The sloshing dynamics of liquefied natural gas (LNG) within storage and transport tanks present significant engineering challenges, particularly during the exit stage, where complex flow phenomena dominate. This study uses computational fluid dynamics (CFD) simulations with OpenFOAM to examine how the wetted region expands and shrinks due to sloshing on the horizontal lid of a two-dimensional prismatic tank with rigid walls, scaled at 1:10, across various high filling levels. The fluids (water and air) are modelled as incompressible and viscous. An optimized and validated numerical solver, benchmarked against experimental data is utilized to capture the complex interplay of impact and exit stages and the pressure evolution as the wetted region evolves. The duration of both stages (impact and exit), maximum wetted-region length, and pressure distribution on the lid of the tank are studied at different high filling levels and two forced amplitudes of sway motion. As the filling level increases, the number of impacts on the lid in a period of time, the duration of impact-exit stages, and the length of the wetted region increase as well. A longer wetted region means more negative added mass. It is found that during the early stage of exit, the negative pressure peak occurs at the top wetted corner of the lid. The observed negative pressures during the exit stage necessitate their explicit consideration in the structural design of prismatic LNG tanks.

Packed bed thermal energy systems (PBTES) are recognized as one of the innovative technologies in the field of energy storage. This study numerically investigates the effects of a porous medium, magnetic field, mechanical vibrations, and various configurations of concrete-phase change material (PCM) on the performance of PBTES. The results indicate that substituting PCM for concrete can increase the discharge-to-charge energy ratio by over 300 times. The presence of a porous medium in the PBTES system with PCM significantly enhances the charge energy ratio (by 3.81–4.14 times) compared to scenarios without a porous medium, due to its influence on the melting process of the PCM. The presence of a magnetic field, along with an increase in its intensity, positively affects the melting process and enhances charge energy, potentially increasing it by approximately 4.132–5.281 times compared to cases without a magnetic field. Mechanical vibrations also influence charge energy in the PBTES system, resulting in an improvement of 4.41–4.56 times compared to the no-vibration scenario, with optimal efficiency achieved at A = 1e-5 m and f = 0.1 Hz. Notably, the use of a porous medium, magnetic field, and forced vibrations reduces discharge energy by approximately 0.34–0.37, 0.36 to 0.47, and 0.39 to 0.41 times, respectively, compared to the baseline scenario. Utilizing the Group Method of Data Handling (GMDH) neural network model based on the available data in this study, the discharge energy to charge energy ratio has been estimated, and the model has accurately predicted the desired parameter with a high degree of precision.

Background: Nanofluids are the most widely used materials in various engineering fields. They have different properties under different conditions, and predicting their properties requires several experiments. Artificial intelligence can predict the properties of nanofluids in the shortest time and cost. Methodology: This study aims to predict the viscosity and share rate of MWCNT-TiO2 (40–60)-oil SAE50 nano-lubricant (NL). Machine learning algorithms and neural networks can respond best to this important matter. For this purpose, the Group Method of Data Handling (GMDH) neural network is combined with the meta-heuristic algorithm Multi-Objective Gray Wolf Optimizer (MOGWO). This way, the experimental data is first given to the artificial neural network (ANN). Then, the meta-heuristic algorithm optimizes the hyperparameters of the ANN to bring the predicted results closer to the experimental data and minimize the error. The MOGWO algorithm’s regulators are the number of iterations and the number of wolves investigated in this study to better select this algorithm. Then, these modes are measured using two criteria, correlation coefficient (R) and rote mean squared error (RMSE), to choose the best mode. Finally, by using the extracted equations by the GMDH neural network, the best models or the Pareto front can be obtained using the MOGWO meta-heuristic algorithm. Results: The error histogram diagram shows the excellent performance of the combination of the GMDH neural network and the MOGWO meta-heuristic algorithm. The values of R and RMSE for viscosity and shear rate are equal to 0.99217, 15.8749, and 0.99031, 68.7723, respectively. The optimization results showed that the best conditions to meet viscosity and cutting rate are when φ, T, and γ equal 1.21*e􀀀 5, 46.71, and 50.11.

