Probabilistic life-cycle assessment and rehabilitation strategies for deteriorating structures: a case study. Issue 6 (18th August 2018)

• Record Type: Journal Article
• Authors: Garavaglia, Elsa; Basso, Noemi; Sgambi, Luca
• Is Part Of: International journal of architectural heritage. Volume 12:Issue 6(2018)
• Page Start: 981
• Page End: 996
• Publication Date: 2018-08-18
• Subjects: life-cycle -- Monte Carlo simulation -- structural aging; Architecture -- Conservation and restoration -- Periodicals; Historic buildings -- Periodicals; Historic preservation -- Planning -- Periodicals; 721.0288
• DOI: 10.1080/15583058.2018.1431727
• Languages: English
• ISSNs: 1558-3058

Abstract

ABSTRACT: When it comes to existing buildings, the estimation of the structural residual bearing capacity is required to evaluate the potential for reuse/conversion. The level of detail and accuracy of surveys dramatically affect structural diagnostics. In order to optimise the experimental survey process, a simulation of the structural life-cycle may be useful. Based on a previously developed approach of Monte Carlo simulation implemented with a damage law for the life-cycle analysis of newly designed constructions, this paper presents the method application to a historic roof steel structure. It aims to identify critical situations, assess the residual life of the system, and plan possible retrofit strategies for the building conversion. The case study is a steel frame roof structure of the ex pig abattoir within the complex of the municipal slaughterhouse in Monza (close to Milan, Northern Italy) and protected from the Cultural Heritage Authority. The life-cycle of the structure is here investigated over different stages of the building lifespan along with the damages caused by aging and negligence. The construction was built in 1902, and abandoned in 1984. Therefore, the periods analysed are: from construction to disuse and from disuse to today. The second phase of life, still on going, has significantly sped up the degradation. The probabilistic evaluation of failure times is discussed and the possible interventions scenarios in terms of costs, and after-maintenance reliability and safety are investigated.