Salahshour, Soheıl

Name Variants

Soheil Salahshour
Salahshour, Soheıl
Soheil SALAHSHOUR
Salahshour, Soheil
Soheıl Salahshour
Soheıl SALAHSHOUR
SALAHSHOUR Soheıl
Salahshour Soheil
Salahshour S.
Salahshour, S.
SALAHSHOUR Soheil
Salahshour Soheıl
Soheıl, Salahshour
S., Salahshour
Salahshour,S.

Job Title

Dr.Öğr.Üyesi

Email Address

soheil.salahshour@okan.edu.tr

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Scholarly Output

158

Articles

154

Citation Count

26

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Now showing 1 - 10 of 158

Numerical investigation of the effect of the number of fins on the phase-change material melting inside a shell-and-tube cylindrical thermal energy storage
(Elsevier, 2024) Rashid, Farhan Lafta; Khalaf, Abbas Fadhil; Alizadeh, As'ad; Al-Obaidi, Mudhar A.; Salahshour, Soheil; Chan, Choon Kit
A numerical analysis of the fin count that affects phase change material (PCM) melting within a cylindrical shell-and-tube thermal energy storage (TES) is provided. Using the ANSYS/FLUENT 16 tool, the enthalpy-porosity combination was quantitatively evaluated. PCMs made of paraffin wax were used in this experiment (RT42). The results of this investigation show that fins significantly affect melting, which reduces the time required to finish the operation. Since melting relies on natural convection, which has a sluggish rate of heat transfer, the process takes longer when there are no fins. The melting process takes 900 min to finish. The melting fraction grew monotonically with the number of fins, and the curve had an initial sharp trend followed by a gradual one. When more PCMs transitioned from a solid state to a liquid state over time, the pace at which they melted decreased, and the thermal resistance between the solid-liquid interface and the heat transfer surface increased. With the same heat storage effect, the maximum time difference was 236 min, and the biggest time difference was caused by the number of fins at 81.4 %. The total melting time was greatly affected by the number of fins in the design.
The Existence and Uniqueness Conditions for Solving Neutrosophic Differential Equations and Its Consequence on Optimal Order Quantity Strategy
(Mdpi, 2024) Momena, Alaa Fouad; Haque, Rakibul; Rahaman, Mostafijur; Salahshour, Soheil; Mondal, Sankar Prasad
Background: Neutrosophic logic explicitly quantifies indeterminacy while also maintaining the independence of truth, indeterminacy, and falsity membership functions. This characteristic assumes an imperative part in circumstances, where dealing with contradictory or insufficient data is a necessity. The exploration of differential equations within the context of uncertainty has emerged as an evolving area of research. Methods: the solvability conditions for the first-order linear neutrosophic differential equation are proposed in this study. This study also demonstrates both the existence and uniqueness of a solution to the neutrosophic differential equation, followed by a concise expression of the solution using generalized neutrosophic derivative. As an application of the first-order neutrosophic differential equation, we discussed an economic lot sizing model in a neutrosophic environment. Results: This study finds the conditions for the existing solution of a first-order neutrosophic differential equation. Through the numerical simulation, this study also finds that the neutrosophic differential equation approach is much better for handling uncertainty involved in inventory control problems. Conclusions: This article serves as an introductory exploration of differential equation principles and their application within a neutrosophic environment. This approach can be used in any operation research or decision-making scenarios to remove uncertainty and attain better outcomes.
Combining neutral scalar and isothermal Shan-Chen lattice Boltzmann method to simulate droplet placement on a wall in isothermal and non-isothermal states
(Elsevier, 2024) Liu, Yanan; Jasim, Dheyaa J.; Sajadi, S. Mohammad; Nasajpour-Esfahani, Navid; Salahshour, Soheil; Zarringhalm, Majid; Rahmani, Amin
