Objective of the present research is to identify, analyze, and assess risk of Paveroud Dam during construction phase. Following collection and analysis of the information related to environmental conditions of the area of study and technical specifications of dam construction, a list of probable risk factors was prepared in the form of a questionnaire, and for verification, the questionnaires were provided to a group of specialists consisting of elites and professors specialized at the disciplines relevant to environment and civil engineering. Number of questionnaires was determined based on Cochran’s formula. In the first step, the expert group in the research was asked to score in Likert scale format so as to analyze the acquired responses and the risks present in the region. Having analyzed the scores using the findings of PHA method, TOPSIS technique was applied to prioritize the identified risks of Paveroud Dam. The results indicated that erosion had the highest priority among 36 risk factors. After prioritization among the risk factors, risk was also assessed using RAM-D technique in which “impact on Sorkhabad Protected Zone with 9 scores, “erosion” with 6 scores, and “work at high elevation” with 3 scores were recognized as three major risks of Paveroud Dam. In order to mitigate the effects of dam risks during construction phase, environmental management planning is crucial, and for this purpose, risk mitigation choices were recommended at the end aimed at coping with the identified risks.
The Sharbyan river is located in the Sharbyan village, Sarab, East Azarbaijan province. This river alluvials are supplied from rock units belonging to Oligo-miocene and Miocene, including conglomerate, sandy lime, limestone, marl and shale. These deposits are used as raw materials of producing hot asphalt in two asphalt plants that have been built in the vicinity of this river, and the produced asphalt is used mainly in the neighbor provinces that have rather cold climate. Combined analysis of the sediments indicate high level of silica, around 60 percent, for which the prepared asphalt is prone to stripping phenomenon in the cold seasons. During this process, the moisture penetration in aggregates and asphalt mixtures, causes weakening bitumen-asphalt materials bounding and finally asphalt demolition. The role of sediments and its impact on the quality of asphalt has not been studied in this area, therefore, the solutions for dealing with this phenomenon is also examined and presented. This study is based on the conventional sedimentology methods, different standards of ASTM, AASHTO and Ministry of Roads and Urban Development guidelines. In this study, the combined effects of hydrated lime (lime filler) and natural filter materials with different proportions was used to deal with the stripping phenomenon, and the parameters of strength, softness, indirect tensile strength, asphalt quality and durability criteria, have been appraised. The results show that these parameters are improved using additives in various proportions and the produced asphalt quality and durability is better. The results illustrate, when the lime is used in its maximum ratio of 3%, stripping score is 1 and is disappeared by other parameters improvement
Previous earthquakes have shown that topographic irregularities have significant impacts on the site seismic response and increasing structural damage by amplifying seismic responses. Studies on seismic behavior of slope topographic have shown that dynamic response of free field and soil-structure system is severely on the influence of topography shape and soil properties. Angle and height of slope, frequency of excitation, nonlinear behavior of soil and depth of bedrock are other parameters that affect on the response of the entire system. Furthermore the studies have shown that presence of structure adjacent to slope is very effective on variation of seismic behavior pattern of this topography but these studies are very limited. In this study the effect of existing structure adjacent to slope to seismic behavior pattern of slope topography have been investigated. The parameters that have studied in this article comprise slope angle and frequency content of excitation. The results show that the presence of structure adjacent to the slope, causes an increase to the response of free field and transmitting maximum response to distance away from structure position.
Maximum surface settlement (MSS) is an important parameter for the design and operation of earth pressure balance (EPB) shields that should determine before operate tunneling. Artificial intelligence (AI) methods are accepted as a technology that offers an alternative way to tackle highly complex problems that can’t be modeled in mathematics. They can learn from examples and they are able to handle incomplete data and noisy. The adaptive network–based fuzzy inference system (ANFIS) and hybrid artificial neural network (ANN) with biogeography-based optimization algorithm (ANN-BBO) are kinds of AI systems that were used in this study to build a prediction model for the MSS caused by EPB shield tunneling. Two ANFIS models were implemented, ANFIS-subtractive clustering method (ANFIS-SCM) and ANFIS-fuzzy c–means clustering method (ANFIS-FCM). The estimation abilities offered using three models were presented by using field data of achieved from Bangkok Subway Project in Thailand. In these models, depth, distance from shaft, ground water level from tunnel invert, average face pressure, average penetrate rate, pitching angle, tail void grouting pressure and percent tail void grout filling were utilized as the input parameters, while the MSS was the output parameter. To compare the performance of models for MSS prediction, the coefficient of correlation (R2) and mean square error (MSE) of the models were calculated, indicating the good performance of the ANFIS-SCM model.
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