جستجوی مقالات مرتبط با کلیدواژه "2" در نشریات گروه "مکانیک"

The aerospace and automotive industries widely use composite materials due to their weight-to-strength ratios. One of the most significant problems with composites is repair and maintenance. This study attempts to repair glass epoxy composites. The repair process involves two stages: 1)optimization of the position of the hole and 2) repair work. To optimize the repair techniques, two distinct holes were performed: 1) at the center of the specimen and 2) at the edges of the specimen. As a result, the hole drilled at the center gives higher strength than the hole drilled at the edges. After the optimization, samples were repaired with a single hole in the center and peak loads of 60% and 90%. The cracked and delaminated areas were repaired with epoxy/hardener. The repaired samples were subjected to a three-point bending test, and the results were compared with the Neat GFRP samples. The results show that the curves of the repaired samples aligned with both the post and the residual flexural strength. The residual flexural strength of the 60% and 90% peak-loaded repaired samples retains about 47% and 76%, respectively.

In biomedical applications, particularly for tumor detection, the need for high-resolution imaging systems is critical. This paper presents the “S” parameter analysis of a three-layer stacked microstrip antenna with Defected Ground Structure (DGS) having a “+” shaped slot. The dimension of the antenna provides an enhanced performance ranging from 4.5-12 GHz. An aperture-coupled mechanism where a direct connection between feed and the FR-4 (Flame Retardant 4) substrate employing the need for three substrates having a dielectric constant (εr = 4.4) and having a thickness of 1.57mm each is utilized in this design. The composite material known as FR4 is structured with its fundamental layer consisting of fiberglass, woven into a thin, fabric-like sheet, providing essential structural support. This innermost layer of fiberglass imparts the necessary stability to FR4. It is then encased and secured by a flame-resistant epoxy resin. The antenna structure incorporates a parasitic patch as the topmost layer and an active patch that is placed below the substrate layer both of which incorporate slots for enhanced performance. The ground layer is sandwiched between the active layer and feedline which ensures separation between the two. Such a structure can help in optimizing both the radiating patch and the feedline independently. The performance of the designed antenna is studied for various slot configurations where the S- S-parameter analysis shows that the antenna provides wideband behavior which makes it suitable for biomedical applications like breast cancer detection. The S parameter analysis done in HFSS software shows a maximum return loss of -40dB which is performed for various slot configurations. The increasing demand for UWB communication systems underscores the critical importance of advanced antenna design to meet expanding data transmission requirements. The design of UWB antennas plays a crucial role in biomedical applications like breast cancer detection, where precise signal accuracy and penetration depth are essential for enhancing diagnostic efficacy and treatment monitoring.

Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computational tool is used to predict the elastic modulus of a composite of longitudinally placed fiber-reinforced polymeric composite. The novelty in carried work is that the property prediction is carried out considering interphase and its properties. For this, tensile properties data of Longitudinally Placed Bamboo Fiber Reinforced Polyester Composite (LUDBPC), Longitudinally Placed Flax Fiber Reinforced Polyester Composite (LUDFPC) and Longitudinally Placed Jute Fiber Reinforced Polyester Composite (LUDJPC) has been procured to generate ANN models. The Levenberg-Marquardt training algorithm is used to generate the ANN models as it gives more accurate results compared to other ANN algorithms based on interphase properties data. The validation of ANN models was also carried out based on fresh experimental results of BPC/FPC by doing the fabrication with hand layup technique and testing of composites with a Universal Testing Machine (UTM). The present work signifies that the developed ANN models give accurate results with experimental results for the prediction of elastic modulus of composite (Ecl) and it can be used for the prediction of longitudinally placed fiber-reinforced composite and Ecl of BPC at volume fraction of fiber (vf):22% is 2248.75 MPa and Ecl of FPC at vf:10% is 3210.50 MPa.

