ArticlePolymers2022
Punching Shear Strength of FRP-Reinforced Concrete Slabs without Shear Reinforcements: A Reliability Assessment.
Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 28 citations in OpenAlex.
- Explainable prediction model for punching shear strength of FRP-RC slabs based on kernel density estimation and XGBoost.Scientific reports · 2024Article
- The Impact of Reinforcement Ratio on the Punching Shear of CFRP Grid-Reinforced Concrete Two-Way Slabs.Materials (Basel, Switzerland) · 2024Article
- Machine Learning-Based Prediction Models for Punching Shear Strength of Fiber-Reinforced Polymer Reinforced Concrete Slabs Using a Gradient-Boosted Regression Tree.Materials (Basel, Switzerland) · 2024Article
- Metaheuristic Optimization of Random Forest for Predicting Punch Shear Strength of FRP-Reinforced Concrete Beams.Materials (Basel, Switzerland) · 2023Article
- Two-Way Shear Resistance of FRP Reinforced-Concrete Slabs: Data and a Comparative Study.Polymers · 2022Article
- A mechanical and simplified model for RC elements subjected to combined shear and axial tension.Scientific reports · 2022Article
- Punching Shear Strength of FRP-Reinforced Concrete Slabs without Shear Reinforcements: A Reliability Assessment.Polymers · 2022Article
- Evaluation of the Strength of Slab-Column Connections with FRPs Using Machine Learning Algorithms.Polymers · 2022Article
- Interpretable Machine Learning Algorithms to Predict the Axial Capacity of FRP-Reinforced Concrete Columns.Materials (Basel, Switzerland) · 2022Article
- Using Artificial Intelligence Techniques to Predict Punching Shear Capacity of Lightweight Concrete Slabs.Materials (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
The recent failure of buildings because of punching shear has alerted researchers to assess the reliability of the punching shear design models. However, most of the current research studies focus on model uncertainty compared to experimentally measured strength, while very limited studies consider the variability of the basic variables included in the model and the experimental measurements. This paper discusses the reliability of FRP-reinforced concrete slabs' existing punching shear models. First, more than 180 specimens were gathered. Second, available design codes and simplified models were selected and used in the calculation. Third, several reliability methods were conducted; therefore, three methods were implemented, including the mean-value first-order second moment (MVFOSM) method, the first-order second moment (FOSM) method, and the second-order reliability method (SORM). A comparison between the three methods showed that the reliability index calculated using the FOSM is quite similar to that using SORM. However, FOSM is simpler than SORM. Finally, the reliability and sensitivity of the existing strength models were assessed. At the same design point, the reliability index varied significantly. For example, the most reliable was the JSCE, with a reliability index value of 4.78, while the Elgendy-a was the least reliable, with a reliability index of 1.03. The model accuracy is the most significant parameter compared to other parameters, where the sensitivity factor varied between 67% and 80%. On the other hand, the column dimension and flexure reinforcement are the least significant parameters compared to other parameters where the sensitivity factor was 0.4% and 0.3%, respectively.
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