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At least 19 records

Portable interactive visualization of large-scale simulations in geotechnical engineering using Unity3D

Development in large-scale geotechnical engineering simulation places tremendous demand for efficient visualization of such simulation data. This study presents a lightweight software tool, i.e. Geotechnical Interactive Visualization (GIV), as a solution to this challenge, which achieves efficient interactive visualization of large-scale simulations data in geotechnical engineering. Visualization data flow and algorithms specifically optimized for common geotechnical engineering applications are implemented in GIV. GIV can visualize geotechnical structure models with time-varying attributes attached to mesh with fixed topology, and also models with time-varying mesh topologies but no attributes attached, the two most common visualization tasks in geotechnical engineering. Furthermore, challenges for large-scale simulation data visualization, including parallel simulation data redundancy, massive data size, dynamic user interaction, and portability are overcome via specifically designed algorithms for simulation data preprocessing and optimized visualization modules using the powerful 3D rendering and interactive game engine Unity3D. Comparison of GIV with several widely used visualization tools for the visualization of large-scale idealized datasets and realistic geotechnical simulations highlights the visualization efficiency, smooth interactivity, and lightweight features of GIV.

42 ENGINEERING↗

Multichannel Analysis of Surface Waves Accelerated (MASWAccelerated): Software for efficient surface wave inversion using MPI and GPUs

Multichannel Analysis of Surface Waves (MASW) is a technique frequently used in geotechnical engineering and engineering geophysics to infer 1D layered models of seismic shear wave velocities in the top tens to hundreds of meters of the subsurface. We aim to accelerate MASW calculations by capitalizing on modern computer hardware available in the workstations of most engineers: multiple cores and graphics processing units (GPUs). We propose new parallel and GPU accelerated algorithms for computing 1D MASW inversion, and provide software implementations in C using Message Passing Interface (MPI) and CUDA. These algorithms take advantage of sparsity that arises in the problem, and the work balance between processes considers typical data trends. We compare our methods to an existing open source Matlab MASW tool. Our serial C implementation achieves a 2x speedup over the Matlab software, and we continue to see improvements by parallelizing the problem with MPI. Here we see nearly perfect strong and weak scaling for uniform data, and improve strong scaling for realistic data by repartitioning the problem to process mapping. By utilizing GPUs available on most modern workstations, we observe an additional 1.3x speedup over the serial C implementation on the first use of the method. We typically repeatedly evaluate theoretical dispersion curves as part of an optimization procedure, and on the GPU the kernel can be cached for faster reuse on later runs. We observe a 3.2x speedup on the cached GPU runs compared to the serial C runs. This work is the first open-source parallel or GPU-accelerated software tool for MASW imaging, and should enable geotechnical engineers to fully utilize all computer hardware at their disposal.

58 GEOSCIENCES↗

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

RANGERS: Methodology Report on Design and Performance Assessment of Engineered Barrier Systems in a Salt Repository for HLW/SNF

Salt formations are one of the potential host rocks for the final disposal of high-level radioactive waste (HLW) in deep geological repositories, both in Germany and the United States. The safe isolation of radioactive waste in these repositories relies on a multi-barrier system, combining engineered and natural barriers. The natural barrier is provided by the salt rock itself, known for its self-sealing properties and long-term stability. The engineered barrier, on the other hand, comprises sealing components strategically placed within the repository to enhance its containment capabilities. In both Germany and the United States, long-term safety assessments require demonstrating the integrity of the natural barrier for a period of up to 1 million years. Concurrently, the engineered barrier system (EBS) must maintain its structural and functional integrity until the long-term sealing, such as the granular salt backfill material, has re-consolidated to its final low porosity and permeability. Based on extensive expertise and experience with engineered barriers in salt formations, BGE TECHNOLOGY GmbH and Sandia National Laboratories have partnered to develop a robust methodology for the integrity and performance assessment of EBS in HLW repositories through the RANGERS project. This collaborative effort aims to establish a unified approach to geotechnical engineering, repository design, integrity and performance evaluation of EBS in salt repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Application of physics-informed neural networks (PINNs) solution to coupled thermal and hydraulic processes in silty sands

Abstract The accurate modeling of water and heat transport in soils is crucial for both geo-environmental and geothermal engineering. Traditional modeling methods are problematic because they require well-defined boundaries and initial conditions. Recently, physics-informed neural networks (PINNs), which incorporate partial differential equations (PDEs) to solve forward and inverse problems, have attracted increasing attention in machine learning research. In this study, we applied PINNs to tackle hydraulic and thermal transport coupling forward problems in silty sands. A fully connected deep neural network was utilized for training. This neural network model leverages automatic differentiation to apply the governing equations as constraints, based on the mathematical approximations established by the neural network itself. We conducted forward problems and compared the solutions derived from PINNs with those from Finite Element Method (FEM) simulations. The forward problem results demonstrate the PINNs model’s capability in predicting hydraulic transport, heat transport, and thermal–hydraulic coupling in silty sands under various boundary conditions. The PINNs exhibited great performance in simulating the thermal–hydraulic coupling problem. The accuracy of the PINNs solutions shows its potential for simulation in geotechnical engineering.

