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Communication Dans Un Congrès Année : 2014

Physical model for damage prediction in structures due to underground excavations

Résumé

Assessing the potential of building damage is a critical issue for existing and new building projects. Simple analytical approaches are still up to now mainly considered to assess the vulnerability of structures. This paper presents a new approach based on a small-scale physical model (1/40 scale factor on the dimensions) under normal gravity. It has been designed for developing and validating experimentally new methods of prediction of damages to masonry structures induced by subsidence (generally resulting from underground excavations of tunnels and mines). The analogical soil is homogenous sand allowing the realization of different simulations. The masonry structure consists of walls built with wood pieces without cohesion (mortar) resting on an elastic foundation. The vertical displacements are applied through the use of an electromechanical jack. The technique of Digital Image Correlation (DIC) is used to measure accurately the displacements and the deformations of the structure. The identification of the damage level is based on the crack width resulting from different vertical displacements. A specific algorithm has been developed to quantify the strain of joints. The total length of opened cracks appears to be a more relevant indicator of damage than the maximum width of cracks. The damage evolution with the vertical displacement can be divided into an initial linear part and a subsequent non-linear part. Guidelines are suggested for the assessment of the masonry damages due to underground excavations.
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Dates et versions

ineris-01863823 , version 1 (29-08-2018)

Identifiants

  • HAL Id : ineris-01863823 , version 1

Citer

Luyen Nghiem, Marwan Al Heib, Fabrice Emeriault. Physical model for damage prediction in structures due to underground excavations. International conference on geotechnical engineering (Geoshanghai 2014), May 2014, Shanghai, China. pp.155-164. ⟨ineris-01863823⟩
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