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Nakhaei A, Soltani F. Modelling and Optimisation in the Design of Pipeline Network Systems Using Ant Colony Optimisation Algorithm (ACO). sjis. 2021; 3 (4) :1-17
URL: http://sjis.srpub.org/article-5-131-en.html
MSc. Petroleum & Gas Eng., University of Salford, Manchester, UK.
Abstract:   (176 Views)
This paper covers the Ant Colony Optimisation Algorithm (ACO) as an optimisation method and discusses and recommends the utilization of the model in design and analysing of varies parameters related in the oil and gas pipeline network systems. This is to achieve the optimum length of the pipeline, pressure and flow rate. Ant Colony Optimisation Algorithm (ACO) is capable of finding minimum path between several paths with their limitations and decreases pipe lengths from the sources to their destinations. It can be used in petroleum and gas refineries, transmissions and distributions lines. The theoretical and mathematical example of Ant Colony Optimisation Algorithm (ACO) between two places were carried and calculated. Optimum length is calculated about100 cm with optimum pressure about 2440 psi and flow rate about 83*106 𝑚𝑚3/ℎ. An example was designed based on the random variables results from 10 to 96 km for MATLAB Software and 0.1 to 1 km for ANTCOL Software as Stochastic Variables (SV) of length (Km) between 14 stages which may show as ‘SV-Matrix = Randi ([10 96], 14)’ and Randi ([0.1 1.5], 14)”. For each iterations the SV matrixes are showed varies range of integrity. An example was assumed between 14 places with varies range of limitations which will be occurred during a pipeline project (FIG. 6 as an initially supposition graph) to find minimum path between stages to conclude optimum range of pressure and flow rate of oil and gases based on the optimum minimum paths of pipeline network systems. SV matrixes are used based on the MATLAB Code and ANTCOL software by the CPU core 2 Duo “Intel” based on the ACO algorithm formulas.  The output lines, graphs and diagrams of ACO algorithm are showed the minimum optimum path between 14 stages about 526 km with start point from station 6 and optimum flow-rate 0.098106 𝑚𝑚3/ℎ𝑟  and pressure drop about 714.638 bar while 3.631 km as minimum length with optimum flow rate 1.515480*106 𝑚𝑚3/ℎ𝑟𝑟 and pressure drop about 1192.83 bar are found by ANTCAL results. The results proved the ability of ACO algorithm to find the optimum path with its effects on the other importance parameters, especially in the pipeline network systems, distribution and transmission lines and refineries.
Full-Text [PDF 2506 kb]   (30 Downloads)    
Type of Study: Research | Subject: Petroleum enginireeng
Received: 2022/09/15 | Accepted: 2021/10/30 | Published: 2021/12/25

References
1. Deneubourg JL, Pasteels JM, Verhaeghe JC. Probabilistic behavior in ants: strategy of errors. J Theoretical Boil. 1983; 105: 259-272. [DOI:10.1016/S0022-5193(83)80007-1]
2. Dorigo M, Maniezo V, Colomi A. The ant system: optimization by a colony cooperating ants. IEEE Trans Syst Man Cybernet. 1996; 229-242.
3. Dorigo M, Di Caro G. The ant colony optimization metaheuristic, In: Corne. Dorigo M, Glover F, editors, New idea in optimization. London: McGraw-Hi 1999; 11-32.
4. Abbaspour KC, Schulin R, Van Genuchten MT. Estimating unsaturated soil hydraulic parameters using ant colony optimization. Adv Water Resour. 2001; 24(8): 827-933. [DOI:10.1016/S0309-1708(01)00018-5]
5. Maier HR, Simpson AR, Zecchin AC, Foong WK, Phang KY, Seah HY, Tan CL. Ant colony optimization for design of water distribution systems. J Water Resour Plan Manag. ASCE 2003; 129(3): 200-209. [DOI:10.1061/(ASCE)0733-9496(2003)129:3(200)]
6. LJS Website, http://ljs.academicdirect.org/A07/43_57.htm
7. 4shared Website, http://dc243.4shared.com/img/-hMTdSx8/preview.html
8. Omicsonline Website, http://omicsonline.org/ArchiveJCSB/2009/June/03/JCSB2.186.php
9. Efe Website, http://efe.ege.edu.tr/~aydin/research.html
10. Wikipedia Website, http://en.wikipedia.org/wiki/Ant_colony_optimization
11. CodeProject Website, http:// codeproject.com/ant colony optimisation

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