Thermal energy storage (TES) is one of the uses of phase change material (PCM). The primary factor contributing to this capability is the elevated latent heat of melting present in these materials. The current study investigates the effect of initial pressure (IP) (ranging from 1 to 5 bar), and atomic ratio (AR) of Iron nanoparticles (NPs) (Fe = 1, 2, 3, and 5 %) on the thermal behavior (TB) and phase transition process of sodium sulfate/Magnesium chloride hexahydrate (Na2SO4/MgCl2⋅6H2O) nanostructures as PCMs using molecular dynamics (MD) simulation. The simulated PCM was positioned inside a spherical atomic channel composed of iron. The TB of simulated nanostructures was examined by reporting changes in viscosity (Vis), thermal conductivity (TC), and phase transition time (PTT). The results reveal that by increasing IP from 1 to 5 bar, the PTT reaches from 3.50 to 3.61 ns, and the TC decreases from 1.03 to 0.94 W/m.K. The results show that adding 3 % of Fe NPs was the optimal ratio to improve the TB of the Na2SO4/MgCl2⋅6H2O-Fe NP. By raising the ratio of Fe NPs from 1 to 3 %, Vis slightly decreased from 4.31 to 4.22 mPa.s. In comparison, adding more Fe NPs with 5 % ratio raised the Vis to 4.30 mPa.s. According to the results, increasing the IP decreased the distance among the particles. So, the attraction among particles increased, leading to greater adhesion and Vis. By increasing the IP, the distance among atoms decreases, and the space between NPs and atoms in the simulation box decreases. Consequently, NP movement and fluctuations decrease, and collisions decrease. The results of this simulation will be effective in heating–cooling and ventilation systems, automotive industries, textile industries, and so on.

One of the most crucial concerns is improving industrial equipment's ability to transmit heat at a faster rate, hence minimizing energy loss. Viscosity is one of the key elements determining heat transmission in fluids. Therefore, it is crucial to research the viscosity of nanofluids (NF). In this study, the effect of temperature (T) and the volume fraction of nanoparticles (φ) on the viscosity of the silica-alumina-MWCNT/Water hybrid nanofluid (HNF) is examined. In this study, a nonlinear curve fitting is accurately fitted using MATLAB software and is used to identify the main effect, extracting the residuals and viscosity deviation of these two input variables, i.e., temperature (T = 20 to 60 °C) and volume fraction of nanoparticles (φ = 0.1 to 0.5 %). The findings demonstrate that the viscosity of silica-alumina-MWCNT/ Water hybrid nanofluid increases as the φ increases. In terms of numbers, the μnf rises from 1.55 to 3.26 cP when the φ grows from 0.1 to 0.5 % (at T = 40 °C). On the other hand, the μnf decreases as the temperature was increases. The μnf of silica-alumina-MWCNT/ Water hybrid nanofluid reduces from 3.3 to 1.73 cP when the temperature rises from 20 to 60 °C (at φ = 0.3 %). The findings demonstrate that the μnf exhibits greater variance for lower temperatures and higher φ.

Phase change material (PCM) is a material that has a specific melting point, and its latent heat of melting is large enough that it can be used to store thermal energy. This study investigated the effect of size (4–8 Å), and the number of layers (3–10 layers) of iron nanoparticles (NPs) channel on thermal behavior (TB) and phase change (PC) process of sodium sulfate/calcium chloride hexahydrate (Na2SO4/MgCl2·6H2O) PCM molecular dynamics (MD) simulation. By increasing the number of layers from 3 to 5, the maximum temperature and heat flux (HF) increased from 406 and 1471 W/m2 to 451.51 K and 1496 W/m2. By increasing the number of layers from 3 to 7 layers, the charging time (CT) and discharge time (DT) of atomic samples decreased from 4.01 ns and 4.25 ns to 3.88 ns and 4.17 ns. By adding the iron NPs with a radius of 4, 5, 6, and 8 Å, the maximum temperature increased to 420, 429, 458, and 503 K, respectively. By adding the iron NPs with different radii from 4 to 8 Å, the HF increased from 1566 W/m2 to 1657 W/m2. By adding the iron NPs into the Na2SO4/MgCl2·6H2O, the received HF increased, and the maximum temperature increased. By adding the iron NPs with different radii, the CT decreased from 3.95 ns to 3.73 ns. The DT increased from 4.33 ns to 4.36 ns by increasing the radius from 4 to 8 Å. According to the TB of this PCM, it should be used in refrigerants instead of toxic and dangerous refrigerants, such as ammonia and chlorofluorocarbon. Moreover, they were used for construction purposes for double-glazed windows.

