Biomedical subjects

G R Munavalli

Publications and source records attributed to G R Munavalli.

3 recordsLinked to original sources

PubMed2005

Water quality parameter estimation in a distribution system under dynamic state.

Chlorine maintenance in distribution systems is an issue for water suppliers. The complex pipe geometry in distribution systems, the dynamic flow conditions experienced within them, and the varied nature of chlorine's reactivity make it difficult to predict chlorine levels throughout a water system. Computer-based mathematical models of water quality transport and fate within distribution systems offer a promising tool for predicting chlorine in a cost-effective manner. Nevertheless, the use of water quality models can only be effective and reliable when both hydraulics and the mechanisms of chlorine dissipation within the water system are properly defined. Bulk water decay can be measured experimentally. However, wall reaction rates are more complex to determine and must be deduced from field measurement by comparison with simulation results. The simulation-optimization model presented in this paper provides an effective tool to simplify the chlorine decay model calibration process that is often tedious. The optimization tool is based on the weighted-least-squares method solved by Gauss-Newton technique. Application of the model onto a real-life system shows that quantity, quality and location of measurement nodes play an important role in estimation of parameters.

Calibration↗

PubMed2004

Dynamic simulation of multicomponent reaction transport in water distribution systems.

Given the presence of nutrients, regrowth of bacteria within a distribution system is possible. The bacterial growth phenomena, which can be studied by developing a multicomponent (substrate, biomass and disinfectant) reaction transport model, is governed by its relationship with the substrate (organic carbon) and disinfectant (chlorine). The multicomponent reaction transport model developed in the present study utilizes the simplified expressions for the basic processes (in bulk flow and at pipe wall) such as bacterial growth and decay, attachment to and detachment from the surface, substrate utilization and disinfectant action involved in the model. The usefulness of the model is further enhanced by the incorporation of an expression for bulk reaction parameter relating it with the organic carbon. The model is validated and applied to study the sensitive behavior of the components using a hypothetical network. The developed model is able to simulate the biodegradable organic carbon threshold in accordance with the values reported in the literature. The spread of contaminant intruded into the system at any location can also be simulated by the model. The multicomponent model developed is useful for water supply authorities in identifying the locations with high substrate concentrations, bacterial growth and lower chlorine residuals.

Bacteria↗

PubMed2004

Modified Lagrangian method for modeling water quality in distribution systems.

Previous work has shown that Lagrangian methods are more efficient for modeling the transport of chemicals in a water distribution system. Two such methods, the Lagrangian Time-Driven Method (TDM) and Event-Driven Method (EDM) are compared for varying concentration tolerance and computational water quality time step. A new hybrid method (EDMNET) is developed which improves the accuracy of the Lagrangian methods. All the above methods are incorporated in an existing hydraulic simulation model. The integrated model is run for different network problems under varying conditions. The TDM-generated solutions are affected by both concentration tolerance and water quality time step, whereas EDM solutions are dependent on concentration tolerance. The EDMNET solutions are less sensitive to variations in these parameters. The threshold solutions are determined for all the methods and compared. The hybrid method simulates the nodal concentrations accurately with least maximum segmentation of network and reasonable computational effort as compared to the other Lagrangian methods.

Models, Theoretical↗