Abstract
The goal of this paper is to show some trends and time profiles of the reliability index relevant to the Serviceability Limit State considering the design service life of RC structures. The interactive web page “RC_LifeTime” – originated by the authors – is used (see http://www.stm.fce.vutbr.cz/). The depassivation of reinforcing steel due to carbonation is considered conservatively as a limiting condition. It is based on model concrete carbonation with 12 random input variables; the Latin Hypercube Sampling simulation method is used. RC_LifeTime offers the following options: Service Life Assessment – a statistical evaluation of service life, where optionally the target value of reliability index ß may be an additional input value and then the corresponding service life is the output value; Concrete Cover Assessment – a statistical evaluation of concrete cover value for the target service life, where optionally the required concrete cover value may be input in this case and the relevant reliability index ß describes the reliability of reinforcement depassivation.
Highlights
Concrete is the premier construction material, and design for durability is a decisive issue in concrete building
Several levels of this design exist, and the most sophisticated level – a probabilistic approach at the micro-level being in the focus of research activities – contrasts with the prescriptive approach given in current codes
The output data are the statistical characteristics of the relevant service life – mean value and standard deviation/coefficient of variation (COV)
Summary
Concrete is the premier construction material, and design for durability is a decisive issue in concrete building. In addition to the assessment or design of service life and its statistical features, the probabilistic approach offers the possibility to estimate the reliability grade in the context of durability. The disadvantages of such an approach are the necessity to utilize mathematical models of deteriorating processes, to deal with random variables or random fields, and to use special statistical methods and simulation techniques. The lack of sufficient and reliable statistical data is an important and rather problematic factor in these situations For these reasons a probabilistic approach is not commonly used in everyday application
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