Numerical investigation of the fullerene and doped fullerene effects on thermal performance of water base-fluid
الموضوعات : Journal of Theoretical and Applied PhysicsAhmad Saadi 1 , Hamid Reza Vanaie 2 , Mojtaba Yaghobi 3 , Ebrahim Heidari 4 , Darush Masti 5
1 - Department of Nuclear Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran.
2 - Department of Sciences, Bushehr Branch, Islamic Azad University, Bushehr, Iran.
3 - Department of Physics, Ayatollah Amole Branch, Islamic Azad University, Amol, Iran.
4 - Department of Sciences, Bushehr Branch, Islamic Azad University, Bushehr, Iran.
5 - Department of Nuclear Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran.
الکلمات المفتاحية: Heat transfer, hybridnanofluids, Molecular Dynamics, Fullerene, doped fullerene,
ملخص المقالة :
In this study, the fullerenes have been inserted into water base-fluid to investigate the atomic and thermal behavior of nanofluid and hybridnanofluid as heat transfer fluid. This choice derives from low cast and high thermal stability of this nanostructure. Our computational results from Molecular Dynamics (MD) simulations indicate that the addition of nanoparticles with 4% atomic ratio produced an appreciable effect on the nanofluid. The maximum value of density, velocity, and temperature profile have reached to 0.029 atom/cubic angstrom, 0.005 angstrom/ps, and 321 centigrade degree. Its thermal conductivity would increase to 0.82 W/m.K. Heat flux reached to 2019 kW/m2 after t= 10 ns. Also, the aggregation phenomenon detected after t= 5.84 ns. This hybridnanofluid has been used to enhance the energy efficiency of the heat exchangers at high temperature for the nuclear industry applications for the first time. Numerically, by the temperature increase of nanofluid structure to 625.15 K, thermal power of nanofluid reached to 3881 MW. The thermal performance of hybridnanofluid can be improved by more than 30% by adding concentration of fullerene and doped fullerene at 4 vol%.
Numerical Investigation of the Fullerene and doped fullerene Effects on Thermal Performance of Water Base-Fluid
Ahmad Saadi b, Hamid Reza Vanaie
, Mojtaba Yaghobi c , Ebrahim Hydari a
aDepartment of Science, Bushehr Branch, Islamic Azad University, Bushehr, Iran
bDepartment of Nuclear Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran
cDepartment of Physics, Ayatollah Amole Branch, Islamic Azad University, Amol, Iran
Abstract
In this study, the fullerenes have inserted into water base-fluid to investigate the atomic and thermal behavior of nanofluid and hybridnanofluid as heat transfer fluid. This choice derives from low cast and high thermal stability of this nanostructure. Our computational results from Molecular Dynamics (MD) simulations indicate that the addition of nanoparticles with 4% atomic ratio produced an appreciable effect on the nanofluid. The maximum value of density, velocity, and temperature profile have reached to 0.029 atom/Å3, 0.005 Å/ps, and 321 ̊C.
Its thermal conductivity would increase to 0.82 W/m.K. Heat flux reache to 2019 KW/m2 after t=10 ns. Also, the aggregation phenomenon detected after t= 5.84 ns.
This hybridnanofluid has used to enhance the energy efficiency of the heat exchangers at high temperature for the nuclear industry applications for the first time. Numericaly, by the temperature increase of nanofluid structure to 625.15 K, thermal power of nanofluid reache to 3881 MW. The thermal Performance of hybridnanofluid can be improved by more than 30% by adding concentration of fullerene and doped fullerene at 4 vol%.
Keywords: heat transfer, fullerene, doped fullerene, hybridnanofluids, molecular dynamics.
Introduction
Nanotechnology is the design, characterization, production, and application of structures, devices, and systems through controlled manipulation of size and shape at the atomic (nanometer) scale with the products exhibiting at least one novel/superior characteristic or property [1-3]. Nanofluids are the promising structures in nanotechnology area [4-5]. In recent years, these nanostructures have been used commonly in mass and heat transfer phenomena for industrial applications [6-8]. Technically, nanofluids contain a small volume fraction of nanoparticles, nanowires, or nanotubes for targeted changes in thermal, rheological, and other properties [9-10]. As reported in other works, the thermal behavior of various nanofluids makes them suitable for many industrial, medical, etc. applications. So the thermal behavior of these structures represents an important topic in today science.
