International Journal of Geo-Engineering最新文献

Abstract

Geodetic monitoring measurements (e.g., of terrain surfaces) are used to detect deformations. Terrestrial laser scanning (TLS) or unmanned aircraft systems (UAS) equipped with lightweight cameras are often utilized for land surveying, resulting in point clouds that represent the surface of the captured object. For image-based acquisition of the area of interest, point clouds must first be generated from overlapping images, for which the Structure-from-Motion (SfM) method is commonly used. To perform deformation analyses and derive changes from them, at least two temporally different measurement epochs of the same area are required. In this article, we present both point cloud- and feature-based models from TLS and SfM-based UAS point clouds. In addition, an image-based 2D approach using optical flow is applied as an example for landslide simulation to detect changes on object surfaces. To eliminate erroneous results in the analyses due to vegetation areas, the 3D data is filtered using the CANUPO algorithm. The results of this research study show, that the task of deformation detection has some challenges, depending on the use case and the methodology. The point cloud-based methods are suitable to detect pure changes between two point clouds. Also, the direction of these changes can be determined to distinguish between material uplift and downlift. In contrast, the feature-based descriptor (Fast Point Feature Histogram, FPFH) assigns pairs of points between two epochs based on similar geometry in both point clouds therewith individual movements can be detected. However, areas that have changed significantly cannot be assigned. Optical flow shows point changes in similar dimensions to the target deformations and allows deformation analysis with much less computational effort than with 3D point clouds. Considering these findings, point cloud-based method are suitable for determining surface-based information, while the feature-based and image-based methods are capable of extracting local changes.

Abstract

The main objective of the current investigation is to study the dynamic behaviour of a 3-pile group with different loading direction under coupled (horizontal and rocking) excitations. To accomplish this objective, machine-induced field excitation tests are conducted on small-scale hollow steel piles. The 3-pile group is driven into the ground in a triangular arrangement with 3d spacing. Two different soil-pile setups, i.e., Pile Group-I and Pile Group-II, are created based on dynamic force directions. In the case of Pile Group-I, the forces are applied to the direction of the median of the triangle, and for Pile Group-II, the forces are applied to other directional loads. From the test results, it is found that the resonant peaks of horizontal and rocking amplitudes for Pile Group-I are lower than Pile Group-II. In the case of resonant frequencies, the values of Pile Group-I are observed to be the same or a little bit higher as compared to Pile Group-II. It is found that the dynamic soil-pile-soil interaction effect is more prominent for Pile Group-II than for Pile Group-I. For numerical investigation, the continuum approach method is utilised with the inclusion of a dynamic group interaction factor to predict the dynamic coupled responses in terms of frequency and amplitude for these two soil-pile setups. To understand the behaviour of pile groups, boundary zone parameters and variations of impedance parameters (stiffness and damping) with operating frequencies are also measured using this theoretical approach.

Abstract

Frost heave action is a major issue in permafrost regions, leading to various geotechnical engineering problems. In this study, we assess the mechanical behavior of a concrete retaining wall subjected to frost heave under different ground conditions. The assessment utilizes ABAQUS integrated with several user subroutines. The numerical simulation model employs a thermo-mechanical coupled analysis with a porosity rate function, which enables to simulate time-dependent variations in porosity and frost heave of the backfill soil. After verification of the predictive reliability of the simulation model, the frost heave action in the soil and mechanical response of the retaining wall were evaluated regarding the initial groundwater level and presence of a drainage material on the backside of the retaining wall. According to the simulation results, as the initial groundwater level decreased in the backfill soil, the area susceptible to frost heave decreased. However, the von Mises stresses applied to the retaining wall increased. Under the same ground conditions, when the drainage material was installed on the backside of the retaining wall, the frost heave pressure acting on the wall significantly decreased, and less deformation and distortion of the retaining wall occurred.

As the anisotropic behavior of sandstones and limestone along the Khorramabad-Zal expressway has not been studied, this research aims to examine the impact of layer orientation on the strength characteristics and failure patterns of layered sedimentary rocks using the Brazilian test. For this purpose, a total of 8 rock blocks were gathered from Kashkan sandstones and Sarvak limestones in three different locations along the Khorramabad-Zal highway in western Iran. The core specimens were drilled with 54 mm diameter and parallel to the laminations. Overall 150 disc-shaped specimens were subjected to Brazilian tensile strength (BTS) in ten different anisotropy angles, which refers to the angle between the loading direction and the lamination plane. The findings revealed that the highest and lowest BTS values were obtained at β = 70° and 20° for all three types of rock. After analyzing the samples that experienced the Brazilian test and examining their failure patterns, three primary modes of failure were identified: parallel to the lamination (PL), across the lamination (AL), and curved fracture (CF). Furthermore, the transitional angle, which signifies the point at which the dominant pattern of failure shifts from PL to AL or from PL to CF, was also determined.

A novel mesh-free solution is proposed for kinematic shakedown analysis of cohesive soils under repeating loads. For this purpose, the continuous velocity field in the mathematical expression of Koiter’s theorem is discretized by the Radial Point Interpolation Method (RPIM), as a mesh-free approach. The strain rate smoothing technique is implemented in conjunction with the RPIM to satisfy the admissibility conditions at the entire problem domain. Using the nodal integration and the discretized velocity field, the kinematic shakedown problem is expressed as a nonlinear optimization problem. The optimization problem is solved by separation of plastic and non-plastic/rigid zones using a repetitive algorithm. Eventually, the efficiency of the proposed approach is elucidated by solving examples of a strip footing resting on cohesive soil and a cohesive half space pavement under repeating loads.

