基于遗传算法的天然气水合物管道提升优化

Optimization of gas hydrate pipe lifting based on genetic algorithm

针对管道对天然气水合物颗粒的水力提升过程中能耗损失大,不利于大规模开发的问题,对深海天然气水合物开采系统中重要组成部分的硬管水力提升过程进行优化分析。首先,建立管道内径、浆体流速、颗粒粒径、矿物密度和体积浓度各工作参数与比能耗关系的目标函数;然后,根据系统所处工作条件,确定各工作参数的范围;最后,基于1stpot软件,采用遗传算法对各工作参数进行优化。仿真结果表明,工作参数的选取对比能耗影响较大,其中矿物密度对输送系统影响最大、颗粒粒径对输送系统影响最小;优化后水力提升过程中的比能耗为0.153,比优化前降低了19.77%,减小了能耗损失,为天然气水合物开发提供了理论参考依据。实验结果表明遗传算法在水力提升过程中能有效减小系统的能耗损失。

For the great energy loss in the process of gas hydrate particle pipe hydraulic lifting,so it is unfavorable for resource mining in large scale.Pipe hydraulic lifting process was optimized,which was the important part of deep-sea gas hydrate mining system.Firstly,the relation of pipe inner diameter,slurry flow velocity,particle diameter,mineral density and volume fraction and specific energy consumption were established.Secondly,according to working condition of system,the scopes of work parameters were determined.Finally,based on 1stpot software,genetic algorithm was used to optimize and analyze the working parameters of hydrate particle pipe hydraulic lifting.The calculation and optimization results show that the selection of working parameters has a great influence on lifting system.Mineral density has the greatest influence on transportation system and particle diameter has the minimum influence on transportation system.The minimum value of specific energy consumption is 0.153 after optimization,which is decreased by 19.77%.The optimum operating condition is favorable to decrease energy loss,which also can provide theory basis for gas hydrate particle pipe hydraulic lifting.The experimental results show that genetic algorithm in the process of hydraulic lifting can effectively reduce energy loss of the system.