Journal of Numerical Methods in Civil Engineering
Volume:3 Issue: 3, Mar 2019

Given the concept of reliability-based design (RBD) and the growing risk management trend in geotechnical engineering, proper understanding and quantification of uncertainties are very important. The complexity of methods and a large volume of calculations of probabilistic design methods are the most critical reasons for civil engineers not to be comfortable using these approaches. In this research, a practical probabilistic innovative approach is used to calculate the reliability index by applying the first-order reliability method (FORM). To analyze the bearing capacity of foundations, the Hansen method is used, and both static and seismic designs have been carried out. A scenario where the foundation is located above flat ground and another scenario where the foundation is located near the slope are both considered. Different angles of the slope are also considered. The reason for choosing two different angles for the slope is to examine the effect of slope increase on RBD. As we know, in the RBD of geotechnical structures, our knowledge of the statistical characteristics of variables is significant. That is why, in this paper, the effect of the parameters distribution type (normal or non-normal), the variables dependence, as well as the effect of coefficient of variation in the design results is evaluated. It is found that assuming normal distribution and independence of the variables yields conservative results. The coefficient of variation (COV) of variables is very influential on the results of RBD, and the effect of variation in the internal friction angle (φ) is more significant than variation in the other parameters.

In this paper, the dynamic response of a concrete gravity dam along with reservoir domain is investigated by frequency analysis and Latin hypercube sampling (LHS) statistical methods using finite element model. In this analysis, the frequency value is assigned to the model as an input variable. Then, the effects of frequency parameter are studied on maximum horizontal displacement of the dam crest, maximum tensile stress in the heel, maximum compressive stress in the toe and hydrodynamic pressure on the heel of the dam. The ANSYS software, according to finite element method (FEM), is applied for modeling and analysis. In order to represent the effect of the dynamic loading frequency, which is an important parameter in the analysis of the structures, the maximum response values are presented as sensitivity and probability curves. According to the sensitivity diagram of the hydrodynamic pressure response vs. the input frequency, it can be concluded that in the frequency of loading near the natural frequency of reservoir, the most critical condition occurs for seismic display, which should be highly considered in designing concrete dams.

The problem of bearing capacity of foundation under rigorous circumstances has always been of a great importance in geotechnical engineering. Various simple and also more sophisticated methods have been developed to improve the bearing capacity calculations. In this paper, the performance of three different approximate methods including the limit equilibrium analysis, upper and lower bound of the limit analysis, and the characteristic method of the slip line solution is evaluated and compared in dealing with marine soil deposits with the heterogeneous soil strength profile under the plane strain condition. The undrained bearing capacity of strip footing rested on a stratum with a linear variation of undrained shear strength was estimated using various methods. It was found that for all methods adopted in the bearing capacity estimation, the undrained bearing capacity increases with the strength density. As a result, the failure mechanism becomes shallower and narrower as the undrained shear strength increases with depth. Comparing the results obtained by the applied methods, the maximum bearing capacity is rendered by the limit equilibrium (assuming Terzaghi failure mechanism), resulting as an unsafe solution. On the contrary, the minimum bearing capacity is yielded by the stress characteristic method, as the most conservative and applicable solution.

In this paper, a new metaheuristic algorithm is developed to sizing optimization of truss structures with discrete variables. The proposed algorithms namely search and rescue optimization algorithm (SAR), imitates the exploration behavior of humans during search and rescue operations. The performance of the proposed algorithm is evaluated using several discrete truss design problems and the obtained results compared with the results of other optimization algorithms. The comparisons demonstrated that the best averages and standard deviations of results were obtained by SAR for all the studied problems and the proposed algorithm outperforms the other compared optimization algorithms in terms of finding the optimized weight of the truss (accuracy). According to the numerical results, it can be concluded that SAR is a very efficient and robust algorithm for designing truss structures with discrete variables.

In the construction of modern buildings, many pipes and ducts are necessary to accommodate essential services like water supply, sewage, etc. These pipes and ducts are usually placed underneath the concrete beams. However, for aesthetic reasons, they are covered by a suspended ceiling. Thus, to avoid increasing the height of the ceiling and dead load floor, it is more productive to pass the pipes and ducts through the beams of the ceiling. For this purpose, beams should be designed with openings. In this paper, beams with three spans and two types of uniform and non-uniform cross sections are modeled in SAP. Then beams are subjected to gravity and lateral loads and then analyzed. The results of SAP (flexural moment and shear force) are substituted in MATLAB code. Most appropriate opening positions are identified at  different parts of the spans in the code and it is observed that the weight of the consumed steel in uniform beam is more than the others in greater gravity load and a large hole. Finally, steel weight is optimized once for a specified cross-section of the beam with different heights of the hole and once again for a specified height of the hole with different cross-sections of the beam by Genetic algorithm (GA). The results show that the amount of steel weight in optimal state is less than its normal value. Therefore, by decreasing the height of the hole, the width, and height of cross-section, it will be reduced to the least amount.

As an essential issue in traffic crashes, human factor plays an indispensable role. This study uses the general health questionnaire (GHQ-12) within some socio-demographic and also a number of daily exercise related questions for prediction of traffic crashes among taxi drivers in the City of Tehran. A novel technique is been developed by applying nonlinear-learning of composition model of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) with M5 model tree. In order to improve the generalization ability of a single data driving algorithm, a cluster of ANFIS models with different nodes and hidden layers are implemented to extract the inherent relationship between traffic accident rates and human factors. The predictions of ANFIS models are combined applying a nonlinear weighted average method composed of M5 tree, and the PSO is utilized to find the optimal parameters of ANFIS models. The performance of the proposed model is evaluated in a case study and the relevant data are collected from a large group of Taxi drivers in the City of Tehran, Iran; as it was carried out to predict the associated accident rates. The Nash-Sutcliffe coefficient (NSE) and different error criteria are utilized to assess the prediction efficiency of the associated Hybrid model. Results indicate that the M5 tree is capable in enhancing the prediction accuracy of the novel model applied in the prediction of the accident rates as in comparison with the popular ANFIS model. Moreover, the linear relationships generated by M5 tree show the sensitivity of ensembled model accuracy on the single ANFIS models, which have a partial tendency in underestimation of the traffic crashes.