Imagen de Portada

A finite element-based machine learning model for hydro-mechanical analysis of swelling behavior in clay-sulfate rocks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Taherdangkoo, Reza, Mollaali, Mostafa, Ehrhardt, Matthias, Nagel, Thomas, Laloui, Lyesse, Ferrari, Alessio, Butscher, Christoph
Formato:	Preprint
Publicado:	2025
Materias:	Geophysics Machine Learning Computational Physics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Inversion of downhole resistivity properties through infrared spectroscopy and whole‐rock geochemistry using machine‐learning
por: Mehdi Serdoun, et al.
Publicado: (2024)

Ultrasonic sensing of the mechanical fingerprint of reactive transport in rock
por: Aminzadeh, Ali, et al.
Publicado: (2025)

A multi-phase thermo-mechanical model for rock-ice avalanche
por: Pudasaini, Shiva P.
Publicado: (2024)

Advancing resistivity-chargeability modeling for complex subsurface characterization using machine learning and deep learning
por: Akingboye, Adedibu Sunny, et al.
Publicado: (2025)

Well-posedness and potential-based formulation for the propagation of hydro-acoustic waves and tsunamis
por: Dubois, Juliette, et al.
Publicado: (2024)

Application of a dispersive wave hydro-sediment-morphodynamic model in the Ria Formosa lagoon
por: Kazhyken, Kazbek, et al.
Publicado: (2022)

Understanding phase transitions of $α$-quartz under dynamic compression conditions by machine-learning driven atomistic simulations
por: Erhard, Linus C., et al.
Publicado: (2024)

Temperature continuously controls the stability of clay slopes
por: Loche, Marco, et al.
Publicado: (2022)

Electrical and seismic refraction methods: fundamental concepts, current trends, and emerging machine learning prospects -- A review
por: Akingboye, Adedibu Sunny
Publicado: (2024)

A machine learning algorithm for predicting naturalized flow duration curves at human influenced sites and multiple catchment scales
por: Friedel, Michael J., et al.
Publicado: (2024)

Hydrogen diffusion in the lower mantle revealed by machine learning potentials
por: Peng, Yihang, et al.
Publicado: (2023)

An novel finite difference dispersion error elimination mechanism in the Lax–Wendroff high‐order time discretization
por: Wenquan Liang, et al.
Publicado: (2024)

Inverting airborne electromagnetic data with machine learning
por: McMillan, Michael S., et al.
Publicado: (2024)

Machine learning-based upscaling of rock permeability from pore scale to core scale: effect of training dataset size and sub-core volumes
por: Guo, Yaotian, et al.
Publicado: (2025)

Poromechanical solution for one-dimensional large strain consolidation of modified cam clay soil
por: Chen, Sheng-Li, et al.
Publicado: (2024)

Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization
por: Bo, Zhenkai, et al.
Publicado: (2026)

Evaluating the performance of machine-learning-based phase pickers when applied to ocean bottom seismic data: Blanco oceanic transform fault as a case study
por: Liu, Min, et al.
Publicado: (2024)

Estimating properties of a homogeneous bounded soil using machine learning models
por: Kalimeris, Konstantinos, et al.
Publicado: (2025)

Sequential hybrid finite element and material point method to simulate slope failures
por: Sordo, Brent, et al.
Publicado: (2024)

A multi-step calibration strategy for reliable parameter determination of salt rock mechanics constitutive models
por: Honório, Hermínio T., et al.
Publicado: (2024)

Heating-induced strengthening or weakening of clays during slow to fast shearing at landslide stress levels
por: Loche, Marco, et al.
Publicado: (2022)

Seismotectonics and Slip Behavior of a Submarine Plate Boundary Fault from Seismicity Repeaters and Tomography using a high-resolution earthquake catalog from machine learning
por: Lange, D., et al.
Publicado: (2025)

Accurate identification of salt domes using deep learning techniques: Transformers, generative artificial intelligence and liquid state machines
por: Kamal Souadih, et al.
Publicado: (2024)

Towards deep learning for seismic demultiple
por: Mario R. Fernandez, et al.
Publicado: (2025)

Temperature compensation in high accuracy accelerometers using multi-sensor and machine learning methods
por: Iafolla, Lorenzo, et al.
Publicado: (2024)

Python workflow for segmenting multiphase flow in porous rocks
por: Spurin, Catherine, et al.
Publicado: (2024)

Neural machine translation of seismic waves for petrophysical inversion
por: Teixeira, José Cunha, et al.
Publicado: (2024)

Oscillatory finite-time singularities in rockbursts
por: Lei, Qinghua, et al.
Publicado: (2025)

Semi-brittle flow of rocks: Cracks, dislocations and strain hardening
por: Brantut, Nicolas
Publicado: (2024)

Time‐domain finite element method based on arbitrary quadrilateral meshes for two‐dimensional SHTE mode seismoelectric and electroseismic waves modelling
por: Jun Li, et al.
Publicado: (2024)

Image-based modelling of elastic properties using unresolved rock images
por: Li, Rui, et al.
Publicado: (2025)

Grain-size effects during semi-brittle flow of calcite rocks
por: Harbord, Christopher, et al.
Publicado: (2023)

Gas trap prediction from 3D seismic and well test data using machine learning
por: Ivlev, Dmitry
Publicado: (2024)

Melting phase relation of seifertite and pyrite-type SiO2 determined by machine learning potentials
por: Park, Doyoon, et al.
Publicado: (2025)

Water saturation in texturally porous carbonate rocks: Shock thermodynamics and dampening of the shock
por: Moreau, Juulia-Gabrielle, et al.
Publicado: (2025)

Azimuthal imaging of rock fractures by incorporating single borehole radar and optical data
por: Shen, Jian, et al.
Publicado: (2024)

Enhancing lithological interpretation from petrophysical well log of IODP expedition 390/393 using machine learning
por: Sahu, Raj, et al.
Publicado: (2025)

Physics-informed extreme learning machine for Terzaghi consolidation problems and interpretation of coefficient of consolidation based on CPTu data
por: Yang, He, et al.
Publicado: (2025)

Image-based modelling of rock non-linear deformation under low-stress levels
por: Li, Rui, et al.
Publicado: (2025)

Physics-constrained generative machine learning-based high-resolution downscaling of Greenland's surface mass balance and surface temperature
por: Bochow, Nils, et al.
Publicado: (2025)