• Smart Structures and Systems
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• 제32권4호
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Geomechanics and Engineering
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• 제14권6호
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• pp.589-600
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• 2018

For foundations in permafrost regions, the displacement characteristics are uncertain because of the randomness of temperature characteristics and mechanical parameters, which make the structural system have an unexpected deviation and unpredictability. It will affect the safety of design and construction. In this paper, we consider the randomness of temperature characteristics and mechanical parameters. A stochastic analysis model for the uncertain displacement characteristic of foundations is presented, and the stochastic coupling program is compiled by Matrix Laboratory (MATLAB) software. The stochastic displacement fields of an embankment in a permafrost region are obtained and analyzed by Neumann stochastic finite element method (NSFEM). The results provide a new way to predict the deformation characteristics of foundations in permafrost regions, and it shows that the stochastic temperature has a different influence on the stochastic lateral displacement and vertical displacement. Construction disturbance and climate warming lead to three different stages for the mean settlement of characteristic points. For the stochastic settlement characteristic, the standard deviation increases with time, which imply that the results of conventional deterministic analysis may be far from the true value. These results can improve our understanding of the stochastic deformation fields of embankments and provide a theoretical basis for engineering reliability analysis and design in permafrost regions.

• Geomechanics and Engineering
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• 제27권6호
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• pp.583-594
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• 2021

The gas permeability behavior of unsaturated bentonite-based materials is of major importance for ensuring effective sealing of high-level radwaste repositories. This study investigated this by taking a sample of Granular Bentonite Material (GBM) at the end of the Engineered Barrier Emplacement (EB) experiment in the Opalinus Clay, placing it under different humidity conditions until it achieved equilibration, and testing the change in the gas permeability under loading and unloading. Environmental humidity is shown to have a significant effect on the water content, saturation, porosity and dry density of GBM and to affect its gas permeability. Higher sensitivity to confining pressure is exhibited by samples equilibrated at higher relative humidity (RH). It should be noted that for the sample at RH=98%, when the confining pressure is raised from 1 MPa to 6 MPa, gas permeability can be reduced from 10^-16 m² to 10^-19 m², which is close to the requirements of gas tightness. Due to higher water content and easier compressibility, samples equilibrated under higher RH show greater irreversibility during the loading and unloading process. The effective gas permeability of highly saturated samples can be increased by 2-3 orders of magnitude after 105℃ drying. In addition, cracks possibly occurred during the dehydration and drying process will become the main channel for gas migration, which will greatly affect the sealing performance of GBM.

• Structural Engineering and Mechanics
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• 제81권2호
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• pp.205-217
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• 2022

The thermodynamic properties of shaft lining concrete (SLC) are important evidence for the design and construction, and the spatial variability of concrete materials can directly affect the stochastic thermal analysis of the concrete structures. In this work, an array of field experiments of the concrete materials are carried out, and the statistical characteristics of thermophysical parameters of SLC are obtained. The coefficient of variation (COV) and scale of fluctuation (SOF) of uncertain thermophysical parameters are estimated. A three-dimensional (3-D) stochastic thermal model of concrete materials with heat conduction and hydration heat is proposed, and the uncertain thermodynamic properties of SLC are computed by the self-compiled program. Model validation with the experimental and numerical temperatures is also presented. According to the relationship between autocorrelation functions distance (ACD) and SOF for the five theoretical autocorrelation functions (ACFs), the effects of the ACF, COV and ACD of concrete materials on the uncertain thermodynamic properties of SLC are analyzed. The results show that the spatial variability of concrete materials is subsistent. The average temperatures and standard deviation (SD) of inner SLC are the lowest while the outer SLC is the highest. The effects of five 3-D ACFs of concrete materials on uncertain thermodynamic properties of SLC are insignificant. The larger the COV of concrete materials is, the larger the SD of SLC will be. On the contrary, the longer the ACD of concrete materials is, the smaller the SD of SLC will be. The SD of temperature of SLC increases first and then decreases. This study can provide a reliable reference for the thermodynamic properties of SLC considering spatial variability of concrete materials.

