Computer aided optimization of natural gas pipe networks using genetic algorithm

El-Mahdy, Omar Fayez Mohamed; Ahmed, Mohamed Ezz Hassan; Metwalli, Sayed M.

doi:10.1016/j.asoc.2010.05.010

Cited by 47 publications

(17 citation statements)

References 12 publications

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“…So, to make some uncontested and appropriate assumptions for the pipeline network system, it is suggested to separate the whole optimization design into two parts. First one is considered as design of layout optimization and second one is considered as design of diameter optimization [8,9].…”

Section: Mathematical Model Of Optimizationmentioning

confidence: 99%

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

Talapatra

Chowdhury

Ujjaman

2019

Journal of Mechanical and Energy Engineering

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Coalbed methane is extracted from the adsorbed state in coal seams with lower pressure and production rate. In previous studies, researchers only focused on the methods that were developed for making a relationship between the underground production rate and surface flow rate without any type of optimization procedure. In this study, the main purpose is to do a review on finding out of surface layout plan to optimize the maximum gas flow rate by developing an improved pipeline network. The more the optimization of the layout plan for designing pipeline network, the lower the amount of investment need to provide. Here, a mathematical model is proposed for the gas transportation based on the hydraulic and thermodynamic calculations of the pipeline network. Not only that, but also the filtration mechanism of depressurization and desorption for the gas flow through pipe section are evaluated here. After that, the pressure drop and pipeline efficiency are explored to find out the best design of pipeline network from the observed results. Finally, based on this study, many uncertainties can be reduced associated with the installation of pipeline network for gas transportation.

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Section: Mathematical Model Of Optimizationmentioning

confidence: 99%

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

Talapatra

Chowdhury

Ujjaman

2019

Journal of Mechanical and Energy Engineering

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“…[39][40][41][42] Formation of the initial population. The first step in the GA procedure is the formation of the initial population (a generation).…”

Section: Genetic Algorithm Optimization Techniquementioning

confidence: 99%

A new approach for optimum selection of a turbocharger using a genetic algorithm

Sanaye

Ghadikolaee

Ghasemi

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

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A new method of selecting an optimum turbocharger for a specific engine using thermodynamic and turbomachinery analyses is presented in this paper. The optimum turbocharger was selected for enhancing the power output of the engine by minimizing an objective function (the sum of the compressor losses and the turbine losses). Constraints in the optimization process were used to locate the operating points of the turbocharged engine at the appropriate position on the compressor map (with a sufficiently large distance from the surge line and the choke line) as well as to satisfy a few parameter values. The design parameters in the optimization procedure were the geometric and aerodynamic parameters of the compressor and the turbine. The proposed method was used to specify the geometry of an optimum turbocharger for an engine (the OM 457 LA diesel engine in our case study) or to select a turbocharger from the vendor list. On applying the above procedure for selecting a turbocharger, the compressor efficiency of the selected turbocharger at various engine speeds was between 0.67 and 0.76, the turbine efficiency was between 0.68 and 0.74, and the index for the appropriate distance from the surge line and the choke line on the compressor map was between 0.2 and 0.72.

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“…Genetic Algorithms are a metaheuristic technique appropriate for this type of optimisation. They have been successfully used to solve related combinatorial problems such as Steiner tree connectivity (Kapsalis et al, 1993), communications network design (Gen et al, 2001;Kim et al, 1999), transportation problems , gas transmission networks (El-Mahdy et al, 2010;Montoya-O et al, 2000) and water distribution networks (Duncker et al, 2005;Frey et al, 1996;Wu et al, 2010). This paper describes the development of a procedure for determining the characteristics of a near-optimal CCS pipeline network that approaches the minimum total cost per tonne of CO 2 avoided.…”

Section: Introductionmentioning

confidence: 98%

Steady-state design of CO2 pipeline networks for minimal cost per tonne of CO2 avoided

Weihs

Wiley

2012

International Journal of Greenhouse Gas Control

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Computer aided optimization of natural gas pipe networks using genetic algorithm

Cited by 47 publications

References 12 publications

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

A new approach for optimum selection of a turbocharger using a genetic algorithm

Steady-state design of CO2 pipeline networks for minimal cost per tonne of CO2 avoided

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