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CONTENTS
Volume 28, Number 4, February25 2022
 

Abstract
Buckling failure is a typical slope instability mode that should be paid more attention to. It is difficult to provide systematic guidance for the monitoring and management of such slopes due to unclear mechanism. Here we examine buckling failure as the potential instability mode for a slope above a railway tunnel in southwest China. A comprehensive model test system was developed that can be used to conduct buckling failure experiments. The displacement, stress, and strain of the slope were monitored to document the evolution of buckling failure during the experiment. Monitoring data reveal the deformation and stress characteristics of the slope with different slipping mass thicknesses and under different top loads. The test results show that the slipping mass is the main subject of the top load and is the key object of monitoring. Displacement and stress precede buckling failure, so maybe useful predictors of impending failure. However, the response of the stress variation is earlier than displacement variation during the failure process. It is also necessary to monitor the bedrock near the slip face because its stress evolution plays an important role in the early prediction of instability. The position near the slope foot is most prone to buckling failure, so it should be closely monitored.

Key Words
buckling failure; critical load; model test; monitoring data; slope

Address
Qian Zhang,Yang Gao and Yanliang Du:Key Laboratory of Structural Health Monitoring and Control, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China
Jie Hu: School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;
Geotechnical and Structural Engineering Research Center, Shandong University, Jinan, 250061, China
Liping Li and Hongliang Liu: Geotechnical and Structural Engineering Research Center, Shandong University, Jinan, 250061, China
Shangqu Sun:Shandong Provincial Key Laboratory of Civil Engineering Disaster Prevention and Mitigation,
Shandong University of Science and Technology, Qingdao 266590, Shandong, China

Abstract
The main concern of this article is to discuss the problem of a two-temperature fiber-reinforced micropolar thermoelastic medium with voids under the effect rotation, mechanical force in the context four different theories with memory-dependent derivative (MDD) and variable thermal conductivity. The three-phase-lag model (3PHL), dual-phase-lag model (DPL), Green-Naghdi theory (G-N II, G-N III), coupled theory, and the Lord˗Shulman theory (L-S) are employed to solve the present problem. Analytical expressions of the physical quantities are obtained by using Laplace-Fourier transforms technique. Numerical results are shown graphically and the results obtained are analyzed. The most significant points are highlighted.

Key Words
derivative; dual-phase-lag model; Laplace and Fourier transforms; memory-dependent rotation; three-phase-lag mode

Address
Amnah M. Alharbi: Department of Mathematics, College of Science, Taif Univeristy, P.O. Box 11099, Taif, 21944, Saudi Arabia
Samia M. Said and Mohamed I.A. Othman: Department of Mathematics, Faculty of Science, Zagazig University, P.O. Box 44519, Zagazig, Egypt
Elsayed M. Abd-Elaziz: Department of Basic Scineces, Zagazig Higher Institute of Eng. and Tech., Zagazig, Egypt

Abstract
Geology conditions are crucial in decision-making during the planning and design phase of a tunnel project. Estimation of the geology conditions of road tunnels is subject to significant uncertainties. In this work, the effectiveness of a novel regression method in estimating geological or geotechnical parameters of road tunnel projects was explored. This method, called Gaussian process regression (GPR), formulates the learning of the regressor within a Bayesian framework. The GPR model was trained with data of old tunnel projects. To verify its feasibility, the GPR technique was applied to a road tunnel to predict the state of three geological/geomechanical parameters of Rock Mass Rating (RMR), Rock Structure Rating (RSR) and Q-value. Finally, in order to validate the GPR approach, the forecasted results were compared to the field-observed results. From this comparison, it was concluded that, the GPR is presented very good predictions. The R-squared values between the predicted results of the GPR vs. field-observed results for the RMR, RSR and Q-value were obtained equal to 0.8581, 0.8148 and 0.8788, respectively.

