حداقل‌سازی نوسانات سطح آب در کانال‌های انتقال با استفاده از بسط فوریه و الگوریتم حرکت دسته جمعی ذرات

نوع مقاله: مقاله پژوهشی

نویسنده

استادیار، دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی شیراز

چکیده

در این پژوهش ایده جدیدی برای کمینه‌سازی نوسانات تراز آب در اثر افزایش ناگهانی در دبی پمپاژ پایین‌دست کانال بر پایه الگوریتم حرکت دسته جمعی ذرات ارائه شد. بهترین هیدروگراف ورودی به کانال که می‌تواند نوسانات تراز سطح آب را حداقل کند با استفاده از بسط فوریه و تعیین ضرایب آن با استفاده از هوش مصنوعی دسته جمعی به‌دست آمد. با این ایده، امکان تبدیل این مسئله به یک مسئله بهینه‌سازی و حل آن با استفاده از روش‌های متداول به‌وجود خواهد آمد. برای این منظور، مدل عددی قوی تحلیل جریان غیر دائمی غیر یکنواخت با خاصیت تسخیر شوک با مدل بهینه‌سازی ترکیب شد. نتایج نشان داد که این روش می‌تواند یک ایده کارآمد برای حل این مسئله و مسائل مشابه باشد. هیدروگراف به‌دست آمده از این روش توانست با روشی ساده‌تر، نسبت به روش‌های پیچیده تحلیلی، نوسانات تراز آب را به مقدار محسوسی کاهش دهد. با استفاده از روش پیشنهادی، نوسانات سطح آب نسبت به حالت بدون کنترل 6/43 درصد و نسبت به حالتی که منحنی کنترل با استفاده از حساب تغییرات به‌دست می‌آید، 4/4 درصد کاهش داشت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Minimization of Water-level Fluctuations Using the Fourier Series and Particle Swarm Optimization Algorithm

نویسنده [English]

  • Abdolhosein Baghlani
چکیده [English]

A novel idea based on the Particle Swarm Optimization (PSO) is presented in this paper to minimize water-level fluctuations due to the sudden increase in downstream pumping discharge. The optimum input hydrograph which is capable of minimizing water surface fluctuations is obtained by using the Fourier Series and the PSO algorithm to determine the unknown coefficients in the Fourier Series. This idea can convert the problem to an optimization one, which can be solved via various optimization methods. To achieve this, a robust shock-capturing model which is able to solve governing equations of the unsteady, non-uniform flow is effectively combined with an optimization method based on the particle swarm optimization algorithm. The results show that the proposed approach is efficient in solving problems of this type. The inflow hydrograph obtained by this technique reduced water-level fluctuations in a much simpler manner compared to the complicated analytical approaches. Also, the proposed method was capable of reducing the fluctuations by 43.6% and 4.4%, respectively, compared to the case of imposing no control or that of control obtained by the variational approach.

کلیدواژه‌ها [English]

  • Minimization of Water-level Fluctuations
  • Conveyance Open Channels
  • Saint Venant Equations
  • Particle Swarm Optimization (PSO)
1.Chow, V.T. (1959). Open-channel hydraulics, McGraw-Hill Inc., New York.

2. Henderson, F.M. (1966). Open channel hydraulics, MacMillan, U.K.

3. Atanov, G.A., and Borovik, O.N. (1995). “Optimal stabilization of water level in canals.” Water Resources, 22(5), 562-567.

4. Atanov, G. A., Evseeva, E.G., and Work, P.A. (1998). “Variational problem of water–level stabilization in open channels.” J. Hydraulic Engineering., 124(1), 50-54.

5. Chau, K. (2005). “A split-step PSO algorithm in prediction of water quality pollution.” Proceeding of Second International Conference on Advances in Neural Networks, Hong Kong Polytechy University, Hong Kong, China, 1034-1039.

6.Suribabu, C.R., and Neelakantan, T.R. (2006). Design of water distribution networks using particle swarm optimization.” Urban Water Journal, 2(3), 1-10.

7. Montalvo, I., Izquierdo, J., Perez, R., and Tung, M.M. (2008). “Particle swarm optimization applied to the design of water supply systems.” Computers and Mathematics with Applications, 56(3), 769-776.

8. Fu, X., Li, A., Wang, L., and  Ji, C. (2011). “Short-term scheduling of cascade reservoirs using an immune algorithm-based particle swarm optimization.” Computers and Mathematics with Applications, 62, 2463-2471.

9. Haddad, O.B., Afshar, A., and Marino,  M.A. (2008). “Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs.” J. Hydroinformatics, 10(3), 257-264.

10. Iqbal, J., and Guria, C. (2009). “Optimization of an operating domestic wastewater treatment plant using elitist non-dominated sorting genetic algorithm.” Chemical Engineering Research and Design, 87(11), 1481-1496.

11. Afshar, M.H. (2010). “A parameter free continuous ant colony optimization algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach.” Advances in Engineering Software, 41(2), 188-195.

12. Mousavi, S.J., and Shourian, M. (2010). “Capacity optimization of hydropower storage projects using particle swarm optimization algorithm.” J. Hydroinformatics,12(3), 275-291.

13. Nourbakhsh, A., Safikhani, H., and Derakhshan, S. (2011). “The comparison of multi-objective particle swarm optimization and NSGA II algorithm: Applications in centrifugal pumps.” Engineering Optimization, 43(10), 1095-1113.

14. Sedki, A., and Ouazar, D. (2012). “Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems.” Advanced Engineering Informatics, 26(3), 582-591.

15. Li, M., Liu, S., Zhang, L., Wang, H., Meng, F., and Bai, L. (2012). “Non-dominated sorting genetic algorithms II based on multi-objective model in water distribution system.” Procedia Engineering, 37, 309-313.

16. Verdaguer, M., Clara, N., and Poch, M. (2012). “Ant colony optimization based method for managing influents in wastewater systems.” AICHE J., 58, 3070-3079.

17. Kennedy, J., and Eberhart, R.C. (1995). Particle swarm optimization.” IEEE International Conference on Neural Networks, Piscataway, NJ, 1942-1948.

18. Hassan, R., Cohanim, B., and de Weck, O. (2004). “A comparison of particle swarm optimization and the genetic algorithm.” American Institute of Aeronautics and Astronautics (AIAA), 1-13.

19. Lima, Jr., Lapa, C.M.F., Pereira, C.M., Cunha, J.J., and Alvim, A.C.M. (2011). “Comparison of computational performance of GA and PSO optimization techniques when designing similar systems-Typical PWR core case.” Annals of Nuclear Energy, 38(6), 1339-1346.

20. Chanson, H. (2004). The hydraulics of open channel flow: An Introduction, Elsevier Pub.

21. Wurbs, R.A., and James, W.P. (2002). Water resources engineering, Prentice-Hall, New Jersey.

22. Liang, D., Falconer, R.A., and Lin, B. (2006). “Comparison between TVD-MacCormack and ADI-type solvers of the shallow water equations.” Advances in Water Resources, 29 (12), 1833-1845.