The present study proposes a novel ML methodology for differentiating between unstabilized aggregate specimens and those stabilized with triangular and rectangular aperture geogrids. This study utilizes the compiled experimental results obtained from stabilized and unstabilized specimens under repeated loading into a balanced, moderate-sized database. The efficacy of five ML models, including tree-ensemble and single-learning algorithms, in accurately identifying each specimen class was explored. Shapley’s additive explanation was used to understand the intricacies of the models and determine global feature importance ranking of the input variables. All the models could identify the unstabilized specimen with an accuracy of at least 0.9. The tree-ensemble models outperformed the single-learning models when all three classes (unstabilized specimens and specimens stabilized by triangular and rectangular aperture geogrids) were considered, with the light gradient boosting machine showing the best performance—an accuracy of 0.94 and an area under the curve score of 0.98. According to Shapley’s additive explanation, the resilient modulus and confining pressure were identified as the most important features across all models. Therefore, the proposed ML methodology may be effectively used to determine the type and presence of geogrid reinforcement in aggregates, based on a few aggregate material properties and performance under repeated loading.

In general, geotechnical investigations deal with the back analysis of the geotechnical parameters on the basis of the field observation. According to the back analysis method introduced in the present study, geometry of a number of failed slopes have been carefully mapped and then statistical features of the groundwater level, the bulk unit weight and other measurable parameters have been determined. After that, a series of two-dimensional models for back analysis of the failures have been established. Moreover, statistical analyses based on probabilistic approaches have been utilized to estimate the variation ranges of the shear strength variables. The study provided the probabilistic back analysis of the slope failure with the two case studies in the copper mines of Anjerd and Daraloo. Results indicated that the approach to the probabilistic back analysis has been effective in the analysis of the slope failures wherein considerable uncertainty has been observed in the shear strength and other influential variables. Furthermore, the probabilistic back analysis presented a lot of information in comparison to the approach to the deterministic back analysis and thus had more reasonable matching with the practice of geotechnical engineering in the real world. Therefore, this method would be beneficial and practical for stability analysis, redesigning the slopes, designing the new slopes under the same geotechnical conditions and promote the construction safety. The probabilistic back analysis could be also used to estimate the shear parameters and analyze the stability of slopes as a cost-effective and high reliability method.

The current study aims at predicting the strength of the problematic clayey soils treated with combinations of pozzolan of natural sources and lime powder when added as soil additives at a nano scale. Multiple linear regression (MLR), artificial neural networks (ANN) and fuzzy logic (FL) tools were employed in the analytical study. The variables of the present study include the following: nano pozzoaln of natural source (NNP) content, nano lime content (NL), median particle size of NNP, active silica content of NNP (SiO_2active), Initial liquid limit (ILL) and initial plastic limit (IPL) of the investigated soils. NNP was added at five percentages, i.e. 0%, 0.5%, 1%, 1.5% and 2%, while NL was added at five percentages, i.e. 0%, 0.3%, 0.6%, 0.9% and 1.2%. Three median particle sizes namely 50, 100 and 500 nm size were studied. Based on the different investigated soils and combinations, 120 soil mixtures were prepared and tested. California bearing ratio (CBR) and plasticity index (PI) were particularly examined. CBR tests were conducted at a soaked condition on specimens compacted to a maximum dry density (MDD) at the optimum moisture content (OMC). PI values were obtained following the Atterberg limits test. Based on the results of the performance criteria of the developed predictive models, it can be concluded that the CBR and PI of the expansive clayey soils can be effectively predicted using ANN and FL techniques. The results obtained by MLR were far from those obtained by both ANN & FL. In addition, ANN tool was slightly more accurate than FL as far as prediction of CBR and PI is concerned. The higher capability of ANN & FL models in predicting CBR & PI values, which generally obtained through time-consuming and expensive tests, could be useful for geotechnical engineers to assess or design a new pavement project. Further, it is recommended to do a re-evaluation of the current study in future, particularly when more data is available in the literature.

Purpose

Sincethe availability of natural aggregates is very sparse, recycled industrial and construction waste provides a sustainable alternative to ground improvement using vibro replacement method. Utilizing recycled building waste caters the requirement for its disposal and offers an effective remedy for the scarcity of natural resources. The aim of this study was to give a sustainable alternative for the natural aggregates as the material for stone column.

Materials and methods

A good stone column material should be hard, dense, chemically inert and must comply with the size requirement. The utilization of construction debris and spent railway ballast as column material has been the subject of numerous researches. This work focuses on finding the suitability of railway ballast and concrete debris as alternatives for stone column material. A detailed laboratory testing of these materials has been carried to judge their strength requirements as the material for both Ordinary Stone Columns (OSCs) and Geosynthetic Encased Stone Columns (GESCs). The improvement in capacity of both OSCs and GESCs is evaluated by performing California Bearing Ratio (CBR) test in laboratory by creating unit cell stone column models of different recycled aggregates and comparing their load settlement behavior with natural aggregates.

Results and discussion

Railway ballast, natural aggregates, concrete debris and virgin soil were found to show decreasing order in CBR test results. Loading required for causing settlement in both OSCs and GESCsshowed remarkable increase as compared to that of virgin clay and the maximum load settlement improvement was observed for railway ballast in both the types of stone columns. The CBR values for GESC made from railway ballast, natural aggregates and concrete debris were 54, 49 and 38% respectively. On the other hand, CBR for OSC made from railway ballast, concrete debris and natural aggregates were found to be 25.5, 20.4 and 24% respectively and CBR of virgin clay was found to be just 11%.

Conclusion

The demonstrated application of sustainable sources in place of natural aggregates provides a crucial pathway for utilizing the recycled aggregates as stone column filler material. Up on encasing the OSC with geotextile the performance of stone columns has improved appreciably in terms of load capacity. Railway ballast and concrete debris can be adopted as an alternate for the natural stone column materials to improve the bearing capacity of site consisting mainly of soft clays.