Ram Kailash Prasad

Extended Period Simulation of Pressure-Deficient Networks Using Pressure Reducing Valves

Generally, the water distribution networks are designed for peak demands so that under normal operating conditions pressure is adequate to meet the nodal demand however, due to this, the pressure remains excessive when the consumption is low. This leads to huge water leakages and pipe bursts due to excess available pressure. These excess of pressure can be reduced by operating pressure reducing valves. Moreover, the pressure deficient conditions of water distribution network depends on many factors such as excess demand (i.e., fire fighting demand), location and elevation of nodes, location and pressure setting values of pressure reducing valve, ageing of pipes (i.e., increase the pipe roughness) etc. In exceptional situations, pressure deficient condition also may occur when there is a fire demand while pressure reducing valves are in operating condition. The available literature of the pressure deficient condition as well as optimal location, number and their pressure setting values of pressure reducing valves are analysed by mathematical programming or optimization methods. Normally, it is cumbersome to the field engineers to use the any toolkit utility functions. Hence in this study, the pressure deficient condition is analysed via the method of modified pressure-deficient network algorithm without using EPANET toolkit functions which are coupled with pressure reducing valve operation. A benchmark problem is analysed and compared for the proposed method. Further, a real water distribution networks is analysed introducing fire demand at junction/distribution node using fixed and diurnal nodal demand pattern coupled with and without pressure reducing valve operation in a single hydraulic simulation.

Optimal design of an in-situ bioremediation system using support vector machine and particle swarm optimization

A methodology based on support vector machine and particle swarm optimization techniques (SVM-PSO) was used in this study to determine an optimal pumping rate and well location to achieve an optimal cost of an in-situ bioremediation system. In the first stage of the two stage methodology suggested for optimal in-situ bioremediation design, the optimal number of wells and their locations was determined from preselected candidate well locations. The pumping rate and well location in the first stage were subsequently optimized in the second stage of the methodology. The highly nonlinear system of equations governing in-situ bioremediation comprises the equations of flow and solute transport coupled with relevant biodegradation kinetics. A finite difference model was developed to simulate the process of in-situ bioremediation using an Alternate-Direction Implicit technique. This developed model (BIOFDM) yields the spatial and temporal distribution of contaminant concentration for predefined initial and boundary conditions. BIOFDM was later validated by comparing the simulated results with those obtained using BIOPLUME III for the case study of Shieh and Peralta (2005). The results were found to be in close agreement. Moreover, since the solution of the highly nonlinear equation otherwise requires significant computational effort, the computational burden in this study was managed within a practical time frame by replacing the BIOFDM model with a trained SVM model. Support Vector Machine which generates fast solutions in real time was considered to be a universal function approximator in the study. Apart from reducing the computational burden, this technique generates a set of near optimal solutions (instead of a single optimal solution) and creates a re-usable data base that could be used to address many other management problems. Besides this, the search for an optimal pumping pattern was directed by a simple PSO technique and a penalty parameter approach was adopted to handle the constraints in the PSO. The results showed that the costs involved in the proposed management solution were consistent with that resulting from other nontraditional optimization techniques which use embedded/linked bioremediation simulation models. Moreover, an optimal transient pumping strategy resulted in an overall reduction in pumping cost by almost 20% when compared to cases where a steady state pumping strategy was adopted. A considerable reduction in the number of simulations was achieved using the SVM approach.

Simulation of Water Distribution Network under Pressure-Deficient Condition

Pressure deficient condition occurs in the water distribution network (WDN) when the nodal demands are in excess of the design discharge as in the case of fire demand, pump failure, pipe breaks, valve failure etc. It causes either no-flow or partial-flow depending upon the available pressure head at the nodes. To evaluate the nodal flows in such condition, node flow analysis (NFA) gives reasonable results in comparison to demand-driven analysis (DDA) and head-dependent analysis (HDA). The NFA works on the predefined pressure-discharge relationship to evaluate the nodal flows. However, this approach requires human intervention and hence cannot be applied to large WDN. Recently, modified pressure-deficient network algorithm (M-PDNA) has been developed by Babu and Mohan (2012) for pressure-deficient analysis with EPANET toolkit. However, it requires modification of the source code of EPANET. In this study a relationship with the M-PDNA and node flow analysis (Gupta and Bhave 1996) has been investigated and it is found that M-PDNA is the simplified version of NFA. Further, the working principle of M-PDNA has been investigated with suitable examples of Babu and Mohan (2012). The theoretical basis of M-PDNA has not been investigated in terms of head-discharge relationship. Herein, a head-discharge relationship based on the working principal of M-PDNA is proposed. Some of the toolkits are also readily available to modify demand driven solver of EPANET 2 to suit for the pressure-driven analysis and then it can be used for analysing pressure deficient network. Also in this study, a modification in M-PDNA approach is proposed which does not require the use of EPANET toolkit which is found to be capable of simulating both pressure-sufficient and pressure-deficient conditions in a single hydraulic simulation. Using the proposed approach, pressure-deficient condition is analysed with constant and variable demand pattern.

