高填土涵洞土压力理论与涵洞结构变形智能预测
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摘要
排泄公路两侧冲沟、溪流的洪水,在不过水时也可作交通使用,单孔跨径小于5m的称为涵。涵洞(管)被广泛地应用于公路、铁路、市政、军工等行业和部门,是“生命线工程”之一种。过去,我国公路中涵洞多为低填,涵洞设计依据规范就可以满足要求。但按照国家公路发展总体目标,我国公路建设投资不断加大、公路等级明显提高,公路中的高填土涵洞结构物所占比重也是越来越大。日益增多的高填土涵洞,缺乏相应的配套理论为指导,导致在实际中暴露出许多问题。所以,高填土涵洞研究有着重要的社会意义。本文采用相似材料模型试验、有限元数值模拟相结合的方法对决定高填土涵洞结构设计的荷载-垂直土压力进行研究,得出垂直土压力分布；不同标高土层的沉降位移分布。在此基础上,建立高填土涵洞垂直土压力计算公式。测试涵洞结构应力分布,探讨涵洞病害原因。采用自行编制的自适应遗传算法-神经网络系统对涵洞断面测点变形(应力)进行预测。具体的研究内容如下所述：
(1)依据相似定理,量纲分析法导出相似指标,作为试验相似与否的判定标准。对比试验确定砂、石膏和硅藻土的混合物为相似材料,得出用水量、砂膏比、膏土比和养护条件与材料力学参数的关系。用相似材料,按几何相似比,制成拱涵和盖板涵的小比例模型,代替其他人采用的有机玻璃、木块制作涵洞模型,可以更加真实反应涵洞结构受力。
(2)对试验箱内涵洞模型逐层填土、千斤顶逐级加载模拟实际施工过程,土压力计测试涵洞填土层的应力变化。填土高度增加,垂直土压力及其增长速度都呈现非线性增长。填土高度较低时,施工荷载和刚度差异引起附加应力作用；填土达到一定高度后,应力重分布产生土拱效应,两者共同影响决定垂直土压力分布。模型试验、结构力法分析涵洞高、低应力区的分布,探究涵洞发生病害原因。施工期临时荷载和刚度差异引起附加应力大于设计的永久荷载而导致涵洞在填土高度较低时出现病害。试验标志点位移测量,得出填土沉降分布,涵洞顶部填土的沉降变形性状为上凸形,且随填土高度增加,沉降差异逐渐缩小。
(3)考虑涵洞埋设的地形条件、填土特性、地基土的土性参数、地基处理方式的不同和涵洞结构特征等因素对高填土涵洞垂直土压力的影响,进行数值模拟。具体分析每一影响因素与涵洞垂直土压力分布之间的联系,与模型试验结果对比,为建立高填土涵洞垂直土压力公式提供参考。
(4)参照模型试验、数值模拟结果,分别建立刚性、柔性两种地基处理方式对应的高填土涵洞垂直土压力计算公式。以填土高度h0为分界,列出附加应力和土拱效应起作用的两阶段土压力公式。与模型试验实测数据对比；同时与其它9种规范公式对同一算例求解,分析各种方法得到的土压力分布情况。
(5)综合遗传算法(Genetic Algorithm, GA)和神经网络(Back-Propagation Network, BP)两种智能方法的优点,编程实现自适应遗传算法-神经网络智能系统(Adaptiave Genetic Algorithm-Back-Propagation Network, AGA-BP),并首次将其应用到高填土涵洞变形(应力)的预测研究中。AGA提出自适应交叉、变异概率公式,改进GA中最优储存策略,AGA-BP采用BP网络累计预测误差标准差作为AGA适应度函数,优化搜索确定网络模型结构。将模型试验的数据(包括定量数据和定性数据)作为样本,网络结构分别用经验公式和AGA-BP系统确定。网络训练、预测结果对比表明,AGA-BP系统优化确定的全局意义的神经网络结构,能够提高网络的泛化能力。
Culvert is mainly used to discharge water from gulley and stream in two sides of road. Culvert can also traffic without water. Span length is less than 5 meters. Culvert is one of lifeline projects, and frequently occurs in the regions where there is no abundant river water or shallow groundwater, such as traffic, highway, railway, municipal works and war industry, etc. An efficient development of water resources in such regions is an important problem for transportation. Culvert is positive buried structure, and its design is guided by norm when the fill on culvert is low in the past. With the development of China highway, highroad grade criterion increased, and the proportion of culvert with high fill is greater. However, under this situation, High filled culvert designed without the reasonable theory instruction, which leads to some of them fail in the period of construction or after completion of work. So research about vertical earth pressure acting on high filled culvert is significant in engineering and society development. Considering some different influencing factors, modest tests and numerical simulation are performed to analyse vertical earth pressure distribution rule and fill layer displacement field. Using of culvert structure's measure data from model test as sample, programmed AGA-BP (adaptive genetic algorithm-back propagation network) system are developed to forecast culvert section stress. The contents of research in the paper as follow,
(1) Based on similarity theory and some experimental results, a renew criterion was firstly put forward to judge rationality whether the test result as to a similarity index. Intermixture with sand, gypsum and diatomite as raw material specimens, tests with different similarity modeling material were performed. The relations among four influencing factors including water quantity, ratio of sand and gypsum, ratio of gypsum and diatomite, curing condition with material mechanical properties were got. According to geometric similarity ratio, similar material was used to make arch and slab culvert model. The model can more objectively reflect culvert force.
