Method for Updating Durability Prediction Model of Concrete Structure Based on Incomplete Information
A concrete structure and predictive model technology, applied in design optimization/simulation, probabilistic CAD, stochastic CAD, etc., can solve problems such as the inability to obtain durability limit threshold sample information
Active Publication Date: 2022-03-22
TSINGHUA UNIV
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[0005] The present invention provides a method for updating the durability prediction model of concrete structures based on incomplete information obtained from non-damage tests, which is used to solve the problem that the current detection technology cannot obtain the durability limit threshold sample information, and only obtains the durability limit threshold directly. Technical Issues in Updating the Structural Durability Prediction Model of Samples
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[0015] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0016] First of all, the embodiment of the present invention is suitable for updating the durability prediction model of concrete structures in corrosive environments with definite durability limit states, specifically including two durability limit states in carbonation environment and chloride corrosion environment: steel bar corrosion limit state and the limit state of rust swelling and cracking. The present invention only considers the effect of a single corrosive environment, and does not consider the coupling o...
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The invention discloses a method for updating a concrete structure durability prediction model based on incomplete information. The method includes: obtaining incomplete information of the concrete structure to be tested by non-damage detection technology; processing the incomplete information to obtain the theoretical results of the corresponding model and the durability limit threshold; The theoretical results are simulated to obtain the prior distribution of the durability failure probability at the detection time; the prior distribution of the durability failure probability is updated by using Bayesian update theory, and the posterior distribution of the durability failure probability at the detection time is obtained; The optimization method and the Monte Carlo simulation method are used to determine the posterior mean and standard deviation of the durability limit threshold according to the posterior distribution of the durability failure probability, and then update the durability prediction model. The method does not need to obtain direct samples of the durability limit threshold, and updates the structural durability prediction model by indirectly updating the durability threshold.
Description
technical field [0001] The invention relates to the technical field of durability prediction of concrete structures, in particular to a method for updating a durability prediction model of concrete structures based on incomplete information. Background technique [0002] "Criteria for Durability Assessment of Existing Concrete Structures" (GB / T 51355-2019), based on the damage detection results, can perform grade assessment and damage prediction for damaged concrete structures in corrosive environments, and serve as the basis for maintenance decisions. However, the damage prediction model in the code still adopts the traditional theoretical model based on accelerated corrosion test, exposure test or engineering experience, without considering the damage history of the detected components and the difference between the durability limit threshold and the theoretical results, and the durability prediction model is not to update. The durability limit threshold here refers to th...
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IPC IPC(8): G06F30/20G06F111/08
Inventor 谷慧李全旺
Owner TSINGHUA UNIV