黄骅港航道淤积预测及优化清淤研究

发布时间：2018-03-14 02:04

本文选题：黄骅港　切入点：微粒群算法　出处：《河北农业大学》2014年硕士论文　论文类型：学位论文

【摘要】：近些年来，随着港口在国民经济中的地位一步一步地提升，港口应用功能的不断扩展，其中航道工程是港口发展的基石，港口管理工作的重点和难点就是维护航道的正常通航水深，解决航道泥沙淤积问题。一个地区建立港口的理想之地当然是优良的港湾和天然的深水岸段。然而由于沿海地区地理位置的制约，我国一部分沿海地区虽然处于对建立港口不利的砂质、粉砂及淤泥质海岸，在地区经济发展的迫切需求下，随着我国经济实力以及技术水平的不断发展进步，在这些地区建立港口已经非常的普遍。我国对砂质、淤泥质海岸的研究比较深入，而随着骤淤现象的出现使得对粉砂质海岸的研究也逐渐重视起来，与前两种海岸相比起来，粉沙质海岸的研究比较肤浅。黄骅港的海岸性质属于典型的粉砂质海岸。由于影响航道淤积的因素具有强非线性、随机性、时变性及高度的不确定性等特点，这些都给航道清淤及淤积预测带来了极大的困难。而建立在粉砂质海岸上的航道工程由于本身砂质的原因，加上环境因素，人为因素的作用，这些航道的淤积问题更是引起了人们的广泛关注。严重的淤积，不仅增加航道正常水深维护的巨额投资，，而且对过往航道船舶的安全靠泊及通航造成严重的影响。本文重点从以下几个方面对黄骅港航道进行了研究： (1)分析了黄骅港的海岸形成过程、海岸特性及港区的自然条件。 (2)归纳了黄骅港综合港区航道淤积的因素，分析了各个因素对黄骅港综合港区航道产生淤积的原因。 (3)运用了具有全局最优和良好泛化能力的SVM模型，其模型参数由微粒群算法PSO进行优化，建立黄骅港综合港区航道的PSO-SVM淤积预测模型，并对已有的淤积量的数据样本分组进行了训练与预测。该模型中不仅考虑了大风的影响，还考虑了地形的影响，从而为航道淤积预测模型的研究提供了一种新思路、新方法。 (4)PSO-SVM淤积预测模型具有良好的拟合性，对于给定的大风强度，可以通过PSO-SVM模型对航道的重点淤积里程段提前进行淤积量的预测，以便及时的安排作业船只的清淤计划。 (5)结合航道的年淤积量分布及沿程水深图对黄骅港综合港区航道清淤船舶进行优化清淤安排，并对黄骅港综合港区现有清淤船舶清淤量提出建议，为黄骅港航道的优化清淤提供指导作用。 (6)对本文研究的内容进行了概况，对研究的不足进行了阐述，并对今后的研究重点进行了展望。
[Abstract]:In recent years, with the status of the port in the national economy step by step, the port application function continues to expand, among which waterway engineering is the cornerstone of port development. The key and difficult point of port management is to maintain the normal navigable depth of the waterway. The ideal place for a region to establish a port is, of course, an excellent harbour and natural deep waterfront. However, due to the geographical location of the coastal area, Although some coastal areas of China are in the sand, silt and silt coasts that are unfavorable to the establishment of ports, under the urgent need of regional economic development, with the continuous development of China's economic strength and technological level, The establishment of ports in these areas has become very common. In China, the study of sandy and muddy coasts has been more in-depth, and with the appearance of sudden siltation, the study of silty coasts has gradually been attached importance to, compared with the former two kinds of coasts. The coastal properties of Huanghua Port belong to the typical silty coast. Due to the strong nonlinear, randomness, time-varying and high uncertainty of the factors affecting the siltation of the channel, These have brought great difficulties to the prediction of siltation and siltation in waterways. However, waterway projects built on silty coasts are affected by their own sand quality, environmental factors and human factors. The siltation of these waterways has aroused widespread concern. Serious siltation not only increases the huge investment in the normal water depth maintenance of the waterway, And it has a serious impact on the safe berthing and navigation of vessels in the past waterway. In this paper, the waterway of Huanghua Port is studied from the following aspects:. The coastal formation process, coastal characteristics and natural conditions of Huanghua Port are analyzed. This paper sums up the factors of channel siltation in Huanghua Port Comprehensive Port area and analyzes the reasons for the siltation of each factor to the waterway of Huanghua Port Comprehensive Port area. The SVM model with global optimum and good generalization ability is used. The model parameters are optimized by the particle swarm optimization algorithm (PSO), and the prediction model of PSO-SVM siltation in the waterway of Huanghua Port integrated port area is established. In this model, not only the influence of strong wind, but also the influence of topography are considered in the model, which provides a new way and method for the study of channel siltation prediction model. The prediction model of PSO-SVM siltation has a good fit. For a given wind intensity, the PSO-SVM model can be used to predict the silt amount of the key silt mileage section of the waterway in advance, in order to arrange the dredging plan of the working vessel in time. (5) to optimize the arrangement of dredging vessels in the waterway of Huanghua Port integrated port area in combination with the annual siltation distribution of the waterway and along the Cheng Shui depth diagram, and to put forward some suggestions for the current desilting ship desilting capacity in the integrated port area of Huanghua Port. It provides guidance for optimizing silt clearing in Huanghua Port. The main contents of this paper are summarized, the shortcomings of the research are expounded, and the future research emphases are prospected.
【学位授予单位】：河北农业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U617.6

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