Italian Group Fracture (IGF): E-Journals / Gruppo Italiano Frattura
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Integrated FEM-Multibody Co-Simulation of Additively Manufactured Hip Prosthesis containing cracks.
Full text linkThe increase in life expectancy and attention to the quality of life of elderly people spurred the need, in the last decades, to increase the capabilities of medical and surgical techniques. Among these, the development of prosthetic implants has been a staple of biomedical engineering research since the 70’s. In order to satisfy the challenging demands, the latest novelties in industrial engineering are being tested in their applicability to subjects. The 3D printing of metal alloys can produce a highly customizable product, which, after the proper heat treatments, can possess adequate mechanical properties to ensure a satisfactory component life. Defective products are often the results of wrong or absent post-processing treatments which may cause an uncontrolled crack propagation and a premature total failure of the implant. The behavior of such a product, with various critical crack conditions, was investigated by an integrated MBD-FEM co-simulation environment, focused on a femur subjected to total hip replacement. It was concluded that the Stress Intensity Factor (SIF) computed by the model is compatible with the premature failures experienced by patients, and as such, this model opens the possibility for further analyses aimed at understanding the role of defects on the durability of prothesi
Enhancement of punching shear behavior of reinforced concrete flat slabs using GFRP grating
Full text linkThe literature review showed insufficient relevant research on the application of Glass-Fiber-Reinforced-Polymers (GFRP) gratings in the structural elements, while GFRP bars, laminate, sheets, and strips, have been extensively explored. This research aims to present a proposal for a new reinforcing system using GFRP gratings to improve the punching shear resistance of RC flat slabs. Results of seven specimens tested experimentally under vertical static loading are displayed, taking into account the influence of the gratings variables. Test results revealed an improvement in the ultimate load ranging between 9.03% and 27.67% for the specimens strengthened by the proposed GFRP grating system. A Nonlinear Finite Element Analysis (NLFEA) was carried out using the ANSYS program with correlational evaluation using load-deflection response and cracking pattern, which resulted in a good convergence of numerical simulations and experimental performance results ranging from 1.0% to 8.0%. Key parameters, namely the concrete compressive strength, steel reinforcement yield strength, main steel reinforcement ratio, secondary steel reinforcement ratio, column dimensions, slab thickness, concrete cover, and GFRP gratings characteristics, were investigated through a parametric study adopting NLFEA by the ANSYS program, where the output results were compared to the recent code provisions
Uniaxial fatigue study of a natural-based bio-composite material reinforced with fique natural fibers
Full text linkThis research addresses environmental concerns by exploring environmentally friendly composite materials as substitutes for non-biodegradable synthetic fibers. The study proposes the development of polymer matrix composites reinforced with natural fique fibers, sourced from a plant cultivated in Colombia. A BioPoxy 36 polymer matrix with a high carbon content was used and reinforced with fique fabric using the vacuum-assisted lamination method. To improve the adhesion between the fibers and the matrix, an alkaline chemical treatment was applied to the fiber using 2% sodium hydroxide by weight. Mechanical properties were assessed through ASTM D3039 tensile and ASTM D3479 fatigue tests. A fractographic analysis was also conducted to identify the different modes of failure present. In terms of material degradation, distinct stages were observed, characterized by stiffness loss and loss factor indicators. The Coffin-Manson model was used to obtain the strain life curve for R = 0.1, using these factors as criteria. The static properties of the composite reinforced with fique fibers indicate an increase of 45% in ultimate strength, 145% in strain, and 27% in Young's modulus compared to the unreinforced matrix. In terms of dynamic properties, the elastic modulus showed a maximum variation of up to 7.88%. Electron microscopy reveals the failure mechanism, a distinct separation between the matrix and the fiber can be observed as a result of mechanical stress. The analysis reveals the brittle fracture of the hard fique fiber and some matrix separation, as well as possible fractured bubbles that may have occurred during the manufacturing process
