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Multicrack detection on semirigidly connected beams utilizing dynamic data / Heung Fai Lam in Journal of engineering mechanics, Vol. 134 N°1 (Janvier 2008) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 134 N°1 (Janvier 2008) . - pp. 90–99. Titre : Multicrack detection on semirigidly connected beams utilizing dynamic data Type de document : texte imprimé Auteurs : Heung Fai Lam, Auteur ; Ching Tai Ng, Auteur ; Andrew Yee Leung, Auteur Année de publication : 2008 Article en page(s) : pp. 90–99. Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Connections  Beams  Data  analysis  Cracking Résumé : The problem of crack detection has been studied by many researchers, and many methods of approaching the problem have been developed. To quantify the crack extent, most methods follow the model updating approach. This approach treats the crack location and extent as model parameters, which are then identified by minimizing the discrepancy between the modeled and the measured dynamic responses. Most methods following this approach focus on the detection of a single crack or multicracks in situations in which the number of cracks is known. The main objective of this paper is to address the crack detection problem in a general situation in which the number of cracks is not known in advance. The crack detection methodology proposed in this paper consists of two phases. In the first phase, different classes of models are employed to model the beam with different numbers of cracks, and the Bayesian model class selection method is then employed to identify the most plausible class of models based on the set of measured dynamic data in order to identify the number of cracks on the beam. In the second phase, the posterior (updated) probability density function of the crack locations and the corresponding extents is calculated using the Bayesian statistical framework. As a result, the uncertainties that may have been introduced by measurement noise and modeling error can be explicitly dealt with. The methodology proposed herein has been verified by and demonstrated through a comprehensive series of numerical case studies, in which noisy data were generated by a Bernoulli–Euler beam with semirigid connections. The results of these studies show that the proposed methodology can correctly identify the number of cracks even when the crack extent is small. The effects of measurement noise, modeling error, and the complexity of the class of identification model on the crack detection results have also been studied and are discussed in this paper. ISSN : 0733-9399 En ligne : http://ascelibrary.org/action/showAbstract?page=90&volume=134&issue=1&journalCod [...] [article] Multicrack detection on semirigidly connected beams utilizing dynamic data [texte imprimé] / Heung Fai Lam, Auteur ; Ching Tai Ng, Auteur ; Andrew Yee Leung, Auteur . - 2008 . - pp. 90–99. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 134 N°1 (Janvier 2008) . - pp. 90–99. Mots-clés : Connections  Beams  Data  analysis  Cracking Résumé : The problem of crack detection has been studied by many researchers, and many methods of approaching the problem have been developed. To quantify the crack extent, most methods follow the model updating approach. This approach treats the crack location and extent as model parameters, which are then identified by minimizing the discrepancy between the modeled and the measured dynamic responses. Most methods following this approach focus on the detection of a single crack or multicracks in situations in which the number of cracks is known. The main objective of this paper is to address the crack detection problem in a general situation in which the number of cracks is not known in advance. The crack detection methodology proposed in this paper consists of two phases. In the first phase, different classes of models are employed to model the beam with different numbers of cracks, and the Bayesian model class selection method is then employed to identify the most plausible class of models based on the set of measured dynamic data in order to identify the number of cracks on the beam. In the second phase, the posterior (updated) probability density function of the crack locations and the corresponding extents is calculated using the Bayesian statistical framework. As a result, the uncertainties that may have been introduced by measurement noise and modeling error can be explicitly dealt with. The methodology proposed herein has been verified by and demonstrated through a comprehensive series of numerical case studies, in which noisy data were generated by a Bernoulli–Euler beam with semirigid connections. The results of these studies show that the proposed methodology can correctly identify the number of cracks even when the crack extent is small. The effects of measurement noise, modeling error, and the complexity of the class of identification model on the crack detection results have also been studied and are discussed in this paper. ISSN : 0733-9399 En ligne : http://ascelibrary.org/action/showAbstract?page=90&volume=134&issue=1&journalCod [...]

Reliability analysis of single-degree-of-freedom elastoplastic systems. I / Siu-Kui Au in Journal of engineering mechanics, Vol. 133 N°10 (Octobre 2007) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 133 N°10 (Octobre 2007) . - pp. 1072–1080. Titre : Reliability analysis of single-degree-of-freedom elastoplastic systems. I : Critical excitations Type de document : texte imprimé Auteurs : Siu-Kui Au, Auteur ; Heung Fai Lam, Auteur ; Ching Tai Ng, Auteur Année de publication : 2007 Article en page(s) : pp. 1072–1080. Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Critical  load  Elastoplasticity  Monte  Carlo  method  Structural  reliability  Vibration  Noise  Excitation Résumé : This paper investigates the application of importance sampling method to estimating the first passage probability of single-degree-of-freedom elastoplastic systems subjected to white noise excitations. The importance sampling density is constructed using a conventional choice as a weighted sum of Gaussian distributions centered among design points. It is well known that the design points, or equivalently the critical excitations in the function space, are difficult to obtain for nonlinear hysteretic systems. An efficient method has been developed recently for finding the critical excitations, on which this paper is based. Characteristics of the critical excitation for elastoplastic systems are explored and the efficiency of the resulting importance sampling strategy is critically assessed. It is found that some efficiency is gained by importance sampling over direct Monte Carlo method but to a lesser extent compared to its linear-elastic counterparts. The cause of this drop in efficiency will be investigated. The study calls for revisiting a basic assumption of importance sampling densities constructed using design points, where they are expected to generate samples lying frequently in the failure region, but in reality their capability should not be taken for granted. A companion paper investigates the approximation of the critical excitation that allows its simple determination. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-9399%282007%29133%3A10%281 [...] [article] Reliability analysis of single-degree-of-freedom elastoplastic systems. I : Critical excitations [texte imprimé] / Siu-Kui Au, Auteur ; Heung Fai Lam, Auteur ; Ching Tai Ng, Auteur . - 2007 . - pp. 1072–1080. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 133 N°10 (Octobre 2007) . - pp. 1072–1080. Mots-clés : Critical  load  Elastoplasticity  Monte  Carlo  method  Structural  reliability  Vibration  Noise  Excitation Résumé : This paper investigates the application of importance sampling method to estimating the first passage probability of single-degree-of-freedom elastoplastic systems subjected to white noise excitations. The importance sampling density is constructed using a conventional choice as a weighted sum of Gaussian distributions centered among design points. It is well known that the design points, or equivalently the critical excitations in the function space, are difficult to obtain for nonlinear hysteretic systems. An efficient method has been developed recently for finding the critical excitations, on which this paper is based. Characteristics of the critical excitation for elastoplastic systems are explored and the efficiency of the resulting importance sampling strategy is critically assessed. It is found that some efficiency is gained by importance sampling over direct Monte Carlo method but to a lesser extent compared to its linear-elastic counterparts. The cause of this drop in efficiency will be investigated. The study calls for revisiting a basic assumption of importance sampling densities constructed using design points, where they are expected to generate samples lying frequently in the failure region, but in reality their capability should not be taken for granted. A companion paper investigates the approximation of the critical excitation that allows its simple determination. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-9399%282007%29133%3A10%281 [...]