was evaluated for a suite of reactions for both hydrothermal and hot dry rock reservoirs and was compared with a baseline case of simply pumping water through the wells. The heat pipe technology was additionally evaluated for an enhanced geothermal system (EGS) with an injection borehole, production borehole, and intervening hydraulically conductive fracture. All reservoir types showed significant improvement in heat recovered over a 20-year operating period ranging from a 1.8X increase for the hot dry rock case to more than 2.5X more energy recovered for the EGS case.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

The Fundamental Creep Behavior Model of Gr.91 Alloy by ICME Approach (Final Report)

The current project mainly focused on the fundamental creep cracking mechanism of the Grade 91 system during the operation conditions in the advanced technologies FE power plants and build the link among Composition-Processing Parameters-Phase Stability-Microstructure-Creep Resistance. A model based on computational thermodynamics and diffusion kinetics will be developed to provide guidance on how to improve the creep resistance of the alloy system. The PI mainly investigate the Gr.91 base alloy and weldment with the Integrated Computational Materials Engineering (ICME) approach. The long-term goal of the proposed program is to develop a model for creep and fatigue resistant alloys with different elemental systems, compositions, and processing parameters of weldment and heat-treatment. In addition, new creep and fatigue resistant alloys are to be designed based on the predictions from the model. The computational as well as experimental results include three sections: 1) The compositional optimization and secondary phases evaluation regarding the creep resistance in Grade 91 steel through the CALPHAD approach. In this section, the formation of the critical secondary phases, M23C6, MX and Z-phase were well predicted based on many conditions like the temperature as well as compositions. Meanwhile, the role of different alloying elements was also considered as they will directly affect the formation of the secondary phases mentioned above based on the compositional evolution of the alloying elements. 2) An investigation of Creep Resistance in Grade 91 Steel through Computational Thermodynamics. We systematically considered the evolution of the four critical temperatures, Ac3, Ac1, the threshold of M23C6 and Z-phase, on basis of the computational approach. Meanwhile, the equilibrium cooling as well as Scheil simulations were also considered to perform further predictions based on the different cooling rates. 3) Creep lifetime and microstructural evolution of the Grade 91 steel. In this part, mainly experimental approach was performed on the real creep test from the beginning of the commercial Gr.91 alloys. The alloys were normalized, tempered, welded (Gleeble) and PWHT and finally subjected to the creep lifetime analyses. Finally, all the samples after each process were further characterized based on the OM, XRD and SEM technique to draw final conclusions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

New Laboratory and Astrophysical Probes of Physics Beyond the Standard Model (Final Technical Report)

The first of these directions centers on new ideas in dark matter detection. As experimental scrutiny narrows the window for new physics at the weak scale, it has become apparent that the solution to the dark matter mystery may not reside there. Theoretical developments such as the hidden sector/valley paradigm have, at the same time, shown that compelling theories of dark matter reside below the weak scale. Searching for dark matter at lower mass scales requires looking beyond the current paradigm of dark matter direct detection based on nuclear recoils. It is the goal of this project to provide new ideas to guide the experimental program looking for light dark matter. I am actively proposing ideas for detecting dark matter as light as a meV, well beyond the current focus of GeV-TeV scale dark matter. Some of the ideas I have proposed, such as superconducting, superfluid, and polar material targets, are actively being developed into experiments. My group will provide the relevant calculations to determine dark matter reach, providing crucial input to experiment on which targets should be developed. We will also provide an effective field theory framework to understand which types of experiments are most sensitive to each interaction type. The second of these directions is on probes of dark matter substructure as a mean to constrain, or observe, models of dark matter. The standard ΛCDM paradigm assumes that the dark matter density perturbations are adiabatic, scale invariant, and produced during inflation. However, many standard models of dark matter will produce modifications of this prediction, such as axion models with symmetry broken below the inflationary scale. Remarkably, we have limited direct measurements of the dark matter clumpiness at mass scales below dwarf galaxies. This allows for the possibility of observing modifications from vanilla ΛCDM due to particle dynamics. In many cases, simulations of dark matter structure in the presence of non-scale invariant fluctu- ations are understudied or completely lacking. I plan to develop both theoretical predictions for small scale structure in models with additional matter power on small scales, as well as observa- tional probes of small scale halos or clumps. One idea I have been recently focused on is pulsar timing, though my group will pursue a variety of lensing and astrometric probes. Lastly, the most risky direction involves spacetime fluctuations from quantum gravity. I showed that if one assumes that metric fluctuations in the Minkowski vacuum, at a surface separating a region in and out of causal contact (which we call a “horizon”), are determined by standard thermodynamic considerations at horizon, these metric fluctuations are large enough to observe in an interferometer with similar sensitivity to LIGO. In a follow-up paper we showed that these assumption holds for the vacuum in AdS/CFT. In future work, I plan to connect this work to recent soft graviton results, to frame this work in a concrete Randall-Sundrum model, and to work out concrete phenomenological predictions from the model. This work unquestionably takes a less trodden path, and works well as part of a well-rounded portfolio of less and more risky ideas. Particle physics is currently at a juncture which requires bold exploration of qualitatively new directions. This proposal outlines some of my plans over the coming years in these directions, leaving room also for surprises.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Quantum Nature of the Neutrino