In-Situ Bioremediation of Contaminated Groundwater using Artificial Neural Network

A methodology has been developed in this study to optimize pumping (extraction/injection) rates in in-situ bioremediation system design with the aid of Artificial Neural Network (ANN). The equation governing in-situ bioremediation system consists of the flow equation and the equation of solute transport coupled with biodegradation kinetics, that results into a highly non linear system of equations. Consequently, the computational effort involved is a significant problem in the design of bioremediation systems. In this study, the computational burden is managed within practical time frame by replacing the BIOPLUME III simulation model with an ANN model. Artificial Neural Network has been considered to be a universal function approximator that generates fast solutions in real time. Besides this, the search for the optimal pumping pattern is directed by a simple genetic algorithm in this study. The results show that the costs involved in the proposed management solution is consistent with those resulting from other non traditional optimization techniques which use embedded bioremediation models. However, it has been observed that one can achieve considerable decrease in the number of simulations involved using the ANN approach.

Analysis of Water Distribution Network Using Epanet and Vertex Method

The analysis of hydraulic behavior of the water distribution network (WDN) is forefront part of the planning and augmentation of any water supply projects. The analysis of WDN determines the estimation of discharges, hydraulic gradient levels (HGL), nodal concentrations, etc., to fulfill the requirements of population. In the conventional approach of analysis, unique value of pipe discharges and hydraulic heads are obtained. The results so obtained may not give satisfactory performance in practice due to many uncertainties in nodal demands, pipe roughness, lengths, diameters of pipes, water levels in reservoirs, head-discharge characteristics of pumps, etc. In this study, the uncertainty in discharges and hydraulic heads are evaluated using two different pipe networks, the data for which is obtained from literature. Further, the membership function of pipe roughness has been used to calculate the membership function of discharges and hydraulic heads by incorporating EPANET with vertex method of fuzzy approach. The uncertainties in discharges and hydraulic heads at different α-cuts are evaluated considering the uncertainties in pipe roughness. The results of pipe discharges are found to vary between 15 and 30 % whereas the hydraulic heads at nodes vary between 0.3 and 3 m when the uncertainty is about 8 % in Hazen–Williams coefficient of pipe roughness in selected four- and five-pipe networks, respectively. Moreover, when the uncertainty of pipe roughness is combined with other kind of uncertainties as discussed above, would further aggravate the uncertainty in pipe discharges and nodal heads. As a result, the reliability of network would decrease in terms of either meeting the required discharges or the nodal heads to the consumers. This study would help to design the pipe network under the conditions of uncertainty in input parameters.

Uncertainty Analysis of Water Distribution Networks Using linked EPANET-Vertex Method

The analysis of hydraulic behaviour of the water distribution network (WDN) is forefront part of the planning and augmentation of any water supply projects. The desired output parameters such as pipe discharges, hydraulic gradient level (HGL) of nodes, nodal concentrations etc., are normally crisp values assuming crisp input parameters. There are many uncertainties in nodal demands, roughness, length, diameters of pipes, valve operations, water levels in reservoirs, head-discharge characteristics of pumps etc. So the results obtained by traditional method keeping the input parameters as crisp may not give satisfactory performance in practice. Hence taking care of this fact, pipe roughness has been considered as fuzzy parameter in this study. The vertex method has been used to obtain the ordered pair values of pipe roughness at each α-cut level. The hydraulic simulations are done by using EPANET 2 in MATLAB environment. The maximum and minimum values of pipe discharges, nodal HGLs are obtained in single simulation run for each α-cut level. The obtained results are compared with past studies and it is found that current method is effective to analyse the uncertainty problem. This study would help to the decision maker to identify the condition of pipes and consequently the corrective action needed.

Groundwater remediation using simulation-optimisation approach: A review

Optimal design of a remediation system has been an active and important area of research since the past several years due to its potential to reduce the remediation cost substantially. The paper presents the state-of-the-art for application of simulation-optimisation approach to design an optimal groundwater remediation system. In the simulation-optimisation approach, the researchers have used embedded techniques, response matrix approach and direct coupling of simulation model in optimisation procedures. The review shows that the simulation-optimisation approach promise for a cost-effective solution to groundwater remediation problems. Further, the methods dealing with uncertainty in model parameters are also discussed. It is observed that future research in this area should be directed to efficient solution methods incorporating uncertainty in groundwater remediation.

Optimal Reservoir Operation with Environmental Flows for Ranganadi Hydroelectric Project in Arunachal Pradesh

Optimal release policy for hydro power has been developed extensively in the past for several river basins in India and abroad. However, there is a lack of available literature which takes into account the optimal release along with the necessary environmental flow to the downstream side. As a consequence several hydropower projects are facing problem due to the environmental concerns. In Arunachal Pradesh, some of the hydropower projects are under critics basically due to environmental factors. In this study, a formulation has been developed to obtain the optimal release for hydropower for Ranganadi Hydro Electric Project (RHEP) in Arunachal Pradesh, considering the constraints of minimum environmental flow. Traditionally reservoirs used to be operated without considering the environmental flows. Whenever the release to the downstream side (or overflow) is to be considered, the flow exceeds the active storage capacity of the reservoir. In this study two models have been formulated, one considers the optimal release for hydropower without consideration of minimum environmental flow and the other with the consideration of environmental flows and have been solved using Lingo. Thus traditional optimal release policy has been compared with the condition of optimal release when minimum environmental flows are enforced at the downstream side of the reservoir. The minimum environmental flow has been obtained based on the practices being followed in India and the other parts of the world.