Earthwork Project Management, Slope Stability Analysis, and Wave-Based Testing Techniques

In most transportation infrastructure projects, earthworks are generally associated with the highest percentage costs and durations. Because these tasks are reliant on heavy machinery and repetitive tasks, they are strongly susceptible to optimization. This paper presents a study based on the application of artificial neural networks (ANN) on data originated from an actual earthwork construction project. Results show a good adjustment to the data while emphasizing the importance of optimal equipment allocation throughout the construction site. Finally, the architecture of an intelligent earthwork optimization system is presented, combining both data mining (DM) and modern optimization technologies, among others, to support equipment distribution optimization in earthwork projects.

Granite is widely spread out in South China. Under severe weathering actions in the subtropical hot climate, the product (granite residual soil) has very unique properties including low density with low compressibility, high in-situ strength yet can cause easy slope sliding during heavy rain. Granite residual soil represents typical problem soils in geotechnical engineering that include expensive soil, loess, etc.. However, compared to other problem soils, granite residual soil has not been studied extensively with few publications on its material properties and its inherent failure mechanisms. Thus, study of granite residual soil remains an important topic in geotechnical field. In this paper, undisturbed granite residual soils samples were collect from an actual building project site in Shenzhen. Triaxial tests were conducted on both undisturbed and remolded soil samples. From the test results, it was found that the initial structure of granite residual soil has significant influence on its behavior. The stress-strain relationships and suitable constitutive models are analyzed with comparisons between undisturbed soils and remolded soils.

Conducting the advancing surrounding rock classification is a piece of necessary work in the process of tunnel construction, which is directly related to subsequent excavation and construction support scheme. To conduct the classification of tunnel surrounding rock in advance effectively, the advancing surrounding rock classification method based on digital drilling technology and genetic algorithm (GA) support vector machine (SVM) is put forward. Based on the digital drilling technology, the method extracts the useful information from the drilling parameters and establishes advancing surrounding rock classification index system. To improve the discrimination precision of SVM in surrounding rock classification, GA was utilized to optimize the SVM parameters in the solution space. Finally, the surrounding rock classification model based on digital drilling technology and GA-SVM was established, which was applied to the advancing identification of surrounding rock classification in the Subsea Tunnel across Qingdao-Jiaozhou Bay, and the results showed that the method had high accuracy in advancing surrounding rock classification and provided a new idea for it.

The present work aims to establish a relationship between field and laboratory moduli obtained from mechanical wave measurements. In this scope, spectral analysis of surface waves (SASW) tests were performed on a clayey sand trial layer during running tests on a full-scale trial. Further, triaxial tests involving S-wave measurements with bender elements and accelerometers were conducted on specimens with similar state conditions, and laboratory shear modulus was determined. Both laboratory and field methodology for the determination of shear modulus was based on S-wave propagation through material, thus involving similar stress and strain levels. A clear match was observed between field and laboratory shear modulus. These results denotes a good relationship between field and laboratory modulus and assumes great importance taking into account that design is based on mechanical properties usually determined from laboratory tests.

Detecting the presence and extent of subsurface voids under a roadway structure is critical in preventing major disasters from occurring. In this study, a 400MHz ground coupled penetrating radar (GCPR) was utilized in two projects to locate voids. The air voids present a strong negative dielectric contrast to electromagnetic waves and, therefore, these anomalies are clearly identified on GCPR results/plots. Two case studies were presented in this paper. Electromagnetic waves were able to locate subsurface voids under the continuously reinforced concrete pavements. Fortunately, those subsurface voids have been identified before severe roadway failure occurred. Otherwise, those voids could have grown in size until the roadway eventually collapsed.

As a popular supporting structure for deep excavation pit or high soil slope, soil nailing has been widely accepted in many civil projects all over the world. In this paper, failure modes of the soil nailing structure are discussed according to its working mechanism and collapsing characters. Global sliding, partly sliding inside the supporting area and pullout of the soil nails are defined as principal failure modes of the supporting system. Considering the randomness of some parameters of calculation model, such as cohesion, inner friction angle of soil, and friction between soil and nail, failure probability of each failure mode could be computed by using the Monte-Carlo method. System failure probability of the soil nailing structure is determined by using of narrow boundary method, which could be used as an important criterion to analyze stability of the supporting system. Because it has included the influence of some random factors of soil and nailing system, the system failure probability method is better than the traditional safety coefficient method based on limit equilibrium theory. Last, the method is proved to be effective by an actual project.

