Hypersonics at Sandia National Laboratories
Brief overview of Hypersonics with emphasis on fluid mechanics at Sandia
Wagnild, Ross Martin [Sandia National Laboratories↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process
Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.
36 MATERIALS SCIENCE↗
Complexity of Fault Rupture and Fluid Leakage in Shale: Insights From a Controlled Fault Activation Experiment
Abstract We observed rupture growth caused by controlled fluid injections at 340‐m depth within a fault zone in the low‐permeability Opalinus Clay in the Mont Terri Underground Research Laboratory (Switzerland). The rupture mechanisms were evaluated using measurements of the three‐component borehole wall displacements and fluid pressure in two sections of the fault zone and located horizontally 3 m apart from each other. One section was set across a secondary segment of the fault and used for stepwise fluid injection intended to trigger rupture growth. The other section was set across the principal shear zone of the fault for monitoring. After stepwise pressure increase up to 5.95 MPa at injection, rupture initiated as slip activation, followed by an overall opening of the fault planes connected to the injection. After 19 s of continued injection, displacements arrived at the monitoring point on the principal shear zone. These displacements are about 2.4 times larger than in the secondary fault segment. Overall, the displacements corresponded to a normal fault activation. About 9 s after the displacement front arrived, a strong pressure increase of 4.17 MPa was measured at the monitoring point, indicating a hydraulic connection had formed along the initially very low permeability fault planes between the injection and the monitoring points. Our analyses highlight that the fault activation is consistent with the state of stress but that injection pressure must be close to the normal stress acting on the fault for permeability to be generated and for fluid leakage to occur.
Guglielmi, Yves↗
Domain decomposition-based coupling of subdomain-local reduced order models (ROMs) in fluid mechanics using the Schwarz alternating method
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Tezaur, Irina Kalashnikova [Sandia National Labora↗
Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework
Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.
70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment
Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding MATLAB scripts that import and plot the data, as well as use it to calculate shear and normal stress. Experiments are performed on 2.5-3 inch long granitoid cores from the Utah FORGE EGS demonstration site, containing a single inclined fracture with small-scale roughness added to the fracture surface. The raw data included here were recorded from an aluminum triaxial pressure vessel (TEMCO) configured with three independent servo-controlled pumps, with distilled water used as the working fluid. The pumps control confining pressure, upstream pore pressure, and axial pressure, with each pump connected to a LabView interface to record applied pressures, cumulative injected water volumes, and pump flow rates. The downstream outlet from the fracture is closed to allow pressurization, which is measured by an external pressure transducer. A linear variable differential transformer (LVDT) attached to the axial piston measures axial displacement, from which we calculate shear displacement along the fracture. Additionally, P-wave transducers are used to record acoustic signatures, where acoustic emission events and maximum amplitudes are compared against seismic moment and shear slip velocity. Fluid injection rates range between 0.05 mL/min, 0.25 mL/min, and 0.75 mL/min for each experiment. Along-fault pressure distributions are progressively less uniform as injection rates increase, representing a switch from steady-state to transient conditions. Triggered shear displacement is used as a proxy for seismic moment and is indexed against cumulative injection volume and rate. Each experiment is performed under constant shear stress conditions, and the sample is fully saturated with DI water. Axial and confining stresses are applied to 3 MPa through pressure-stepping in 500 kPa increments. The pore pressure is held constant at 200 kPa prior to initiating the experiment, and initial axial displacement is recorded. The axial stress is then increased to initiate shear mobilization during the loading phase (run-in) until a peak steady state is achieved. The initial shear stress is reduced to approximately 80% of the peak shear stress by decreasing the axial stress, then held constant for the duration of each experiment.
15 GEOTHERMAL ENERGY↗
A sticky situation: The heterogeneity and implications of magma mush unlocking
Magma, partially molten rock below Earth's surface, can be made up of both fluid (melt) and particles (crystals). The relative fraction of the fluid and particles matters for the magma's mobility and ability to reach Earth's surface. Here we conduct physical laboratory experiments to examine the mechanisms through which a magma becomes mobile and the speed at which pure melt and infiltrate a mixture of fluids and particles. The results have implications for understanding magma mobility and the mechanisms that move magma to Earth's surface. Poster presented at the 2025 International Association of Volcanology and Chemistry of Earth's Interior Meeting (IAVCEI).
