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Due to the low thickness of cold-formed steel (CFS) sections, welding of traditional studs on them is not recommended; and there is a need to use shear connectors suitable for this type of sections. In this paper, the behavior of U-shaped shear connectors as connectors compatible with CFS composite beams has been investigated, to offer practical relationships for predicting the ultimate strength of this type of connectors. Accordingly, after the development of finite element (FE) models with the ability to predict the ultimate strength of U-shaped connectors, their performance against experimental results was validated. Then, an extensive parametric study, consisting of 216 numerical samples, was accomplished to provide a reliable database. As the main and most important of this study, two methods of artificial neural networks and stepwise regression were developed, and practical formulations were proposed to predict the ultimate strength of U-shaped shear connectors in CFS composite beams. Finally, in addition to evaluating the accuracy of the proposed formulas, a comparison was made between them and the relationships proposed by AISI, AS/NZS and EC3 codes for CFS screw connections. The relationships presented in this paper can be used by practical engineers in the design process of CFS composite beams. [ABSTRACT FROM AUTHOR]

This study presents a methodology that utilizes a new combination of two compressed damage indices as input data of an artificial neural network (ANN) ensemble to detect multi-damages in the braces of cold formed steel shear walls. To identify an efficient input data for ANN, first, three main groups of damage indices are considered: modal parameter-based damage indices; frequency response functions (FRFs)-based damage indices and time series-based damage indices. Furthermore, principal component analysis (PCA) technique is applied to reduce the dimensions of FRFs and time series-based input pattern. By a sensitivity study, two suitable damage indices of PCA-compressed time series data and PCA-compressed FRFs are identified and then combined to produce a new efficient input data for a hierarchy of ANN ensembles. The numerical results show that the ANN ensemble-based damage detection approach with the proposed collection of two damage indices is effective and reliable. Key words: damage detection, neural network ensemble, frequency response function, principal component analysis, cold formed steel, strap brace, time series, damage index, shear wall. Dans le cadre de cette etude, on presente une methodologie qui utilise une nouvelle combinaison de deux indices de dommages comprimes comme donnees d'entree d'un ensemble de reseaux de neurones artificiels (RNA) afin de detecter de multiples dommages dans les contreventements des murs de contreventement en acier plie a froid. Dans le but de determiner des donnees d'entree efficaces pour les RNA, en premier, on considere trois principaux groupes d'indices de dommages : les indices de dommages bases sur les parametres modaux; les indices de dommages bases sur les fonctions de reponse en frequence (FRF) et les indices de dommages bases sur les series chronologiques. En outre, la technique de l'analyse des composantes principales (ACP) est appliquee afin de reduire les dimensions des motifs d'entree des FRF et des series chronologiques. Au moyen d'une etude de sensibilite, deux indices de dommages convenables, soit des donnees chronologiques comprimees a l'aide d'ACP et des FRF comprimees a l'aide d'ACP, sont determines et ensuite combines afin de produire de nouvelles donnees d'entree efficaces pour une hierarchie d'ensembles de RNA. Les resultats numeriques montrent que l'approche de detection de dommages basee sur les ensembles de RNA utilisant la combinaison proposee de deux indices de dommages est efficace et fiable. [Traduit par la Redaction] Mots-cles : detection de dommages, ensemble de reseaux neuronaux, fonction de reponse en frequence, analyse des composantes principales, acier plie a froid, contreventement par courroies, serie chronologique, indice de dommages, mur de contreventement., 1. Introduction Structural damage detection has become an important research topic for evaluation of structural systems safety during their lifetime. Over the last three decades various methods have been developed [...]

In this paper, cold-formed steel C-shaped connectors, as one of the most commonly used components in steel wall/framing systems, were investigated under the pull-out failure modes using a detailed numerical study. Finite element models were validated using the data obtained from an experimental program; and the results were compared with the current design equations. Finally, a new pull-out strength equation was proposed based on the critical parameters affecting the behaviour of C-shaped connectors. In addition, initial bending stiffness of C-shaped connectors was studied using a simplified analytical approach; and the results obtained from the proposed new stiffness equation were compared with the initial slope of experimental and numerical force-displacement curves. These comparisons confirm the accuracy of the new strength and stiffness equations in order to apply to the analytical methods such as component-based method in future works. [ABSTRACT FROM AUTHOR]

In some of biaxial voided slabs, spherical or ellipsoidal plastic balls enclosed in steel cages are used to eliminate ineffective concrete. To investigate the bending and shear behavior of this system, five full‐scale specimens were cast including two bending specimens for investigating bending capacity and cracking distribution as well as three shear specimens used to study the shear capacity, cracking distribution, and concrete casting effect on the shear behavior. Moreover, the effects of the steel cage rods were studied on the bending and shear capacity. It was found that while both solid and biaxial voided specimens exhibited almost similar failure mode, both the bending and shear capacity of biaxial voided specimens were affected by the steel cages. In contrast, the voided specimens exhibited a significantly lower shear capacity than the solid ones while the different concrete casting methods had no effects on the capacity and behavior of biaxial voided specimens. Finally, a comparison was made with experimental results and ACI 318‐14, MC 2010, and Eurocode 2 recommendations. [ABSTRACT FROM AUTHOR]

The advanced programmatic risk analysis and management model (APRAM) is one of the recently developed methods that can be used for risk analysis and management purposes considering schedule, cost, and quality risks simultaneously. However, this model considers those failure risks that occur only over the design and construction phases of a project's life cycle. While it can be sufficient for some projects for which the required cost during the operating life is much less than the budget required over the construction period, it should be modified in relation to infrastructure projects because the associated costs during the operating life cycle are significant. In this paper, a modified APRAM is proposed, which can consider potential risks that might occur over the entire life cycle of the project, including technical and managerial failure risks. Therefore, the modified model can be used as an efficient decision-support tool for construction managers in the housing industry in which various alternatives might be technically available. The modified method is demonstrated by using a real building project, and this demonstration shows that it can be employed efficiently by construction managers. The Delphi method was applied in order to figure out the failure events and their associated probabilities. The results show that although the initial cost of a cold-formed steel structural system is higher than a conventional construction system, the former's failure cost is much lower than the latter's. [ABSTRACT FROM AUTHOR]