In this manuscript, replacing traditional antennas with biodegradable PLA substrates aims to reduce e-waste in today's technologically advanced age. This work achieves its objectives by designing the miniaturized (56 x 56 x 1.6) mm3 hexagonal patch antenna with partial ground (18.2 x 52) mm2 and incorporating complementary split ring resonators (CSRRs) in the HFSS (High-Frequency Structure Simulator). This innovative approach combines unconventional antenna design with metamaterial technology to enhance antenna performance, making it flexible, lightweight, and suitable for multi-band applications. An evaluation of PLA compared to other substrates revealed that PLA is more suitable for its eco-friendliness, and the simulation result is also satisfactory for bandwidth, return loss, VSWR, directivity, efficiency, and other parameters. Additionally, the integration of taffeta fabric as a conductive patch material provided elasticity and enhanced wearability. Using this unique method, the proposed antenna resonates at multiband frequencies of 2.6 GHz, 8.6 GHz, 10.5 GHz, 12.4 GHz, and 15.3 GHz, which gives return losses of -26.84 dB, -22.16 dB, -29.87 dB, -39.43 dB, and -26.35 dB, respectively. In addition to its biocompatibility and achievement of the SAR threshold, the antenna serves as a long-term solution for multi-band wireless applications. This further advances the realm of environmentally friendly wearable technology.

Composites are widely used for different applications in engineering mainly due to their tailored benefits, durability, reduced maintenance, and enhanced performance. GFRP is a synthetic material that has revolutionized the aerospace industry, offering a high strength-to-weight ratio, fuel efficiency, and enhanced performance for advanced applications. In structures like aircraft components, holes or notches are often present due to design requirements or secondary joining processes through rivets or bolted connections, which leads to wear and tear. Further, how these materials behave under tensile loads near these openings is critical for ensuring the safety and reliability of such structures. In the present study, GFRP/Epoxy composite laminates are subjected to open hole tensile test under ON and OFF axis orientations. The effect of loading under different sequences was studied. The nature of failure near the hole region was reviewed and presented. It is noted that the dominant failure was LGM type under the ON-axis and different under the OFF-axis which is not limited to shear failure, interlaminar delamination, and mixed mode failures. These trends are noted for different hole dia, namely 6,9,12 and 18mm. The study also presents the nature of the stress-strain curve for both configurations. The OFF-axis specimens displayed a non-linear behavior to failure as compared to the On-axis type. While, the on-axis specimens showed a marked reduction in peak load and tensile strength as hole dia increased with reductions up to 65.23% and 63.57%, respectively relative to hole-less specimens. The inclined failure in off-axis specimens varied between 500 - 550. Further, the damage tolerance in OFF-axis samples was higher as compared to ON-axis specimens.

This paper presents a multi-scale strategy for the thermal simulation of frictional systems, such as brakes, considering the microscale properties of the polymer composites. A finite element model is supposed to model the system components at the macro scale. At the microscale, the thermal properties are evaluated to identify the effective thermal properties of the polymer composites. As regards wear, Archard's law is used with a wear rate coefficient depending on temperature. The micro-scale properties of the polymer composites are integrated into the macro-scale model using the COMSOL computational package. In the conducted study, it is determined that the contact temperature for organic disk brake pad material reaches the highest value at 727 K, followed by ceramic material pad at 691 K, and semi-metallic material at 689 K. Focusing on epoxy and epoxy-fiber composites, it is observed that the Kevlar-epoxy composite exhibits temperature performance characteristics comparable to those of the semi-metallic and ceramic materials, registering a contact temperature of 693 K. In contrast, both epoxy and epoxy-carbon fiber composites display significantly higher temperatures, with values of 1254 K and 944 K, respectively. Consequently, these findings suggest that Kevlar epoxy shows promise in serving as a future brake pad material for the automotive industry. The multi-scale study on different materials focusing on the use of computational results for replacing the traditional brake pad material with advanced composites is the novelty of the study.

