Hasil untuk "Engineering geology. Rock mechanics. Soil mechanics. Underground construction"

Abolfazl Eslami, Amirhossein Ebrahimipour, Meysam Imani et al.

Abstract Conventionally, foundations have been classified as shallow or deep in routine civil engineering practice. However, due to recent developments, two other approaches, semi‐deep and ground modification foundations, are now available, complicating foundation categorization. Accordingly, a new concept for foundation categorization is introduced in this paper based on insights into the theory of structure analysis. Based on the form aspect, foundation systems can be categorized as one‐dimensional (linear), two‐dimensional (planar), and three‐dimensional (volumetric). Based on the load transfer aspect, foundations can also be categorized as vector‐acting (piles), section or surface‐acting (rafts and shells), and block‐acting (piled rafts). As a step toward implementing this new categorization scheme, a database of 22 cases has been compiled, symbolizing novel introduced foundation systems. This compilation involves structures such as offshore jackets, high‐rise buildings, towers and storages, and diverse geomaterials. Among them, a few have been selected for detailed evaluation, emphasizing influential factors in foundation selection, comprising superstructure, subsoil condition, foundation system, circumferential conditions, and supplementary considerations, that is, constructional and sustainability‐based issues. Lessons learned from experience and these knowledge‐based cases have described for foundation selection and implementation. Geotechnical and practical aspects with critical components have been realized as major performance assessment and comparison factors. Foundation systems have been compared and ranked using the improved analytic hierarchy process approach. Finally, four categories of buildings, from low‐rise to towers and four prevailing levels of soil strength, from soft to very hard, have been considered to propose a perspective for building substructure implementation, adapted via relevant cases. Overall, the introduced categorization is recognized as an efficient algorithm for the experimentation of appropriate foundations for specific structures and subsoil conditions.

Xuefei Wang, Jianhua Li, Jiale Li et al.

Real-time assessment of subgrade compaction quality poses a significant challenge in the implementation of intelligent compaction (IC). Current compaction evaluation models are confined to specific scenarios and lack robustness. This study proposes a subgrade compaction strategy that utilizes a heterogeneous dataset to estimate compaction quality across diverse scenarios while maintaining model accuracy. Field compaction tests are conducted in four distinct scenarios, considering various construction parameters. Compaction models are developed using several machine learning algorithms. The datasets are thoroughly assessed in terms of quality, diversity and similarity. The proposed model exhibits good performance in new scenarios by incorporating an additional 5%–8% of new data for retraining. The model's generalization capability is enhanced by conducting a limited number of field tests, which are labor-saving and time-efficient. The model's accuracy consistently improves across diverse scenarios and optimal algorithms. The proposed compaction strategy adopts a physics-and-data dual-driven approach, aimed at practical engineering applications and guiding the compaction procedure.

LIU Feiyue 1, 2, 4 , YANG Tianhong 2 , ZHU Wancheng 2, YANG Zhenqi 3, DENG Wenxue 2, LI Hua 2, CHEN Wanyun 1

The stability of rock slopes is one of the most critical issues for the safe production in an open-pit mine. Providing early warning signals and issuing accurate evacuation orders for the rock landslides is of practical engineering significance. By collecting and analyzing 32 rock landslide cases in open-pit mines, it is proposed that the rockfall or slope movement acts as a precursor of early warning of the rock landslides. Following the safety monitoring standards for open-pit mines, the abundance of monitoring videos can provide valuable data for the early warning of rock landslides. In this study, the motion target tracking algorithm is utilized to identify rockfalls or slope movement areas from the monitoring videos. By setting appropriate thresholds, early warnings with leading time ranging from tens of seconds to hours can be provided for the areas where landslides have initiated but not yet spread. An undisclosed open-pit quarry and the Yanshan open-pit mine are employed to demonstrate the proposed method. The results indicate that the rock landslides progress through four phases including occasional rockfall, small-scale rockfall, continuous rockfall and overall landslide. For the rock landslides with heights of 6 m and 30 m, the early warning leading time is 35 s and 113 s, respectively. The proposed method for early warning of landslide of rock slopes based on rockfall video monitoring holds extensive application prospects in open-pit mines. However, extensive field tests and further research are required.

