Rock Mechanics
Mohammad-Taghi Hamzaban; Alireza Chehreghan; Roozbeh Geraili Mikola
Abstract
Back analysis of tunnel excavation plays a fundamental role in calibrating geomechanical parameters using field monitoring data. However, conventional direct back analysis procedures remain computationally demanding and highly dependent on operator supervision. This study presents an integrated Finite ...
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Back analysis of tunnel excavation plays a fundamental role in calibrating geomechanical parameters using field monitoring data. However, conventional direct back analysis procedures remain computationally demanding and highly dependent on operator supervision. This study presents an integrated Finite Difference Method–Genetic Algorithm (FDM–GA) framework for automated tunnel back analysis, implemented entirely within the FLAC environment using the embedded FISH programming language. The proposed approach eliminates the need for external optimization software and data transfer between numerical and artificial intelligence platforms. A simplified genetic algorithm is coupled directly with finite difference simulations to iteratively minimize the discrepancy between measured and computed tunnel convergences. The framework incorporates constrained parameter optimization, automated handling of non-convergent models, and a robust convergence-based stopping criterion that avoids predefined error thresholds. Verification is performed using two synthetic plane-strain tunnel models representing stiff cohesive soil and dense granular material. Six unknown parameters (ρ, E, ν, c, φ, and K0) are back-calculated using only three convergence measurements. Results from multiple independent runs demonstrate stable convergence toward very small error values (on the order of 10-6–10-5) and consistent reproduction of synthetic monitoring data. The method successfully narrows broad initial parameter ranges and produces multiple acceptable parameter sets, explicitly acknowledging the non-uniqueness inherent in back analysis problems. The developed FDM–GA framework provides an efficient, self-contained, and adaptable tool for practical tunnel back analysis applications.
Rock Mechanics
M. T. Hamzaban; H. Memarian; J. Rostami
Abstract
Rock abrasivity is an essential factor for selecting cutting tools, estimating tool wear and life, and ultimately, matching various mechanized excavation systems with a given geologic condition. It also assists engineers to determine economic limits of different cutting tools and machines used in civil ...
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Rock abrasivity is an essential factor for selecting cutting tools, estimating tool wear and life, and ultimately, matching various mechanized excavation systems with a given geologic condition. It also assists engineers to determine economic limits of different cutting tools and machines used in civil and mining projects. The Cerchar abrasion test is a simple and most widely used method for rock abrasivity assessments. However, it has some shortcomings to describe the steel-rock interaction during the cutting process. In this work, two new parameters are used to describe the pin-rock interaction in the Cerchar abrasion test and to evaluate the efficiency of the rock scratching process. A set of 41 different rock samples are tested by a newly developed testing device. The device provides a more precise control of the testing operational parameters, and measures the applied frictional force on the pin and its horizontal and vertical displacements on the sample surface. The results obtained are used to calculate the Modified Cerchar Abrasion Index (MCAI) and the Scratch Energy Index (SEi), as two newly developed parameters. The accuracy of the calculated parameters is discussed. Our investigations show that MCAI has closer correlations with rock mechanical parameters than CAI, and therefore, has a higher potential to estimate the rock cutting tool wear in tunneling applications. Also SEi shows sensible correlations with sample hardness and mechanical properties. The results obtained show that SEi can be used to compare the efficiency of various pin hardnesses to create scratches on various rock samples, and could be used as a determinative parameter in selecting the cutting tool hardness.
