基于遗传算法的高速公路中央绿化带滴灌管径优化设计
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摘要
滴灌作为一种高效、节能的灌溉方式有着重要的意义,在大田作物中已得到较广泛的应用,然而,有关高速公路应用的报道尚不多见。现有的高速公路中央绿化带滴灌系统设计主要是设计人员根据大田作物的田间灌溉设计经验进行粗略估算,而田间灌溉与高速公路在地形条件、管径组合、加压方式等方面存在着较大的差异,因此,应用中还不够完善,尤其水力设计中所沿用的设计标准、设计方法在高速公路滴灌适应性方面存在很多问题,滴灌水力设计缺乏符合高速公路滴灌系统特性的、完整合理的滴灌设计理论和方法做指导。目前,该类工程项目在设计管道的管径时,通常采用的方法是先用传统的经济管径法初估,再根据要求进行调整,最后进行比较确定,不但设计效率低,而且难免造成工作量的增加和投资的浪费。因此,研究高速公路滴灌管径的优化设计对提高滴灌系统应用的可靠性、有效降低灌溉系统投资,进一步发展滴灌技术在高速公路中的应用具有重要意义。
     本文分析了高速公路滴灌系统规划设计的具体步骤,提出蓄水池修建、滴头选择、干支管铺设合理长度以及灌溉制度拟定的具体原则,在综合国内外管径优化研究现状的基础上,以管径经济性和系统运行可靠性为原则,采用多孔变径管设计,以管径投资费用最小为目标函数,以节点压力、管径长度、设计流速为约束条件,建立管径优化数学模型。采用目前在求解速度和质量上优于其他优化算法的遗传算法对其进行求解,并利用VC6.0++编写了相应的优化软件。最后,通过遂渝高速公路k8+400—k10+500段工程实例对算法进行了验证,发现用遗传算法进行管径优化后,其投资比传统方法每km投资节约了205.25元,且设计效率大大提高。研究结果表明:
     (1)考虑高速路滴灌系统的投资和灌溉均匀度,其蓄水池修建高度以12~16m为佳;干管单向设计适宜长度为2km,采取双向供水干管适宜为长度4km左右。
     (2)将多孔变径管应用于高速公路滴灌系统设计,根据其水利特性,导出的沿程水头损失近似计算公式,可以求出整个管道任意一点的水头损失,且精度较传统的分段计算法高。
     (3)利用遗传算法对以上所建具有离散特点的多元、非线性灌溉系统优化模型求解,效果较好。避免了传统方法早熟、提前收敛以及易陷入局部最优等弊端,得出的解具有全局性等优点。
     (4)种群初始化时,如果将小管径对应的编码放在最前优先生成,那么初始化种群的适应度高,可保证解的稳定性和精度。
     (5)利用遗传算法解决实际问题时,其参数的选择是一个重要的过程。迭代步数、交叉率、变异率等都需要经过多次试算才能最终确定,而其中交叉概率的选择对结果影响最大。
As a highly efficient drip irrigation, energy-saving irrigation methods have an important significance. It has been the central green belts on the highway which is widely used in irrigation. While the diameter of the traditional design is only based on the experience of the designer a rough estimate, not only the design of low efficiency, but it will also cause a waste of investment and lack of reliability of system operation. Optimal design of pipe diameter has an important significance on reducing the effective investment in irrigation systems and drip irrigation to further develop the application on the highway.
     At present, Optimal Design of drip irrigation is mainly used in urban water supply and field irrigation, there are some differences between highway conditions and the existence of a larger application .In this paper, a comprehensive optimization study of the status quo at home and abroad diameter on the basis of an analysis of highway planning and design of drip irrigation system, concrete steps, pointing out that construction of the reservoir, emitter option, Heavenly Stems and Earthly Branches reasonable length of pipe laying as well as the development of irrigation system of the specific principles. Diameter and then to run the economy and the feasibility of the system as the goal, the use of porous adjustable design to minimize the investment cost as the objective function, optimization of the mathematical model to establish diameter. The use of genetic algorithms for solving them and to make use of VC 6.0+ + to prepare the corresponding optimization software. Finally, the k8+400—k10+500 of sui-yu highway are for examples of software projects are verified and found that the genetic algorithm to optimize the diameter, its investment per kilometer than the traditional method of 205.25 yuan investment savings, and design is efficiency greatly enhanced. The research results show that:
     (1)Considering highway investment in drip irrigation system and irrigation uniformity, the better highs of the pull is 12~16m ; and its design is for one-way trunk length of 2 km, taking a two-way pipe for water supply for the length of 4 km around.
     (2) porous tube adjustable drip irrigation system is used in highway design, in accordance with its water features along the way derived approximate formula for calculating head loss can be obtained throughout the pipe sections and pipe the head loss of any certain head loss, and accuracy is a little bit higher of traditional calculated method.
     (3)making use of genetic algorithm to build on the above characteristics with discrete multiple, non-linear optimization model for irrigation systems to solve satisfactorily. Early to avoid the traditional method in advance, as well as convergence and it is so easy to fall into local optimum drawbacks coming with the overall solution and so on..
     (4) population initialization, if the small diameter of the corresponding priority code generated on the front, then initialize the population to adapt to high, which can guarantee the stability and accuracy of solution.
     (5) the use of genetic algorithms to solve practical problems, the parameter selection is an important process. Iterative steps, cross-rate, mutation rate and it needs to go through several times in order to finalize the spreadsheet,which is the choice of crossover probability the greatest impact on the results.
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