RUI Dahu 1, 2 , WANG Jiayi 1, ZHANG Jun 1, 2, PAN Weidong3 , WANG Miao 4

The freeze-thaw synergistic chemical washing can remove heavy metal contaminants from clayey soils. However, the intake of eluent is low during the freezing process, resulting in low washing efficiency. Based on the idea of improving the frost heave of clayey soils and increasing water migration to improve the leaching efficiency, the freeze-thaw-leaching tests on soil columns are carried out by taking heavy metal-contaminated clayey soils as the research object and selecting strong frost-heave Akadama soil as the admixture. The results indicate that under the same freezing conditions, the frost-heave rate of Akadamas soil 124.48%, with the corresponding increase in the frost-heave amount and water intake of 5.85 times and 4.82 times that of clayey soils, respectively. This indicates an extremely strong frost-heave characteristic. The adsorption capacity of Akadama soil for Pb and Cd is weak, and it can be reused. After incorporating Akadama soil, the frost-heave amount and water intake of clayey soils significantly increase, with the maximum increments of 130.91% and 113.39%, respectively. After three freeze-thaw cycles, the removal rates of Pb and Cd reach 57.51% and 66.77%, respectively, representing an increase of 173.73% and 113.94% compared to those of the control group without Akadama soil. The SEM tests show that the structure of Akadama soil is severely broken and the number of pores increases, which is conducive to the migration and storage of water after freeze-thaw cycles. The method of using Akadama soil as an admixture soil to improve the freeze-thaw leaching efficiency has operability and universality in practical engineering applications. It provides a new approach for the remediation of heavy metal-contaminated clayey soils in seasonal frozen regions.

Chengxin Feng, Marcos A. Valdebenito, Marcin Chwała et al.

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering. The latter is particularly true for slope stability assessment, where the effects of uncertainty are synthesized in the so-called probability of failure. This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint. In view of this issue, this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments. The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion. Then, failure probabilities are estimated employing maximum entropy distribution with fractional moments. The application of the proposed approach is examined with two examples: a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope. The results show that the proposed approach has excellent accuracy and high efficiency, and it can be applied straightforwardly to similar geotechnical engineering problems.

J. Kozubal, D. Bhat, P. M. Pradhan

In this paper, flysch is presented as a representative material of a wide section of the Carpathian Mountains, with some areas in Poland highlighted. The geological structure of this area is complex due to the alternating layers of blocky rock masses and soil (Vessia et al., 2017). Such a complex pattern is seen in some Alpine flysch slopes, such as the Ingelsberg landslide area (Romeo et al., 2015). Many authors are monitored, predicted landslides (Allasia et al., 2013; Bertacchini et al., 2009; Casagli et al., 2010) by sophisticated sensors. The rock-soil flysch successions have become intensively fissured as a result of their geological history, weathering (precipitation and snowmelt), and long-term water retention, especially on the surface layers. These complex materials are characterised by heterogeneous lithologies, whose mechanical properties are largely uncertain. These geological structures have also been confirmed by monitoring and control studies performed on a large number of landslides (Bednarczyk, 2014). One of the most striking phenomena is the sudden decrease in the strength parameters in the studied rocks in the direction parallel to the layers due to watering. The process is made possible by heterogeneous fractured strong rock layers with high permeability coefficients for water. This study precisely describes the phenomena occurring at the contact area between the component layers of flysch under the wet conditions of a weak plane. An elastic-plastic analysis method that considers the developed strength model at the surfaces of the contact areas (Biernatowski & Pula, 1988; Pula, 1997) has been used to estimate the load capacity for piles working under a horizontal load. The piles are part of a reliability chain (Pula, 1997) in a given construction and are the first element of concern for monitoring (Muszynski & Rybak, 2017). A particular device intended to study the dependence of the shear stress on a fixed failure surface in a controlled consolidation condition was utilized. The study was conducted for a wide range of displacements and for different values of stabilized vertical stresses of consolidation. The complexity of the processes occurring in the shear zone, presented as a detailed study of the material crack mechanics, is highlighted. The laboratory results were used to construct the mechanical model of the slip surface between the soil and rock with the description supported by a neural network (NN) approximation. The artificial NN was created as a multi-layered, easy to use approach for interpreting results and for quick reconstruction of approximated values useful for the calculations presented in laterally loaded piles. For the calculations, long, sheared strips of material were considered in a semi-analytical procedure to solve a differential equation of stability. The calculations are intended to reveal the safety indexes for a wide range of boundary tasks as the most significant indicator for design decisions.

