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In this research a mathematical model was developed to study bed elevation variation of alluvial rivers. It utilizes two principal modules of hydraulics and sediment transport for simulation purposes. SDAR (Scour and Deposition model of Alluvial Rivers) is a new model with both one and semi-two dimensional (S-2D) computational schemes. It is regarded S-2D in a sence that lateral variation of velocity, hydraulic stresses, and geometrical specifications are achieved by dividing the main channel into serveral stream tubes. In order to overcome the existing limitations, a new idea of reachwise stream tube concept was also introduced. This allows to include branch connections and withdrawal points across the tube barriers. Sediment routing and bed variation calculations are accomplished along each river strip desigated by virtual interfaces of the tubes. Presently, quasi-steady gradually varied flows are processed by the model. It should also be emphasised that this version is only valid for alluvial rivers composed of noncohesive bed material. To assess the model, several river cases and laboratory data base were used. During calibration runs, the ability of model in longitudinal and transversal bed profile simulation and armor layer development predection were especially detected. Results of simulation are also compared with the results of well-known models, e.g. HEC-6, GSTARS-2, and FLUVIAL-I2. It was found that the ability of model in simulating bed variation is noticeably increased when S-2D concept is introduced. Indeed, the comparative validity tests confirm SDAR"s promising functioning in facing with complex real engineering cases. Obviously more article discussions would bring oppurtunities to demonestrate it"s technical cappabilities profoundaly.

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A novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (WDS) for the purpose of its hydraulic model calibration is presented. The problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. The objectives are to maximise the calibrated model accuracy and to minimise the number of sampling devices as a surrogate of sampling design cost. Model accuracy is defined as the average of normalised traces of model prediction covariance matrices, each of which is constructed from a randomly generated sample of calibration parameter values. To resolve the computational time issue, the optimisation problem is solved using a multi-objective genetic algorithm and adaptive neural networks (MOGA-ANN). The verification of results is done by comparison of the optimal sampling locations obtained using the MOGA-ANN model to the ones obtained using the Monte Carlo Simulation (MCS) method. In the MCS method, an equivalent deterministic sampling design optimisation problem is solved for a number of randomly generated calibration model parameter samples.The results show that significant computational savings can be achieved by using MOGA-ANN compared to the MCS model or the GA model based on all full fitness evaluations without significant decrease in the final solution accuracy.

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The objective of this paper is to determine the drift demand hazard curves of steel moment-resisting frames with different number
of stories in territory of Tehran this is done through the combination of the results obtained from probabilistic seismic hazard
analysis and the demand estimated through the best probabilistic seismic demand models. To select the best demand model, in
this paper, a Bayesian regression has been used for the statistical analysis of the results obtained from incremental dynamic
analysis in order to estimate the unknown parameters of model and to select the best Intensity Measure (IM) parameter also the
probability of overall collapse of structures has been computed. Considering the efficiency and sufficiency of the models, the
results indicate that the accuracy of models with one single IM is a function of the number of stories, consequently the current
widely used model with spectral acceleration in first period as IM is not suitable for all structural heights. Furthermore,
regarding the fact that it is difficult to prepare a seismic hazard curve for a combined IM, it seems that the best model can be
found among models with two single IMs. In other words, the best model to cover all structural heights is the one with linear
combination of spectral acceleration of the first and the second period. Furthermore, using different models to calculate the
curves shows that regardless of the number of IMs, estimated demands strongly depend on the standard deviation of model.
 

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Compared to conventional chlorination methods which apply chlorine at water treatment plant, booster chlorination has almost

solved the problems of high dosages of chlorine residuals near water sources and lack of chlorine residuals in the remote points

of a water distribution system (WDS). However, control of trihalomethane (THM) formation as a potentially carcinogenic

disinfection by-product (DBP) within a WDS has still remained as a water quality problem. This paper presents a two-phase

approach of multi-objective booster disinfection in which both chlorine residuals and THM formation are concurrently optimized

in a WDS. In the first phase, a booster disinfection system is formulated as a multi-objective optimization problem in which the

location of booster stations is determined. The objectives are defined as to maximize the volumetric discharge with appropriate

levels of disinfectant residuals throughout all demand nodes and to minimize the total mass of disinfectant applied with a specified

number of booster stations. The most frequently selected locations for installing booster disinfection stations are selected for the

second phase, in which another two-objective optimization problem is defined. The objectives in the second problem are to

minimize the volumetric discharge avoiding THM maximum levels and to maximize the volumetric discharge with standard levels

of disinfectant residuals. For each point on the resulted trade-off curve between the water quality objectives optimal scheduling of

chlorination injected at each booster station is obtained. Both optimization problems used NSGA-II algorithm as a multi-objective

genetic algorithm, coupled with EPANET as a hydraulic simulation model. The optimization problems are tested for different

numbers of booster chlorination stations in a real case WDS. As a result, this type of multi-objective optimization model can

explicitly give the decision makers the optimal location and scheduling of booster disinfection systems with respect to the tradeoff

between maximum safe drinking water with allowable chlorine residual levels and minimum adverse DBP levels.

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In the water industry tunnels can be used to transfer water from a basin to other areas over varying distances. The construction of such tunnels is inherently risky and can result in unpredicted events and incidents. It is therefore necessary that thorough risk assessments are carried out as a priority of the owner, contractor and consultant organization. This is so that, through a systematic and logical plan, they can risk posed by these unforeseen events and incidents. In this paper, the risks and their main causes which are often encountered in such projects are identified and assessed. A fault tree method is applied in order to identify the main causes of events and incidents. By its nature a Risk assessment cannot be defined by absolute values and so fuzzy data must be used in order to calculate the probability of incidence and the severity of the risk. This is done on the four main criteria of time, cost, quality and safety. In order to estimate the significance of each criterion and to calculate the significance of the total influence of risk Analytic Hierarchy Process (AHP) is applied. In this paper the case study of Dasht-e Zahab water conveyance tunnel has been selected for discussion as it was subjected to severe and multiple hazards. The results obtained using the method were validated by conducting different interviews with the field experts. It was concluded that by applying the proposed methodology on the case study the risks of the project can be evaluated in a more methodical and accurate way than could be done without using the method. This approach is therefore recommended for similar types of projects where there are complicated risks that must be thoroughly investigated and understood.