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早期水化反应对于硅酸盐水泥浆体微观结构的形成和强度的发展有着重要影响.然而由于水泥水化过程中发生了多相多尺寸并且相互关联的复杂的化学和物理变化,因此使得人工推导水化动力学方程的研究存在很高的难度.利用基因表达式编程与粒子群算法相结合的进化计算方法从观测到的硅酸盐水泥水化程度时间序列数据中自动地萃取出了水化早期的动力学方程,并通过GPU进行并行加速来减少运算时间.研究显示,根据该动力学方程得到的模拟曲线可以很好的吻合水化早期观测到的实验数据,而且即使化学组成、颗粒尺寸和养护条件发生改变,该方程仍然具有良好的泛化能力.
Early hydration reaction has an important influence on the formation of microstructure and the development of strength of Portland cement paste.However, due to the complex chemical and physical changes of multi-phase and multi-size and interdependence in cement hydration process, It is very difficult to derive the study of hydration kinetics equation.Using the evolutionary computation method of gene expression programming and particle swarm optimization to automatically extract water from the observed time series data of hydration degree of Portland cement The early kinetic equations and GPU parallel acceleration to reduce the operation time.Research shows that the simulation curve obtained according to the kinetic equation can be well consistent with the hydration observed early experimental data, and even if the chemical composition, the particles The size and curing conditions change, the equation still has good generalization ability.