Italian Group Fracture (IGF): E-Journals / Gruppo Italiano Frattura
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Damage assessment in beam-like structures by correlation of spectrum using machine learning
Get PDFDamage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the problem faced is the difficulty in controlling the excitation in structures. Therefore, the output-based structural damage identification method is becoming attractive because of its potential to be applied to an actual application without being constrained by the collection of the information excitation source. An approach of damage assessment based on supervised Machine Learning is introduced in this study by using the correlation of spectral signal as an input feature for artificial neural network (ANN) and decision tree. The output of machine learning algorithms consists of the appearance of new cuts, the level of cutting and the cutting position. A supported beam model was constructed as an experiment to determine if the method is reasonable for engineering structures. Two machine learning algorithms have been applied to check the relevance of the proposed feature from vibration data. This study contributes a standard in the damage identification problem based on spectral correlation
Compressive study on recycled concrete: experiment and numerical homogenization modelling
Get PDFThis paper describes a study of recycled concrete under compressive loads. The study was conducted in two main parts. In the first part, experimental tests were carried out on concrete samples with varying levels of substitution (25%, 50%, and 75%) with recycled aggregate in order to measure the mechanical properties of the recycled concrete. In the second part of the study, a nonlinear homogenization model was developed on the basis of a classical secant approach to predict the behavior of recycled concrete. In this model, we assume that the behavior of the mortar phase, the concrete, and the recycled aggregates follow Mazars damage law. Comparison with the experimental data shows that the proposed homogenization model is accurate and efficient in predicting the correct nonlinear behavior of the recycled concrete. By better understanding the properties and behavior of recycled concrete, it will be possible to develop more effective methods for incorporating recycled materials into concrete structures
Structural integrity analysis of the pre-stressed concrete dome of the Belgrade fair hall 1
Get PDFBelgrade fair hall 1 is well known for its dome, which is still the world largest self-supported construction made of pre-stressed concrete, with its diameter of 106 m. In this paper the Finite Element Method (FEM) was performed to analyze different loading and supporting conditions. At the same time, crack growth in a support column was simulated by the extended FEM (XFEM). Results of numerical calculations indicate ingenious design of such a complex structure which was based on “hand” calculation decades ago, without computers. In addition to classical engineering and more advanced numerical calculations, risk based analysis was performed taking into account artificially introduced crack and Failure Analysis Diagram, obtained using stress intensity factor and net stress, as well as fracture toughness and critical stress. This analysis, made for the first time for Belgrade fair hall 1, proved that its structural integrity is jeopardized only when a crack reaches half the thickness of a steel bar.  
Fracture Simulation of Concrete Beams to assess softening behavior by varying different fractions of Aggregates
Get PDFSimulating the concrete fracture unlike other elastic and brittle materials quite different due to its quasibrittleness. The present research focussed on assess softening behavior by varying different fractions of aggregates and cement matrix in micro details. Extended Finite Element Method (XFEM) for crack modeling implemented for simulating and visualizing crack propagation through Cement matrix, Interfacial Transition Zone (ITZ) and Aggregates . This approach permits the initializing crack by from enrichment zone and propagation of crack through element by traction separation law .The crack formation initiates when the maximum principal tensile stress reaches the tensile strength.
The work involves creating python script for iterative process of random distribution of aggregates with in the matrix using Monte Carlo method and creating Cohesive zone element for zero thickness ITZ. introduces a finite element modeling technique for investigating multiscale fracture characteristics. This approach encompasses multiple levels of analysis, including the generation of aggregate particles using a Monte Carlo method implemented via a Python script. Additionally, we replicate the Interfacial Transition Zone (ITZ) between aggregate and mortar in the model. The load-deflection curves can be used to assess the softening behavior of concrete and suggest the realistic fraction of coarse aggregate in mix proportion to impart more ductility to beams
Effect of Pre-tensioning Force on Behavior of Buckling Restrained Brace (BRB) Supported by Double Pre-tensioning System
Get PDFThe study explores the feasibility of a new all-steel buckling restrained brace (BRB) with the double pre-tensioning system as an alternative to conventional concentrically braced frames by using finite element method (ABAQUS program), And to verify modeling, use U-V1 specimen results and compare them with test results. The restraining element in an all-steel BRB is built from a rectangular plate with a double cross arm and cables, making it easy to fabricate, inspect, and replace after a severe earthquake. Numerical analyses were conducted on four groups: first group of specimens using dynamic loading to achieve the minimum thickness for stable hysteretic behavior and high efficiency for BRB, and three groups of specimens using monotonic loading to achieve the best pre-tensioning forces value in steel 37, 44 and 52 for greater efficient use of all steel BRB. The results showed a 66% improvement in bearing capacity, with the external restraining case thickness reduced to 20 mm, making it lightweight, economical, and easy to maintain. The specimens with a pre-tensioning force of 70 kN, 50 kN and 40 kN providing a 31%, 51% and 73.2 % for steel 37, 44 and 52 respectively over than the design specimen without pre-tensioning system
