【作者】 周飞鹏；

【导师】 王立久；

【作者基本信息】 大连理工大学 ， 材料学， 2006， 硕士

【摘要】 随着全世界化石燃料能源——煤和石油等的消耗量日益增加,燃烧过程中排放的硫的氧化物和氮的氧化物越来越多,导致这些气态化合物在大气中反应生成硫酸和硝酸,这些酸性物质随雨雪等从大气层降落,形成“酸雨”,已成为举世瞩目的重大环境问题。在我国,尤其以西南地区为重。 首先,本文通过量纲分析的方法确定了混凝土的强度和酸化深度与浸泡液的SO₄^2-离子浓度、H⁺离子浓度、浸泡时间和混凝土初始强度之间的含有待拟和系数的函数关系式。 然后,了解到我国西南地区的酸雨类型为硫酸型,所以配制出不同浓度硫酸根离子、不同pH值的酸性浸泡溶液,通过干湿交替的周期浸泡实验方法,加速侵蚀液对砂浆和混凝土试件的腐蚀,研究了砂浆、细石混凝土和普通混凝土在不同浓度的SO₄^2-离子和H⁺离子的交互作用下,其质量、抗折、抗压强度和酸化深度的具体变化情况。 随后,通过实验所得到的强度和酸化深度的具体实验数据,利用MATLAB软件的强大计算能力,应用非线性回归的方法,回归出了砂浆、细石混凝土和普通混凝土的强度损失率和酸化深度的数学模型,模型可以较好的反映实验结果,对混凝土的酸雨腐蚀有一定预测作用。最后,利用BP和径向基神经网络的高精度逼近任意非线性函数和强大的建模能力,建立砂浆的抗折强度损失率和细石混凝土的抗压强度损失率神经网络,达到了很好的效果。 本文最后所得到的腐蚀后的强度和酸化深度的数学模型和神经网络,可以较好的反映混凝土受酸雨腐蚀的变化情况,对我国南方酸雨区的混凝土腐蚀的耐久性和经济评估有一定参考价值。更多还原

【Abstract】 The consumption of fossil fuel （coal and petroleum） is becoming more and more. So lots of sulfur oxide and nitrogen oxide is expelled during the combustion of these energy materials, which can be converted to vitriol and nitric acid. These acid materials fall down with rain or snow and that is so-called "acid rain", which is becoming an attractive environmental problem. In China, the southwest is the most serious part.First of all, the relationship between concrete strength、 acidified depth and the solution density of SO₄^2- 、H⁺, marinating period and concrete initial strength before marinating is established with dimension analysis method.Secondly, the artificial acid rain solution used in the laboratory is confected with different density of SO₄^2- 、H⁺, The mass loss、 flexural strength、 compressive strength and acidified depth of the mortar、 fine aggregate concrete, and normal concrete in different solutions are systematically studied through dry-wet cycles method.Thirdly, the mathematic model between mortar、 fine aggregate concrete and normal concrete strength and the acidified depth has been gotten from the test data using nonlinear regression method under MATLAB condition. The model can comparatively predict the acid rain corrosion of concrete. Finally, two neural networks are established here with Back-Propagation network and Radial Basis Function network, which can be used to reflect the mortar flexural strength loss percentage and concrete compressive strength loss percentage.The mathematic model and the neural networks between strength after acidifying and acidified depth can reflect the corrosion condition of mortar and concrete, which have certain referential value for estimating the acidifying resistance durability of concrete in southwest China.更多还原