Wang Yu-Xue
School of Mathematical Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China
Zhou Shao-Hua
School of Mathematical Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China
WEI Shu-Hui
School of Mathematical Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China
Wang Yin-Feng
School of Mathematical Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China
ABSTRACT
This study presents a method to calibrate pipe friction factor in oilfield water injection pipeline based on particle swarm algorithm. Particle swarm algorithm is simple and easy to implement without gradient information, especially its natural characteristics of real number encoding is suitable for processing the continuous optimization problem. Particle swarm algorithm possesses good capability to avoid the local extremum and obtain the global extremum. Grouping method is used is to reduce the number of optimization variables. Finally, a practical example verified the feasibility of the presented method.
PDF References Citation
Received: June 02, 2013;
Accepted: October 09, 2013;
Published: November 13, 2013
How to cite this article
Wang Yu-Xue, Zhou Shao-Hua, WEI Shu-Hui and Wang Yin-Feng, 2013. Calibration of Pipe Friction Factor Based on Particle Swam Algorithm. Journal of Applied Sciences, 13: 5280-5283.
DOI: 10.3923/jas.2013.5280.5283
URL: https://scialert.net/abstract/?doi=jas.2013.5280.5283
DOI: 10.3923/jas.2013.5280.5283
URL: https://scialert.net/abstract/?doi=jas.2013.5280.5283
REFERENCES
- Eberhart, R.C. and J. Kennedy, 1995. A new optimizer using particle swarm theory. Proceedings of the 6th International Symposium on Micro Machine and Human Science, October 4-6, 1995, Nagoya, Japan, pp: 39-43.
CrossRefDirect Link - Kennedy, J., 1997. The particle swarm: Social adaptation of knowledge. Proceedings of the International Conference on Evolutionary Computation, April 13-16, 1997, Indianapolis, IN., pp: 303-308.
CrossRefDirect Link - Liggett, J.A. and L.C. Chen, 1994. Inverse transient analysis in pipe networks. J. Hydraulic Eng., 120: 934-955.
CrossRef - Sablani, S.S., W.H. Shayya and A. Kacimov, 2003. Explicit calculation of the friction factor in pipeline flow of Bingham plastic fluids: A neural network approach. Chem. Eng. Sci., 58: 99-106.
CrossRef - Shayya, W.H. and S.S.Sablani, 1998. An artificial neural network for non-iterative calculation of the friction factor in pipeline flow. Comput. Electr. Agric., 21: 219-228.
CrossRef