Mechanical and Fracture Characterization of Epoxy/PLA/Graphene/SiO2 Composites
Get PDFThis work investigated the effects of graphene and SiO2 addition on the mechanical and fracture properties of epoxy (80%) - Polylactic acid (PLA) (20 %) composites. Epoxy-PLA composites were loaded with graphene and SiO2 (0.1-0.5 wt. % with equal weightage of each filler), and were manufactured by bath sonication followed by manual casting. The tensile, flexural strength and fracture toughness of nanocomposites increased with an increase in filler concentration till it reached 0.3 wt. %. The addition of filler content higher than 0.3 wt. % drastically reduced the mechanical and fracture properties. The fractured surfaces from the tensile tests were examined using Scanning electron microscopy imaging to understand the effects of filler addition. The numerical analysis was also performed to simulate the impact of filler concentration on the tensile strength of nanocomposites using representative volume element (RVE) in ANSYS workbench
Matrix Hybridization Effects on Interlaminar Fracture Toughness of Glass Epoxy Laminates using Nano and Micro fillers
No full textThe composite materials are normally made of reinforcements and resins. High-performance composites are generally termed hybrid composite materials. Generally, fiber-reinforced composite laminates are very weak in their out-of-plane properties, to address this issue unidirectional (UD) Glass laminates are prepared by modifying epoxy matrix using plasma-treated multi-walled carbon nanotubes (MWCNTs) and compared with low-cost micro fillers like Aluminum oxide (Al2O3) and Sodium Carbonate (Na2CO3) in the epoxy matrix. All these Nano and Micro fillers were loaded in the range of 0.5wt% to 2wt% in epoxy. The addition of these fillers in the epoxy matrix was found to be effective in increasing the out-of-plane load-bearing capacity of the composites as compared to plain Glass epoxy laminates. Also, the fracture toughness enhanced in the range of 20-26% and 14-17.5% under mode I and mode II loading respectively. Scanning electron microscopic analysis was done for delaminated glass laminates and found that the delamination of fibers is the significant failure mechanism during crack initiation from the crack tip
Crack simulation for the cover of the landfill – A seismic design
Get PDFThe stability of the landfill is an environmental issue. The collapse of the landfill causes environmental pollution and influences human life. In the present study, the crack on the cover of the landfill was simulated. Rankine’s theory and the Phantom Node Method were used for the simulation length of the crack and the mechanism of the crack propagation in the nonlinear extended finite element method (NXFEM). Artificial Neural Networks (ANNs) based on Levenberg-Marquardt Algorithm and Abalone Rings Data Set mode were used to predict displacement in critical points of the model. The vibration mechanism of the landfill was changed in each model. During applying seismic load on the model, the optimized thickness of the clay cover on the landfill was discussed. The thickness of the landfill cover controls the seismic response of the landfill. The numerical simulation shows differential displacement of the landfill impacts on the crack propagation and the need for the appropriate design of the cover thickness of the landfill
Damage and restoration of historical urban walls: literature review and case of studies
Get PDFWithin this work, the causes of collapses and damages occurred in masonry artefacts have been evaluated to properly identify suitable monitoring and restoration methods. In this regard, a comprehensive literature review has been performed. Based on the results, the moisture has found to be a critical parameter, which affects the structural health of masonry artefacts. Diverse non-destructive methods were employed to measure the moisture and monitor the materials involved: the Infrared Thermography, the Electrical Resistivity Tomography and the Ground Penetrating Radar, the Laser Scanning and Digital Terrestrial Photogrammetry, the Global Navigation Satellite Systems, the Unilateral Nuclear Magnetic Resonance, the Laser-Induced Fluorescence technique, the Acoustic Imaging and the Acoustic Tomography, the Geographic Information System and on-site survey process as well as computer modeling of the structure with specific FEM software. Finally, the implementation of tie-beams, Fiber Reinforced Polymers layers, ventilation, draining systems, and high-quality materials are proposed as solutions for controlling the moisture effect and retrofitting
Automatic detection of concrete cracks from images using Adam-SqueezeNet deep learning model
Get PDFCracks on concrete surface are typically clear warning signs of a potential threat to the integrity and serviceability of structure. The techniques based on image processing can effectively detect the cracks from images. These techniques, however, are generally susceptible to user-driven heuristic thresholds and extraneous distractors. Inspired by recent success of artificial intelligence, a deep learning based automated crack detection system called CrackSN was developed. An image dataset of concrete surface is collected by smartphone and carefully prepared in order to develop and train the CrackSN system. This proposed deep learning model, built on the Adam-SqueezeNet architecture, automatically learns the discriminative feature directly from the labeled and augmented patches. Hyperparameters of SqueezeNet are tuned with Adam optimization additive through the training and validation procedures. The fine-tuned CrackSN model outperforms state-of-the-art models in recent literature by correctly classifying 97.3% of the cracked patches in the image dataset. The success of CrackSN model demonstrated with light network design and outstanding performance provides a key step toward automated damage inspection and health evaluation for infrastructure.