(2) Adding soil by layers and load by jack to simulate real constructing course, the regularity of vertical earth pressure on the high filled culvert was investigated in the thesis. Vertical earth pressure increased nonlinearly with fill height increase. Subsidiary stress from stiffness differences and soil arching action decided the vertical earth pressure together. Model test and structural mechanics method analysed culvert's high and low stress distribution in order to detect the disease reason. Subsidiary stress causing by temperate construction load and stiffness differences is bigger than lastly load which leads to disease with lower fill. By measurement of index point's displacement, the displacement on top of culvert was protruding plane. With fill height increasing, differential settlement was reduced.
(3) Considering some influencing factors including topographies of galley, fill characters, parameters of foundation soil, different foundation treatment and culvert structure form, numerical simulation based on ANSYS software was performed. Different parameters related with vertical earth pressure were found which could offer a reference to deducing a high filled culvert vertical earth pressure formula.
(4) On the basis of results from modal test and numeric simulation, distribution regularities of vertical earth pressure got and came to the conclusion that the earth pressure should be different as the height of fill over h0 meters. So, vertical earth pressure formula found respectively according to rigid and flexible foundation processing mode. By contrasting with measurement data and calculating one example with other nine norm formulas, the thesis discussed the results from every formula.
(5) Combined with the advantages of genetic algorithm and BP network, programmed AGA-BP intelligence system can forecast culvert displacement. AGA changes cross, mutation probability which can prevent random nomadism in the late of evolution. In order to prevent overtraining effectively, AGA fitness function is defined as standard deviation of accumulation forecast errors. The neural network with optimal architecture determined by AGA is used to train and forecast sample from model test data. Results show that neural network structure determined by AGA-BP system can forecast displacement about culvert with high fill effectively.
(1)依据相似定理,量纲分析法导出相似指标,作为试验相似与否的判定标准。对比试验确定砂、石膏和硅藻土的混合物为相似材料,得出用水量、砂膏比、膏土比和养护条件与材料力学参数的关系。用相似材料,按几何相似比,制成拱涵和盖板涵的小比例模型,代替其他人采用的有机玻璃、木块制作涵洞模型,可以更加真实反应涵洞结构受力。
(2)对试验箱内涵洞模型逐层填土、千斤顶逐级加载模拟实际施工过程,土压力计测试涵洞填土层的应力变化。填土高度增加,垂直土压力及其增长速度都呈现非线性增长。填土高度较低时,施工荷载和刚度差异引起附加应力作用；填土达到一定高度后,应力重分布产生土拱效应,两者共同影响决定垂直土压力分布。模型试验、结构力法分析涵洞高、低应力区的分布,探究涵洞发生病害原因。施工期临时荷载和刚度差异引起附加应力大于设计的永久荷载而导致涵洞在填土高度较低时出现病害。试验标志点位移测量,得出填土沉降分布,涵洞顶部填土的沉降变形性状为上凸形,且随填土高度增加,沉降差异逐渐缩小。
(3)考虑涵洞埋设的地形条件、填土特性、地基土的土性参数、地基处理方式的不同和涵洞结构特征等因素对高填土涵洞垂直土压力的影响,进行数值模拟。具体分析每一影响因素与涵洞垂直土压力分布之间的联系,与模型试验结果对比,为建立高填土涵洞垂直土压力公式提供参考。
(4)参照模型试验、数值模拟结果,分别建立刚性、柔性两种地基处理方式对应的高填土涵洞垂直土压力计算公式。以填土高度h0为分界,列出附加应力和土拱效应起作用的两阶段土压力公式。与模型试验实测数据对比；同时与其它9种规范公式对同一算例求解,分析各种方法得到的土压力分布情况。
(5)综合遗传算法(Genetic Algorithm, GA)和神经网络(Back-Propagation Network, BP)两种智能方法的优点,编程实现自适应遗传算法-神经网络智能系统(Adaptiave Genetic Algorithm-Back-Propagation Network, AGA-BP),并首次将其应用到高填土涵洞变形(应力)的预测研究中。AGA提出自适应交叉、变异概率公式,改进GA中最优储存策略,AGA-BP采用BP网络累计预测误差标准差作为AGA适应度函数,优化搜索确定网络模型结构。将模型试验的数据(包括定量数据和定性数据)作为样本,网络结构分别用经验公式和AGA-BP系统确定。网络训练、预测结果对比表明,AGA-BP系统优化确定的全局意义的神经网络结构,能够提高网络的泛化能力。