Interleaving Carbon-Glass Veil in Glass Epoxy Composite for Improved Mode-I Fracture Toughness – A Hybrid Approach
Full text linkThe present study investigates the influence of hybrid interleaving technique using Glass and Carbon veils to improve the mode-I fracture toughness in Glass epoxy laminates. Commercially available non-woven Carbon and Glass veils with different areal densities were used to develop hybrid interleaved composites. Two approaches of interleaving, namely inter-ply and inter-weaved veils, were followed to manufacture the interleaved composite laminates using the hand layup technique. Double Cantilever Beam (DCB) samples were tested to estimate the interlaminar fracture toughness (IFT). Test results indicate that the inter-ply interleaved composite (I-C30G30) exhibited an improved initial and propagation fracture toughness of about 16.98% and 3.08%, respectively. A decreased IFT during initiation and propagation was observed for I-C15G30 and I-C20G30 when compared to plain samples. In case of inter-weaved veil interleaving approach, an improved fracture toughness (GIC and GIP) of about 7.96% and 12.94%, respectively, was observed for W-C15G30 sample, nevertheless W-C20G30 and W-C30G30 showed a drop in fracture toughness (GIC) of an about 12.15% and 9.22%, respectively, and an improvement in fracture toughness (GIP) of about 12.37% and 13.82%, respectively, when compared to plain sample. Scanning electron photo images (SEPI) of cracked laminates witnessed the fracture mechanisms involved in hybrid ply interleaved and non-interleaved composite laminates
Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process
Full text linkThis study focuses on ductile fracture behavior prediction for Ti6Al4V alloys fabricated via Selective Laser Melting (SLM). A modified Gurson-Tvergaard-Needleman (GTN) model characterizes void growth and shear mechanisms under uniaxial stress. The research explores the impact of Artificial Neural Network (ANN) architecture, specifically hidden layers and neurons, on predicting fracture parameters. Results reveal that increasing hidden layers substantially enhances accuracy, particularly for fracture displacement. Notably, predicting maximum force requires fewer layers than fracture displacement. Using selected layers and neurons, the system consistently achieved R2-values exceeding 0.99 for both maximum force and fracture displacement. The study identifies the initial void volume fraction (f0) parameter as having the most significant influence on both properties
Civil Structural Health Monitoring and Machine Learning: A Comprehensive Review
Full text linkIn the past five years, the implementation of machine learning (ML) techniques has surged in civil engineering applications, particularly for optimizing and predicting solutions to various challenges. More robust prediction models may be produced by combining test data collected in the laboratory or field with ML. These models may be used to estimate the compressive strength of masonry or repair mortars, probable damage scenarios in buildings, concrete models, beams, and columns for determining the mechanical characteristics of materials, damage detection in civil structures, and so on. This comprehensive review aims to clarify the array of ML-based methods employed in civil engineering, specifically focusing on their efficacy in strengthening energy efficiency and cost-effectiveness. In combination with ML, the review explores corresponding soft computing methodologies such as fuzzy logic (FL) and design of experiments (DOE). A variety of case examples that highlight the versatility of these approaches, particularly in applications linked to structural reinforcement, enhance the story. The review navigates difficulties associated with the integration of soft computing in civil engineering and expands its scope to include emerging research directions. This synthesis of advanced artificial intelligence (AI) serves as a guide, providing new researchers with knowledge about a developing field. These methods could revolutionize the current situation by providing creative answers to complex problems that arise in civil structural applications
Machining effects and multi-objective optimization in Inconel 718 turning with unitary and hybrid nanofluids under MQL