• Geomechanics and Engineering
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• 제21권6호
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• pp.551-564
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• 2020

High-stress and complex geological conditions impose great challenges to maintain excavation stability during deep underground mining. In this research, large anisotropic deformation and its management by support system at a deep underground mine in Western Australia were simulated through three-dimensional finite-difference model. The ubiquitous-joint model was used and calibrated in FLAC3D to reproduce the deformation and failure characteristics of the excavation based on the field monitoring results. After modeling verification, the roles of mining depth also the intercept angle between excavation axis and foliation orientation on the deformation and damage were studied. Based on the results, quantitative relationships between key factors and damage classifications were presented, which can be used as an engineering tool. Subsequently, the performance of support system installation sequences was simulated and compared at four different scenarios. The results show that, first surface support and then reinforcement installation can obtain a better controlling effect. Finally, the influence of bolt spacing and ring spacing were also discussed. The outcomes obtained in this research may play a meaningful reference for facing the challenges in thin-bedded or foliated ground conditions.

• Safety and Health at Work
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• 제9권1호
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• pp.10-16
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• 2018

Background: A detailed evaluation of the underground mine climate requires extensive measurements to be performed coupled to climatic modeling work. This can be labor-intensive and time-consuming, and consequently impractical for daily work comfort assessments. Therefore, a simple indicator like a heat stress index is needed to enable a quick, valid, and acceptable evaluation of underground climatic conditions on a regular basis. This can be explained by the unending quest to develop a "universal index," which has led to the proliferation of many proposed heat stress indices. Methods: The aim of this research study is to discuss the challenges in identifying and selecting an appropriate heat stress index for thermal planning and management purposes in underground mines. A method is proposed coupled to a defined strategy for selecting and recommending heat stress indices to be used in underground metal mines in the United States and worldwide based on a thermal comfort model. Results: The performance of current heat stress indices used in underground mines varies based on the climatic conditions and the level of activities. Therefore, carefully selecting or establishing an appropriate heat stress index is of paramount importance to ensure the safety, health, and increasing productivity of the underground workers. Conclusion: This method presents an important tool to assess and select the most appropriate index for certain climatic conditions to protect the underground workers from heat-related illnesses. Although complex, the method presents results that are easy to interpret and understand than any of the currently available evaluation methods.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2004년도 춘계학술발표회 논문집
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• pp.219-229
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• 2004

In this article a comprehensive review of the Rock Mass Rating and Q-rockmass classification systems is made with reference to their scope with in the constraints of underground mining operations. The modifications suggested by KIGAM for both the RMR and Q for the calculation of a safe unsupported span were tested for Daesung and Pyunghae underground limestone mines. Even though the suggested modifications were site specific, the additional parameters considered in the above classification systems are very significant for a design of stable underground openings, considering any general mining conditions.

• Geomechanics and Engineering
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• 제17권6호
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• pp.573-581
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• 2019

Excavation of underground cavern and shaft was proposed for the construction of a ventilation facility in an urban area. A shaft connects the street-level air plenum to an underground cavern, which extends down approximately 46 m below the street surface. At the project site, the rock mass was relatively strong and well-defined joint sets were present. A kinematic block stability analysis was first performed to estimate the required reinforcement system. Then a 3-D discontinuum numerical analysis was conducted to evaluate the capacity of the initial support and the overall stability of the required excavation, followed by a 3-D continuum numerical analysis to complement the calculated result. This paper illustrates the application of detailed numerical analyses to the design of the required initial support system for the stability of underground hard rock mining at a relatively shallow depth.

• 터널과지하공간
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• 제10권1호
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• pp.80-91
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• 2000

석회석의 노천 채굴법은 갱내 채굴법에 비하여 채수율, 품위조절, 원가, 안전면에서 유리한 것으로 인식되고 있으나 발파로 인한 지반진동, 소음, 분진 등 환경 오염원을 유발시키며 특히 지형과 산림을 훼손한다 본고에서는 백두대간에 인접한 한라 석회석 광산을 모델로설정하고 연구하였다. 환경 오염원을 저감시키고, 원 지형 및 산림의 보존을 위하여 노천 채굴과 함께 갱내 채굴을 동시에 채택할 것을 제의한다. 갱내 채굴의 경우 중단 채굴법을 추천하며 이때 한 광획의 크기는 80(높이)$\times$70(너비)$\times$(100~120m)(연장)이며, 태수율은 약 42%로 예상된다. 환경오염 저감을 위한 대책도 제시하였다. 파쇄입도의 조정을 위하여 암반태 불연속면의 발달 상태를 고려하고, 장약공 밑부분과 중간부분의 장약밀도를 변경해야 한다. 환경오염 저감의 한 방안으로 차폐벽의 채택과 갱내 채굴시 출광 가능량 등을 검토하였다.

• Geomechanics and Engineering
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• 제30권3호
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• pp.259-272
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• 2022

Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.