The principal moot point in this investigation is heat removal from surfaces with high heat flux, which is the use of tabulators and parts with a particular geometry, it has been chosen as a solution to this moot point. The primary hypothesis in this investigation is to increase fluid heat transfer by increasing turbulence and heat transfer by increasing the plane of heat transfer and establishing a vortex flow. The fundamental idea and novelty of this investigation is the simultaneous use of a turbulator (to improve turbulence and provide more effective heat transmission) and increasing the contact surface (through the installation of parts with unique geometry), which can be obtained from different turbulator used in other geometries. In this research, the limited volume method to solve governing equations in three-dimensional space and Cartesian coordinates has been used on the network using Ansys Fluent software. In order of comparison, turbulators SLT and then TRT is compared to other turbulators (TRT, SHT, RET) It has the highest Nusselt number, and in the Reynolds numbers in the turbulent flow regime, they have the most significant reduction in the friction coefficient.

Background and objective: The molecular dynamics (MD) simulation is a powerful tool for researching how cancer patients are treated. The efficiency of many factors may be predicted using this approach in great detail and with atomic accuracy. Methods: The MD simulation method was used to investigate the impact of porosity and the number of cancer cells on the atomic behavior of cancer cells during the hematogenous spread. In order to examine the stability of simulated structures, temperature and potential energy (PE) values are used. To evaluate how cell structure has changed, physical parameters such as gyration radius, interaction force, and interaction energy are also used. Results: The findings demonstrate that the samples’ gyration radius, interaction energy, and interaction force rose from 41.33 Å, − 551.38 kcal/mol, and − 207.10 kcal/mol Å to 49.49, − 535.94 kcal/mol, and − 190.05 kcal/mol Å, respectively, when the porosity grew from 0% to 5%. Also, the interaction energy and force in the samples fell from − 551.38 kcal/mol and − 207.10 kcal/mol to − 588.03 kcal/mol and − 237.81 kcal/mol Å, and the amount of gyration radius reduced from 41.33 to 37.14 Å as the number of cancer cells rose from 1 to 5 molecules. The strength and stability of the simulated samples will improve when the radius of gyration is decreased. Conclusions: Therefore, high accumulation of cancer cells will make them resistant to atomic collapse. It is ex- pected that the results of this simulation should be used to optimize cancer treatment processes further.

In this research, the effect of vortex generators (VGs) with various geometric shapes and Cu-TiO2/H2O nanofluid (NF) on thermal-hydraulic (TH) performance, energy efficiency and exergy of a solar collector (SC) has been perused. In this research, the turbulent flow regime (TFR) was used to study the stated parameters. The QUICK algorithm is used for the discretization of the equations. According to the assumption of a TFR, the flow behavior of Cu-TiO2/ H2O NF in the Re range of 4000–16,000 was studied. In addition, the k-ω SST model was utilized to modelling the turbulent flow. Also, due to considering the NF as two-phase, the Eulerian two-phase method was used for modeling. Two-phase hybrid NFs with Cu and TiO2 nanoparticles in solid volume fractions of SVF=1, 3, and 5% were modeled. The findings of the research illustrate that convective heat transfer (CHT), Nuavg (average Nusselt number), and pressure drop (PD) increase with the increase of the inlet velocity of Cu-TiO2/ H2O NF flow. In addition, the results of PEC evaluation indicate that the adding VGs and changing their placement states is desirable in terms of PEC. In the SC along with the case D turbolator and SVF= 5 %, the exergy efficiency increases by 45.87 % with the increase of the Reynolds number (Re) from 4000 to 16,000.