multiphase flows↗
New systems in MOOSE
The Multiphysics Object-Oriented Simulation Environment (MOOSE) serves as a common library of classes between applications developed for advanced reactor analysis, fusion device engineering, spent fuel cask analysis, geochemistry studies, among other fields. These applications drive the development of the framework to meet their needs. Systems in MOOSE group capabilities that share a common purpose and generally common code. They can be leveraged by all downstream applications, providing extensive code re-use and shared maintenance. They facilitate the discovery by new users of the classes meeting at least partially their needs, and offer the same opportunities for customization as other systems. The addition of a new system to MOOSE opens new ways of solving or discretizing nonlinear problems, of performing distributed postprocessing, and a plethora of other needs. While new systems can be introduced in downstream applications rather than at the framework level, the framework team monitors common needs across the community and often triggers their addition. Documentation, training material, development needs can be centralized, limiting duplicated work across the community. The last three years have seen a large expansion in the capabilities of MOOSE. The supporting role of the framework in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has created numerous feature requests to support neutronics, thermal hydraulics, computational fluid dynamics and thermo-mechanics simulations in the Griffin, SAM, Pronghorn and Bison applications respectively. Similarly, laboratory-directed research and development (LDRD) projects in additive manufacturing, high-Reynolds flow simulations, structure optimization also necessitate an expansion of the framework capabilities. This summary reports on the new systems created in MOOSE, their design, their capabilities and some of the relevant interfaces.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Exploration of Rayleigh-Taylor seeding mechanisms in laser- and pulsed-power-driven inertial fusion
The ubiquitous Rayleigh-Taylor instability (RTI) has been observed in fluids and plasmas in a wide range of parameter regimes from astrophysical to laboratory plasmas. In high-energy-density (HED) laboratory plasmas, such as laser-driven inertial confinement fusion (ICF) plasmas, the RTI can have a detrimental impact on achieving fusion ignition through the generation of hydrodynamic mix. Hence, an understanding of the seeding mechanisms that produce the RTI and identifying ways to mitigate hydrodynamic mix is of critical importance. Appropriately aligned magnetic fields have been known to stabilize short-wavelength RTI. A number of numerical and experimental studies have demonstrated the benefits of using imposed magnetic fields in laser-driven ICF to achieve higher ion temeratures, higher neutron yields, and a relaxation of the ignition criteria. This work addresses seeding mechanisms in laser-driven implosions to understand critical early-stage physics that ultimately leads to substantial growth of the RTI along with mechanisms for mitigation of this growth. Surface perturbations due to machining tolerances and single-feature seeds (for example due to fill tubes) can produce substantial RTI growth in the ignition-relevant high-convergence ratio targets for laser- driven ICF implosions. RTI growth from single-feature seeding in laser-based implosions has the potential to be mitigated through appropriately aligned externally applied magnetic fields and the goal of this work has been to quantify that numerically and experimentally. Resistive-magnetohydrodynamic (MHD) simu- lations are used to study the seeding and evolution of the RTI leveraging previous support from the DOE HEDLP program. Furthermore, experimental data has been obtained and applied towards code validation of unmagnetized and magnetized evolution of single-feature seeded RTI growth.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines (Final Report)
This is the final report for project DE-FE0031924 titled “High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines.” The report provides a summary of the entire project efforts from October 2020 through December 2024 including the high-temperature commercial dry gas seal (DGS) tests and thermal modeling of Task 2, as well as the high-temperature, large-diameter seal design and high-temperature tests of large-diameter seals in Task 3. A key outcome of Task 2 was the testing completion of specially instrumented commercial DGS in the GE-SwRI Apollo sCO 2 compressor (27,000 rpm). Test data from the DGS showed elevated temperatures upwards of 350 o F, which are close to the higher operating temperature limit of the DGS. The temperature measurements provide insight into the expected thermal loads on DGS operating in high-speed sCO 2 compressor and provided test data for validation of an in-house thermal model of the compressor/seal. Under Task 2.0, this report also presents the development of a steady-state conjugate heat-transfer model of the DGS operating in the sCO 2 compressor – a first of its kind model for modeling heat transfer of sCO 2 in an actual operating compressor. The findings of the thermal model show a reasonable match between temperature predictions of the model and the measured temperature data, also pointing out the validity of the approach and assumptions made in modeling the flows, heat transfer coefficients and windage modeling in the rig. Under Task 3.0, this report presents the preliminary design of a large-diameter hybrid face seal (14 inch and 26-inch diameter) for field testing in a land-based GE turbine. The preliminary seal design effort presented in this report under project DE-FE0031924 builds on the development and successful laboratory testing for such large diameter hybrid face seal under the prior DE-FE0024007 project. Key aspects of seal fluid analyses with CFD, mechanical design considerations and assembly considerations in a land-based turbine are presented. Finally, under Task 3.0, this report also presents the continued high-temperature testing of the 14-inch diameter hybrid face seal developed previously under the DE-FE0024007 program. Specifically, test data demonstrating successful non-contact seal operation and seal effective leakage of 0.001-inch with seal inlet temperatures above 700 o F are presented in this report. Successful hybrid seal operation in a laboratory environment for a large diameter (14-inch) seal at temperatures above 700 o F is a major technological milestone for this technology.
