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CONTENTS
Volume 36, Number 5, March10 2024
 

Abstract
Shield tunneling method is widely used to build tunnels in complex geological environment. Stability control of tunnel face is the key to the safety of projects. To improve the excavation efficiency or perform equipment maintenance, the excavation chamber sometimes is not fully filled with support medium, which can reduce the load and increase tunneling speed while easily lead to ground collapse. Due to the high risk of the face failure under non-fully support mode, the tunnel face stability should be carefully evaluated. Whether compressive air is required for compensation and how much air pressure should be provided need to be determined accurately. Based on the upper bound theorem of limit analysis, a non-fully support rotational failure model is developed in this study. The failure mechanism of the model is verified by numerical simulation. It shows that increasing the density of supporting medium could significantly improve the stability of tunnel face while the increase of tunnel diameter would be unfavorable for the face stability. The critical support ratio is used to evaluate the face failure under the non-fully support mode, which could be an important index to determine whether the specific unsupported height could be allowed during shield tunneling. To avoid of face failure under the non-fully support mode, several charts are provided for the assessment of compressed air pressure, which could help engineers to determine the required air pressure for face stability.

Key Words
pressure gradient; shield tunnelling; support mode; support ratio; tunnel face stability

Address
Dalong Jin, Yinzun Yang and Dajun Yuan: Key Laboratory of Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing, China;
School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China
Rui Zhang and Kang Zhang: Jinan Rail Transit Group Co, Ltd, Jinan 250000, China


Abstract
This study concentrates on the 301 comprehensive caving working face, notable for its considerable mining height. The roof model is established by integrating prior geological data and the latest borehole rock stratum's physical and mechanical parameters. This comprehensive approach enables the determination of lithology, thickness, and mechanical properties of the roof within 50 m of the primary mining coal seam. Utilizing the transfer rock beam theory and incorporating mining pressure monitoring data, the study delves into the geometric parameters of the direct roof, basic roof movement, and roof pressure during the initial mining process of the 301 comprehensive caving working face. The direct roof of the mining working face is stratified into upper and lower sections. The lower direct roof consists of 6.0 m thick coarse sandstone, while the upper direct roof comprises 9.2 m coarse sandstone, 2.6 m sandy mudstone, and 2.8 m medium sandstone. The basic roof stratum, totaling 22.1 m in thickness, includes layers such as silty sand, medium sandstone, sandy mudstone, and coal. The first pressure step of the basic roof is 61.6 m, with theoretical research indicating a maximum roof pressure of 1.62 MPa during periodic pressure. Extensive simulations and analyses of roof subsidence and advanced abutment pressure under varying working face lengths. Optimal roof control effect is observed when the mining face length falls within the range of 140 m-155 m. This study holds significance as it optimizes the working face length in thick coal seams, enhancing safety and efficiency in coal mining operations.

Key Words
optimization of the working face length; roof parameters; stope roof model; thick coal seam

Address
Chang-Xiang Wang, Meng Zhang and Cheng-Yang Jia: State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui
University of Science and Technology, Huainan Anhui 232001,China
Qing-Heng Gu: State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui
University of Science and Technology, Huainan Anhui 232001,China;
State and Local Joint Engineering Laboratory for Gas Drainage & Ground Control of Deep Mines,
Henan Polytechnic University, Jiaozuo 454000, China
Bao-Liang Zhang: School of Architecture & Civil Engineering, Liaocheng University, Liaocheng 252059, China
Jian-Hang Wang: Beijing Tiandi Huatai Mining Management Co., Ltd.,Beijing 100013, China

Abstract
Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

Key Words
C5.0 decision tree; karst sinkhole; sinkhole susceptibility prediction

Address
Boo Hyun Nam and Kyungwon Park: Department of Civil Engineering, College of Engineering, Kyung Hee University, 1732 Deogyeong-daero,
Giheung-gu, Yongin-si, Gyeonggi-do 17104, Republic of Korea
Yong Je Kim: Department of Civil and Environmental Engineering, Lamar University, 4400 MLK Blvd., Beaumont, TX 77710, USA