Today, the problems, such as the environmental pollution caused by the consumption of fossil fuels, which have disrupted the ecological conditions and created environmental risks, as well as the limited reserves of fossil fuels, have caused countries worldwide to pay more attention to this type of energy. Biofuels are a type of fuel obtained from biomass sources. Biodiesel is one of the fuels produced from natural and renewable sources, which does not harm the environment. On the other hand, the presence of nanoparticles in alternative fuels is particularly important because adding nanoparticles reduces the ignition delay. This study investigated the effect of different nanoparticles, such as copper oxide (CuO) and aluminium oxide (Al2O3), on methyl ester-biodiesel (as base fluid) fuel’s combustion performance. The following investigated the effects of different volume fractions of CuO nanoparticles. This research used the molecular dynamics (MD) simulation, and the LAMMPS software package. The results show that CuO nanoparticles had better thermal performance than Al2O3 nanoparticles. By adding Al2O3 and CuO nanoparticles to the base fluid, the heat flux of the simulated nanofluid converged to a numerical value of 2410.31 W/m2 and 2410.31 W/m2, respectively. Because CuO nanoparticles show better thermal performance than Al2O3 nanoparticles, the effect of the volume fractions of CuO nanoparticles on the thermal performance of the studied nanofluid was investigated. For this purpose, CuO nanoparticles with atomic ratios of 1%, 2%, 3%, 5% and 10% were added to the base fluid. The results reveal that the heat flux in atomic samples reached 4448.89 W/m2 in the presence of 10% CuO nanoparticles. It is expected that by optimizing this process, the combustion performance of fuels will be improved, fuel consumption will be optimized, and the emission of pollutants will be reduced.

This paper provides a numerical simulation to explore natural convection and fluid flow in a three-dimensional wavy cubical enclosure subjected to a magnetic field along the z-axis. The main emphasis of this research is to discuss entropy generation inside a wavy porous cavity. Brinkman's extended non-Darcy flow model is utilized for studying the free convection in the permeable medium. The equations of the mathematical model were solved using Galerkin finite element method. Isotherms, streamlines, velocity profile, and variation of average Nusselt number are calculated for various values of Ra (103–106), Ha (0–100), and φ (0–0.08). The results show that the streamlines and isotherms increase with the increase of Darcy and Rayleigh numbers. Besides, entropy generation is sensitive to the values of Darcy number, Rayleigh number, Hartmann number, and the number of undulations. Besides, the variation of the Nusselt number is affected by the Rayleigh number and Darcy number. The highest Nusselt number can be obtained for a maximum number of undulations only at the small values of the Rayleigh number. Otherwise, this pattern will be changed in the opposite trend at large values of the Rayleigh number. At the highest values of Ra, increasing Ha from 0 to 100 decreased Nuavg by 23%, while increasing Da from 10−5 to 10−2 enhanced it by 177%. Finally, it was found that the values of Beavg are only being enhanced by only one parameter, namely the Hartmann number. The obtained results from the current non-Darcy flow model agree well with the available literature results.

The current study discusses the mixed convection boundary layer around an isothermal solid sphere utilizing numerical simulation; two fluid types of hybrid and mono micropolar nanofluids with constant wall temperature in an MHD field are examined. To improve a base fluid's thermophysical, optical, rheological, and morphological qualities, two different types of nanoparticles Copper oxide CuO and Graphite oxide (GO) are combined to create hybrid nanofluids. The sensitivity analysis was made to unveil the impacts of the mixed convection factor, the field strength and the micro-rotation factor. The results reveal that the improving effect of using NF by the induced micro-rotational effect is more prominent at lower angles and diminished at higher angles. Another point that could be obtained is that the thermal boundary layer thickness is directly proportional to the magnetic parameter; by increasing the M value from 0.5 to 2, the thermal boundary layer thickness increases from 1.4 to 1.8. Also, using hybrid instead of mono NF has nearly no effect on altering the angular velocity at y > 4; for other ones (y < 4), the difference is<15 %.

