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Record W4405634475 · doi:10.1016/j.gete.2024.100616

A systematic model- and experimental approach to hydro-mechanical and thermo-mechanical fracture processes in crystalline rocks

2024· article· en· W4405634475 on OpenAlexafffund
Olaf Kolditz, Christopher McDermott, Jeoung Seok Yoon, Mostafa Mollaali, Wenqing Wang, Mengsu Hu, T. SASAKI, J. Rutqvist, Jens Birkhölzer, Jung–Wook Park, Chan–Hee Park, Hejuan Liu, Peng‐Zhi Pan, Thomas Nagel, Son Nguyen, Saeha Kwon, Changsoo Lee, Kwang‐Il Kim, Teklu Hadgu, Yifeng Wang, Łi Zhuang, Keita Yoshioka, Gonçalo Benitez Cunha, Andrew Fraser‐Harris

Bibliographic record

VenueGeomechanics for Energy and the Environment · 2024
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsCanadian Nuclear Safety Commission
FundersH2020 European Research CouncilEngineering and Physical Sciences Research CouncilChinese Academy of SciencesNuclear Waste Management OrganizationNational Natural Science Foundation of ChinaBundesministerium für Wirtschaft und KlimaschutzU.S. Department of EnergyCanadian Nuclear Safety CommissionBaltimore Gas and Electric Company
KeywordsMaterials scienceFracture (geology)Composite materialGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

The paper presents the key findings of Task G SAFENET of the DECOVALEX 2023 project “Safety Assessment of Fluid Flow, Shear, Thermal and Reaction Processes within Crystalline Rock Fracture NETworks”. It utilizes a systematic and experimental approach to numerically simulate mechanical (M), hydro-mechanical (HM), and thermo-mechanical (TM) fracture processes in brittle rocks. The Task team introduced, applied, and compared a wide range of numerical methods, including both continuum and discontinuum methods, for simulating related fracture processes. Task G is based on three key experiments: the Freiberg, GREAT cell, and KICT experiments, which analyze M, HM, and TM processes respectively. Classic HM and THM benchmark exercises serve as a common basis by using analytical solutions for a plane line discontinuity in a poro-elastic medium (Sneddon and Lowengrub, 1969) and a point heat source in a thermo-poro-elastic medium (Booker and Savvidou, 1985), (Chaudhry et al., 2019). These solutions also serve as a reference for rough fractures and simple fracture networks. A systematic set of new benchmark cases has been derived based on the GREAT cell experiments. An analysis of the constant normal load (CNL) experiment has been conducted using micro- and macroscopic approaches, based on the Freiberg experiment. The GREAT cell experiments provided a database for evaluating the mechanical and hydro-mechanical responses of various rock samples (resin, greywacke, gneis) in triaxial tests with a rotational stress field. Fracture permeability was determined as a function of normal stresses in the rotational stress field. The KICT experiments were used to investigate thermally induced shear slip and dilation processes. The SAFENET Task contributed to the Open Science concept in DECOVALEX by providing a freely accessible Jupyter notebooks for selected benchmark exercises. • Systematic and experimental-based approach to numerical simulation of fracture processes • Large variety of numerical methods, continuum and discontinuum methods compared • Benchmark suite based on Freiberg, GREAT and KICT laboratory experiments • Experiments covering mechanically, hydraulically and thermally induced fracturing • Open Science contribution: Initiation of a DECOVALEX Jupyter Lab (Appendix C).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.189
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes2
Has abstractyes

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