Browsing by Author "Hekmatifar, Maboud"

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Citation Count: 0
Corrosion and mechanical properties of Al/Al₂O₃ composites fabricated via accumulative roll bonding process: Experimental and numerical simulation
(Elsevier Science Sa, 2024) Salahshour, Soheıl; Daneshmand, Saeed; Alabboodi, Khalid O.; Ali, Ali B. M.; Jasim, Dheyaa J.; Salahshour, Soheil; Hekmatifar, Maboud
With the advancement of science and technology and the construction of metal-based composites (MMC), it became possible to achieve improved properties that were not easily available in an alloy. In fact, with the emergence of such technology, manufacturers were able to adjust the resulting materials according to their needs in such a way as to provide mechanical strength, hardness, corrosion resistance, or other desired properties. These composites were used in various aerospace, automotive, construction, and production industries. Aluminum-based composites are among the structures that have taken an important place in the industry due to their lightweight and high strength. The present study produced bi-alloy aluminum-based 1060/5083 composites fabricated with alumina particles with a Hot ARBp at T = 380 degrees C. Also, the effect of rolling steps on the roll bonding mechanism is investigated using numerical simulation. As the novelty of this study and for the first time, a bi-alloy 1050/5083 composites reinforced Al2O3 particles via ARB process have been produced and then, potential dynamic polarization in 3.5 Wt% NaCl solution was used to study the corrosion properties of these composites. The corrosion behavior of these samples was compared and studied with that of the annealed aluminum. The study aimed to investigate the bonding behavior between the bi-alloy layers. So, as a result of enhancing influence on the number of ARBp, this experimental investigation revealed a significant enhancement in the main electrochemical parameters and the inert character of the Alumina particles. Reducing the active zones of the material surfaces could delay the corrosion process. Results showed that the corrosion resistance of the sample fabricated after six steps improved more than 100 % in comparison with the initial annealed Al alloy. Also, the average peeling force improved from 45 N to 94 N for the sample fabricated with six steps. Moreover, at a higher number of steps, the corrosion of MMC improved. Moreover, increasing the number of ARB steps illustrated an improvement in the wear resistance of samples. Finally, the samples' bonding interface, corrosion surface, and peeled surface were investigated using scanning electron microscopy (SEM).
Citation Count: 0
Mechanical properties of aluminum /SiC bulk composites fabricated by aggregate accumulative press bonding and stir-casting process
(Elsevier, 2024) Daneshmand, Saeed; Salahshour, Soheıl; Basem, Ali; Mohammed, Abrar A.; Wais, Alaa Mohammed Hussein; Salahshour, Soheil; Hekmatifar, Maboud
Today, the emergence of composite structures can be considered a huge transformation on an industrial scale, especially in the transportation industry. Among all the structures made by the composite process, aluminum- based composites (AMMCs) are particularly popular both in the scientific and industrial fields. These structures are very light in weight and, at the same time, have significant strength. The ability to work with the machine in these structures is very high, and their plastic deformation is so high that they can be used in different industry sectors. Today, various methods are used to induce plastic deformation in aluminum-based composites (AMMCs). One of these methods is called aggregate accumulative press bonding (APB). The advantage of this method compared to other methods is that this method can create a homogeneous nanocomposite with ultra-fine grains. In the present study, the investigation of mechanical properties (MP's) of AA5083/5%SiC bulk composites fabricated via APB vs. pressing temperature (Temp) was conducted. All primary composite samples were fabricated via the stir-casting process (SCP). APB process was done on composite samples as a supplementary process. Finally, the effect of pressing Temp on the MP and microstructural properties (MSP) was investigated. The pressing Temp was varied between the ambient Temp's up to T = 300 degrees C. The MP were measured in this study by the Vickers micro-hardness (VMH) test, tensile test, and scanning electron microscopy (SEM). It was realized that the pressing Temp has a prominent effect on the MS and MP of fabricated 400 degrees C. degrees C . Samples fabricated at the ambient Temp have low ductility and high strength while for samples fabricated at T = 300 degrees C, the elongation and toughness values were higher than others. The TS of samples after 2 steps of APB at T = 200 degrees C degrees C is 1.31 times more than that of fabricated at T = 300 degrees C. degrees C . Elongation was reduced sharply to 1.8% after the two steps at the ambient Temp, while it was 21% for the annealed AA5083.