Key Words
engineering geology; Gaussian process regression; geomechanical parameters; tunneling; tunnel geology

Address
Arsalan Mahmoodzadeh and Hunar Farid Hama Ali: Department of Civil Engineering, University of Halabja, Halabja, Kurdistan Region, Iraq
Mokhtar Mohammadi: Department of Information Technology, College of Engineering and Computer Science,
Lebanese French University, Kurdistan Region, Iraq
Sazan Nariman Abdulhamid and Hawkar Hashim Ibrahim: Department of Civil Engineering, College of Engineering, Salahaddin University-Erbil, 44002 Erbil, Kurdistan Region, Iraq
Shima Rashidi: Department of Computer Science, College of Science and Technology, University of Human Development,
Sulaymaniyah, Kurdistan Region, Iraq

Abstract
The glacial tills and shales in Midwestern states of the USA often show strength degradation after construction. They are often in need of applying soil modification techniques to remediate their strength degradation with weathering process. This study investigated the weathering durability of these natural soils and biopolymer treated soils by comparing direct shear test results for wet-dry and wet-freeze-thaw-dry cycled specimens. The tests showed that untreated glacial tills maintained only 62% and 50% initial shear strength after eight wet-dry cycles and eight wet-freeze-thaw-dry cycles, respectively. These untreated soils could not withstand by themselves after 16 weathering cycles. The same soils treated with 1.5% (by dry weight) food-grade Xanthan gum maintained 140% and 88% initial shear strength of untreated soils after 16 weathering cycles for wet-dry cycles and wet-freeze-thaw-dry cycles, respectively. The same soils treated with 1.5% (by dry weight) Gellan gum maintained 82% and 60% initial shear strength of untreated ones after 16 weathering cycles, respectively. Similar results were obtained for crushed shales, manifesting that the biopolymerization method may be adopted as a new eco-friendly method to enhance the weathering durability of these problematic soils of glacial tills and shales.

Key Words
biopolymer; glacial till; Gellan gum; shale; weathering; Xanthan gum

Address
Soroosh Amelian: University of Nebraska – Lincoln, Lincoln, 362B Whittier, 2200 Vine St. Lincoln, NE 68503, USA
Chung R. Song: University of Nebraska – Lincoln, 362N Whittier, 2200 Vine St. Lincoln, NE 68503, USA
Yongrak Kim: Texas A&M University, 503H, DLEB, College Station, TX 77843, USA
Mark Lindemann: Geotechnical Engineer, Nebraska DOT, 1500 NE-2, Lincoln, NE 68502, USA
Layal Bitar: University of Nebraska – Lincoln, 362B Whittier, 2200 Vine St. Lincoln, NE 68503, USA

Abstract
The accurate determination of the subgrade reaction modulus (Ks) of soil is an important factor for geotechnical engineers. This study estimated the Ks of soft soil improved with floating deep cement mixing (DCM) columns. A novel prediction model was developed that emphasizes the accuracy of identifying the most significant parameters of Ks. Several multi-layer perceptron (MLP) models that were trained using the Levenberg Marquardt (LM) backpropagation method were developed to estimate Ks. The models were trained using a reliable database containing the results of 36 physical modelling tests. The input parameters were the undrained shear strength of the DCM columns, undrained shear strength of soft soil, area improvement ratio and length-to-diameter ratio of the DCM columns. Grey wolf optimization (GWO) was coupled with the MLPs to improve the performance indices of the MLPs. Sensitivity tests were carried out to determine the importance of the input parameters for prediction of Ks. The results showed that both the MLP-LM and MLP-GWO methods showed high ability to predict Ks. However, it was shown that MLP-GWO (R = 0.9917, MSE = 0.28 (MN/m2/m)) performed better than MLP-LM (R =0.9126, MSE =6.1916 (MN/m2/m)). This proves the greater reliability of the proposed hybrid model of MLP-GWO in approximating the subgrade reaction modulus of soft soil improved with floating DCM columns. The results revealed that the undrained shear strength of the soil was the most effective factor for estimation of Ks.

Key Words
DCM columns; grey wolf optimization; soft soil; subgrade reaction modulus

Address
Ali Dehghanbanadaki: Department of Civil Engineering, Damavand Branch, Islamic Azad University, Damavand, Iran
hmad Safuan A. Rashid, Kamarudin Ahmad,
Nor Zurairahetty Mohd Yunus and Khairun Nissa Mat Said: 2Department of Geotechnics & Transportation, School of Civil Engineering, Faculty of Engineering,
Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia

Abstract
Accurate prediction of the undrained shaft resistance is essential for robust design of bored piles in undrained condition. The undrained shaft resistance is calculated using the undrained adhesion factor multiplied by the undrained cohesion of the soil. However, the available correlations to predict the undrained adhesion factor have been developed using simple regression techniques and the accuracy of these correlations has not been thoroughly assessed in previous studies. The lack of the assessment of these correlations made it difficult for geotechnical engineers to select the most accurate correlation in routine designs. Furthermore, limited attempts have been made in previous studies to use advanced data mining techniques to develop simple and accurate correlation to predict the undrained adhesion factor. This research, therefore, has been conducted to fill these gaps in knowledge by developing novel and robust correlation to predict the undrained adhesion factor. The development of the new correlation has been conducted using the multi-objective evolutionary polynomial regression analysis. The new correlation outperformed the available empirical correlations, where the new correlation scored lower mean absolute error, mean square error, root mean square error and standard deviation of measured to predicted adhesion factor, and higher mean, a20 -indexand coefficient of correlation. The correlation also successfully showed the influence of the undrained cohesion and the effective stress on the adhesion factor. Hence, the new correlation enhances the design accuracy and can be used by practitioner geotechnical engineers to ensure optimized designs of bored piles in undrained conditions.

Key Words
evolutionary computing; statistical assessment; undrained adhesion factors; undrained shaft capacity

Address
Saif Alzabeebee: Department of Roads and Transport Engineering, College of Engineering, University of Al-Qadisiyah, Al-Qadisiyah, Iraq
Ali Adel Zuhaira: Technical Institute of Al-Najaf, Al-Furat Al-Awsat Technical University, Iraq
Rwayda Kh. S. Al-Hamd: School of Applied Sciences, Abertay University, Dundee, UK

Abstract
Cavity expansion and contraction solutions for cylindrical and spherical cavities in unsaturated residual soils are presented in this paper. Varying soil state in the plastic zone is accounted by a numerical approach, wherein an element-by-element discretization of the plastic zone of both expanding and contracting cavities is carried out. Unlike existing methods utilizing self-similarity technique, the solution procedure enables the prediction of entire soil-state at any stage of expansion and subsequent contraction. It is also applicable for both cavity creation and expansion problems. The approach adopts constant contribution of suction to effective stress (constant xs drainage condition) for analysis. The analysis procedure is validated by interpreting the previously reported pressuremeter test results in lateritic residual soil. The typical cavity expansion and contraction characteristics of unsaturated Indian lateritic soil were then examined using this solution procedure. The effect of initial soil-state on cavity limit pressure, plastic radius, reverse yield pressure, and reverse plastic radius are also presented.

Key Words
cavity contraction; cavity expansion; soil state; suction; unsaturated residual soil

Address
Alpha Lukose and Sudheesh Thiyyakkandi: Department of Civil Engineering, Indian Institute of Technology, Palakkad, Kerala, India

Abstract
The necessity of estimating the time and cost required for tunnel construction has led to extensive research in this regard. Since geological conditions are significant factors in terms of time and cost of road tunnels, considering these conditions is crucial. Uncertainties about the geological conditions of a tunnel alignment cause difficulties in planning ahead of the required construction time and costs. In this paper, the continuous-space, discrete-state Markov process has been used to predict geological conditions. The Monte-Carlo (MC) simulation (MCS) method is employed to estimate the construction time and costs of a road tunnel project using the input data obtained from six tunneling expert questionnaires. In the first case, the input data obtained from each expert are individually considered and in the second case, they are simultaneously considered. Finally, a comparison of these two modes based on the technique presented in this article suggests considering views of several experts simultaneously to reduce uncertainties and ensure the results obtained for geological conditions and the construction time and costs.

Key Words
construction time and costs; continuous-space discrete-state Markov process; road tunnels; tunnel geology

Address
Arsalan Mahmoodzadeh and Hunar Farid Hama Ali: Department of Civil Engineering, University of Halabja,Halabja, Kurdistan Region, Iraq
Mokhtar Mohammadi: Department of Information Technology, Lebanese French University, Kurdistan Region, Iraq
Sirwan Ghafoor Salim: City Planning Department, Technical College of Engineering, Sulaimani Polytechnic University,
Sulaymaniyah, Kurdistan Region, Iraq
Sazan Nariman Abdulhamid and Hawkar Hashim Ibrahim: 4Department of Civil Engineering, College of Engineering, Salahaddin University-Erbil, 44002 Erbil, Kurdistan Region, Iraq
Shima Rashidi: Department of Computer Science, College of Science and Technology, University of Human Development, Sulaymaniyah, Kurdistan Region, Iraq

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