جستجوی مقالات مرتبط با کلیدواژه "w" در نشریات گروه "فنی و مهندسی"

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.

This study focuses on the mechanical characterization and application of the various Multiple Attribute Decision Making (MADM) approaches for the selection of composites fabricated using two natural fibers, kenaf, and sawdust. Mechanical characterization involves testing the physical properties of these materials, such as tensile strength, flexural strength, and impact strength along with density and water absorption, to determine their mechanical behavior and suitability for various applications. The MADM approaches namely VIKOR and PSI are used to evaluate the mechanical properties of kenaf and sawdust reinforced composites for different applications based on multiple criteria or attributes. The study analyzes the trade-offs between different attributes to identify the optimal composite configuration for a given application. MADM technique offers a helpful framework for assessing the mechanical attributes of fiber-reinforced composites thereby determining their possible uses in a variety of sectors. However, it is essential to use the MADM approach in conjunction with other methods of material characterization and testing to ensure that the final decision is based on a comprehensive understanding of the material's properties and performance. The outcomes of this feasibility study will benefit researchers, manufacturers, and decision-makers involved in the selection and development of composite materials. It can assist in optimizing the material selection process, promoting sustainable and environmentally friendly choices, and enhancing the overall performance and cost-effectiveness of composite materials in various applications.

The article incisively analyzes the impact of piezoelectricity on Love wave transmission in an inhomogeneous bi-layered structure consisting of smoothly embedded thin piezoelectric material bonded to a semi-infinite fiber-reinforced medium. By applying the variable-separable method, a general form of dispersion equations, analyzing the Love waves’ characteristics in electrically open and shorted cases of the piezoelectric material has been derived. The crux of the study lies in the fact that the presence of the prestresses in the upper layer and lower half-space along with elastic, piezoelectric, and permittivity coefficients lead the derived frequency relation to merge with the classical form of equations of the Love waves. The procured dispersion relation substantiates that the depth of the upper layer prestresses, and piezoelectricity coefficients play a guiding role in the transmission of Love waves. The numerical discussions and findings carry wider applications and may imply guidance of additive manufacturing of varied composite multi-materials for pre-stressed and microstructural configurations with partial and global dispersion properties

Conventional overcurrent protection schemes may not be sufficient to provide the complete protection of microgrids, especially in the islanded mode (ISM) of operation. Directional overcurrent relays (DOCRs) in microgrid may malfunction due to significant changes in fault current level and change in topology from grid-connected mode (GCM) to ISM. The novel contribution of this study is to determine the optimal settings of time-voltage-current-based dual-setting DOCRs with mixed inverse characteristics, valid in both GCM and ISM, without any miscoordination of relay pairs. The relay coordination problem is formulated as a mixed integer non-linear programming (MINLP) problem and optimally solved using an improved environmental adaption method (IEAM). The proposed relay coordination scheme has been tested on a 7-bus microgrid, the low-voltage section of the modified IEEE-14 bus benchmark system. The performance of the proposed protection scheme has been compared with the existing schemes, considering conventional DOCRs, time-voltage-current-based DOCRs, and dual-setting DOCRs.

In recent years, due to rising social welfare, the reliability has become one of most important topics of modern power network and electricity companies try to provide the electric power to the consumers with minimal interruptions. For this purpose, the electricity companies to improve the reliability of the power system can utilize different techniques. In this paper, new developments occurred in electricity industry including integration of large-scale renewable resources, integration of large capacity energy storage systems, integration of combined heat and electricity units into power network and demand side response plans are taken into account, and these events impact on power network reliability is assessed. Power networks are affected with integration of renewable resources. Multi-state reliability models for renewable generation plants are obtained, in the paper. Suitable number of states in the proposed reliability model is selected by calculating XB index. Besides, fuzzy c-means clustering approach is utilized for determining probability of states. For study impact of energy storage systems with large capacity on power network reliability, load model is modified. To investigate effect of combined heat and power plants on power network reliability, failure of composed elements and produced thermal power are considered in reliability model of these plants. To evaluate demand side response impact on reliability of power network, the load model is modified. The effectiveness of the proposed techniques on the reliability enhancement of power network is satisfied using numerical results performed on reliability test systems based on the suggested methods.

The widespread adoption of microgrids in electric power systems has brought numerous advantages such as decentralized control, reliability, cost-effectiveness, and environmental benefits. However, one of the most critical challenges faced by islanded microgrids is ensuring frequency and voltage stability. This paper addresses these stability issues that arise when microgrids operate independently, disconnected from the main network through the point of common coupling (PCC). These microgrids rely on renewable resources like photovoltaic (PV) systems, wind turbines, and energy storage systems, which often require DC to AC conversion through inverters to simulate synchronous generators. To overcome the frequency and voltage stability challenges, this research utilizes the droop control technique to regulate the active and reactive power of distribution generators (DGs). The droop control technique is implemented and simulated using MATLAB software, specifically employing a multi-DC bus-based inverter. The simulation results demonstrate that the DGs successfully supply the required total power to meet load demands while maintaining frequency and voltage stability. Through the droop control technique, active and reactive power sharing is achieved, ensuring stability at nominal values. The DGs can effectively maintain a constant power profile at desired values, even in the presence of static and dynamic loads.