Full text linkDesigning tooling and cooling systems to prevent cutting tool damage is crucial while machining difficult-to-cut nickel alloys. This study investigates the machining effects during turning Inconel 718 using unitary aluminum oxide (Al2O3) and hybrid aluminum oxide+multi-walled carbon nanotube type (Al2O3+MWCNT) nanofluids under minimum quantity lubrication (NFMQL) through mathematical modeling and multi-objective optimization. The worn-out tools were analyzed for damage and wear mechanisms through images captured using optical and scanning electron microscopes. The study indicates that hybrid nanofluids outperform unitary nanofluids, which could be attributed to the better lubricating and cooling capabilities of MWCNT and the higher surface tension and thermal conductivity of Al2O3 nanoparticles. The cutting parameters were optimized by combining the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) and genetic algorithm. The study reveals an average error of less than 10% between experimental and predicted responses from the proposed optimization model. This study found lower cutting force up to 80 N, surface roughness of 0.6–0.7 µm, and tool life over 10 minutes with a cutting speed of 50–70 m/min and a lower feed and depth of cut of 0.1 mm/rev and 0.2 mm, respectively, using a hybrid Al2O3+MWCNT nanofluid under NFMQL conditions
Assessing structural integrity of non-homogeneous systems by means of Acoustic Emissions and Non-Extensive Statistical Mechanics
Full text linkTaking advantage of the interevent time intervals, namely the time intervals between two successive acoustic events recorded during mechanical loading of structural elements, it is attempted to detect indices warning about upcoming failure. The innovative aspect of the study is that the analysis is implemented in the frame of Non-Extensive Statistical Mechanics, a discipline founded on a class of entropies violating the additivity principle, which is the cornerstone of the Boltzmann-Gibbs Statistical Mechanics. The specimens used for the experiments were marble blocks simulating either fragmented and restored epistyles or mutually interconnected intact epistyles of the Parthenon Temple on the Acropolis of Athens. The specimens consisted of three materials (marble, metallic connectors and cementitious pastes) exhibiting, thus, a strongly non-homogeneous nature. The entropic index, i.e., the parameter quantifying the degree of non-additivity, was used for the analysis of the experimental data. The results were considered in juxtaposition to the respective ones from experimental protocols with specimens of macroscopically homogeneous nature. It was concluded that the temporal evolution of the entropic index provides very good insight into the level of damage accumulated in the loaded structure, independently of whether the structure is homogeneous or not, providing an interesting pre-failure indicator
ANSYS implementation of the phase field fracture approach
Full text linkIn this study, we present a new implementation of the phase field fracture approach in the finite element code ANSYS and its numerical background. The framework is general, and is supported by addressing several classical 2D boundary value problems as well as the ductile fracture and 3D surface flaws behaviors of particular interest. The 3D implementation exploits the analogy between the phase field formulations and the magnetic vector potential equation. The influence of the mode mixity and biaxiality loading conditions of the cracked bodies on phase fields is evaluated as a function of the crack length scale parameter, characterising the scale at which damage effects become significant. As a result of the FE calculations of phase field distributions for propagating cracks, the effects of both the fracture mode and the biaxial stress-strain state are determined. The size of the fracture process zone or damaged region is determined across a wide range of cracked body loading conditions. Developed code: https://github.com/Andrey-Fog/ANSYS-USERELEMENT-PHFLD
Application of deep learning for technological parameter optimization of laser shock peening of Ti-6Al-4V alloy
Full text linkThe paper is devoted to the development of the method of laser shock peening (LSP) of metals. To optimize the mode of LSP for Ti-6Al-4V specimens a deep learning model for predicting residual stresses by laser shock peening was developed. A numerical-experimental method was used to carry out the model training, in which an experimental study of the effect of different processing mode on the depth and distribution of residual stresses was carried out. The Johnson-Cook model was used as the governing relationship for modeling the dynamic deformation process. At the second stage, the problem of static equilibrium of a body with a plastically deformed area was numerically solved to determine residual stresses. The results of research on determination of the optimal configuration of the deep learning model showed that when using sinusoidal activation function of the neural network with 4 hidden layers and the number of neurons 10, the best level of accuracy in solving the problem is achieved. The obtained model allows us to optimally determine the LSP mode according to the given limitations of values and depth of residual stresses