Hybrid-nanofluids are potential fluids that present superior thermophysical properties and thermal performance than common heat transfer fluids mono-nanofluids. Hybrid nanofluid is a new fluid produced by dispersing two dissimilar types of nano-particles into the base fluid. Some researchers have reported that conventional coolants could be replaced by hybrid-nanofluids, particularly fluids that work at very high temperatures. Accordingly, these types of nanofluids could lead to saving energy [11-14 ]. For the atomic study of common nanofluids, various methods have been introduced by researchers. Molecular Dynamics (MD) approach is one of the best methods to describe the atomic and thermal behavior of nano-scale structures [15-18]. Previous researche have reported the appropriate performance of MD simulations in thermal behavior of nanometric structures. Jolfaei et al. [19] calculated the thermal properties of Deoxyribonucleic acid with precise atomic arrangement via equilibrium and non-equilibrium molecular dynamics approaches. In these methods, each Deoxyribonucleic acid molecule is represented by C, N, O, and P atoms and is implemented dreiding potential to describe their atomic interactions. Their results showed the calculated rate of thermal conductivity via equilibrium and non-equilibrium molecular dynamics methods was 0.381 W/m K and 0.373 W/m K, respectively.By comparing results from these two methods, it was found that the results from equilibrium and non-equilibrium molecular dynamics methods were relatively identical. Asgari et al. [20] reported the atomic behavior of H2O/Cu Nanofluid by using MD simulation approach. The Copper Nanochannel with sphere barriers was simulated to study the nanofluid flow and the atomic interactions of these structures were described by Embedded Atom Model and Lennard-Jones (LJ) interatomic potentials. Technically, to study the atomic behavior of these structures, physical parameters such as temperature, density and velocity profiles of the nanofluid were reported. MD results show that such parameters of H2O/Cu Nanofluid inside non-ideal nanochannel affected by atomic barriers’ number and size of them changes. In other computational work, Ashkezari et al. [21] reported the thermal conductivity of Human serum albumin (HSA) with equilibrium/non-equilibrium molecular dynamic approaches. In these methods each HSA molecule is exactly represented by C, N, O and S atoms and their implemented dreiding potential. Finally by using Green-Kubo and Fourier's law the thermal conductivity of HSA/H2O mixture was calculated. Their calculated values for thermal conductivity via equilibrium/non-equilibrium molecular dynamics methods were 0.496 W/m K and 0.448 W/m K, respectively. The calculated thermal conductivity of the understudy structure was very close to the thermal conductivity calculated for water molecules as reported by other research groups.
In this work, we used fullerenes nanoparticles with 1%, 2%, 3%, 5%, and 10% atomic ratio to improve the thermal behavior of H2O molecules as base-fluid. In Fullerene, carbon atoms are arranges in honeycomb structure with strong bonds, which makes them stable against high ratio of pressure and temperatures. On the other hand, the structural form of fullerene causes appropriate rotational and translational movements during heat transfer process. Therefore, this type of nanoparticle have been used in current research to improve heat transfer ratio inside base fluid for common applications in nuclear industries. Regarding the computational processes, an MD simulations tool of the type Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) manufactured by Sandia National Laboratories(2021) was used [22-24]. During the MD simulations, the ideal (atomically) fullerenes nanoparticles were inserted into initial water base-fluid inside atomic channel and the evolution of simulated structures were reported to design optimized atomic arrangement for various applications such as heat and mass transfer in industrial, medical and etc. applications.
