“…Limited research works derived temperature-dependent probabilistic models for the construction material properties, i.e., models for normal-strength concrete, mild steel, and insulating materials, can be found in [29][30][31][32]. The approach in this paper aims to develop temperature-dependent probabilistic models for the compressive strength of masonry.…”
Masonry has superior fire resistance properties stemming from its inert characteristics, and slow degradation of mechanical properties. However, once exposed to fire conditions, masonry undergoes a series of physio-chemical changes. Such changes are often described via temperature-dependent material models. Despite calls for standardization of such models, there is a lack in such standardized models. As a result, available temperature-dependent material models vary across various fire codes and standards. In order to bridge this knowledge gap, this paper presents three methodologies, namely, regression-based, probabilistic-based, and the use of artificial neural (ANN) networks, to derive generalized temperature-dependent material models for masonry with a case study on the compressive strength property. Findings from this paper can be adopted to establish updated temperature-dependent material models of fire design and analysis of masonry structures.
“…Limited research works derived temperature-dependent probabilistic models for the construction material properties, i.e., models for normal-strength concrete, mild steel, and insulating materials, can be found in [29][30][31][32]. The approach in this paper aims to develop temperature-dependent probabilistic models for the compressive strength of masonry.…”
Masonry has superior fire resistance properties stemming from its inert characteristics, and slow degradation of mechanical properties. However, once exposed to fire conditions, masonry undergoes a series of physio-chemical changes. Such changes are often described via temperature-dependent material models. Despite calls for standardization of such models, there is a lack in such standardized models. As a result, available temperature-dependent material models vary across various fire codes and standards. In order to bridge this knowledge gap, this paper presents three methodologies, namely, regression-based, probabilistic-based, and the use of artificial neural (ANN) networks, to derive generalized temperature-dependent material models for masonry with a case study on the compressive strength property. Findings from this paper can be adopted to establish updated temperature-dependent material models of fire design and analysis of masonry structures.
“…A mechanical analysis of the concrete slab has not been performed. Karaki et al (2021) perform a full probabilistic analysis of the temperatures of concrete slabs subjected to different fire scenarios. The evolution of the rebar and surface temperatures is used as failure criteria.…”
PurposeThe design check regarding the fire resistance of concrete slabs can be easily performed using tabulated values. These tables are based on experimental results, but the level of safety, which is obtained by this approach, is not known. On the other hand, performance-based methods are more accepted, but require a target reliability as performance criterion. Hence, there is a need for calibration of the performance-based methods using the results of the “traditional” descriptive approach.Design/methodology/approachThe calibration is performed for a single span concrete slab, where the axis distance of the reinforcement is chosen according to Eurocode 2 for a defined fire rating. A “standard” compartment is selected to cover typical fields of application. The opening factor is considered as parameter to obtain the maximum peak temperatures in the compartment. A Monte Carlo simulation, in combination with a response surface method, is set up to calculate the probabilities of failure.FindingsThe results indicate that the calculated reliability index for a standard is within the range, which has been used for the derivation of safety and combination factors in the Eurocodes. It can be observed that members designed for a fire rating R90 have a significant increase in the structural safety for natural fires compared to a design for a fire rating R30.Originality/valueThe level of safety, which is obtained by a design based on tabulated values, is quantified for concrete slabs. The results are a necessary input for the calibration of performance-based methods and could stimulate discussions among scientists and building authorities.
“…However, employing 100% GGBS led to minor surface cracks on the cubes, rendering it unsuitable for slab applications [25]. Considering the variability of the input variables, a low-reliability index is determined for buildings with no basic firefighting measures, and adding intervention measures, sprinkler systems, and detection systems will increase the reliability index by 53%, 85%, and 89%, respectively [26]. The hybrid CG laminate maintain its stiffness up to 250°C and it shows better fire resistance at service load as its elasticity modulus showed less degradation at elevated temperature as compared to the commonly used C and G sheets in strengthening reinforced concrete structural members [27].…”
Many of the existing reinforced concrete structures throughout the world are in urgent need of rehabilitation, repair, or reconstruction. Because of deterioration due to various factors like corrosion, lack of detailing the failure of bonding between beam, column joints, accidental fire, loss of strength, deflection, etc. Use of externally bonded FRP for strengthening the structures has received considerable attention in recent years. This study exclusively focuses on assessing the load-carrying capacity of fire-damaged Cement and Geopolymer Concrete structural elements wrapped with BFRP laminates. And the scope of this study is expected to provide cost-effective and retrofit solutions that can be implemented in the concrete industry. The slab specimens were subjected to temperatures of 200, 400, 600 and 800°C for a period of 1, 2, and 3 hours followed by retrofitting with BFRP laminate. The results showed that the ultimate load-carrying capacity of both cement and geopolymer concrete slabs increased when exposed to 200ºC for 1 hour. However, beyond this point, the capacity started to decrease. Nevertheless, a decline in ultimate load capacity was noted for higher temperature ranges and prolonged fire exposure durations.The application of Basalt FRP wrapping to the soffit of slabs led to an 80% increase in the ultimate load capacity of both cement and geopolymer concrete slabs that had been damaged by fire. The analysis of test data led to the conclusion that retrofitting with Basalt FRP Laminates achieved a strengthening effect on the firedamaged cement and geopolymer concrete slabs.
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