Fossil fuels, a non-renewable source, supply more than 81% of the world’s primary energy and contribute heavily to global climate change. This paper represents a strategy to address the administration of forest bio residue in the northern Himalayan district of India. Uttarakhand state, the north part of India, is rich in bio residues such as Pine needles of Chir Pine (Pinus roxburghii). Every year during the summer, there is a forest fire breakout, mainly caused by these dry pine needles, which cover a forest floor and are highly flammable. This forest bio residue is renewable and is a potential energy source for rural livelihoods, which would also generate social business enterprises among the locals. This is an effort to develop a practical manual-operated briquetting machine (BM) capable of fabricating briquettes from forest waste. The primary materials utilized to make briquettes are pine needles and forest waste. The proposed method inculcates principles of compression molding along with necessary optimizations. Briquetting is one of the cheapest ways to harvest the destructive energy of pine needles in a clean and economically viable way. Briquetting machines reduce forest fires by reducing dependency on wood from forests for fuel while simultaneously lowering carbon emissions by using biomass or agricultural waste as alternative fuel sources. This dual benefit protects forests and helps battle climate change and local air pollution, making it a long-term option for environmental protection. The developed BM is one solution that can solve the dual purpose of climate change mitigation and employment. The designed and developed machine fabricates thirty-three briquettes per hour and is currently installed in the Uttarkashi district of Uttarakhand, India.

A propeller guard is an instrument that helps to avoid Unmanned Aerial Vehicles (UAVs) or drone damage. Commercially, they are made from an engineering plastic such as Acrylonitrile Butadiene Styrene (ABS). This work aims to introduce the hemp fiber-reinforced polypropylene composites as a new competitive material for propeller guards. In this study, polypropylene was thermally mixed with different ratios of hemp fibers by internal mixing at 190°C. Tensile and impact testing were carried out according to ASTM D638 and ASTM D256, respectively. The results showed that the high contents of hemp fibers can enhance the modulus of their composites. Polypropylene composite with 45 wt.% of hemp fibers obtained the highest modulus at 1169.4 MPa. Also, the impact resistances of these composites were higher while the fiber contents were increased. Furthermore, application in drone propeller guard was executed by SIMCENTER 3D software for proving their propeller protection performance of as-prepared composites. The results indicated that polypropylene and its hemp fibers-reinforced composites could be the materials for this drone propeller guard.

Wood/PLA biocomposite filament is a 3D printing material that blends Polylactic Acid (PLA), a biopolymer, with wood powder acting as reinforcement. This combination results in a sustainable 3D printing filament that has grown in popularity in recent years due to its eco-friendliness and the natural appearance of 3D-printed parts. To assess the suitability of wood/PLA biocomposite for various additive manufacturing applications, it is essential to determine its mechanical properties. This study employs fused deposition modeling (FDM) as the additive manufacturing process and focuses on assessing the mechanical properties (tensile, flexural, and impact) of 3D-printed biocomposite. The Taguchi L27 design of the experiments is utilized, and the key process parameters under consideration are infill pattern, layer thickness, raster angle, nozzle temperature, and infill density. A layer thickness of 0.3 mm and an infill density of 100% yielded the highest tensile strength of 42.46 MPa, flexural strength of 83.43 MPa, and impact strength of 44.76 J/m. The dataset has been carefully prepared to facilitate machine learning for both training and testing, and it contains the experimental results and associated process parameters. Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). Given the intricate nature of the dataset and the presence of nonlinear relationships between parameters, XGBoost and AdaBoost exhibited exceptional performance. Notably, the XGBoost model delivered the most accurate predictions. The results were assessed using the coefficient of determination (R2), and the achieved values for all observed mechanical properties were found to be greater than 0.99. The results signify the remarkable predictive capabilities of the machine learning model. This study provides valuable insights into using machine learning to predict the mechanical properties of 3D-printed wood/PLA composites, supporting progress in sustainable materials engineering and additive manufacturing.