Background: In the current article, two-phase thermal fluxes are created by combining the thermal model of the neutral scalar model with the two-phase Shan-Chen model of the lattice Boltzmann method (LBM). Methods: The different intermolecular powers for the isothermal Shan-Chen model show how a droplet would be placed on a wall. By raising the droplet intermolecular power parameter, the surface area increases and becomes wet. Next, the isothermal Shan-Chen method and the neutral scalar method are combined to investigate multiphase thermal problems. The droplet placement on the hot wall is therefore done at relatively high Rayleigh numbers. By raising the Rayleigh number, the isothermal lines within the droplet's interior gradually become less ascending and less descending until they eventually achieve a uniform state when it is placed against a hot wall. Additionally, the channel's Rayleigh-Benard convective heat transfer is enhanced by increasing the Rayleigh number. Significant findings: Natural convection in the enclosures can be used in solar collectors. As the Rayleigh number increases, the average Nusselt number (Nuavg) rises as would be expected. The results demonstrate that LBM is a practical method for simulating multi-phase thermal flows.
The effect of the initial temperature, pressure, and shape of carbon nanopores on the separation process of SiO2 molecules from water vapor by molecular dynamics simulation
(Elsevier Ltd, 2024) Mei,B.; Jasim,D.J.; Alizadeh,A.; Hekmatifar,M.; Nasajpour-Esfahani,N.; Salahshour,S.; Toghraie,D.
Today, with the advancement of science in nanotechnology, it is possible to remove dust nanostructures from the air breathed by humans or other fluids. In the present study, the separation of SiO2 molecules from H2O vapor is studied using molecular dynamics (MD) simulation. This research studied the effect of initial temperature, nanopore geometry, and initial pressure on the separation of SiO2 molecules. The obtained results show that by increasing the temperature to 500 K, the maximum velocity (Max-Vel) of the samples reached 2.47 Å/fs. Regarding the increasing velocity of particles, more particles pass via the nanopores. Moreover, the shape of the nanopore could affect the number of passing particles. The results show that in the samples with a cylindrical nanopore, 20 and 40% of SiO2 molecules, and with the sphere cavity, about 32 and 38% of SiO2 particles passed in the simulated structure. So, it can be concluded that the performance of carbon nanosheets with a cylindrical pore and 450 K was more optimal. Also, the results show that an increase in initial pressure leads to a decrease in the passage of SiO2 particles. The results reveal that about 14 and 54% of Silica particles passed via the carbon membrane with increasing pressure. Therefore, for use in industry, in terms of separating dust particles, in addition to applying an EF, temperature, nanopore geometry, and initial pressure should be controlled. © 2023 Elsevier Ltd
Solvability Criteria for Uncertain Differential Equations and Their Applicability in an Economic Lot-Size Model with a Type-2 Interval Phenomenon
(Mdpi, 2023) Rahaman, Mostafijur; Haque, Rakibul; Alam, Shariful; Zupok, Sebastian; Salahshour, Soheil; Azizzadeh, Fariba; Mondal, Sankar Prasad
Interval numbers comprise potential fields of application and describe the imprecision brought on by the flexible nature of data between boundaries. The recently added type-2 interval number allows a more thorough understanding of interval numbers. Differential equations are commonly employed in mathematical models to handle dynamic problems. It is essential to provide theories of differential equations to describe these models in an ambiguous environment controlled by type-2 interval numbers. This study proposes the type-2 interval context solvability requirements for the initial-valued first differential equation. The conditions for the solution's existence and uniqueness must be met before a brief manifestation of the solution under generalized Hukuhara differentiation occurs. An economic order quantity model analysis in a type-2 interval scenario uses a generalized Hukuhara differentiation approach.
The molecular dynamics simulation of coronavirus- based compound (6OHW structure) interaction with interferon beta-1a protein at different temperatures and pressures: Virus destruction process
(Pergamon-elsevier Science Ltd, 2024) Sun, Di; Gataa, Ibrahim Saeed; Aljaafari, Haydar A. S.; Cardenas, Maritza Lucia Vaca; Kazem, Tareq Jwad; Mohammed, Abrar A.; Eftekhari, S. Ali
