One of the concerns about the use of passive Infrared Thermography (IRT) for structural health monitoring (SHM) is the determination of a favorable period to conduct the inspections. This paper investigates the use of numerical simulations to find appropriate periods for IRT-based detection of subsurface damages in concrete bridge slabs under passive heating along a 1 year of time span. A model was built using the Finite Element Method (FEM) and calibrated using the results of a set of thermographic field inspections on a concrete slab sample. The results showed that the numerical simulation properly reproduced the experimental thermographic measurements of the concrete structure under passive heating, allowing the analysis to be extended for a longer testing period. The long-term FEM results demonstrated that the months of spring and summer are the most suitable for passive IRT inspections in this study, with around 17% more detections compared to the autumn and winter periods in Brazil. By enhancing the possibility of using FEM beyond the design stage, we demonstrate that this computation tool can provide support to long-term SHM.
Purpose
– Trusses constitute a fertile field to demonstrate the application of optimization techniques because of the possibility of several different configurations. Using such techniques allows the search for designs that minimize the use of material to safely comply with the imposed loads. Truss optimization can be classified into three categories: cross-section, shape, and topology. The purpose of this paper is to present a numerical and experimental study developed to minimize the weight of aluminum trusses, taking both the cross-sectional dimensions of the elements and the nodal coordinates as design variables.
Design/methodology/approach
– Initially, several numerical computer simulations were performed with an optimization program developed by combining the displacement method and a simulated annealing optimization method. Subsequently, two aluminum trusses were selected and built in order to validate the numerical results obtained.
Findings
– Experimental tests verified the excellent performance of the optimized model.
Originality/value
– In addition, it was concluded that significant savings could be obtained from the application of the proposed formulation.
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