01 COAL, LIGNITE, AND PEAT↗
Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder
Sodium-cooled fast reactors (SFR), which use high temperature fluid near ambient pressure as coolant, are one of the most promising types of GEN IV reactors. One of the unique challenges of SFR operation is purification of high temperature liquid sodium with a cold trap to prevent corrosion and obstructing small orifices. We have developed a deep learning long short-term memory (LSTM) autoencoder for continuous monitoring of a cold trap and detection of operational anomaly. Transient data were obtained from the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The cold trap purification at METL is monitored with 31 variables, which are sensors measuring fluid temperatures, pressures and flow rates, and controller signals. Loss-of-coolant type anomaly in the cold trap operation was generated by temporarily choking one of the blowers, which resulted in temperature and flow rate spikes. The input layer of the autoencoder consisted of all the variables involved in monitoring the cold trap. The LSTM autoencoder was trained on the data corresponding to cold trap startup and normal operation regime, with the loss function calculated as the mean absolute error (MAE). The loss during training was determined to follow log-normal density distribution. During monitoring, we investigated a performance of the LSTM autoencoder for different loss threshold values, set at a progressively increasing number of standard deviations from the mean. The anomaly signal in the data was gradually attenuated, while preserving the noise of the original time series, so that the signal-to-noise ratio (SNR) averaged across all sensors decreased below unity. Results demonstrate detection of anomalies with sensor-averaged SNR < 1.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Coupled Thermo-Hydrological-Mechanical-Chemical Behavior of Anisotropic Granite for Geologic Disposal of High-Level Radioactive Waste: A Core-Scale Laboratory Investigation
The coupled thermo-hydrological-mechanical-chemical (THMC) behavior of rock within an Excavation Damaged Zone (EDZ) is critical for the safety and long-term performance of a geological repository for high-level radioactive wastes. While many laboratory experiments have been conducted to investigate EDZ rocks, the flow and deformation characteristics resulting from anisotropic rock textures and microcrack distribution under triaxial loading and elevated temperatures remain poorly understood. Particularly, cracks at various scales serve as fast paths for fluid flow and solute transport and present as focal points of mechanical weakness, which complicate the coupled THMC processes in anisotropic EDZ rocks and challenge modeling predictions. Here, in this study, a series of core-scale experiments was conducted on three granite samples under repository-relevant conditions. These rock samples were obtained from the Grimsel Underground Research Laboratory (URL), featured by anisotropic minerals (represented by bedding layers) and microcrack distributions and coarse cm-scale grain sizes. During the experiments, samples were subjected to an elevated temperature at 90 °C and different triaxial loading conditions either by radial (normal to bedding layers) or axial (parallel to bedding layers) compaction. Water was injected into the samples, and the rock permeability evolutions and effluent water chemistry were monitored closely. For intact samples, thermal expansion of minerals at 90 °C resulted in a large, 75% irreversible permeability reduction and rock strengthening under radial compaction, while thermal impact was limited to a 15% permeability reduction under axial compaction. In contrast, for a sample containing open cracks, the growth of fractures during the experiment resulted in an abrupt permeability increase and fast failure at 90 °C. The effluent water chemistry indicates much more considerable mineral dissolution from large shear sliding than that in rocks dominated by mechanical compaction. These results helped better understand the coupled THMC processes in anisotropic rocks containing cracks, evaluate the behaviors of EDZ rocks, and predict the long-term evolution of EDZ for the performance of the repositories.
Coupled THMC processes↗
Modeling of fluid injection-induced fault reactivation using coupled fluid flow and mechanical interface model
The present study is aimed at developing a numerical model to reproduce coupled hydro-mechanical processes associated with fault reactivation by fluid injection in low permeability rock, as part of the DECOVALEX-2019 project Task B. We proposed a modeling approach for simulating the processes using the TOUGH-FLAC simulator, and modeled a fault reactivation experiment conducted at Mont Terri Rock Laboratory in Switzerland. The first step of the study involved benchmark calculations considering a simplified fault plane and geometry. Fluid flow along a fault was modeled using elements of aperture-sized thickness on the basis of Darcy's law and the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by zero-thickness interface elements in FLAC3D upon which a slip and/or separation is allowed. A methodology to connect a TOUGH2 volume element to a FLAC3D interface element was developed for handling the hydro-mechanical interactions on the fault during fluid injection. Two different fault models for describing the evolutions of hydraulic aperture by elastic fracture opening and failure-induced aperture increase were considered in the benchmark calculations. In the coupling process, the changes in geometrical features and hydrological properties induced by mechanical deformation were continuously updated. The transient responses of the fault and host rock to stepwise pressurization were examined during the simulation. The hydro-mechanical behavior, including the injection flow rate, pressure distribution around the borehole, stress conditions, and displacements in normal and shear directions were monitored in the surrounding rock and along the fault. The results of benchmark calculations suggest that the developed model reasonably represents the hydro-mechanical behavior of a fault and the surrounding rock. This modeling approach was applied to the fault reactivation experiment of the Mont Terri Rock Laboratory. In this interpretive modeling, a parametric study was conducted to examine the effects of input parameters regarding in situ stress and fault properties on the hydro-mechanical responses of the fault to water injection. Then, an optimal parameter set to reproduce the field experiment results was chosen by trial-and-error. The injection flow rate and pressure response during fault reactivation closely matched those obtained at the site, which indicates the capability of the model to appropriately capture the progressive pathway evolution during fault reactivation tests at the site. Finally, the anchor displacements were overestimated by the model, but a fair agreement was obtained in terms of the order of magnitude and the variation tendency.