The Interferon beta-1a protein is a cytokine in the Interferon family that is used to treat a variety of ailments. Molecular Dynamics simulation was used to characterize the atomic disintegration of 6OHW structure of a corona virus-based compound with Interferon beta-1a protein in this computational study. Molecular Dynamics simulation results on the atomic evolution of the 6OHW structure were presented with estimating physical variables. Physically, our simulations showed the attraction forces between the virus and the atomic protein in the presence of H2O molecules, resulting in viral annihilation after t = 10 ns. The molecular dynamics package's initial pressure and temperature (Temp) changes were important for virus-protein system evolution. Numerically, increasing primary T and P from 300 K and 1 bar to 350 K and 5 bar reduced the atomic distance between virus and protein structures from 10 & Aring; to 2.71 & Aring; and 2.45 & Aring;. Bonding energy was another reported physical quantity in our Molecular Dynamics simulation work. The atomic parameter ranged from 152.57 kcal/mol to 148.54 kcal/mol due to changes in initial Temp and pressure. Ultimately, the diffusion coefficient of protein being simulated inside the atomic virus changed from 0.48 mu m2/s to 0.59 mu m2/s. This calculation demonstrated the suitable conduct of simulated protein throughout virus destruction process.
Battery thermal management system by employing different phase change materials with SWCNT nanoparticles to obtain better battery cooling performance
(Elsevier, 2024) Ren, Jiaxuan; Rasheed, Rassol Hamed; Bagheritabar, Mohsen; Abdul-Redha, Hadeel Kareem; Al-Bahrani, Mohammed; Singh, Sandeep; Toghraie, D.
Maintaining a stable temperature within a battery is essential for optimizing the performance of battery thermal management systems. Phase change materials (PCMs) have demonstrated potential in achieving this stability. This study investigates the use of single-walled carbon nanotubes (SWCNTs) dispersed in three PCMs with varying fusion temperatures to regulate the temperature of a lithium-ion battery (LIB) during discharge, a common scenario in electric vehicles. A Computational Fluid Dynamics (CFD) approach was utilized to simulate the liquid-solid transition of the PCMs, incorporating buoyancy forces in the liquid phase surrounding the LIB. The study examined the effects of different C-rates (1, 2, and 3), SWCNT volume fractions (0, 2, and 4 %), and three types of PCMs (RT27, RT35, and RT58) across multiple simulation scenarios to evaluate their impacts on LIB temperature and PCM melting fraction. Results indicate that nano-enhanced PCMs, which exhibit superior convection effects in the liquid phase, significantly enhance battery cooling performance. Specifically, at a C-rate of 1, using a 4 % volume fraction of nanoparticles in the PCM reduces the battery temperature by an average of 4.138 K compared to cases without nanoparticles. Additionally, while nanoparticles are generally reported to have a minor effect on cooling and melting processes, this study reveals that considering the beneficial effects of SWCNTs and the physical properties of the selected PCMs, the cooling performance of LIBs improves by 4.69 percentage points for the scenario with a C-rate of 3, RT58, and phi = 0.02. In this particular case, the melting process is more pronounced in the top half of the battery, where the increased velocity magnitude of the melted region contributes to enhanced battery cooling.
Prediction and extensive analysis of MWCNT-MgO/oil SAE 50 hybrid nano-lubricant rheology utilizing machine learning and genetic algorithms to find ideal attributes
(Elsevier Sci Ltd, 2024) Baghoolizadeh, Mohammadreza; Pirmoradian, Mostafa; Sajadi, S. Mohammad; Salahshour, Soheil; Baghaei, Sh.
Genetic algorithms and machine learning methods can accurately anticipate hybrid nanofluids' complicated rheology. Scientists and engineers can understand hybrid materials by using genetic algorithms to optimize and machine learning to discover complicated relationships between input variables and rheological responses. As a continuation of the author's previous research on the rheological properties of a nano-lubricant based on engine oil and hybrid nanoparticles, this study uses machine learning and genetic algorithms to theoretically assess the dynamic viscosity of the MWCNT-MgO/oil SAE 50 hybrid nanofluid and identify optimal properties. MLR, DTree, Ridge, PLR, SVM, Lasso, ECR, GPR, and MPR are used for regression analysis. Best multi-objective issue solutions are represented by the Pareto front. The NSGA-II algorithm determines the Pareto front. The MPR and NSGA-II algorithms provide a Pareto front with the most precise optimal spot boundaries. The Weighted Sum Method (WSM) simplifies multi-objective problems into single-objective problems, making optimal solutions easier to find. The results show that the maximum margin of deviation for mu nf and tau is - 2.5615 and - 5.239, respectively. According to the Taylor chart, the best mu nf mode for R, RMSE and STD is equal to 0.9983, 7.6639, 130.0056. Also, these values for tau are equal to 0.9996, 15.4515, and 516.0219.