Over the last 100 years we have learned much about the neutrino, but there remain interesting questions about this weakly interacting particle. In particular, at LLNL we are developing an experiment to measure the quantum nature of the neutrino. The 2015 long range plan recom mended tonne-scale neutrinoless double beta decay experiments as the top new project priority and this experiment will target the quantum nature of the neutrino. The LLNL team is motivated and focused on developing the best technology for this experiment which is a liquid xenon time projection chamber called nEXO. Work on nEXO at LLNL started in 2015 with an LDRD and program development funds to de velop the nEXO concept, publish sensitivity predictions, explore alternatives and risks, and to build a credible project team and this effort is on going. In addition, we received research funding from DOE-SC NP and LLNL manages pre-conceptual R&D for the nEXO collaboration a portion of which is executed at LLNL. LLNL has a long history of building large projects, science projects and time projection chambers, but nEXO is in fact the first project of this scale that LLNL is prepared to lead for DOE-SC NP. We have the tools, skills, people and motivation to make nEXO a reality. The current program devel opment dollars are used to prepare the nEXO concept for down select and CD1. These internal LLNL dollars pay for a number of things including project staff to organize the nEXO collaboration for the various reviews, to develop the draft plans and structure to manage the project as well as setting up external advisory committees. The DOE-SC NP base funding is targeted at simulation and analysis of the nEXO concept in preparation for the down select and refinement of the under standing of the detector as well as scientific effort on the large xenon test stand (LXTS) that will burn down one of the largest risks to the nEXO project. Lastly, LLNL is leading the pre-conceptual R&D effort and managing the funds for the nEXO collaboration. LLNL continues to build the best scientific team for nEXO and this year that includes adding Ethan Bernard to lead the efforts on the LXTS. We will also soon add a new postoc, Samuel Hedges, in the fall to the LLNL nEXO team. The effort this year was influenced by the portfolio review, and there were a number of scientific activities led by LLNL to prepare for this review. In addition, we again took a lead role on the new sensitivity paper as well as publishing a paper based analyzing the effects of skin xenon in nEXO. LLNL leads the software and analysis for the project and we continued work in this area as well. High voltage remains a significant risk for the project and we continue to make progress on the LXTS that will mitigate this risk. Lastly we remain active in looking at how to scale the technology to larger scales, and expect to produce a paper on this topic in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A data-driven peridynamic continuum model for upscaling molecular dynamics

Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition. However, the integrands in these operators are difficult to define from the data that are typically available for a given physical system, such as laboratory mechanical property tests. In contrast, molecular dynamics (MD) does not require these integrands, but it suffers from computational limitations in the length and time scales it can address. To combine the strengths of both methods and to obtain a coarse-grained, homogenized continuum model that efficiently and accurately captures materials’ behavior, we propose a learning framework to extract, from MD data, an optimal Linear Peridynamic Solid (LPS) model as a surrogate for MD displacements. To maximize the accuracy of the learnt model we allow the peridynamic influence function to be partially negative, while preserving the well-posedness of the resulting model. To achieve this, we provide sufficient well-posedness conditions for discretized LPS models with sign-changing influence functions and develop a constrained optimization algorithm that minimizes the equation residual while enforcing such solvability conditions. This framework guarantees that the resulting model is mathematically well-posed, physically consistent, and that it generalizes well to settings that are different from the ones used during training. We illustrate the efficacy of the proposed approach with several numerical tests for single layer graphene. Our two-dimensional tests show the robustness of the proposed algorithm on validation data sets that include thermal noise, different domain shapes and external loadings, and discretizations substantially different from the ones used for training.

homogenization↗
DOE OSTI2021

SECARB Regional Project Assessment

The SECARB Cranfield Early Test Project was designed to safely demonstrate large-scale, long-term CO 2 injection and storage in a CO 2 -enhanced oil recovery (EOR) operation and associated saline reservoir. Storage during EOR operations has the potential to offset commercial costs, holding a significant promise for future large-scale deployment in the southeastern United States. Denbury Onshore LLC began CO 2 -EOR operations in July 2008 at the Cranfield oilfield located east of Natchez, Mississippi (Figure 1). The location offered an ideal setting to investigate storage monitoring at a commercial CO 2 -EOR operation. The field team, led by the Gulf Coast Carbon Center of the Bureau of Economic Geology at the University of Texas at Austin, deployed the largest suite of monitoring, verification, accounting (MVA) technologies to collect data to assess long-term CO 2 utilization and storage. The CO 2 injection interval is within the 3,000-meter-deep fluvial lower Tuscaloosa Formation, a large and regionally extensive saline reservoir, at a broad four-way structural closure that defines the Cranfield oilfield. Tests were conducted in the oil-producing area as well as in the non-oil-producing brine aquifer. The CO 2 used during EOR operation was transported via pipeline from the Jackson Dome, a natural source of CO 2 . The study focused on four integrated research areas: (1) the High-Volume Injection Test area (HiVIT); (2) the Detailed Area of Study (DAS); (3) the Geomechanical area; and (4) the near-surface observatory, also called the “P-site.” CO 2 injection occurred at the HiVIT and the DAS (Figure 2 and Figure 3). The DAS was located down-dip of the oil-water interface of the Cranfield oilfield. The well layout included one injection well and two down-dip observation wells. The team was the first of the regional partnerships to monitor more than 1 million metric tons of CO 2 . At the end of the project, the team monitored more than 11 million metric tons of CO 2 injected and 5 million metric tons of CO 2 stored. The Cranfield Project was the fifth project worldwide, and the first such project in the United States, to reach this CO 2 injection volume while being monitored to demonstrate storage effectiveness.

01 COAL, LIGNITE, AND PEAT↗