Feng, Yuan↗

Approximate inverse-based block preconditioners in poroelasticity

We focus on the fully implicit solution of the linear systems arising from a three-field mixed finite element approximation of Biot’s poroleasticity equations. The objective is to develop algebraic block preconditioners for the efficient solution of such systems by Krylov subspace methods. In this work, we investigate the use of approximate inverse-based techniques to decouple the native system of equations and obtain explicit sparse approximations of the Schur complements related to the physics-based partitioning of the unknowns by field type. Here, the proposed methods are tested in various numerical experiments including real-world applications dealing with petroleum and geotechnical engineering.

54 ENVIRONMENTAL SCIENCES↗

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗

Assessment of the hydromechanical higher-order MPM for the simulation of geotechnical problems

The Material Point Method (MPM) has been increasingly used to simulate large strain deformations. Linear interpolation functions are commonly used to perform the spatial integration. It is well-known that the discontinuities in the interpolation function derivatives induce shock-like artifacts known as ‘cell-crossing’ error. These errors compound with volumetric locking errors when used with hydromechanical formulations for porous media, where different velocity fields are used for each phase. The capabilities of higher-order MPM frameworks have not been explored for real-scale geotechnical problems. As such, this paper aims to assess, validate, and further discuss a higher-order B-spline MPM (BS-MPM) framework. First, the BS-MPM framework is verified against the large-strain oedometer consolidation problem. Second, the framework is validated against a real-scale slope failure experiment triggered by pore water pressure recharge. Landslide features that are captured using the higher-order framework are specifically highlighted, and results (e.g., pore water pressure and deformation) are validated with field measurements. A generally convergent numerical solution is observed when using cubic interpolation functions. Third, a footing penetration problem is simulated using the multi-patch BS-MPM. Trends are examined with respect to penetration velocity and variation in hydraulic conductivity. The BS-MPM framework ultimately presents a stabilized numerical solution that captures plausible hydromechanical interaction trends important in geotechnical engineering applications.

36 MATERIALS SCIENCE↗

An experimental study on gas-liquid phase fluid migration in hydrate-bearing sediments during hydrate dissociation

Natural gas hydrate production tests face problems such as severe sand blockage, poor gas-liquid phase separation, and significant land subsidence. This is because of the insufficient understanding of the complex phase transition and gas-liquid multi-phase fluid migration during hydrate dissociation. In hydrate-bearing sediment systems, hydrate phase transition couples with gas-liquid fluid migration. The phase transition causes changes in pore structure, which in turn modifies porous infiltration parameters and fluid flow capacity. Meanwhile, alterations in phase interfaces affect key parameters like surface tension and wettability. Gas-liquid fluid migration influences heat and mass transfer, thus affecting phase equilibrium and dissociation rates. To bridge the gap in describing gas-liquid fluid migration during hydrate dissociation in experiments, this research innovatively integrated an unsteady-state gas displacement by water and a quantitative hydrate dissociation process, independently developed a multi-phase seepage experimental system suitable for hydrate dissociation and determined the relationship between seepage parameters and hydrate saturation under different porosity. The results are as follows: a) Core samples with higher initial porosity show a greater recovery rate of fluid flow capacity. b) The retarding effect of multi-phase fluid has a more significant impact on the migration of the wetting phase fluid (water) than that of the non-wetting phase fluid (methane). c) During hydrate dissociation, the evolution of absolute permeability shows an “S-shaped” pattern, and the evolution of relative permeability shows a “wiring-harness” pattern. In conclusion, the findings can provide a theoretical basis for preventing geological disasters and for geotechnical engineering design during hydrate production.

58 GEOSCIENCES↗

Field-scale estimation of soil properties from spectral induced polarization tomography

Estimates of soil properties such as Cation Exchange Capacity (CEC), water content, grain size characteristics, and permeability are important in geotechnical engineering, water resources, and agriculture. We develop a non-intrusive approach to estimate these properties in the field using spectral induced polarization (SIP) tomography. This geophysical method provides information about the frequency dependence of the complex electrical conductivity of porous media. Using 18 soil samples collected from a Bordeaux vineyard, we first conducted a laboratory study using SIP over the frequency range 10 mHz-45 kHz. The laboratory data were used to confirm the accuracy of a recently developed dynamic Stern layer petrophysical model. The results are consistent with published values from previous works using soils. A comparison was made by comparing the field complex conductivity spectra and the experimental data at two locations where core samples were obtained. The model was then used in concert with field data to image the spatial distribution of CEC, water content, permeability, and mean grain size along a vineyard transect. For clay and sandy textures found in the field, measured and estimated CEC agree rather well (from 6 to 40% discrepancy). Furthermore, our approach provides an efficient way to estimate important soil properties in a non-invasive manner, in high resolution, and over field-relevant scales of the critical zone of the Earth.

54 ENVIRONMENTAL SCIENCES↗

Editorial for Multiscale & Multifield Coupling in Geomechanics

We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering. The purpose of this special issue is dedicated to gathering the latest research work on Multiscale & Multifield Coupling in Geomechanics, where we delve into the intricate interplay of various fields and scales that govern the behavior of geomaterials. In total, 30 manuscripts from USA, China, UK, Germany, Canada, India and United Arab Emirates are selected to be included in this issue.

