基于青藏盐蚀区混凝土结构材料抗冻融耐久性能的多尺度机理研究

Applicant has been working extensively on assessing multiscale durability mechanisms of performance based concrete mixtures over a decade. Previous research focused on applying 3D Discrete Element Approach (DEM) to establish data base for spatial structure of random aggregate particles in cement concrete. Voronoi-Delaunay Tessellation of geometric topology concept was applied to mathematically describe macro-scale structure of aggregate particles in concrete, serving for constitutive model in the near future. Former study took advantage of innovative test methods to integrate meso-scale pore structure of concrete in order to further conduct bi-directional flow of moisture solid coupling numerical simulation and 3D pore structure modeling. One of completed projects provided the background of applying artificial neural network (ANN) modeling on concrete surface characteristics to modify American Association of State Highway and Transportation Officials (AASHTO) PaveME software. Based on preliminary theory, current proposed research sought to assess freezing-thawing durability multi-scale mechanisms of concrete in salt-erosion area of Qinghai-Tibet Plateau. With the development of cutting edge test approaches, geometric topology concept, DEM on pore structure rebuilding, and flow of moisture solid coupling numerical simulation, the physical mechanisms of fluid penetration and saturation theory on concrete durability can be improved. In addition, the chemical reaction mechanisms of magnesium and calcium chloride reacting with cement hydration products leading to durability failure can be analyzed through establishing new phase diagrams. Eventually, performance testing, such as relative dynamic moduli, can be conducted on the samples from typical freeze-thaw deterioration service-in-place concrete structures. ANN model, therefore, can be established using the parameters of deterioration mechanisms to predict the durability of concrete structures subjected to freezing and thawing in cold and salt erosion regions.

申报人长期从事功能性水泥混凝土结构材料服役性能方面的研究。完成了利用三维离散元程序对随机骨料建立空间结构等模拟数据库并利用拓扑几何中三角形网格化概念，实现了混凝土宏观颗粒结构的数学描述，使定量分析其内部颗粒结构分布对本构关系的影响成为可能。申报人引入创新方法对宏细观孔隙结构进行跨尺度整合，为水气双向流固耦合数值模拟和三维孔隙结构模拟服务。利用人工神经网络（ANN）建立材料物理性能预测模型也成功应用于修正美国道路设计规范当中。本项目基于前期理论，拓展到完善青藏盐蚀区结构混凝土抗冻融机理，利用最前沿的测试手段，辅以拓扑几何图像分析和离散元孔隙结构模拟，通过流固耦合数值计算，完善流体渗透及饱和度理论的物理机理。另外建立相图对镁、钙氯盐溶液与水泥基的化学反应机理进行解析。最终对典型冻融破坏的服役混凝土取样后进行宏细观性能分析，将上述引致混凝土破坏机理的重要参数予以ANN建模来预测其耐久性。

本研究利用先进的材料表征方法解析了流体、饱和度、渗透对混凝土的影响，首先，采用CT扫描技术，压汞实验方法和Matlab图像识别技术对混凝土早龄期与硬化之后的孔隙结构进行测试与分析，利用不同的分形维数计算方法对压汞实验结果中的孔隙几何拓扑特征进行统计和分析，实现了水气双向流固耦合数值模拟，通过实验厘正上述水气在混凝土中输运物理机理的可靠性和准确性，在细观和宏观两个层面分析混凝土冻融循环的性能劣化行为与混凝土中流体饱和度，流体输运规律以及细观孔隙结构之间的相关性，阐明了混凝土孔隙抗冻性能的规律；其次，基于混凝土早期及硬化后孔隙结构的分析，评估了环境条件、试验程序和外加剂用量等变量对混凝土化学外加剂作用效果的影响，设定了外加剂与水泥凝胶材料的兼容判定阈值，并提出了混凝土引气剂气泡稳定性的评估方法；再次，通过盐溶液与混凝土涂层材料实验结果，结合MIP、Helium pycnometer和LT-DSC的分析结果，可以分别识别孔隙大小的分布情况、孔隙率、新的形成阶段和次氯酸钙形成的变化，建立了水泥砂浆膨胀和老化试验的目视评定方法，用来预测经不同涂层材料处理后混凝土的性能。此外通过微观结构特征和宏观性能分析表明，硅酸盐、硅溶胶和硅酸盐晶体涂层材料可以减缓镁或钙基除冰盐的变质速度，然而具有疏水性质的涂层材料更为有效；最终，基于青藏盐蚀区的氯盐侵蚀特点及抗冻融耐久性需求，采用人工神经网络模型（ANN），参照现有的测试与施工标准，给出针对高寒地区材料、配比的标准建议范围，建立从机理到测试的科学理解与技术支持并提出工程性能混凝土的概念，使其可以满足高寒地区混凝土的应用要求，形成了青藏盐蚀区工程性能混凝土配合比设计的建议方法。本研究的研究成果将积极促进青藏盐蚀区混凝土耐久性的系统定量研究并为当地混凝土材料配合比提供有效的多尺度甄别与改善方法。