Shuqin Wen, Bing Wei, Junyu You et al.

Production prediction is crucial for the recovery of hydrocarbon resources. However, accurate and rapid production forecasting remains challenging for unconventional reservoirs due to the complexity of the percolation process and the scarcity of available data. To address this problem, a novel model combining a long short-term memory network (LSTM) and support vector regression (SVR) was proposed to forecast tight oil production. Three variables, the tubing head pressure, nozzle size, and water rate were utilized as the inputs of the presented machine-learning workflow to account for the influence of operational parameters. The time-series response of tight oil production was the output and was predicted by the optimized LSTM model. An SVR-based residual correction model was constructed and embedded with LSTM to increase the prediction accuracy. Case studies were carried out to verify the feasibility of the proposed method using data from two wells in the Ma-18 block of the Xinjiang oilfield. Decline curve analysis (DCA) methods, LSTM and artificial neural network (ANN) models were also applied in this study and compared with the LSTM-SVR model to prove its superiority. It was demonstrated that introducing residual correction with the newly proposed LSTM-SVR model can effectively improve prediction performance. The LSTM-SVR model of Well A produced the lowest prediction root mean square error (RMSE) of 5.42, while the RMSE of Arps, PLE Duong, ANN, and LSTM were 5.84, 6.65, 5.85, 8.16, and 7.70, respectively. The RMSE of Well B of LSTM-SVR model is 0.94, while the RMSE of ANN, and LSTM were 1.48, and 2.32.

Eduardo A. Oliveira, Leon Sterling

This paper describes how motivational models can be used to cross check agile requirements artifacts to improve consistency and completeness of software requirements. Motivational models provide a high level understanding of the purposes of a software system. They complement personas and user stories which focus more on user needs rather than on system features. We present an exploratory case study sought to understand how software engineering students could use motivational models to create better requirements artifacts so they are understandable to non-technical users, easily understood by developers, and are consistent with each other. Nine consistency principles were created as an outcome of our study and are now successfully adopted by software engineering students at the University of Melbourne to ensure consistency between motivational models, personas, and user stories in requirements engineering.

Walid Maalej, Yen Dieu Pham, Larissa Chazette

Requirements Engineering (RE) is the discipline for identifying, analyzing, as well as ensuring the implementation and delivery of user, technical, and societal requirements. Recently reported issues concerning the acceptance of Artificial Intelligence (AI) solutions after deployment, e.g. in the medical, automotive, or scientific domains, stress the importance of RE for designing and delivering Responsible AI systems. In this paper, we argue that RE should not only be carefully conducted but also tailored for Responsible AI. We outline related challenges for research and practice.