Abstract
Seismic movements have varying effects on structures based on characteristics of local site. During an earthquake, weak soils are susceptible to damage due to amplified wave amplitudes. Soil-structure interaction issue has garnered increased attention in Türkiye, after devastating earthquakes in Kocaeli Gölcük (1999), Izmir (2020), Kahramanmaraş Pazarcik and Elbistan (2023). Consequently, liquefaction potential has been investigated in detail for different regions of Türkiye, mainly with available field test results. Çankiri, a city located close to North Anatolian Fault, is mainly built on alluvium, which is prone to liquefaction. However, no study on liquefaction hazard has been conducted thus far. In this study, groundwater level map, SPT map, and liquefaction risk map have been generated using Geographical Information System (GIS) for the Bugday Pazari District of Çankiri province. Site investigations studies previously performed for 47 parcels (76 boreholes) were used within the scope of this study. The liquefaction assessment was conducted using Seed and Idriss's (1971) simplified method and the visualization of areas susceptible to liquefaction risk has been accomplished. The results of this study have been compared with the City Council's precautionary map which is currently in use. As a result of this study, it is recommended that minimum depth of boreholes in the region should be at least 30 m and adequate number of laboratory tests particularly in liquefiable areas should be performed. Another important recommendation for the region is that detailed investigation should be performed by local authorities since findings of this study differ from currently used precautionary map.

Key Words
alluvium; geographical information system; liquefaction; liquefaction hazard assessment; site characterization

Address
Eren Yurdakul and Ender Sarifakioglu: Department of Civil Engineering, Çankiri Karatekin University, Uluyazi Campus, 18100, Çankiri, Türkiye
Şevki Ozturk: Department of Civil Engineering, Çankaya University, Central Campus, 06790, Etimesgut, Ankara, Türkiye

Abstract
Uniaxial compressive strength (UCS) is a critical geomechanical parameter that plays a significant role in the evaluation of rocks. The practice of indirectly estimating said characteristics is widespread due to the challenges associated with obtaining high-quality core samples. The primary aim of this study is to investigate the feasibility of utilizing the gene expression programming (GEP) technique for the purpose of forecasting the UCS for various rock categories, including Schist, Granite, Claystone, Travertine, Sandstone, Slate, Limestone, Marl, and Dolomite, which were sourced from a wide range of quarry sites. The present study utilized a total of 170 datasets, comprising Schmidt hammer (SH), porosity (n), point load index (Is(50)), and P-wave velocity (Vp), as the effective parameters in the model to determine their impact on the UCS. The UCS parameter was computed through the utilization of the GEP model, resulting in the generation of an equation. Subsequently, the efficacy of the GEP model and the resultant equation were assessed using various statistical evaluation metrics to determine their predictive capabilities. The outcomes indicate the prospective capacity of the GEP model and the resultant equation in forecasting the unconfined compressive strength (UCS). The significance of this study lies in its ability to enable geotechnical engineers to make estimations of the UCS of rocks, without the requirement of conducting expensive and time-consuming experimental tests. In particular, a user-friendly program was developed based on the GEP model to enable rapid and very accurate calculation of rock's UCS, doing away with the necessity for costly and time-consuming laboratory experiments.