Microgrid operators (MGOs) try to restore as much demand as possible when they are faced with electrical power outages corre-sponding to extreme events. This work suggests an outage management strategy (OMS) to improve microgrid resilience by using two optimal actions that are distribution feeder reconfiguration (DFR) and scheduling of the distributed energy resources (DERs). Later happening a line fault, the radial network topology is determined by the proposed model using an evaluation of the inci-dence matrix. The presented work handles the uncertain behavior of non-dispatchable DERs and the electrical loads which model by the robust optimization approach. To expand the flexibility of the proposed model, the demand response program (DRP) is treated as the curtailed demand. The aim of optimization is the minimization of the total cost for dispatchable DER operation and electrical load decrease. The recommended robust linear problem (RLP) model is simulated by the CPLEX solver in GAMS software. Applying the suggested model in the 69-bus unbalanced test system demonstrate that the proposed model averagely decreases total operation cost and execution time by 10.62% and 22.23% on all scenarios in comparison with the de-terministic model.

Ensuring an adequate and healthy blood supply is a persistent challenge that healthcare systems worldwide face. The need for blood donors and their products is constant, while the supply from donors is somewhat irregular, and the demand for these products is often unpredictable. Furthermore, the levels of demand and blood donation are uncertain. As a result, uncertainty plays a crucial role in the blood supply chain, especially during crises such as earthquakes and pandemics. In this regard, designing the  Blood Supply Chain Network (BSCN) under uncertainty is essential for meeting fluctuating demand, addressing logistical challenges, responding to emergencies, and ensuring the quality and safety of blood products throughout the supply chain. This research aims to present a Mixed-Integer Linear Programming (MIP) model under uncertainty for strategic and tactical decision-making in the blood supply chain over a determined planning horizon. The fuzzy theory approach has been used to incorporate uncertainty into the model's parameters. An interactive fuzzy solution approach based on credibility measurement has been developed to solve the fuzzy optimization model. The results obtained from designing and implementing the proposed model in a case study indicate the desirable efficiency of this model in determining the optimal number and location of facilities in a BSCN, including fixed facilities, temporary facilities, and blood banks, as well as the optimal amount of blood transfer between different entities of the blood supply chain. Furthermore, a sensitivity analysis of the parameters is performed to determine the most influential factors affecting the objective function of the problem.

Nowadays, online shopping plays a vital role in providing services and delivering goods to customers in the context of business intelligence and e-commerce. This research analyzes the customer purchase data of an Iranian online shopping company in Tehran. Among the available datasets provided by the company, 200 thousand records of one week of transactions have been selected for the present study. Several classification methods (i.e., Random Forest, gradient-boosted trees, K-Nearest Neighbor (KNN), Naïve Bayes, Kernel Naïve Bayes, and Neural Networks) and clustering approaches have been applied to discover the knowledge and patterns. The results show that before balancing the dataset, the KNN algorithm with K=5 is the best classification method among the existing methods. However, after balancing, gradient-boosted trees outperform the other classification methods. For clustering methods, the results show that the K-Means algorithm with K=3 is more efficient regarding the average within centroid distance for each cluster. Finally, concluding remarks and suggestions for future studies are stated.

The common presuppositions and limitations regarding the Resource Constrained Project Scheduling Problem (RCPSP) were investigated in addition to their reliability in modeling in order to investigate the possibility of availability of renewable resources using a new attitude. The objective of modeling RCPSP was the quantification of total costs and minimization of delays in projects. Hence, in order to mathematically model RCPSP, the first non-linear complex integer math programming was transformed into a linear programming model using the features of exponential functions. To solve the final linear math problem, some experimental examples were designed in different dimensions aiming to study the performance and efficiency of the designed model. For solving low-dimension problems, the exact (epsilon) constraint multi-objective optimization method was used in the Lingo software. A meta-heuristic algorithm called NSGA-II was employed to find solutions for high-dimension problems that the Exact method could not solve. The results of using these algorithms and the statistical analysis (with 95% reliability) indicated that the performance was suitable for the Genetic Algorithm (GA). The calculation error between the Exact method and the meta-heuristic method for the three target categories of total cost, time delay, and reliability was calculated based on the obtained results. The number of errors in calculating the total cost was 26%, 19%, and 5%, respectively. Also, the delay objective function error was equal to 28%, 24%, 12 %, and 14%, respectively. Finally, the reliability objective function error value was equal to 8%, 3%, 29%, and 36%, respectively. Accordingly, it can be concluded that this meta-heuristic algorithm (GA) has more efficiency and more apposite performance for the recommended model compared with the Exact optimization software. The use of the math model designed in this study can result in decreasing the time delays in projects and the costs of scheduling problems, as well as increasing the reliability in multi-mode activities.

This study introduces an advanced performance measurement system for 31 municipalities in Tehran and Shahriar, integrating the Balanced Scorecard (BSC) and Data Envelopment Analysis (DEA) methodologies. The combination of BSC and DEA was chosen because BSC offers a multidimensional framework for assessing performance from diverse perspectives, while DEA provides a quantitative tool for evaluating efficiency, particularly useful when dealing with multiple inputs and outputs. Together, they allow for both qualitative and quantitative evaluation of municipal performance, addressing the need for comprehensive performance assessment. However, traditional DEA models often fail to account for dynamic changes and intermediate linkages between these perspectives over time. The Dynamic Network Slacks-Based Model (DNSBM) of DEA, proposed in this study, addresses these limitations by incorporating both network interdependencies and dynamic changes in performance evaluation. Field studies and expert interviews revealed interconnections between BSC perspectives, and dynamic changes were modeled by linking networks over multiple periods. The model estimated efficiency values for each period, showing an average overall score of 0.857, with specific scores for financial (0.94), learning and growth (0.83), internal processes (0.96), and customer (0.34). Statistically significant correlations were found between most perspectives, except financial and learning/growth. The model identified dynamic performance trends, inefficiency levels, and strategies to improve underperforming DMUs, offering a comprehensive approach to enhancing municipal performance.