The main aim of this research is to optimize the injection molding process parameters in order to mitigate the shrinkage of polypropylene (PP) spur gears. The methodology used integrated experimental approaches with artificial neural networks (ANN), and Taguchi methods to determine the optimal combination of injection molding parameters. The experimental data was used to create an ANN model using Matlab software that accurately predicts unseen data with a variation of less than 5%. The trained ANN model was further used to predict gear shrinkage in the context of Taguchi-based design of experiments. The investigation involved the use of Taguchi and analysis of variance techniques, determining that cooling time is the most important and relevant parameter. This is followed by packing time and melt temperature. The analysis revealed that the gears saw the least amount of shrinkage when the molding was carried out using the optimal combination of injection molding parameters.

This study investigated the effects of atmospheric aging through three summer months on the mechanical properties of polyester reinforced with different mass rates of alfa fibers (Stipa Tenacissima). For this purpose, three-point bending tests were performed on pure polyester and polyester /alfa fiber composite specimens. A finite element model of flexural testing was developed to analyze the mechanical behavior of the Alfa/polyester composite. The test results showed that the alfa coarse fibers with 30 wt % were capable of enhancing the mechanical properties of the polyester/alfa composite.

The present study investigates the mechanical behaviors of hybrid fiber-reinforced polyester composites in developing a new strengthened material. The experiments were planned as per the design of experiments, the selected input parameters were fiber length (mm), NaOH treatment (%), and fiber weight (%) and the output parameters were tensile, flexural, and impact strength conditions. A Non-Linear Regression Modelling (NLRM) and Fuzzy logic model have been designed to predict and analyze the mechanical properties in unknown test conditions. Every input factor was categorized into three linguistic descriptors, while each output factor was classified into three linguistic categories. A triangular membership function was employed to define all these variables. The effectiveness of the nonlinear regression analysis and fuzzy logic model was evaluated through confirmatory experiments. The model predicted the mechanical results with an error of 7.19%, 5.38%, and 2.33% respectively. The proposed approach can significantly simplify real-life multi-response optimization problems, thereby reducing fabrication costs and enhancing composite fabrication efficiency.

Experimental and numerical studies are implemented in this work to investigate the modal characteristics of three-layered viscoelastic sandwich beams and plates with a natural rubber core and distinct isotropic face layers. In this study, the material of face layers in both beams and plates is varied with uniform face thickness by keeping the core constant to maintain the constant volume. Through the use of the Impact Hammer Modal Testing technique, experimental modal analysis is carried out with SAMURAI and ME' Scope software. The beams and plates are subjected to numerical analysis using ANSYS 19.2 Mechanical APDL Software, a finite element analysis (FEA) tool to evaluate the modal characteristics. The modal characteristics including natural frequencies and mode shapes of both beams and plates are evaluated under various boundary conditions, such as Clamped-Free (C–F), Simply-Supported (S–S), Clamped–Simply Supported (C–S), and Clamped-Clamped (C–C) for beams. Other plate boundary conditions that are taken into consideration for plates in this inquiry include C-F-F-F (Cantilever), S-S-S-S (All edges simply-supported), C-F-C-F (opposite edges clamped and other edges free), and C-C-C-C (All edges clamped). Ultimately, an excellent agreement is established when the outcomes of the experimental modal analysis are compared to those from ANSYS. The research also investigates how varying face layer material densities and end conditions affect natural frequencies at constant volume.

The aerospace and automotive engineering industries are seeing a growing need for materials that are both lightweight and very durable. This increased demand has prompted the development of innovative metal matrix composites based on aluminum. The current study aimed at developing and characterization Al7020 metal matrix composites by reinforcing micro boron carbide particles, Al7020/B4C MMCs are fabricated by stir casting method by varying the boron carbide particles in wt.% (0, 2, 4, 6, and 8wt. %). Lastly, the prepared samples were subjected to tensile, compression, hardness, and fracture toughness tests to evaluate the impact of B4C particles on density, mechanical, and microstructural parameters. By incorporating B4C particles into the Al7020 alloy, the experimental results demonstrated that metal matrix composites exhibited enhanced ultimate tensile strength, yield strength, hardness, and compression strength. In addition, the lowest density, highest toughness, and superior micrograph were observed in Al7020/B4C MMCs with 8 wt. % reinforcement of B4C particles with a minor decrease in elongation.

