JOURNAL OF NEW APPROACHES IN CIVIL ENGINEERING
Year:2018 | Volume:1 | Issue:2 |Papers Count:4

In the present study static response of cantilever retaining walls have been investigated by consideration of various soil constitutive models by means of finite element method with using PLAXIS 2-D software. Simulations have been performed at heights of 3, 6, and 9 meters retaining walls with considering two types of soils (cohesive and cohesionless) as backfill material. In this study, analysis have been conducted for two kinds of cohesionless backfill (loose and dense sand in dry condition) and at both conditions, saturated and unsaturated, for cohesive backfill. Analysis have been carried out by using three constitutive behavioral methods: Mohr-Coulomb (MC), Hardening-Soil (HS) and Hardening soil model with Small-Strain stiffness (HSS) for cohesionless backfill and additional method, Soft Soil model (SS), for cohesive backfill. The results show that, for cohesionless and cohesive backfill materials the lateral forces acting on the retaining wall are underestimated by the MC and SS constitutive models, respectively.

The need for rapid construction of the tunnel along with the safety of surface structures has increased the use of mechanized tunnel boring machines in the urban environment. In this paper, shield mechanized tunneling is introduced as one of the modern tunneling methods. In the following, the mechanism of operation of the TBM-EPB as the most commonly used boring machine in urban environments, along with the benefits of using this device, and the new technologies in the design of all-section boring machines, are introduced. Considering the importance of surface settlement in urban environments, controlling soil pressure, continuous injection of grout and controlling the volume of excavated materials, is one of the most important ways of preventing surface settlement in tunneling using a mechanized boring machine. In this study, the Plaxis software is used to investigate the effect of cement grout injections between the outer surface of concrete linings and the shield of the machine during tunnel boring operations on the surface settlement.

Nowadays, the phenomenon of global warming due to the emission of greenhouse gases by mankind is seen as an important environmental concern that endangers future prosperity. Carbon dioxide gas has the greatest impact on the global warming phenomenon among greenhouse gases in the atmosphere. Increasing greenhouse gas emissions, including carbon dioxide, results in global warming, rising sea levels and occurrence of biologic changes in the environment, subsequently it leads to the damage to plants, animals and ecosystems. In the present study, the approximate amount of carbon dioxide generated by industries in the industrial town was estimated, and then the amount of green space needed for its control and management is calculated, so in this regard, the information of 39 industrial units from different types of production is compiled and then analyzed. Based on the calculations, the approximate amount of CO2 generation in the region was 2105738 kg per day or 768594 tons per year. To absorb and control this amount of CO2 around 35 million trees per year and 23333 hectares of arable land are required. Based on the obtained values, complete management of generated carbon dioxide by green space and tree planting in that area is impossible. It should be noted that these values are calculated for all industrial units of the town in active mode, considering the closure of some of the industrial units, the actual amount will certainly be less than the calculated value.

Simulation and evaluation of sediment and extending the relation among streamflow and sediment is an important and applicable issue in the water resource management which is useful in the organizing reservoirs, rivers and avoiding additional costs. In this paper, the efficiency of Wavelet-based Support Vector Machine (WSVM) model was examined for prediction of monthly Suspended Sediment Load (SSL) of the Aji-Chay River. Then for this purpose, at first step, SSL was predicted via ad hoc SVM and Artificial Neural Network (ANN) models. Therefore in the hybrid models, streamflow and SSL time series were decomposed into sub-signals via wavelet transform, and these decomposed subseries were imposed into SVM and ANN to simulate discharge-SSL relationship. The results showed that SVM yield to better outcomes with Determination Coefficient (DC)= 0.65 than ad hoc ANN with DC=0.61. On the other hand, WSVM showed better consequences than wavelet-based ANN (WANN) model in monthly SSL prediction, and wavelet data pre-processing could lead to catch more accurate results, e.g., DCLSSVM=0.65 was increased to the DCWLSSVM=0.82.