【作者】 宋志刚；

【导师】 刘建坤； 盛煜；

【作者基本信息】 北京交通大学 ， 岩土工程， 2012， 硕士

【摘要】 多年冻土区道路成败的关键在于维护多年冻土路基的稳定性,影响多年冻土路基稳定性的最为突出的因素是路基下伏多年冻土的融化沉降变形。块碎石路基作为保护冻土稳定,防止病害的一种措施,主要通过调控对流来冷却地基,消除融沉。块碎石路基由于其降温效果明显、施工难度相对较小、便于取材、环境友好等特点,在青藏铁路、青藏公路、青康公路等工程中得到了广泛的应用,并且,在将来的道路工程中将得到进一步推广使用。因此,对其适用性评价的研究,对多年冻土区的道路工程就具有重大的意义。本文以多年冻土区的块碎石路基适用性为研究目标,在系统了解国内外关于块碎石路基降温机理、降温特征、降温效果的研究基础上,分析了影响块碎石路基适用性的影响因素,并结合评价指标体系理论,建立了多年冻土区块碎石路基适用性评价指标体系。最后,利用突变级数法及BP神经网络法建立了评价数学模型,并通过工程验证。通过研究,得出如下结论：1、通过分析国内外关于块碎石路基的室内外实验研究、数值模拟计算等方面的研究文献成果,总结和提炼了多年冻土区块碎石路基方面的研究成果,为定量评价多年冻土区块碎石路基适用性的研究奠定了基础。2、按外部气候条件、冻土内在因素、路基工程特点三大类分析了多年冻土区块碎石路基适用性影响因素。外部气候条件是影响块碎石路基适用状况的诱因与动力；冻土内在因素是直接地影响着路基温度场和水分场在路基体系中的传递的根本机制；路基工程特性是唯一可人工调节的影响因素。3、在影响因素分析基础上,结合评价指标体系理论,总结归纳了对块碎石路基适用性影响较大且作用机理明确的12个评价指标,依据一定的层次关系,建立了由目标层(多年冻土区块碎石路基适用性)、准则层(外部气候条件、冻土内在因素和路基工程特点)和指标层(12个具体指标)三个层次结构体系组成的多年冻土区块碎石路基适用性评价指标体系。4、根据评价指标的相互作用关系,建立了基于突变级数法的综合评价模型,并选用28个工程实例进行验证分析,论证了该综合模型的合理性和实用性。5、选取BP神经网络法作为验证模型,对块碎石路基适用性进行了验证评价,结果表明,经过训练学习,BP神经网络法也能够较为准确的对块碎石路基适用性进行评价预测。更多还原

【Abstract】 As far as roadway in permafrost regions is concerned, the stability is determined by subgrade, the stability of subgrade is determined by permafrost, and the key problem to permafrost is thaw settlement. As an effective solution to protect the underlying permafrost and prevent the roadway damages, Block-rock-embankment (BRE) achieves the cooling effect of the foundation and eliminates the thaw settlement by adjusting the convective heat transfer. Due to the advantages of obvious cooling effects, relatively small construction difficulties, easy sampling, and environmentally friendly, the Block-rock-embankment has been widely used in Qinghai-Tibet railway, Qinghai-Tibet highway, Ching-Hong road, and will be further promoted to other roadways in the future. Therefore, it would be very important and meaningful to study on the application evaluation of BRE in permafrost regions. The adaptability of Block-rock-embankment in permafrost regions has been selected as the object of this study. On the basis of systematically understanding the study on cooling mechanisms, cooling characteristics, cooling effects of BRE at home and abroad, we analyze the factors affecting the adaptability of BRE; build the integrated indicator system of the adaptability of BRE in permafrost regions based on the theory of evaluation index system. Finally, the mathematical model of evaluation is established by catastrophe progression method and BP neural network method, and verified by practical engineering projects. The main achievements include the following parts:1﹑By analyzing the research literature results about the BRE in the field of indoor and outdoor experiment, numerical simulation calculation,etc at home and abroad, The study achievements of BRE in permafrost has been summarized and refined to lay foundation for the quantitative evaluation study of adaptability of BRE in permafrost regions.2﹑The factors affecting the adaptability of BRE are summarized and analyzed by the classification of external climate conditions, frozen soils internal factors and subgrade characteristics. External climate conditions are incentives and motivations to influence the applicable condition of BRE; frozen soils internal factors are fundamental mechanisms directly affecting the transmission of temperature and moisture fields in roadbeds; subgrade characteristics is the only manual adjustment factors.3﹑Based on the theory of evaluation index system, evaluation indexes of12which impact significantly on the adaptability of BRE and function clearly are extracted from the factors affecting the adaptability of BRE. Then, the integrated indicator system of the adaptability of BRE in permafrost regions is set up according to definite hierarchical relationships between factors, which consists of three levels:object hierarchy, rule hierarchy and index hierarchy.4﹑According to the correlations among indicators, The mathematical model of evaluation is established by catastrophe progression method. Practical engineering projects of28are selected to verify the rationality and practicability of the model.5、The integrated assessment model set up by BP neural network method is selected to validate the evaluation results. It is concluded that, after training and learning, the adaptability of BRE can be evaluated and predicted more accurately.更多还原