Citation Count: 1
The molecular dynamics description of Polycaprolactone coating effect on mechanical behavior of Polycaprolactone/BG-AK bio-nanocomposites
(Elsevier Sci Ltd, 2024) Du, Xiuli; Salahshour, Soheıl; Sajadi, S. Mohammad; Hekmatifar, Maboud; Salahshour, Soheil; Sabetvand, Roozbeh; Toghraie, Davood
In current computational research, the effect of Polycaprolactone (PCL) coating on the mechanical properties (MP) of biomimetic calcium phosphate (BCP)/Baghdadite (BG)-AK nanocomposite (NC) is investigated by using molecular dynamics simulation (MDS). Our study models BCP/BG-AK-PCL samples by Universal Force Field (UFF) and DREIDING potential functions. The outcomes of MDS on the MP of atomic samples are presented by computing physical factors like temperature (Temp), potential energy (PE), Young's modulus (YM), and ultimate strength (US). Physically, MD outputs indicate the physical stability of the BCP/BG-AK-PCL sample after 5 ns. Also, by inserting the PCL coat into the pristine matrix, the YM of this structure reaches 0.39 MPa, and the US increases to 20.28 MPa. These numerical results show the important effect of PCL coats on the MP of pristine BCP/BG-AK NC, which can be used for clinical applications.
Citation Count: 0
Molecular dynamics simulation of mechanical and oscillating characteristics of graphene nanosheets with zigzag and armchair edges
(Elsevier, 2024) Fei, Qiang; Salahshour, Soheıl; Sajadi, S. Mohammad; Alawadi, Ahmed Hussien; Haroon, Noor Hanoon; Jasim, Dheyaa J.; Hekmatifar, Maboud
An oscillator is a circuit that can produce a continuous, repetitive, and alternating waveform without any input. However, the oscillations caused by the conversion between the two forms of energy cannot last forever. As a result, the amplitude decreases until it becomes zero, thus causing their nature to decrease. After discovering graphene nanosheets, their use in nanoelectricity science was much considered. Due to the amazing properties of graphene nanosheets, they can be used to establish permanent oscillations. The results show that graphene nanosheets ' mechanical properties and electrical properties depend on their structure and shape. Therefore, this study investigates the effect of graphene nanosheets type, size, and temperature on the simulated nanostructure's mechanical properties and oscillating behavior with Molecular Dynamics simulation. The results show that the graphene nanosheets with zig-zag edges has higher mechanical strength than armchair edges. Young's modulus and Ultimate strength of graphene nanosheets with zig-zag edges are numerically 1079 and 115 GPa, respectively. On the other hand, the resistance in graphene nanosheets can be expressed by reducing the oscillation amplitude and increasing the oscillation frequency. The results show that by changing the armchair edges to zigzag, the oscillation amplitude of graphene nanosheets decreases from 10.36 to 9.82 angstrom. Also, by enhancing the length of graphene nanosheets from 30 to 100, the oscillation amplitude of graphene nanosheets increases from 7.59 to 12.12 angstrom. This increase is due to the increases in the contact surface of the atomic structures. Consequently, the interactions between the carbon particles and mechanical resistance decrease. According to the results of this project, the findings improve the dynamics of nanoscale oscillators and cause a significant improvement in the performance of various devices.