58 GEOSCIENCES↗
Deterministic Calibration of MFiX-PIC, Part 1: Settling Bed
The Particle-in-cell (PIC) numerical approach for modeling granular solids in fluid flow has gained significant interest in recent years. Valued for its often shorter time-to-solution, the PIC formulation relies on modeling statistical groupings of particles called parcels in cooperation with a solids stress model to affect local solids velocity. This is in contrast to the discrete element model (DEM) where every particle in a system is modelled individually and directly coupled to local solids velocity through Newtonian mechanics. The U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) develops and maintains Multiphase Flow with Interphase eXchanges (MFiX), a collection of open-source computational fluid dynamics (CFD) solvers. Included in the MFiX suite are traditional two-fluid model (TFM) and DEM solvers, and a recently added PIC solver (NETL, 2021). In general, PIC methodologies offer an accuracy trade-off in lieu of computational speed; and therefore, it is important to assess the credibility of MFiX-PIC simulations. For this purpose, a systematic verification, validation and uncertainty quantification (VVUQ) effort was initiated at NETL to assess the new PIC solver
42 ENGINEERING↗
Mechanical Response of Castlegate Sandstone under Hydrostatic Cyclic Loading
The stress history of rocks in the subsurface affects their mechanical and petrophysical properties. Rocks can often experience repeated cycles of loading and unloading due to fluid pressure fluctuations, which will lead to different mechanical behavior from static conditions. This is of importance for several geophysical and industrial applications, for example, wastewater injection and reservoir storage wells, which generate repeated stress perturbations. Laboratory experiments were conducted with Castlegate sandstone to observe the effects of different cyclic pressure loading conditions on a common reservoir analogue. Each sample was hydrostatically loaded in a triaxial cell to a low effective confining pressure, and either pore pressure or confining pressure was cycled at different rates over the course of a few weeks. Fluid permeability was measured during initial loading and periodically between stress cycles. Samples that undergo cyclic loading experience significantly more inelastic (nonrecoverable) strain compared to samples tested without cyclic hydrostatic loading. Permeability decreases rapidly for all tests during the first few days of testing, but the decrease and variability of permeability after this depend upon the loading conditions of each test. Cycling conditions do affect the mechanical behavior; the elastic moduli decrease with the increasing loading rate and stress cycling. The degree of volumetric strain induced by stress cycles is the major control on permeability change in the sandstones, with less compaction leading to more variation from measurement to measurement. The data indicate that cyclic loading degrades permeability and porosity more than static conditions over a similar period, but the petrophysical properties are dictated more by the hydrostatic loading rate rather than the total length of time stress cycling is imposed.
58 GEOSCIENCES↗
Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure
Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology
58 GEOSCIENCES↗
Fluid‐Driven Cohesive Strengthening: Critical Role of Reaction Kinetics as the Determinant for Frictional Stability
After an earthquake, faults in the Earth's crust lock up and slowly regain strength. This process, called fault healing, plays a key role in determining how often earthquakes happen and how large they can be. While scientists know that healing involves both mechanical friction and chemical changes in rocks, it has been unclear how these processes work together, especially over shorter timescales in laboratory settings. In our study, we ran controlled experiments on the mineral anhydrite under different fluid conditions. We found that the presence and pressure of water speeds up fault healing by triggering a chemical reaction that strengthens the fault over time. This strengthening makes the fault more resistant to sliding, which could delay future earthquakes—but also sets the stage for larger ones when they do occur. We propose a model that combines frictional and chemical processes to explain this water‐activated, time‐dependent healing. Importantly, our results show that even faults typically considered stable could still produce earthquakes if they undergo sufficient chemical healing. This has broad implications for understanding where and when earthquakes might strike, especially in fluid‐rich environments such as subduction zones and geoenergy settings.
Affinito, R [Pennsylvania State Univ., University ↗