58 GEOSCIENCES↗

Thermo-Hydro-Mechanical Modeling of Brine Migration in a Heated Borehole Test in Bedded Salt

Abstract This research paper focuses on the thermo-hydro-mechanical (THM) modeling of brine migration in a heated borehole test conducted as part of the ongoing Brine Availability Test in Salt (BATS) at the Waste Isolation Pilot Plant (WIPP) in New Mexico. It is a component of the international collaboration project DECOVALEX-2023 (DEvelopment of COupled models and their VALidation against EXperiments), which aims to understand the THM processes governing brine flow in heated rock salt repositories through collaborative analysis by multiple research teams. Using the TOUGH–FLAC simulator, THM simulations were performed and compared with data from the BATS phase 1a. This experiment involved two identical horizontal-borehole arrays, one heated and one serving as a control, both equipped with sensor arrays. Analysis of measurements revealed water flow rate surges during heater power transitions, with the highest jump observed during cooling. Acoustic emission activity exhibited distinct patterns in response to heater power changes, suggesting that damage to rock salt is particularly pronounced during the cooling phase. The THM simulations successfully captured these phenomena, highlighting the significance of thermal effects, brine migration, and mechanical behavior in predicting brine availability in heated and damaged rock salt. Our modeling also revealed the critical interplay between heating and cooling-induced damage and its influence on flow properties, particularly affecting brine inflow estimation. Notably, we found that cooling-induced brine inflow spikes result from increased permeability due to tensile dilatancy. These findings have important implications for the development of robust containment strategies and enhance our understanding of the complex processes involved in repository performance.

58 GEOSCIENCES↗

Stress Dependency of Brittle Creep in Granite: Insights into Source Mechanisms and Parameters

Creep in rocks refers to the gradual deformation of rock material over time under the influence of constant stress. Characterizing these deformations is of great importance for engineering design, geotechnical assessment, mining operations, geological studies, and understanding natural hazards. While laboratory experiments and a variety of numerical approaches have offered explanations for microcrack interaction and damage accumulation under the three stages of creep (primary, secondary and tertiary) in conventional creep experiments, the micromechanisms of the fractures produced in brittle creep and its dependency on the applied stress have not been explored in detail. The present study focused on investigating the fracturing mechanisms that occur during creep-induced fracturing at different stress levels and estimation of the source parameters and energy budget components. A series of uniaxial compression creep experiments have been conducted at different stress level ratios (70%, 75%, 80% and 85%), to the unconfined compressive strength (UCS) of double-flawed Barre granite specimen. Creep measurements were complemented with the Acoustic Emission (AE) measurements. The creep-induced fractures were classified into double-couple (DC), compensated linear vector dipole (CLVD) and isotropic (ISO) components using the AE moment tensor decomposition technique. The results show that non-double-couple sources dominated during creep at all the specified stress levels; however, their proportions decreased as the stress level was increased. The source parameters estimation indicated a significant increase in the magnitude of the events and the radiated seismic energy with increasing levels of stress and a slight increase in the evaluated source radius and stress drop with increasing stress levels. Furthermore, this study contributes to the existing knowledge of creep-induced fracturing by providing insights into the fracturing mechanisms and the radiated seismic energy produced, which can be helpful for the development of improved models and strategies for rock engineering and geoscience applications.

58 GEOSCIENCES↗

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗

Geomechanical characterization of Rock Valley carbonates

In Rock Valley, Nevada, the USA, past earthquake sequences and shallow faulting in Paleozoic carbonates remain poorly understood. Carbonates are typically more ductile rocks that do not experience large stress drops or fracture coalescence, which contradicts previous observations in the region. As part of the Source Physics Experiment, an effort has been made to experimentally characterize the petrophysical and geomechanical properties of carbonates from Rock Valley. Well core and outcrop samples were used to determine the difference between shallow-buried Tertiary limestones and deeply buried Paleozoic limestones and dolostones. The carbonates possessed porosities between 3 and 9%, with V P and V S in the Tertiary carbonates around 2700 and 1800 m/s, respectively, and 6000 and 3100 m/s, respectively, in the Paleozoic carbonates. Microstructural characterization revealed that the Paleozoic carbonates contained significantly more pre-existing damage and alteration than the Tertiary carbonates, though the deformation varies from localized to diffuse. Unconfined Brazilian tests and triaxial tests with confining pressures between 0 and 50 MPa showed that, although samples all experienced failure, the dolostones typically failed at greater stresses and possessed greater E/ν ratios than the limestones. Furthermore, the Hoek–Brown failure criterion was used to construct failure envelopes with the compressive and tensile failure tests. Velocity, density, and porosity measurements were used to construct a hypothetical velocity-depth profile and compare the results with the theoretical petrophysical measurements. Using brittleness analysis, the likely failure conditions were determined to be low-porosity dolomitic rock for fault nucleation in the Paleozoic basement.

Brittleness↗