Abstract: Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.
Abstract: In recent years, new techniques for solving complex
problems in engineering are proposed. One of these techniques is
JPSO algorithm. With innovative changes in the nature of the jump
algorithm JPSO, it is possible to construct a graph-based solution
with a new algorithm called G-JPSO. In this paper, a new algorithm
to solve the optimal control problem Fletcher-Powell and optimal
control of pumps in water distribution network was evaluated.
Optimal control of pumps comprise of optimum timetable operation
(status on and off) for each of the pumps at the desired time interval.
Maximum number of status on and off for each pumps imposed to the
objective function as another constraint. To determine the optimal
operation of pumps, a model-based optimization-simulation
algorithm was developed based on G-JPSO and JPSO algorithms.
The proposed algorithm results were compared well with the ant
colony algorithm, genetic and JPSO results. This shows the
robustness of proposed algorithm in finding near optimum solutions
with reasonable computational cost.
Abstract: Carefully scheduling the operations of pumps can be
resulted to significant energy savings. Schedules can be defined
either implicit, in terms of other elements of the network such as tank
levels, or explicit by specifying the time during which each pump is
on/off. In this study, two new explicit representations based on timecontrolled
triggers were analyzed, where the maximum number of
pump switches was established beforehand, and the schedule may
contain fewer switches than the maximum. The optimal operation of
pumping stations was determined using a Jumping Particle Swarm
Optimization (JPSO) algorithm to achieve the minimum energy cost.
The model integrates JPSO optimizer and EPANET hydraulic
network solver. The optimal pump operation schedule of VanZyl
water distribution system was determined using the proposed model
and compared with those from Genetic and Ant Colony algorithms.
The results indicate that the proposed model utilizing the JPSO
algorithm is a versatile management model for the operation of realworld
water distribution system.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial
Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water
flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by
sensors to construct an empirical model for time series prediction and
classification of events. These two components have been installed,
tested and verified in an experimental site in a UK water distribution
system. Verification of the system has been achieved from a series of
simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network
management.