Development of an Unconditional Mathematical Model to Design Sewer Networks

Document Type : Research Paper

Author

Assist. Prof. of Civil Eng., Dept. of Eng., Shahid Chamran University, Ahwaz

Abstract

Design of sewer networks involves many constraints and technical criteria. These issues make the problem complicated and the feasible alternatives difficult to achieve. Besides, the methods of handling these constraints play a major role in optimization approaches for the least cost design. In this work an integrated analysis-design model is developed thereby all constraints are automatically satisfied during designing. A normal design alternative is defined herein which is a vector of values between zero and one. This vector represents the sewers diameters, slopes and pump station locations. The normal alternative is then decoded to real design parameters based on the hydraulics rules and the problem constraints. Using the proposed model every normal alternative is feasible and consequently the input design parameters are totally unconditional. At the end the abilities of the model is shown introducing and solving a relatively large sewer network. Furthermore, to demonstrate the capability and easiness of integrating the model with optimization tools, a Simulated Annealing (SA) algorithm is also applied to obtain the least cost design of the example. The results show that the optimum design and the rate of optimization convergence are significantly improved using the proposed method.

Keywords

References

1- Heidari, M., Chow, V.T., Kokotović, P.V., and Meredith, D.D. (1971). “Discrete differential dynamic programming approach to water resources system optimization.” Water Resour. Res., 7(2), 273-282.
2- Mays, L.W., and Yen, B.C. )1975(. “Optimal cost design of branched sewer system.” Water Resour. Res., 11)1(, 37-47.
3- Mays, L.W., and Wenzel, H.G. (1976). “Optimal design of multilevel branching sewer system.” Water Resour. Res., 12(5), 913-917.
4- Mays, L.W., Wenzel, H.G., and Liebman, J.C. (1976). “Model for layout and design of sewer systems.” J.of Water Resour. Plng. And Mgmt. 102(2), 385-405.
5- Li, G., and Matthew, R.G.S. (1990). “New approach for optimization of urban drainage system.” J. of Environ. Eng., 116(5), 927-944.
6- Pan, T.C., and Kao, J.J. (2009). “GA-QP  Model to optimize sewer system design.” J. of Environ. Eng., 135(1), 17-24.
7- Mansuri, M.R., and khanjani, M.J. (1999). “Optimization of sewer system by nonlinear programming.” J. of Water and Wastewater, 30, 20-30. (In Persian)
8- Liang, L.Y., Thompson, R.G., and Young, D.M. )2004(. “Optimizing the design of sewer networks using genetic algorithms and tabu search.” Eng., Constr., Archit. Manage., 11(2), 101-112.
9- Afshar, M.H., Afshar, A., Marino, M.A., and Darbandi, A.A.S. (2006).“Hydrograph-based storm sewer design optimization by genetic algorithm.” Can. J. of Civil Eng., 33(3), 310-325.
10- Afshar, M.H. (2006). “Application of a genetic algorithm to storm sewer network optimization.” J. of Scientia Iranica, 13(3), 234-244.(In Persian)
11- Swamee, P.K. (2001). “Design of sewer line.” J.of Environ. Eng., 127(9), 776-781.
12- Henderson, D., Jacobson, S.H., and Johnson, A.W. (2003). “Theory and practice of simulated annealing.” Glover, F., and Kochenberger, G. (Eds.). Handbook on MetaHeuristics, Dept. of Mathematical Sciences, USA.
Journal of Water and Wastewater; Ab va Fazilab ( in persian )
Volume 23, Issue 3 - Serial Number 3
Serial number:83
September and October 2012
Pages 28-39

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