Residual soils are widely distributed in south China. Its performance in many cases is like rock mixed soils (RSM). Water is a key triggering factor of slope failure. Rainfall and underground water seepage are typical. A special permeability test apparatus for RSM has been designed. Test results show that, when density of RSM keeps constant, with increase of mass percent of stone, coefficient of permeability also increases. Based on unsaturation seepage theory, two-phase flow theory in RSM is studied, which is coupled into free lossless automated codec (FLAC). In this numerical simulation based on FLAC, saturation degree distribution in RSM slopes under four types of rainfall combined underground water seepage is studied. From numerical results, compared with underground water seepage quantity, when rainfall quantity is not so big, then larger saturation degree is close to the bedrock, or it is close to the shallow layer. Then after some time, the saturation degree contour line extends.

In allusion to the uncertainty of engineering rock mass numerical calculation and stability evaluation, the equivalent rock mass parameter identification and stability analysis method have been studied according to onsite displacement monitoring. The basic ideas and the process of stability dynamic prediction numerical analysis method for engineering rock mass were introduced. This method is mainly used for orthogonal numerical analysis, using the least square method in regression analysis to establish the functional relation between engineering rock mass calculated displacement and rock mass parameters. Then, the minimum sum of the squares of the differences between measured displacement and the calculated displacement as the optimization goal according to the onsite monitoring information was used to determine the equivalent rock mass parameters of the corresponding monitoring displacement and slope situation. The proposed equivalent model identification and dynamic stability analysis method can be more reliable to predict rock mass deformation and its stability, playing an important role in guiding the actual production.

There are no available guidelines for lateral earth pressure envelope in gravel formations, especially for high gravel content ranging from 70% to 86%. Design of retaining structures and anchors in gravel is typically based on empirical experience and that was often too conservative. Therefore, this research collects 25 deep excavation cases in gravel deposits in Taichung areas. The value of apparent earth pressure had the tendency to increase as the depth of excavation increased. Comparison was made with the apparent earth pressure envelopes. The acquired shape of the envelope was trapezoid. However, the value of the coefficient of apparent earth pressure was less than half of the values suggested by various researchers. The distributions of apparent earth pressure at different excavation depths, 15, 20, and 27 m, could be obtained and normalized based on this study. The shape of the envelopes is similar to the one suggested by researchers, but the apparent earth pressure is much less.

This paper presents a new method of analyzing the slope stability that considers the spatial variability of soil properties from the probabilistic point of view. Orthogonal decomposition is performed to spatial covariance matrix of soil strength by Karhunen-Loève expansion (K-L). Then the Latin hypercube sampling (LHS) and the Cholesky decomposition methods are used to optimize the generated spatial random fields. In the proposed method, a readily available concise algorithm is utilized to calculate the factor of safety for each preset slip surface. The optimization technique is then adapted to search for the global critical slip surface. The generated samples are examined to be rational because they are good enough to match the objective function. Results showed that the samples could reduce the simulation number greatly compared to the Monte Carlo (MC) method, whereas the calculated failure probabilities from the LHS method and MC methods were close to one another. Sensitivity analysis of geometric parameters showed that the correlation length exerts minor influence on the slope stability. The failure probability increased with the increasing of slope angle, slope height and the coefficient of variability. For a given slope, the results showed that only the combined use of factor of safety and failure probability could be effective enough for the slope safety evaluation.

This paper examines two numerical methods commonly used in shoring design, namely the beams on elastic foundation method using WALLAP and the finite element method (FEM) using PLAXIS. Numerous design parameters are also investigated to study the effects of the parametric variations on each method. The shoring model analyzed in this study is based on a deep excavation project in the Sydney central business district. One of the significant findings of this study was that the results obtained from both WALLAP and PLAXIS showed marginal numerical errors, which, in turn, need to be examined closely. Generally, the beams on elastic foundation method are more conservative than the FEM. In comparison with the FEM, the soil modulus has more significant effects than the shear strength parameters in the beams on elastic foundation method. Moreover, the resulting shear forces, bending moments, and lateral displacements of the shoring are less sensitive to the variation of the soil friction angle than the cohesion. The findings of this study can be taken into consideration by practicing civil engineers when designing appropriate shoring systems in urban areas.