XIE Xiao-li , WANG Zi-fan , YE Bin

The existing studies demonstrate that the history of earthquake liquefaction is an important factor affecting the liquefaction resistance of sand. The researchers think the intrinsic mechanism of these effects is the generation of stable or unstable sand mesostructure after the previous liquefaction event. However, few studies have directly given the experimental results of the evolution behaviors of the sand mesostructure during the whole process of liquefaction. In this study, the centrifuge shaking table tests are conducted to model the earthquake liquefaction of a saturated sand deposit. The pore pressures and accelerations at different depths and the settlements of the sand deposit are measured. Besides, the mesoscopic digital images of the sand mesostructure are recorded simultaneously by a mesoscopic image acquisition system. The experimental results show that the small shaking increases the contacts and decreases the voids among sand particles. The particle contacts are reconstructed and the voids are redistributed with the larger shaking. Approximately vertically and horizontally linked large voids are caused by the upper seepage effects of the pore fluid. The sand particles nearby the approximately vertically large voids rotate vertically under the seepage effects.

Kunping Liang, Guofan Cheng, Qingyan Qin et al.

The Xinhua phosphate mining are alocated in Zhijin County, Guizhou Province, is a famous superlarge low-grade phosphate deposit containing rare earth elements in the southwest of China.The average P2O5 grade of the deposit is 17.22%.The proven phosphorite ore resources are 1.348 billion tons, and the rare earth resources are 3 500 kilotons.In recent years, experts and scholars have found that the fluctuation of Xinhua phosphorite ore grade is closely related to weathering, leaching and enrichment effects.To further clarify the influence of weathering and leaching on the element geochemistry as well as the secondary enrichment of phosphate rock, the author focuses on the Gezhongwu ore block and carries out field observations and descriptions of phosphate rock series.A total of 19 chemical analysis samples were collected using block knocking method and 16 rock ore samples were identified through polarizing microscope.On these basis, identification and comprehensive research on the samples were conducted.The results show that the contents of P2O5 in the weathered phosphate rock are 8%-18%, higher than that in the primary phosphate rock, while the contents of MgO are 4%-7%, lower than that in the primary phosphate rock.The weathering intensity of phosphate rock is in the weak to mature stage.The formation of Xinhua weathered phosphate rock in Zhijin County is controlled by lithology, geological structure and hydrological conditions.The purpose of this paper is to provide new information for the further study of the influences of the secondary weathering mineralization of the ore deposit on the chemical composition of phosphate rock, to enrich the metallogenic theories of weathering eluvial phosphate mining in China and to provide the oretical guidance for the rational development and utilization of weathering phosphate resources in the mining area.

Joshua O. Minai, Darrell G. Schulze, Zamir Libohova

Much older soils information, collectively known as legacy soils data lies idle in libraries or in the personal collections of retired soil scientists. The probability is very high for this legacy data to be lost or destroyed. We demonstrate the stepwise process of bringing legacy soils data “back to life” using the Reconnaissance Soil Survey of the Busia Area (quarter degree sheet No. 101) in western Kenya as an example. The first step, site identification, involves meeting and deliberating with key institutions to identify a setting for the study. The second step, data archeology, involves locating and cataloging legacy soil data from key institutions, which often requires numerous site visits and the assistance of individuals familiar with the target data. The third step, data rescue, involves converting paper copies of data into a digital format by scanning the maps, narrative descriptions, and tables, and storing the information in a database. The fourth step, data renewal, consists of bringing the data to modern standards by taking advantage of technological and conceptual advances in geoinformation technology. In our example, the resulting digital (scanned) soil map of the Busia Area is a significant upgrade from the fragile paper map. The fifth step, data interpretation, entails careful interpretation of the soil information available within the legacy soil survey to provide additional agronomic information. This allowed us to produce 10 land quality maps showing the ability of the land to perform specific agronomic functions, and 18 different crop suitability maps that were not previously available. The rescued maps and their associated tabular and narrative data also provide crucial inputs for generating more detailed soil maps using digital soil mapping techniques that were unavailable when the original mapping was conducted.

Aaryan Jagetia, Umang Goenka, Priyadarshini Kumari et al.