Key Words
gene expression programming; machine learning; uniaxial compressive strength; user-friendly software

Address
Ibrahim Albaijan: Mechanical Engineering Department, College of Engineering at Al-Kharj,
Prince Sattam Bin Abdulaziz University, Al Kharj 16273, Saudi Arabia
Daria K. Voronkova: Department of Mathematics and Natural Sciences, Gulf University for Science and Technology, Mishref Campus, Kuwait;
Bauman Moscow State Technical University Moscow, Russia
Laith R. Flaih: Department of Computer Science, Cihan University-Erbil, Kurdistan Region, Iraq
Meshel Q. Alkahtani: Civil Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia
Arsalan Mahmoodzadeh: IRO, Civil Engineering Department, University of Halabja, Halabja, 46018, Iraq
Hawkar Hashim Ibrahim: Department of Civil Engineering, College of Engineering, Salahaddin University-Erbil, 44002 Erbil, Kurdistan Region, Iraq
Adil Hussein Mohammed: Department of Communication and Computer Engineering, Faculty of Engineering,
Cihan University-Erbil, Kurdistan Region, Iraq


Abstract
Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

Key Words
artificial intelligence; fuzzy models; geology; geostatic simulation; slope resistance; uncertainty

Address
Timothy Chen: Guangdong University of Petrochem Technol, Sch Sci, Maoming City, Kuan-Du Avenue, No. 139, Peoples R China 525000;
Division of Eng App Sci, Caltech, CA 91125, USA
Ruei-Yuan Wang, Yahui Meng and Z.Y. Chen:Guangdong University of Petrochem Technol, Sch Sci, Maoming City, Kuan-Du Avenue, No. 139, Peoples R China 525000


Abstract
Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R2 of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created .

Key Words
factor of safety; graphical user interface; ML; PLAXIS; slope stability

Address
Bowen Liu and Zhenwei Wang: School of Civil Engineering, North China University of Technology, Beijing 100144, China
Sabih Hashim Muhodir: Department of Architectural Engineering, Cihan University-Erbil, Kurdistan Region, Iraq
Abed Alanazi and Shtwai Alsubai: Department of Computer Science, College of Computer Engineering and Sciences in Al-Kharj, Prince Sattam bin Abdulaziz University,
P.O. Box 151, Al-Kharj 11942, Saudi Arabia
Abdullah Alqahtani: Software Engineering Department, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University,
P.O. Box 151, Al-Kharj 11942, Saudi Arabia

Abstract
Underground openings significantly affect the mechanical stability of underground spaces and create damaged zones. This study investigated the acoustic emission (AE) characteristics associated with the formation of damaged zones around circular openings. Uniaxial compression experiments were conducted on three types of rock specimens, namely, granite (GN-1 and GN-2), gabbro (GB), and slate (SL), containing a circular opening. AE and digital image correlation (DIC) techniques were used to monitor and evaluate the damaged zones near the circular openings. The AE characteristics were evaluated using AE parameters, including count, energy, amplitude, average frequency, and RA value. The DIC results revealed that the estimated diameters of the damaged zones of GN-1, GN-2, GB, and SL were 1.66D, 1.53D, 1.49D, and 1.9D, respectively. The average displacements at the surface of the damaged zones for these specimens were 0.814, 0.786, 0.661, and 0.673 mm, respectively, thus demonstrating a strong correlation with Young's modulus. The AE analysis with DIC revealed that tensile failure occurred in the direction parallel to the maximum compression axis as the load increased. Thus, this study provides fundamental data for a comprehensive analysis of damaged zones in underground openings and will facilitate the optimization of rock engineering projects and safety assessments thereof.

Key Words
acoustic emission (AE); circular opening; damaged zone; digital image correlation (DIC)

Address
Jong-Won Lee: Research Institute of Industrial Technology, Pusan National University, 2 Busandaehak-ro 63beon-gil,
Geumjeong-gu, Busan 46241, Republic of Korea
Eui-Seob Park, Junhyung Choi and Min-Jun Kim: Deep Subsurface Storage & Disposal Research Center, Korea Institute of Geoscience and Mineral Resources (KIGAM),
124 Gwahak-ro, Yuseong-gu, Daejeon 34132, Republic of Korea
Tae-Min Oh: Department of Civil and Environmental Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil,
Geumjeong-gu, Busan 46241, Republic of Korea

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