A molecular dynamics study of the external heat flux effect on the atomic and thermal behavior of the silica aerogel/ paraffin /CuO nanostructure
(Pergamon-elsevier Science Ltd, 2024) Ren, Jiaxuan; Basem, Ali; Al-Bahrani, Mohammed; Jasim, Dheyaa J.; Al-Rubaye, Amir H.; Salahshour, Soheil; Alizad, A.
Investigating the nanostructure's atomic and thermal properties (TP) might help enhance energy conversion and storage technologies. This is particularly important when considering phase change materials (PCM) and their use in thermal energy storage systems. However, understanding the behavior of nanostructure's atomic and thermal components in response to temperature (Temp) changes is critical, as is improving its heat transfer capacities for a wide range of applications by examining the effect of external heat flux (EHF). As a result, the major goal of this research was to determine the effect of EHF on the atomic and TP of silica aerogel (SA)/ paraffin/CuO nanostructures. This investigation was done using molecular dynamics (MD) simulation and LAMMPS software. To achieve this, a study was undertaken into the effect of EHF of different magnitudes (0.01, 0.02, 0.03, and 0.05 W/m2) on the maximum (Max) density (Dens), velocity (Vel), and Temp, as well as HF, thermal conductivity (TC), and charging and discharging time. The results show that when the EHF increased to 0.05 W/m2, the Max Dens value decreased to 0.0754 atoms per square centimeter. Furthermore, the Max Temp and Vel increased to 1018.82 K and 0.0139/fs, respectively. Increased external heat discharge improved the thermal effectiveness of simulated construction. Increasing the EHF raised the TC and HF to 95.93 W/m2 and 1.93 W/mK, respectively. Finally, the results of this simulation are expected to improve understanding of nanostructure TP and their potential applications in improved energy conversion and storage technologies.
An Innovative Approach Combination of Powder Metallurgy and Accumulative Press Bonding To Fabricate Al/ Graphite Nanocomposites and Investigate the Tribological and Wear Properties
(Elsevier, 2025) Vini, Mohammad Heydari; Basem, Ali; Daneshmand, Saeed; Jasim, Dheyaa J.; Hekmatifar, Maboud; Salahshour, Soheil
In this study, Al/Gr Nanocomposites (NC) were fabricated using an innovative approach that is a combination of powder metallurgy (PM) and accumulative press bonding (APB). By this combination method, many of defects are removed from the composite matrix which improves the mechanical properties. The APB process is a unique technique that made it possible to create NCs with distinct properties. In simpler terms, this process involves compressing a series of overlapping bulky samples that achieves a specific reduction ratio, such as 50 %. It is worth noting that extensive research has been done to understand the properties of Al/Gr-NCs comprehensively. By increasing the Gr value up to 10 %, hardness and friction coefficient dropped and wear rate increased by 23 %, 214 % and 37 %, respectively. Focusing on the analysis of microstructural, and tribological properties (TP), with special emphasis on the effect of Gr content as an additive component. In addition, the use of a scanning electron microscope (SEM) has facilitated the study of the surface and microstructure of tribo-NC. The result of this study revealed desirable behaviors. It was observed that with the increase of Gr content, the hardness and friction coefficient (FC) of the NC samples decreased, while the density and WR rate of the samples increased. These results indicate the importance of Gr addition in adjusting the MP and TP of NCs. Finally, the combination of PM and the APB process offers a promising way to fabricate nanoparticle (NP)-reinforced materials with desirable MP.

Salahshour, Soheıl

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Scholarly Output

158

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154

Citation Count

26

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0

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