... allowed researchers to incorporate physics into neural network models, enabling the forecasting of necessary parameters using inverse analysis algorithms. In this study, we employ the PINN approach to estimate unknown parameters associated with under-lying clay layer thickness and consolidation-aided...

... characterization instability displacement algorithm lidar resolution switzerland government fracture 001 figure 1 europe government insar derron crest landslide 15th ISRM Congress 2023 & 72nd Geomechanics Colloquium. Schubert & Kluckner (eds.) © ÖGG Use of combined monitoring remote sensing...

... of machine learning algorithms that use different data sources to obtain geotechnical parameters. Three algorithms were applied to the data sources and the scores varied depending on the comparisons and the acceptance criteria. It was observed that when the adjustment sequence is made in a more flexible...

... characterization rock mechanic algorithm strength nazarbayev university instability application kazmineral correspond 15th ISRM Congress 2023 & 72nd Geomechanics Colloquium. Schubert & Kluckner (eds.) © ÖGG A reliability-based design approach for geotechnical domain modelling in pit slope design...

... to examine the infrared thermal response of a rock sample to a fixed-frequency sinusoidal heat wave. To automate detection, a cutting-edge deep-learning technique was used to identify, localize, and segment cracks. A sizable dataset of images with a resolution of 640×480 was produced for the algorithm...

... upstream oil & gas deep learning reservoir geomechanics reservoir characterization shear strength prediction algorithm deep learning-aided prediction fine-tuning simulation specimen validation artificial intelligence geological subdiscipline rock mechanic data-driven pss criteria...

... assessment rock tunnel face optimization database indicator multi-source database risk and uncertainty assessment asia government algorithm machine learning dataset engineer stacked deep learning bay second submarine tunnel co stability construction 15th ISRM Congress 2023 & 72nd...

... prediction models are built. We postulated that TBM machine sensors may capture both actions of the machine and the reactions of the ground. Hence the prediction of settlement can be made if an appropriate algorithm is applied. There are a few sequential algorithms such as vanilla LSTM, LSTM with attention...

... strength and to establish rock mass classes based on RMR or GSI. Machine Learning (ML) algorithms are well suited to learning underlying patterns in large data sets. For example, a convolutional neural network study for predicting tunnel liner yield demonstrates the benefit of ML (Morgenroth et al. 2022...

... ABSTRACT: Digital Image Correlation (DIC) is a non-contact displacement measurement method that uses image correlation algorithms to measure displacement. The algorithms used are often designed for structures having uniform geometry without cavities. However, in the rock engineering problems...

... ABSTRACT: Human-induced seismicity in underground mining has significant impacts on productivity, safety, and operating costs. Accurate predictors for microseismic event sources are crucial to minimize disasters such as rockbursts. This study develops machine learning algorithms to predict...

... was newly introduced to the FI-DDA, and then, efficient contact detection and contact stiffness matrix assembly algorithms suitable for parallel processing were proposed and introduced to the FI-DDA. The analysis code was parallelized with OpenMP and the performance of the developed method was verified...

.... The maximum tangential stress criterion was used to predict the crack growth paths using the incrementally increasing cracks lengths in the predicted direction. Several examples were solved to evaluate the accuracy and efficiency of the proposed algorithm. It is concluded that the fatigue crack growth...

... to predict TBM performance with time, including recurrent neural networks, long-short term memory network (B. Gao et al., 2021; X. Gao et al., 2019; Lin et al., 2022). Hybrid models that combine ML and optimization algorithms have better performance through tunning hyperparameters (Yang et al., 2020; Yu et...

...) is developed to study the flow behavior in a fractured porous media using SL. Using a Finite Volume discretization (FVM) and Discrete Fracture Network (DFN) to simulate rock matrix and fracture network, Bresenham line algorithm is used to embed the DFN into FVM cells. Pressure equations are solved with a two...

... algorithm proppant concentration real time system srv history engineering threshold prediction real-time prediction mse long short-term memory university geotechnical engineering extract information 15th ISRM Congress 2023 & 72nd Geomechanics Colloquium. Schubert & Kluckner (eds.) © ÖGG...

... consists in solving the corresponding compliance matrix equation by means of the least square best fit multi-regression approach in groups of samples, which are then averaged. The second is based on minimizing the error in the stress invariant by means of a non-linear gradient algorithm. Results...

... geomechanics matrix geologist structural geology rock type reservoir characterization fragment limestone breccia a-ii calcite matrix algorithm limestone limestone fragment lefkada island tectono-diagenetic dolomite breccia uniaxial compressive strength correlation journal e-ii classification...

... trajectory algorithm axis mining science apparatus rock mechanic international journal calculation tracking fragment rotation resolution fragmentation frag 50 fragment trajectory viewpoint development giacomini Abstract In this paper, an apparatus to track rock fragment...

... human computer interaction machine learning rnn algorithm artificial intelligence investigation rqd procedure equation derivative neural network information exploration operation variation estado unido mexicanos sensation figure 1 sequence geotechnical safety sediment...