Any reliability analysis based on just deterministic values of daily average or peak demands, cannot represent the overall system reliability realistically. Using a stochastic model in this paper variations of the system and nodal reliability values are investigated through a period of time. Considering probabilistic nature of demands, this paper combines the extended period simulation of water...

Cascade-Correlation (CC) network is a new architecture and supervised learning algorithm for artificial neural networks. The learning algorithm of CC network and its network structure are described in this paper, the CC network with an excellent fitting ability is applied to fitting vibration characteristics of hydraulic turbine units according to different parts under three water heads. Compar...

Artificial Neural Networks (ANNs) have proved to be good modelling tools in hydrology for rainfall-runoff modelling and hydraulic flow modelling. Representative datasets are necessary for the training phase in which the ANN learns the model’s input-output relations. Good and representative training data is not always available. In this publication Genetic Algorithms (GA) are used to optimise tr...

This paper describes and demonstrates a method for on-line hydraulic state prediction in urban water networks. The proposed method uses a Predictor-Corrector (PC) approach in which a statistical data-driven algorithm is applied to estimate future water demands, while near real-time field measurements are used to correct (i.e., calibrate) these predicted values on-line. The calibration problem i...

Many techniques, approaches and tools were used in this Research to achieve the Methodology. Using artificial neural network to simultaneous hydraulic parameters is one of these techniques. Transmissivity and storativity consider the most important parameter in each aquifer due to the reality of their effect on the aquifer properties. In this research, it is assumed that the transmissivity (T) ...

energy costs comprise considerable amount of operation costs in water distribution networks. optimal management of energy costs to provide required water for consumers with desired quality is of high importance. to achieve this, optimization is defined as a powerful tool. in this paper, by focusing on operation phase, multi-objective optimization of water supply network considering hydraulic, q...

The desiccation of upper soil horizons is a common phenomenon, leading to a decrease in soil microbial activity and mineralization. Recent studies have shown that fungal communities and fungal-based food webs are less sensitive and better adapted to soil desiccation than bacterial-based food webs. One reason for a better fungal adaptation to soil desiccation may be hydraulic redistribution of w...

The increasing demand for sufficient and clean energy forces industrial and service companies to align their strategies towards efficient consumption. This trend refers also to the residential building sector. There, large amounts of energy consumption are caused by house and facility heating. Many of the operated hot water heating systems lack hydraulic balanced working conditions for heat dis...

Hydraulic fracturing has been used widely to stimulate production of oil, natural gas, and geothermal energy in formations with low natural permeability. Numerical optimization of fracture stimulation often requires a large number of evaluations of objective functions and constraints from forward hydraulic fracturing models, which are computationally expensive and even prohibitive in some situa...

The Big Bang-Big Crunch (BB–BC) method is a relatively new meta-heuristic algorithm which inspired by one of the theories of the evolution of universe. In the BB–BC optimization algorithm, firstly random points are produced in the Big Bang phase then these points are shrunk to a single representative point via a center of mass or minimal cost approach in the Big Crunch phase. In this paper, the...