Civil Engineering

As an important part, Construction Industry provides important compositions for promotion of economy. Meanwhile most of projects have experienced various delays in a special form which are mostly for primary time and estimation of costs. Delay in construction is one of the specific problems with a converse effect on projects success from viewpoints of time, costs, quality and safety. This paper is about time function in dam making projects in Iran and defining any reasons for delay and also their severity according to the ideas of contractors and consultants through a questionnaire research. Its field research includes 34 contractors and 30 consultants. About 52 factors of delay were defined through this research. The conclusion of research was defining five serious reasons of delay including: Political conditions, Economic conditions, Limited imports, Granting of project with least tender prices, Delay in payment by employer and lack of equipment.

The adverse effects of erosion may be not much noticeable in short term, yet it will be important in long term. Soil loss and erosion is one major factor interfering reduced fertility, reduced products, deposition of materials in waterways, irrigation canals and rivers, a decrease in reservoir capacity of dams and their reduced life, floods, environment pollution and road closures. The current research was carried out using GIS technique and PSIAC model in order to estimate the erosion and sediment of Sardasht watershed located in Kohkiluyeh& BoyerAhmad province with an area of 5940 hectares. PSIAC studies erosion status and sediment production in a business unit based on the strength and weakness of 9 environmental factors including; geology, soil, climate, runoff, topography, land cover, land use, surface erosion and river erosion. Here, layers corresponding to model factors are prepared in GIS environment and, in the end, the amount of sediment is measured using spatial analysis and overlapping layers of information. In order to measure particular erosion, SDR index (ratio of precipitation evolution) was used and 27.88 tons per hectare per year was estimated as erosion amount for the area considered. In the evaluation of soil erosion and sediment production of Sardasht basin, among factors influencing the erosion, land cover and land use with highest ratio (15.24) are first and weather with lowest ratio (4.11) is the last in rank. Qualitative classification of basin based on PSIAC model guide shows that the basin as a whole is located in high erosion class. The approximation of results from the model considered (27.88 tons per hectare per year) with real statistical analysis (30.3 tons per hectare per year) shows that currently, this model is effective for the basin.

The application of artificial neural network (ANN) methodology for modeling flood prediction for a large size catchment of the river Jhelum in Jammu and Kashmir (India) is presented. Development of flood prediction models for river Jhelum, flowing through the Srinagar city (J and K ) based on the tail side discharge of upstream tributaries is studied because major inundation caused due to the floods in river Jhelum occurs in the highly populated and largely developing city of Srinagar. The 22 years data records between the years 1990-2012 were used and ANN technique along with conventional regression analysis was employed. The performance was compared based on statically parameters root mean squared error (RMSE), mean square error (MSE), coefficient of determination (R2) and absolute average deviation (AAD) values. NNtp model emerged as the best model with the highest value of R2 compared to other models as 0.93, value of MSE and RMSE being the least as 0.008 and 0.09 respectively. The study proved ANNs to be much better in predicting the flood discharge when judged on all the above parameters. It also showed that transfer function tan-sig performs better than pure-lin in the networks developed for flood prediction. The flood discharge could be thus predicted at least a day before the discharge reaches the station with a high predictability based on the ANN model NNtp.

The adopted strategy to overcome the housing shortage crisis in Iran is the mass production. The way forward to accelerate the mass production, is adopting the industrial building systems with the increased prefabrication. One of the most optimal new building systems is Lightweight Steel Framing (LSF) Technology. Parand Residential Complex as the first serious project to industrialize the construction processes in Iran is facing the various problems during the processes of manufacture and execution of LSF components. The research is to offer an optimized model for the manufacture and execution processes of LSF Technology in the constructive projects. So, the manufacture and execution processes of LSF Technology in the research case-study were taken into consideration to recognize the existing advantages and disadvantages. Finally, offering four strategies to compensate the deficiencies and three strategies to intensify the strengths, a model to coordinate these two processes presented.

In recent decades, duo to increase in population, demand for reliable water supplies has increased. The situation is critical in places where groundwater is the only accessible water resource and the discharge rate of water is more than the rate of recharge. In such areas, artificial recharge of groundwater is an important management strategy. In establishing an artificial recharge scheme, site Selection is the prime prerequisite and its success depends on the collection and analysis of a great deal of geographic data. The use of ELECTRE in site selection projects allows the decision-makers to incorporate unquantifiable information into decision model. In new researches of site selection multiple criteria decision- makers methods have been considered. In this paper, site selection of artificial groundwater recharges using an integrated method of ELECTRE has been carried out by raster layers in GIS. The result and findings of Research show that in ELECTRE method, zones (3,4) dominated (5) times and defeated (1) time, so it is located in the first rank with (4) points and is the most suitable zone for establish damp. In contrast, zone (1) defeated (6) time and dominated no time, therefore it is located in the last rank with (-6) points and is not the most suitable zone for artificial recharge. And, zones (5, 6, 7, 2,) dominated (4, 2, 1, 1) times and defeated (2, 4, 5, 5,) and located in other ranks with (2, -2, -4, -4) points respectively. Also, zones (7, 6, 2, 1) should be omitted because their defeated times are more than dominated times.