Citation Count: 0
A molecular dynamics study of the effect of initial pressure on the mechanical resilience of aluminum polycrystalline
(Elsevier, 2024) Salahshour, Soheıl; Jasim, Dheyaa J.; Alizadeh, As'ad; Chan, Choon Kit; Salahshour, Soheil; Hekmatifar, Maboud
Polycrystalline materials are essential in engineering due to their ability to withstand various forces, heat, and environmental conditions. The arrangement of atoms within these crystals significantly affects their mechanical properties. This study used molecular dynamics simulations to explore how initial pressure affects the mechanical resilience of aluminum polycrystals. Aluminum composite materials, known for their strength, flexibility, and environmental sustainability, are the focus of this investigation. We particularly investigated stress- strain reactions at 1, 2, and 3 bar initial pressures. Reduced free volume causes atomic migration to be hampered as pressure increases, therefore affecting mean square displacement and diffusion coefficient. The results show that ultimate strength and Young's modulus of the polycrystalline samples were 30 and 6.64 GPa at 1 bar pressure. Moreover, the results demonstrated a notable decrease in mechanical performance by increasing pressure; the ultimate strength and Young's modulus of the polycrystalline samples diminished to 5.66 GPa and 22.43 GPa, respectively, at 3 bar. Furthermore, the heat flux increased by rising initial pressure in the Al- polycrystalline sample due to the compression of material that reduced atomic distances. This improved atomic arrangement facilitated more efficient heat transfer. These insights are essential for engineering applications, as they establish a foundation for the production of aluminum components that maintain structural integrity in the face of extreme conditions.
Citation Count: 0
A new approach for recycling, fabrication, and heat treatment of al base composites reinforced with rice husk ash particles
(Pergamon-elsevier Science Ltd, 2024) Vini, Mohammad Heydari; Salahshour, Soheıl; Hassan, Waqed H.; Khaddour, Mohammad H.; Jaafar, Mahdi Sh.; Salahshour, Soheil; Hekmatifar, Maboud
As a novel combined environmental toxicology technique to reduce the environmental hazards to humans, the utilization of agriculture waste as a novel waste material recycling process in aluminum metal matrix composites has been getting more attention to fabricate and improve the properties of this kind of composites. In this study, a new kind of metal matrix composite reinforced with rice husk ash particles has been fabricated. In the first step, the Al base composites reinforced with rice husk ash particles were fabricated via the compa casting process and the second step was the study of their mechanical, electrical, physical and wear properties. It also highlights the current application and future potential of agriculture-industrial waste-reinforced composites for various applications with a focus on material manufacturing in vessels, automobiles and other construction industries. Also, the annealing was performed after ARB on fabricated composites. Different elongation can happen during heating and annealing since the thermal expansion coefficients of composite samples are not equal and could weaken the strength of the interface. The examination unveiled that composites containing 10% by weight of RHA particulates exhibit superior mechanical and wear resistance compared to monolithic samples. Moreover, the average Vickers hardness of the samples increased from 154.0 to 168.0 for monolithic and 10% RHA samples, respectively, marking a 9% improvement.
Citation Count: 1
A numerical study of carbon doping effect on paraffin-reinforced silica aerogel mechanical properties: A molecular dynamics approach
(Elsevier, 2023) Zhang, Wei; Salahshour, Soheıl; Alizadeh, As'ad; Nasajpour-Esfahani, Navid; Hekmatifar, Maboud; Sabetvand, Roozbeh; Toghraie, D.
Aerogels are different types of porous and solid materials that exhibit a strange set of extraordinary material properties. Aerogels have great potential for use in the fields of heat, sound, electronics, and especially thermal insulation. This paper investigates the influence of carbon doping concentration on the mechanical properties of paraffin-reinforced silica aerogel (PRSA). To do this investigation, Young's module (YM), stress-strain curve, and ultimate strength (US) values at various carbon-doped particles of 1 to 10 % were reported by molecular dy-namics (MD) simulation. The results show that the PRSA, under the influence of carbon doping, has dual per-formance. To be more precise, by adding the amount of carbon doped from 1 to 3 %, the US and YM of the PRSA rose from 329.96 and 1137.20 MPa to 353.73 and 1268.44 MPa. In other words, the mechanical strength of the PRSA increases in a limited ratio. However, by increasing carbon doping from 3 to 10 %, the US and YM of the PRSA reduced to 306.233 and 1041.88 MPa, respectively. So, it is expected that the mechanical behavior of the PRSA matrix to be manipulated with carbon doping for actual applications.
