ABSTRACT
Recent developments indicate that the application of pultruded FRP profiles has been continuously growing in the construction industry. Generating more complex structures composed of pultruded FRP profiles requires joining them. In particular, I-shape glass fiber pultruded profiles are commonly used and the possible joints to connect them should be specifically studied. The mechanical behavior of adhesively and bolted joints for pultruded Glass FRP (GFRP) profiles has been experimentally addressed and numerically modeled. A total of nine specimens with different configurations (bolted joints, adhesive joints, web joints, web and flange joints, and two different angles between profiles) were fabricated and tested, extending the available published information. The novelty of the research is in the direct comparison of joint technologies (bolted vs. adhesive), joint configuration (web vs. flange + web) and angles between profiles in a comprehensive way. Plates for flange joints were fabricated with carbon fiber FRP. Experimental results indicate that adding the bolted flange connection allowed for a slight increase of the load bearing capacity (up to 15%) but a significant increase in the stiffness (between 2 and 7 times). Hence, it is concluded that using carbon FRP bolted flange connection should be considered when increasing the joint stiffness is sought. Adhesively connections only reached 25% of the expected shear strength according to the adhesive producer if comparing the numerically calculated shear strength at the failure time with the shear strength capacity of the adhesive. Apart from assessing adhesive connections, the implemented 3D numerical model was aimed at providing a simplified effective tool to effectively design bolted joints. Although the accurate fitting between experimental and numerical results of the mechanical response, especially the stiffness of the joint, the local failure experimentally observed was not automatically represented by the model, because of the simplified definition of the materials oriented to make the model available for a wide range of practitioners.
ABSTRACT
Composite materials have been increasingly used to produce hybrid structures together with concrete. This system is commonly applied to bridges and roof structures. The main idea of the current research was to extend this approach by replacing the concrete with a fabric-reinforced cementitious matrix (FRCM) composite, resulting in a combination of composite materials. The main aim was to characterize the structural behavior of fiber-reinforced polymer (FRP) profiles and FRCM hybrid superficial elements. Two different prototypes of the hybrid superficial structural typology were tested to cover bidimensional and three-dimensional application cases of the proposed technology. After mortar cracking, the experimental results revealed a ductile response and a high mechanical capacity. A finite element model was implemented, calibrated, and validated by comparing numerical data with experimental results of the two prototypes. The output was a validated model that correctly captured the characteristic response of the proposed technology, which consisted of changing the structural response from a stiff plate configuration to a membrane type due to cracking of the FRCM composite part of the full solution. The suggested numerical model adequately reflected the experimental response and proved valuable for understanding and explaining the resistive processes established along this complicated FRP-FRCM hybrid structure.
ABSTRACT
Hybrid slabs made of carbon-fiber-reinforced polymer (CFRP) and concrete provide a solution that takes advantage of the strength properties of both materials. The performance of the system strongly depends on the CFRP-concrete interaction. This study investigates the shear behavior in the interface of the two materials. Eight full-scale experiments were carried out to characterize the interface shear response of these hybrid elements using different connection solutions. An untreated surface is compared to a surface with aggregates, with a novel system comprising a flexible, straight glass fiber mesh and an inclined glass fiber mesh. The experimental results show that the fabric connection improves the friction between materials and is responsible for the pseudo-plastic performance of the specimens. The inclined mesh produces a more uniform tightening effect compared to the straight mesh. In simulations via the finite element method, we used an adjusted frictional model to reproduce the experiments.
ABSTRACT
In order to combat corrosion issues, several studies on progressively replacing steel reinforcement elements with composite ones have been conducted in recent years. Hybrid steel-concrete thin slabs in which the steel acts as formwork are also candidates for update in the coming years. Achieving a reliable connection between fiber-reinforced polymer (FRP) and cast-in-place concrete is key to promoting this technology. This study analyzed different connection systems and proposes the novel approach of embedding a flexible fiber fabric as a superficially distributed connector between concrete and FRP. Eight specimens with four different connection strategies were tested using an experimental modal analysis and a quasi-static three-point bending test. The impact of the connection system on the vibrational response, flexural ultimate load, moment response, neutral axis position, shear and dissipated energy was obtained and compared. The results show that the use of an embedded mesh increases the frictional mechanism and produces the best performance in terms of load-bearing capacity and ductility.
ABSTRACT
There is a variety of fuzzy classifiers, one of which is Adaptive Neuro-Fuzzy Inference system (ANFIS) classifier. One of the main challenges in designing such data classifiers is selection of effective and appropriate type and location of membership functions and its training method to reduce the classification error. In this paper, a new technique (based on intelligent methods) is presented and implemented to select and locate the membership functions and simultaneous training using a new method based on Inclined Planes System Optimization (IPO) to minimize errors of an ANFIS classifier for the first time. The presented method is evaluated for classification of data sets with different reference classes and different length feature vectors, which have acceptable complexity. According to the results of the research, the presented method has a higher level of accuracy and efficiency in selecting the type and location of membership functions (based on intelligent methods) and simultaneous training with IPO, compared to other methods, such as particle swarm optimization, genetic algorithm, differential evolution, and ACOR algorithms.
