Abstract
Methods for inferring the design value of the resistance based on test have long been studied extensively, but the existing methods have several limitations on unified guarantee rate ensurance and reliability control. Firstly, the rationales and deficiencies of the present methods in ISO 2394 : 2015 and EN 1990 : 2002 were generalized. Secondly, in view of the disadvantages, a new inferring method combining the probability model of resistance with statistical approach was put forward. The proposed method established a relationship among design resistance, probability characteristics of known factors, and statistical results of unknown factors and possessed a rigorous and sound theoretical basis on both conditions that the coefficient of variation of model uncertainty was unknown and full known. Lastly, a contrast work was carried out between the Eurocode method and the proposed method; the results showed that the latter method had a higher inferring value, which means a better inferring result.
Highlights
Method in ISO 2394 : 2015. e design resistance of a structural element obtained from test, whose direct basis is the analysis model, can be calculated as follows [4]: 1 Rd cdηdg xd, w, (1)
Θ is assumed as a lognormal distribution and its design value θd can be inferred from the Bayesian estimation method based on Jeffreys noninformative prior distribution [4, 10, 11]:
E abovementioned method, which is based on the probability model of resistance and builds a relationship among design resistance, probability characteristics of known factors, and statistical results of unknown factors by statistical theory directly, has a rigorous and sound theoretical basis for both conditions where the coefficient of variation of θ is unknown and full known
Summary
Rn are the samples of resistance, the inference of Rd can be expressed as equation (7) when the coefficient of variation VR (which means the distribution parameter σln R) is unknown and equation (8) when VR is known according to the Bayesian estimation method [2]: Rd exp mln R − knsln R, (7) If the coefficient of variation of θ is known, the inference design resistance can be expressed as the following equation
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