The novelty and main contributions of this research are to investigate simultaneously static bending, free vibration, and buckling responses of a sandwich beam composed of a five-layer beam using sinusoidal shear deformation theory (SSDT). In this work, five layers of a sandwich beam including a honeycomb core, carbon nanotubes reinforced composite (Matrix and Resin) (CNTRC) at the top and bottom of the core, and also, shape memory alloy (SMA) in the form of nanoscale particles with matrix in top and bottom of CNTRC are derived. In this study, the governing equations of equilibrium are obtained using the principle of minimum potential energy for deflection and buckling analyses, while Hamilton's principle is employed to obtain the governing equations of motion. Then, based on Navier's type method for simply supported boundary conditions, the deflection, critical buckling load, and the natural frequency for a sandwich beam composed of five layers are obtained. To validate the results, they are compared with existing literature, and there is a good agreement between them. Also, the effects of the thickness of the core, volume fraction of carbon nanotubes, and volume fraction of SMA are analyzed. The results reveal that changing the volume fraction from 0 to 0.01 results in a 30% decrease in deflection. It is concluded that with an enhancement in thickness ratio, the heat flux decreases due to the increase in the thickness of the core, while the thickness of face sheets decreases because the conductivity coefficient for CNT is higher than the core. Moreover, increasing temperature softens the material, leading to a decrease in the critical buckling load.

Grewia Optiva fiber-based polymer composites were prepared with the addition of Marble dust (MD) in varying percentages by hand-layup technique. To understand the behavior of the material, a detailed physical, mechanical, and thermo-mechanical analysis of the samples was conducted. The findings reveal that the addition of MD to 10 wt. % helps in enhancing the interfacial bonding between the fiber and epoxy. Due to the high void fraction and poor surface interaction, further addition of MD restricts beneficial changes in the composite. The thermo-mechanical analysis (DMA) illustrates that adding marble dust powder results in a decrease in chain mobility, hence enhancing the storage modulus of all samples. Due to its maximum elastic and low viscous regions, the GM-2 (MD 10 wt. %) specimen exhibits the lowest level of energy dissipation. The research also focuses on the sliding wear behavior of the material, and a Taguchi design approach is also used for parametric analysis of wear response. In conclusion, the Grewia Optiva fiber polymer composite with (GM-2) 10 wt.% marble dust shows the best mechanical, thermo-mechanical, and sliding wear results due to its superior interfacial bonding and can be found suitable for fabrication of portable cabins.

Because of the relatively high specific mechanical properties of LY556 epoxy resin, is often used as an important matrix for structural composites in high-performance applications. In the current study, an atomistic simulation based on molecular dynamics was performed to characterize the mechanical properties of LY556 epoxy (EP) nanocomposites reinforced with graphene oxide (GO) nanoparticles. The stiffness matrix and elastic properties such as Young’s modulus, shear modulus, and Poisson’s ratio for the pure EP and EP/GO nanocomposites were estimated using the constant-strain method. Three distribution methods including ultrasonic with a probe, mechanical mixing with an ultrasonic cleaner, and a high-shear turbo mixer with an ultrasonic cleaner were employed. The role of the distribution method on the tensile behavior of epoxy reinforced with varying percentages of GO nanoparticles (0.3 and 0.5 wt. %) was investigated. In addition, X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) were employed to investigate the quality of GO distribution in nanocomposites. In the M3 method (the optimal method) the tensile strength of the EP/GO nanocomposite was increased about 15% (76 MPa) at 0.3 wt% and 22% (80 MPa) at 0.5 wt%. Moreover, the toughness of the EP/GO nanocomposite was improved by around 34% (1.37 J.m-3) and 50% (1.53 J.m-3) at 0.3 and 0.5 wt% respectively.

