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首页> 外文期刊>Applied Mathematical Modelling >Stochastic chemo-physical-mechanical degradation analysis on hydrated cement under acidic environments
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Stochastic chemo-physical-mechanical degradation analysis on hydrated cement under acidic environments

机译：酸性环境下水化水泥的随机化学-物理-机械降解分析

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摘要

The accumulation of material degradation under contact with aggressive aqueous environments could lead to reduced structural reliability. In terms of hydrated cementitious materials, such interactions often result in the chemo-physical-mechanical (CPM) degradation, which represents a multiphysics process of high non-linearity and complexity. By further considering the inevitable uncertainties associated with both the materials and the serving conditions, solving such a process requires novel probabilistic approaches. This paper presents a stochastic chemo-physical-mechanical (SCPM) degradation analysis on the hydrated cement under acidic environment. The SCPM analysis consists of modelling the stochastic chemophysical degradation by finite element method, and assessing the mechanical deterioration through analytical micromechanics. The proposed modelling framework couples the conventional Monte Carlo Simulation with a novel support vector regression algorithm. The present method is able to not only address the detailed degradation mechanisms, but also ensure low computational costs for an accurate SCPM degradation assessment. (C) 2019 Elsevier Inc. All rights reserved.
机译：与侵蚀性水性环境接触时，材料降解的累积会导致结构可靠性降低。就水合胶结材料而言，这种相互作用通常会导致化学物理机械（CPM）降解，这代表了高度非线性和复杂性的多物理过程。通过进一步考虑与材料和使用条件有关的不可避免的不确定性，解决这种过程需要新颖的概率方法。本文提出了在酸性环境下水化水泥的随机化学-物理-机械（SCPM）降解分析。 SCPM分析包括通过有限元方法对随机化学物理退化进行建模，并通过分析微力学评估机械退化。所提出的建模框架将传统的蒙特卡洛模拟与新颖的支持向量回归算法结合在一起。本方法不仅能够解决详细的降级机制，而且能够确保较低的计算成本，以进行准确的SCPM降级评估。 （C）2019 Elsevier Inc.保留所有权利。

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