Citation Count: 0
An RBF-based artificial neural network for prediction of dynamic viscosity of MgO/SAE 5W30 oil hybrid nano-lubricant to obtain the best performance of energy systems
(Elsevier, 2024) Gao, Jie; Salahshour, Soheıl; Sajadi, S. Mohammad; Eftekhari, S. Ali; Hekmatifar, Maboud; Salahshour, Soheil; Toghraie, Davood
Technological progress and complications in microfluidics usage have led researchers to use nanomaterials in different scientific fields. The properties and characteristics of hybrid Nanofluids are more enhanced compared to nanofluids based on single nanoparticles and conventional liquid. Recently, modeling methods have replaced most common statistical methods. Due to the high accuracy of the response and generalizability in various conditions, artificial neural networks (ANNs) to estimate nanofluids' viscosity and thermal conductivity have become common. Dynamic viscosity (mu) (estimation analyzes one of the key factors in determining the hydro-dynamic behavior of nanofluids. In this manuscript, an RBF-ANN is used to simulate the input-output relation of dynamic viscosity of the MgO-SAE 5W30 Oil hybrid nanofluid versus three important parameters, including volume fraction of nanoparticles, temperature, and shear rate. The results show that for this nanofluid, by increasing temperature and shear rate, the dynamic viscosity is decreased. In contrast, the volume fraction of nanoparticles directly affects the output, although this consequence can be neglected. By increasing the tem-perature from 5 degrees to 55 degrees C, the dynamic viscosity would decrease. Also, changing the shear rate from 50 to 1000 rpm decreases the dynamic viscosity from 400 cP to 25 cP. It is worth mentioning that the obtained trends and deviation of dynamic viscosity for MgO-SAE 5W30 Oil hybrid nanofluid versus temperature, the volume fraction of nanoparticles, and shear rate can be used by the academic community as well as an industrial section to obtain the best performance of energy systems based on this nanofluid.
Citation Count: 0
Regression modeling and multi-objective optimization of rheological behavior of non-Newtonian hybrid antifreeze: Using different neural networks and evolutionary algorithms
(Pergamon-elsevier Science Ltd, 2024) Jin, Weihong; Salahshour, Soheıl; Baghoolizadeh, Mohammadreza; Kamoon, Saeed S.; Al-Yasiri, Mortatha; Salahshour, Soheil; Hekmatifar, Maboud
The research used an artificial neural network (ANN) model to examine the rheological properties of hybrid nonNewtonian ferrofluids (HNFFs) composed of Fe-CuO, water, and ethylene glycol. The performance of neural network was optimized using seven regression methods (RMs), namely Group Method of Data Handling (GMDH), Decision Tree (D-Tree), Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), Extreme Learning Machine (ELM), Radial Basis Function (RBF), and Multiple Linear Regression (MLR). The findings highlighted GMDH method's superior performance when compared to neural networks. R and RMSE values attained by GMDH for the objective function (OF) mu nf were 0.99436 and 2.0135, respectively. For the torque function OF, the values were 0.97652 and 4.8952. Margin of difference (MOD) calculations across various algorithms, such as MLP, SVM, RBF, D-Tree, ELM, MLR, and GMDH-Algos revealed significant disparities, indicating GMDH's efficacy. Comparison of R, RMSD, and standard deviation values between GMDH and MLR algorithms further underscored performance discrepancies. Specific parameters for which NSGA II Algo was rated highest among evaluation indices were as follows: a crossover rate of 0.7, a mutation rate of 0.02, a population size of 50, and 500 generations. Post-optimization, optimal values for mu nf and torque (To) were determined as 6.595 and 3.543, respectively, with corresponding values for 9, T, and gamma obtained as 0.185, 49.372, and 3.163, respectively. This comprehensive analysis sheds light on the effectiveness of various regression methods in modeling the rheological behavior of hybrid non-Newtonian ferrofluids, contributing to advancements in fluid dynamics research.