The objective of the current study is to improve the strength and drainage capabilities of compressible clayey soil through the utilization of waste-to-energy plant ash. Numerous experiments, including consistency limits tests, compaction tests, unconfined compressive strength, California bearing ratio tests, and permeability tests, have been carried out in the laboratory on various combinations of highly compressible clayey soil and waste-to-energy plant ash or Municipal solid waste incinerated ash. The trial testing results show that adding waste to energy plant ash mix with the soil sample improves the strength properties of clayey soil, reducing the issue of ash dumping as well as developing a healthy environment. According to the test results, the falling head permeability test shows an improvement of permeability from 6.2×10-6 to 5.85×10-5 cm/sec for soil and soil with 20% MSWI ash mixed proportion respectively. Moreover, the mix produced by adding incineration plant ash may effectively be used as a sub-grade material, achieving cost-effective benefits. The findings showed that adding an adequate amount of bottom ash (20%) and soil sample (80%) made the soil more effective as a subgrade material by decreasing the value of differential free swell and consistency limitations of the soil and the value of UCS increased by more than 146 % and the soaked CBR values increased by 118% was noticed. The leaching test showed that when up to 20% of the ash is combined with the soil, the concentration of heavy metals lies within acceptable limits.

Developing customized drilling processes that minimize damage and improve overall performance in natural fiber composites relies on a thorough understanding of their drilling performance and potential damages. This study explores the variations in delamination and thrust force in a redmud-filled polyester composite reinforced with coconut sheath fibers. Employing a Taguchi factorial design, the experiment investigates the impact of drilling parameters, including drill diameter, spindle speed, and feed rate. The ANOVA analysis is employed to validate the experimental results. The findings indicate that increased feed rates and spindle speeds contribute to elevated thrust forces and delamination, influenced by the composite's inherent brittleness due to the addition of red mud. Among the drilling parameters, feed rate exerts the most significant influence on thrust force (ca. 30%), while the point angle has the greatest impact on delamination (ca. 60%). The analysis of drilled hole surfaces reveals matrix cracks, fiber extraction, and matrix smearing, underscoring the importance of optimizing drilling parameters, selecting appropriate tools, and implementing effective cooling methods to improve the overall surface finish and quality of drilled fiber composites. The research has the potential to aid in the development of strategies to minimize damages and enhance overall surface quality; ultimately, it contributes to advancing knowledge in materials science and engineering, with applications in the manufacturing and utilization of natural fiber composites across diverse industries.

The automotive industries have been compelled to build lighter, more fuel-efficient vehicles because of rising fuel costs and environmental laws. When the overall vehicle weight is reduced by adopting lightweight metals like aluminum-based composites, the fuel consumption also gets reduced. Aluminum-based composites are broadly used in the automotive and air transport industry due to their remarkable mechanical and tribological characteristics. The importance of composites made of aluminum used in automobile applications, as well as their damping characteristics, are discussed in this article. Due to the need for mechanical stability and performance in engineering applications, vibrations are unacceptable. Damping capability refers to the ability of materials to manage mechanical vibrations at the time of cyclic stress. To reduce mechanical vibrations in today's environment, materials with superior mechanical and damping capabilities are needed. Composites are a better alternative because they have better mechanical properties and damping capacity. The literature delves into the different aspects that influence aluminum-based composites and the need for damping studies in automotive applications. Finally, the research progress of aluminum-based composites towards damping characteristics has been reported by the Scientometric approach using VOSviewer. The Scopus engine search found 1329 documents relevant to Damping & vibration studies. Subsequently, a statistical analysis was conducted exclusively for the 628 research documents spanning the years 2010 to 2022.