OS-C501

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Offshore Standard DNV-OS-C501, November 2013 Sec.10 Component testing – Page 164 reflecting uncertainties in the underlying material property estimates as well as uncertainties in the applied analysis models. 3.4.4 If the results of an analysis by means of the available analysis models are unbiased, the mean of the estimate of µ R is to be taken as: µ µ ’=µ RA 3.4.5 If the results of an analysis by means of the available analysis models are encumbered with a bias, the mean of the estimate of µ R is to be taken as: µ µ ’=µ RA +∆ in which ∆ represents the effect of the conservatism implied in the analysis leading to µ RA . ∆ is sometimes referred to as the bias and needs to be estimated. 3.4.6 An estimate of the characteristic value of the resistance, prior to any component testing, can now be obtained with 95% confidence as: x C ’=µ µ ’-1.64σ µ ’-2σ R 3.4.7 After component testing is performed, the characteristic value of the component should be updated based on the test results (and Bayesian updating theory). 3.4.8 When a total of n tests are performed, leading to n resistance values x 1 ,…x n , the sample mean is defined as 3.4.9 Based on the test results, the following updated values of the mean and the standard deviation of the estimate of the mean resistance m R can be obtained: µ µ ” = [n ⋅ µ test ⋅σ µ ’ 2 + µ µ ’ ⋅ σ R 2 ]/( n ⋅ σ µ ’ 2 + σ R 2 ) and σ µ ” = [(σ µ ’ 2 ⋅ σ R 2 )/( n ⋅ σ µ ’ 2 + σ R 2 )] 1/2 3.4.10 Based on this, the following updated estimate of the characteristic resistance can be obtained with a confidence of 95%: x C ”=µ µ ”-1.64σ m ”-2σ R 3.4.11 When the standard deviation σ µ ’of the mean resistance estimate prior to testing is not available, and when a significant, conservative bias ∆ in the resistance estimate is implied by the available analysis models, then σ µ ’ may be approximated by ∆/2, unless a better approximation can be estimated. This approximation is not valid when the bias ∆ is small or zero. Guidance note: The present note gives some more details related to the derivations above (see [3.4.1]-[3.4.11]). Assume that an estimate of µ R is sought. The estimate can be based on a prediction by means of available engineering models. Such models are usually encumbered with uncertainty owing to simplifications and idealisations, so the estimate becomes uncertain. The combined effect of simplifications and idealisations are on the conservative side, such that they imply systematic errors in the predictions, i.e., the estimator µ R ’* applied in the estimation of µ R comes out with a bias and is thus not a central estimator. The bias is denoted ∆ and is defined as: ∆=µ R -E[µ R ’*] where E[µ R ’*] = the mean value of the estimator µ R ’* for µ R . The bias ∆ has to be estimated based on all available information and a best possible engineering judgement. This estimation of ∆ is a very crucial stage. Once the bias ∆ has been estimated, an unbiased central estimate of the mean resistance can be established with mean value: µ µ ’=E[µ R ’]= E[µ R ’*]+∆ The standard deviation of the unbiased central estimate of the mean resistance is taken as: σ µ ’=D[µ R ’*] where D[µ R ’*] = standard deviation of the estimator µ R ’* for µ R . 3.5 Specimen geometry - scaled specimen ---e-n-d---of---G-u-i-d-a-n-c-e---n-o-t-e--- 3.5.1 The specimen geometry for testing may be chosen to be different from the actual under certain conditions. 3.5.2 Scaled specimens may be used if analytical calculations can demonstrate that: µ = — all critical stress states and local stress concentrations in the critical part of the scaled specimen and the 1 n ∑ test x i n i= 1 DET NORSKE VERITAS AS
Offshore Standard DNV-OS-C501, November 2013 Sec.10 Component testing – Page 165 actual component are similar, i.e., all stresses are scaled by the same factor between actual component and test specimen — the behaviour and failure of the test specimen and the actual component can be calculated based on independently obtained material parameters. This means no parameters in the analysis should be based on adjustments to make large scale data fit — the sequence of predicted failure modes is the same for the scaled specimen and the actual component over the entire lifetime of the component — an analysis method that predicts the test results properly but not entirely based on independently obtained materials data may be used for other joint geometry if it can be demonstrated that the material values that were not obtained by independent measurements can also be applied for the new conditions. 3.5.3 Tests on previous components may be used as testing evidence if the scaling requirement in [3.5.2] is fulfilled. 4 Testing components with multiple failure mechanisms 4.1 General 4.1.1 A component or structure may fail by more than one failure mechanism. In that case it is important that all the critical failure mechanisms will not occur during the lifetime of the structure. Critical failure mechanisms are the ones that are linked to functional requirements in Sec.3 and their occurrence will be a violation of a limit state. Guidance note: A typical case for a component with multiple failure mechanisms is an adhesive joint. If the joint is loaded failure may occur in one of the substrates, in the adhesive, or in one of the two interfaces. 4.2 Static tests ---e-n-d---of---G-u-i-d-a-n-c-e---n-o-t-e--- 4.2.1 Static tests are usually dominated by one failure mode. In that case the testing described in [2] and [3] is sufficient. 4.2.2 If the tests show more than one failure mode each failure mode shall be evaluated individually according to the methods given in [2] and [3]. 4.2.3 If a component shows two failure modes (X and Y) test results with failure X may be interpreted for the statistical analysis in [2] and [3] in a way that failure mode Y occurred also at the same load as failure mode X. The same approach can be applied for more than two failure modes. More advanced statistical treatments may be used to evaluate two or more failure modes. 4.2.4 If testing is carried out to verify an analysis of the structure the analysis should predict possible two (or more) failure modes for the given test load. 4.2.5 Generally, the occurrence of two different failure modes should be avoided. 4.3 Long term tests 4.3.1 Even if static tests show only one failure mode a change of failure modes may happen over time. Such a change can be caused by different time dependencies of the changes in material properties or by changes in failure mechanisms, e.g. a ductile-brittle transition. 4.3.2 If test periods to obtain long term data are as long as the design life or design number of cycles, data can be evaluated the same way as described in [4.2]. 4.3.3 If design life or number of cycles exceed testing conditions it is not possible to qualify a component with more than one failure mode just by component testing. Some additional information about the long term characteristics of the individual failure modes is needed. This information must be combined with test results by analytical reasoning. 4.3.4 The designer shall document that none of the critical failure mode will occur within the lifetime of the structure. 4.3.5 One possible way to document that none of the critical failure mode will occur within the lifetime of the structure is: — if the design life is longer than the testing time the reduction of strength with time shall be established individually for each failure mode by testing or analysis — if the expected number of cycles is more than the tested number the reduction of strength with number of cycles shall be established individually for each failure mode by testing or analysis DET NORSKE VERITAS AS
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OS-C501

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