In this study, the thermal conductivity (knf) of ZnO -TiO2 (50 %–50 %)/ Ethylene Glycol hybrid nanofluid using Artificial Neural Networks (ANNs) was predicted. The nanofluid was prepared at different volume fractions (φ) of nanoparticles (φ = 0.001 to 0.035) and temperatures (T = 25 to 50 °C). In this study, an algorithm is presented to find the best neuron number in the hidden layer. Also, a surface fitting method has been applied to predict the knf of nanofluid. Finally, the correlation coefficients, performances, and Maximum Absolute Error (MAE) for both methods have been presented and compared. It could be understood that the ANN method had a better ability in predicting the knf of nanofluid compared to the fitting method. This method not only showed better performance but also reached a better MAE and correlation coefficient.

Near the suction/injection area, a scientific definition for laminar boundary layer flow and heat transfer of an incompressible viscous flow over a stretching cylinder is given. In the study, differential equations with partial derivatives are converted into dimensionless coupled equations using numerical and analytical methods of Akbari- Ganji and Finite Elements Methods. The goal of this first stage of research and research on this topic is to use simplified forms to simplify equations using derivatives of simplified forms; the analysis of the displacement of the heat flux and the velocity gradient will be done using the changes of the Prandtl number. Based on the results obtained on this issue, it is found that the suction process increments surface firmness and quality, whereas the injection decreases surface skin friction. Also, at the points where the water and oil are attached to the surface of the cylinder, the heat has reached its maximum value, and as the distance increases along the Y axis, the temperature decreases. The highest temperature gradient is observed for water fluid. This shows that the use of water fluid around the cylinder accelerates the process of heat transfer from the surface to the outside of the boundary layer. One of the differences between the use of oil and water fluid around the cylinder according to the 2D contours is the difference in the temperature gradient of the two fluids. So that the highest temperature gradient is observed for water fluid.

In this article, we investigate the temperature and concentration of particles around a vessel in three different locations using the reaction and diffusion relations, the reaction between three chemical particles, and the relationship between temperature changes and the rate of chemical reaction. The goal and necessity of this research is that we were able to visualize these chemical agents by using a finite mathematical fluid method, changing the physical properties of the materials, and learning about how chemical reactions affect concentration and temperature and how they relate to one another. The innovation of this essay is that it compares the parameters of concentration and temperature of substances involved in chemical reactions in different places of the inner vessel to the larger vessel, with and without the presence of a heat source. We also achieved the highest and best efficiency of concentration and heat transfer of chemical reactions (a), (b), and (c) using the finite method in Flexpde, Ansys fluent, and Design - Expert software (c). The obtained results show that the concentration changes significantly as the temperature of the reactants rises and more heat is released. According to the test conducted with the RSM method, the best efficiency and optimization of temperature and concentration parameters occurs in heat source = 2.555°, diffusivity = 0.025 and diameter of inner vessel = 3.144 cm.

The hydrodynamic problem of a two-dimensional symmetric wedge vertically entering the water, initially flat, with a deadrise angle of 30 is considered. This numerical study assesses turbulence, gravity, viscosity, and surface tension during the early stage of penetration. The OpenFOAM software package has been used to simulate the water entry of the wedge at a constant speed of 3 m/s. The governing equations have been numerically built in the solver called overInterDyMFoam. The method has also been used to model the turbulence effect. The effects of turbulent and laminar flow assumptions and for the laminar flow, viscosity, gravity, and surface tension influence on pressure distributions along the wedge's walls have been investigated. It is illustrated that turbulence, viscosity, and surface tension have negligible effects on the pressure distribution in the primary water entry process. However, the pressure distribution is found to be significantly influenced by gravity.

We numerically study gravity’s effect on sloshing in a two-dimensional tank which is highly filled by water (95% water and 5% air). Both fluids are considered to be incompressible and inviscid. The surface tension and phase change are neglected. OpenFOAM software is used for the simulation. A standing wave of water impacting the lid of the tank at its center and a symmetric wetted region starts to advance along the lid. The simulation carried out (only on the right-half side of the tank due to symmetric geometry of the impact) with and without gravity to investigate the influence of gravity on this impact. The numerical results are validated by comparing to published data. The effect of gravity on the size of the wetted region, free-surface elevation and on the pressure distribution has been analyzed. It is shown that gravity is affecting the free-surface elevation and consequently the size of the wetted region. These effects growth as time goes. Pressure distribution along the wetted region of the lid is also influenced by gravity.