Our food security is built on the foundation of soil. Farmers would be unable to feed us with fiber, food, and fuel if the soils were not healthy. Accurately predicting the type of soil helps in planning the usage of the soil and thus increasing productivity. This research employs state-of-the-art Visual Transformers and also compares performance with different models such as SVM, Alexnet, Resnet, and CNN. Furthermore, this study also focuses on differentiating different Visual Transformers architectures. For the classification of soil type, the dataset consists of 4 different types of soil samples such as alluvial, red, black, and clay. The Visual Transformer model outperforms other models in terms of both test and train accuracies by attaining 98.13% on training and 93.62% while testing. The performance of the Visual Transformer exceeds the performance of other models by at least 2%. Hence, the novel Visual Transformers can be used for Computer Vision tasks including Soil Classification.

Panos Pantidis, Mostafa E. Mobasher

We present a new Integrated Finite Element Neural Network framework (I-FENN), with the objective to accelerate the numerical solution of nonlinear computational mechanics problems. We leverage the swift predictive capability of neural networks (NNs) and we embed them inside the finite element stiffness function, to compute element-level state variables and their derivatives within a nonlinear, iterative numerical solution. This process is conducted jointly with conventional finite element methods that involve shape functions: the NN receives input data that resembles the material point deformation and its output is used to construct element-level field variables such as the element Jacobian matrix and residual vector. Here we introduce I-FENN to the continuum damage analysis of quasi-brittle materials, and we establish a new non-local gradient-based damage framework which operates at the cost of a local damage approach. First, we develop a physics informed neural network (PINN) to resemble the non-local gradient model and then we train the neural network offline. The network learns to predict the non-local equivalent strain at each material point, as well as its derivative with respect to the local strain. Then, the PINN is integrated in the element stiffness definition and conducts the local to non-local strain transformation, whereas the two PINN outputs are used to construct the element Jacobian matrix and residual vector. This process is carried out within the nonlinear solver, until numerical convergence is achieved. The resulting method bears the computational cost of the conventional local damage approach, but ensures mesh-independent results and a diffused non-local strain and damage profile. As a result, the proposed method tackles the vital drawbacks of both the local and non-local gradient method, respectively being the mesh-dependence and additional computational cost.

Osvaldo P.M. Vitali, Tarcisio B. Celestino, Antonio Bobet

Rock masses with remarked rock structure are likely to be highly anisotropic; thus, the relative orientation of the tunnel with respect to the rock structure will affect the tunnel behavior. Displacements measured at the walls of tunnels in highly anisotropic rock masses often reveal an asymmetric deformation pattern around the tunnel perimeter, which is often interpreted as the result of rock heterogeneity or changing geology. However, numerical and analytical investigation of tunnels in anisotropic rock masses show that the tunnel axis misalignment with the principal directions of stress and material anisotropy induce anti-symmetric axial displacements (i.e., axial distortion of the tunnel cross section) far behind the tunnel face. Near the face, the axial distortion is partially constrained, causing asymmetric radial displacements. In this study, tunnels excavated with and against dip of the major rock mass discontinuity are explored using 3D FEM modeling. A detailed analysis on the mechanisms associated with the direction of excavation is provided. It is shown that the asymmetric displacements near the face may strongly affect the displacements measured at the tunnel walls, which may explain the asymmetric displacements commonly observed on tunnels in anisotropic rock.

Raoof Gholami, Arshad Raza, Minou Rabiei et al.

Drilling through active shale formations has been a challenging practice in the oil and gas industry for a long period of time, given the complexity of shale structure and its interaction with Water Based Muds (WBMs). Although there have been many additives and methodologies proposed for a safe drilling through shale formations using WBMs, little success has been reported to the application of these methods once tested under different field conditions. In this paper, a new WBM formulated by nanomaterials was proposed to stabilize active shale layers during drilling. A series of rheological, density, filtration loss, bentonite dispersion and shale recovery tests were conducted on the mud samples formulated by nanosilica and Nano Glass Flakes (NGFs). The results indicated that NGF, as a cheap but effective nanomaterial, is able to significantly reduce the flirtation loss without posing any significant impacts on the density and the rheology of WBMs. It also appeared that the bentonite molecules were incapable to either hydrate or disperse in the drilling fluid system in the presence of NGFs. It seems that NGFs can stabilize clay minerals and reduce the filtration loss as remarkably efficient additive, but caution must be taken to ensure that they are properly disperse in the WBMs.