Culvert is mainly used to discharge water from gulley and stream in two sides of road. Culvert can also traffic without water. Span length is less than 5 meters. Culvert is one of lifeline projects, and frequently occurs in the regions where there is no abundant river water or shallow groundwater, such as traffic, highway, railway, municipal works and war industry, etc. An efficient development of water resources in such regions is an important problem for transportation. Culvert is positive buried structure, and its design is guided by norm when the fill on culvert is low in the past. With the development of China highway, highroad grade criterion increased, and the proportion of culvert with high fill is greater. However, under this situation, High filled culvert designed without the reasonable theory instruction, which leads to some of them fail in the period of construction or after completion of work. So research about vertical earth pressure acting on high filled culvert is significant in engineering and society development. Considering some different influencing factors, modest tests and numerical simulation are performed to analyse vertical earth pressure distribution rule and fill layer displacement field. Using of culvert structure's measure data from model test as sample, programmed AGA-BP (adaptive genetic algorithm-back propagation network) system are developed to forecast culvert section stress. The contents of research in the paper as follow,
(1) Based on similarity theory and some experimental results, a renew criterion was firstly put forward to judge rationality whether the test result as to a similarity index. Intermixture with sand, gypsum and diatomite as raw material specimens, tests with different similarity modeling material were performed. The relations among four influencing factors including water quantity, ratio of sand and gypsum, ratio of gypsum and diatomite, curing condition with material mechanical properties were got. According to geometric similarity ratio, similar material was used to make arch and slab culvert model. The model can more objectively reflect culvert force.
(2) Adding soil by layers and load by jack to simulate real constructing course, the regularity of vertical earth pressure on the high filled culvert was investigated in the thesis. Vertical earth pressure increased nonlinearly with fill height increase. Subsidiary stress from stiffness differences and soil arching action decided the vertical earth pressure together. Model test and structural mechanics method analysed culvert's high and low stress distribution in order to detect the disease reason. Subsidiary stress causing by temperate construction load and stiffness differences is bigger than lastly load which leads to disease with lower fill. By measurement of index point's displacement, the displacement on top of culvert was protruding plane. With fill height increasing, differential settlement was reduced.
(3) Considering some influencing factors including topographies of galley, fill characters, parameters of foundation soil, different foundation treatment and culvert structure form, numerical simulation based on ANSYS software was performed. Different parameters related with vertical earth pressure were found which could offer a reference to deducing a high filled culvert vertical earth pressure formula.
(4) On the basis of results from modal test and numeric simulation, distribution regularities of vertical earth pressure got and came to the conclusion that the earth pressure should be different as the height of fill over h0 meters. So, vertical earth pressure formula found respectively according to rigid and flexible foundation processing mode. By contrasting with measurement data and calculating one example with other nine norm formulas, the thesis discussed the results from every formula.
(5) Combined with the advantages of genetic algorithm and BP network, programmed AGA-BP intelligence system can forecast culvert displacement. AGA changes cross, mutation probability which can prevent random nomadism in the late of evolution. In order to prevent overtraining effectively, AGA fitness function is defined as standard deviation of accumulation forecast errors. The neural network with optimal architecture determined by AGA is used to train and forecast sample from model test data. Results show that neural network structure determined by AGA-BP system can forecast displacement about culvert with high fill effectively.
引文
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