We consider the effects of gravity on the two-dimensional flow caused by a symmetric body vertically entering into initially calm water at constant speed. Surface tension,viscosity and the compressibility of the liquid are neglected. The flow is potential. The region of contact of the water with the body surface starts from a single point and grows monotonically in time. The effects of gravity on the size of the contact region, the hydrodynamic force on the body, the hydrodynamic pressure distribution on the wetted part of the body surface, and the free-surface elevation are analysed for the initial stage of impact, using asymptotic methods with a small-valued gravity-related parameter. It has been well accepted that the effects of gravity on water impact characteristics are small. The analysis reveals that the effects of gravity are relatively small even for impact conditions,where formally these effects should be included in the model. It is found that gravity:slows down the contact points, reduces the hydrodynamic pressure at the periphery of the contact region, but increases the pressure in the central part of the wetted region, and hence increases the total fluid force on the body. The asymptotic contributions are sensitive to the gravity correction to the size of the contact region, even though it is relatively small.The effects of gravity become more important with time for the later stages.

The numerical solution for a time-fractional diffusion equation supplemented with initial and boundary conditions is considered. The scheme is based on the Galerkin finite element method. The uniform space discretization is applied to study the stability of the solution of the problem within our approach. An analytically solvable example is presented to make a comparison between the exact solution and our numerical solution. By presenting the absolute error with different step-sizes and different values for time-fractional derivative, reliability and efficiency of our proposed numerical method is manifested.

Severe Plastic Deformation (SPD) is the most appropriate top-down method for making nanocrystalline or ultrafine grained metal structures. Achieving a good distribution and higher values of equivalent plastic strain in one pass is the main parameter in severe plastic deformation processes. To solve this challenge, integrating different SPD processes is required. The planartwist channel angular extrusion process is one of the recently proposed methods of SPD as a rearrangement of two Simple Shear Extrusion (SSE) and Equal Channel Angular Pressing (ECAP) processes. In this study, Finite Element (FE) simulation of the variousroutes in the 2ndcycle of this method is done. Then, the micro hardness test of the processed samples was performed. Finite element analysis results illustrate that the C1, C2,A1, and B2 routes have the most uniform distribution of equivalent plastic strain in the cross section area of the specimen, and B2 and A1 paths have more equivalent plastic strain values. The highest non-uniform distribution of the equivalent plastic strain is illustrated in the paths B1 and D2. The results of the micro hardness test validated FEM results. Therefore, the best options for the second cycle of the PTCAE method are the paths A1 and B2.

The numerical simulation of the flow of fluid through one or a set of objects that causes the flow to separate from the surface of them has been the subject of interest by researchers over the past few decades. One of the most important types of these objects is those with a square cross section which have important and diverse applications in different industries. One of the practical applications of these types of streams is flow around chimneys, high-rise buildings, naval structures, suspended bridges, airplane wings, ship propellers and ducts. In this research, the immersed interface method is used which is a non-conforming method to the boundary. Eulerian mesh for fluid field, and Lagrangian mesh for solid field is used. The connection of these two networks is established by the Dirac Delta function. Considering the cylinder as a rigid immersion boundary within the flow. First, the flow around a square cylinder was simulated and we surveyed different flow patterns. The changes in the number of Strouhal and the Drag coefficient were investigated in different Reynolds. The flow around the two cylinders was simulated. It was observed that with the increase of Reynolds number and the gap between cylinders, the vortex shedding (Strouhal number) would increase.

Immersed interface method is a non-matching boundary approach that has been taken into consideration in recent years. In this method, there is no need to coincide between the fluid and the solid grids. Eulerian grid is used for fluid domain and Lagrangian grid is used for solid domain. Using the Dirac Delta function, the connection between these two grids is established. Separation of the flow from the cylinder surface causes a high pressure drop in some parts of the cylinder, resulting in a dramatic increase in drag force. Drag force reduction is very important in some engineering issues, and several methods have been proposed to achieve this goal. In this study, the flow around a rigid cylinder is simulated. The goal is to reduce the drag force on the cylinder through one and two horizontal plates. The results are in good agreement with prior numerical results.