Peyman Jafarpour, Reza Ziaie Moayed, Afshin Kordnaeij

Permeation grouting with cement agent is one of the most widely used methods in various geotechnical projects, such as increasing bearing capacity, controlling deformation, and reducing permeability of soils. Due to air pollution induced during cement production as well as its high energy consumption, the use of supplementary materials to replace in part cement can be attractive. Natural zeolite (NZ), as an environmentally friendly material, is an alternative to reduce cement consumption. In the present study, a series of consolidated undrained (CU) triaxial tests on loose sandy soil (with relative density Dr = 30%) grouted with cementitious materials (zeolite and cement) having cement replacement with zeolite content (Z) of 0%, 10%, 30%, 50%, 70% and 90%, and water to cementitious material ratios (W/CM) of 3, 5 and 7 has been conducted. The results indicated that the peak deviatoric stress (qmax) of the grouted specimens increased with Z up to 50% (Z50) and then decreased. The strength of the grouted specimens reduced with increasing W/CM of the grouts from 3 to 7. In addition, by increasing the stress applied on the grouted specimens from yield stress (qy) to the maximum stress (qmax), due to the bond breakage, the effect of cohesion (c′) on the shear strength reduced gradually, while the effect of friction angle (φ′) increased. Furthermore, in some grouted specimens, high confining pressure caused breakage of the cemented bonds and reduced their expected strength. Keywords: Permeation grouting, Sand, Zeolite, Cement, Improvement

Kevin G. O'Dwyer, Bryan A. McCabe, Brian B. Sheil

In recent years, there has been an increased resort to microtunnelling/pipe-jacking as a means of constructing underground conduits (for water, sewage, gas, and other utilities) to avoid on-street disruption in urban areas. In this paper, technical details of two 1 200 mm internal diameter microtunnels in silty sand totalling over 550 m in length are discussed. While average skin friction values are extremely low for both drives suggesting effective lubrication practice, differences in normalised bentonite volumes appear to be responsible for differences in skin friction. Full or near full buoyancy of the pipeline has been demonstrated for the majority of the drive. The frictional stress increase after a stoppage is shown to depend on not only the stoppage duration but also on the normalised lubrication volume. Interpretation of data in the manner presented in the paper is an important means of assimilating experience of microtunnelling in different ground conditions.

Jean-Sebastien Spratt, Mauro Rodriguez, Kevin Schmidmayer et al.

Viscoelastic material properties at high strain rates are needed to model many biological and medical systems. Bubble cavitation can induce such strain rates, and the resulting bubble dynamics are sensitive to the material properties. Thus, in principle, these properties can be inferred via measurements of the bubble dynamics. Estrada et al. (2018) demonstrated such bubble-dynamic high-strain-rate rheometry by using least-squares shooting to minimize the difference between simulated and experimental bubble radius histories. We generalize their technique to account for additional uncertainties in the model, initial conditions, and material properties needed to uniquely simulate the bubble dynamics. Ensemble-based data assimilation minimizes the computational expense associated with the bubble cavitation model. We test an ensemble Kalman filter (EnKF), an iterative ensemble Kalman smoother (IEnKS), and a hybrid ensemble-based 4D--Var method (En4D--Var) on synthetic data, assessing their estimations of the viscosity and shear modulus of a Kelvin--Voigt material. Results show that En4D--Var and IEnKS provide better moduli estimates than EnKF. Applying these methods to the experimental data of Estrada et al. (2018) yields similar material property estimates to those they obtained, but provides additional information about uncertainties. In particular, the En4D--Var yields lower viscosity estimates for some experiments, and the dynamic estimators reveal a potential mechanism that is unaccounted for in the model, whereby the viscosity is reduced in some cases due to material damage occurring at bubble collapse.