2. Computational Details
Technically, MD simulation is one of the promising methods to describe the atomic behavior of various nanostructures such as nanocomposites, nanofluids, etc. This computational approach is utilized in the present paper to describe the atomic/thermal behavior of H2O base-fluid in the presence of Fullerenes nanoparticles with various atomic ratios. The time evolution of H2O-fullerene nanofluid was performed using Newton’s equation, where the atomic interaction between various nanostructures is defined with the inter-atomic potential concept. H2O molecules in current study was modeled by TIP4P model [25]. Here, the atomic interaction between H2O molecules and fullerenes was determined by Universal Force Field (UFF) [26]. The Lennard-Jones (LJ) equation is implemented in this potential to describe the nonbond interactions [27]:
|
where ε constant, σ constant, and rij represent the minimum potential’s depth, the diameter of an atom, and the distance between various atoms (i and j), respectively. Furthermore, the simulated atomic walls as depicted in figure 1, denotes the interaction between nanofluid particles and LJ. Finally, fullerene nanoparticles were modeled by TERSOFF potential in MD simulation box [28-29]. The following equation can describe the TERSOFF potential function:
(2)
where, fR is a 2 body term and fA includes 3 body interactions. After the interatomic potential was defined in the simulated structures, the MD approach steps were followed. For this purpose, the nanostructures were interacted and moved to other positions with new atomic velocity. The atomic force (
, position (
), and momentum (
) of atoms can be calculated by the following equations [30]:
| ||||
|
Simulation Parameter | Parameter Ratio/Setting |
Box Length | 100×65×65 Å3 |
Boundary Condition in X, Y, and Z Directions | Periodic, Periodic, and Fix |
Simulation Algurithms | NPT/NVE |
Initial Temperature | 321 ̊C |
Initial Pressure | 16 MPa |
Time Step | 1 fs |
Temperature Damping Ratio | 10 |
Pressure Damping Ratio | 100 |
3. Computational Results
3.1. Physical Stability of Nanofluid / hybridnanofluid
In the first step of our computational study, the equilibrium phase of H2O-fullerene nanofluid was reported to be at T0=321 ̊C as initial temperature. Our results in this step show that the atomic position and defined interatomic potential in nanofluid arrangement are matched with each other properly. This result was described by temperature and total energy calculation after t=10 ns (as shown in figure 2). Our MD calculations indicated that the temperature of atomic nanofluid was converged to 321 ̊C. This thermal behavior shows that t=10 ns is a sufficient MD time for equilibrium phase detection. Also, total energy calculation would indicate the equilibrium phase of the simulated H2O-fullerene nanofluid. As depicted in figure 2b, the total energy of nanofluid would increase by fullerene atomic ratio enlarging in MD simulation box. Numerically, the nanoparticles’ atomic ratio will increase from 1% to 10%, and the total energy of nanofluid will increase from -389.360 eV to -723.057 eV. The total energy enlargement by the insertion of fullerene nanoparticles to base-fluid shows an atomic stability and attraction force increase between various part of simulated structures. We expected the change of thermal behavior of H2O base-fluid affected by nanoparticles’ atomic ratio. Physically, attraction force between various atoms would cause the improvement of thermal behavior of pristine fluid (water molecules) which is described exactly in the next computational step.
Hybridnanofluid Increase stability and improve of suspension of nano-particles by adding the type of doped fullerene.
Figure 2. a)Temperature, and b)total energy variation of H2O-fullerene nanofluid as a function of MD simulation time.
Next, to validate the computational method in the current simulations, the Radial distribution function (RDF) and the density of water are calculated. The RDF of simulated structures can describe the atomic arrangement of them. Computationally, the RDF denoted in equation (7) by g(r), describes the probability of finding particles at r distance from other atoms [40],
(7)
where ρ is the atomic density, dnr is a function that calculates the number of atoms within a shell of thickness dr. Figure 3a shows RDF of O atoms in H2O molecules which is consistent with the previous reports [41].
Figure 3. The O-O radial distribution function (RDF) after equilibrium process.
3.2. Thermal Behavior of H2O-Fullerene Nanofluid
After the equilibrium phase of simulated structures, the thermal behavior of H2O-fullerene/fullerenes nanofluid/hybridnanofluid was reported. In this step of our calculations, we use the Green-Kubo approach to describe the thermal behavior of simulated nanofluid [42-44]. Technically, thermal calculation in current study was done using micro-canonical ensemble (NVE) as equation :
|
In this equation kB, V, and S define Boltzmann constant (1.380649×10−23 J⋅K−1), volume, and the heat vector, respectively. At each simulation time step in LAMMPS computational package, the heat current of atoms can be estimated using velocity and stress tensor. The mean of the heat current autocorrelation function is represented by <S(t).S(0)>. Figure 4 shows the thermal conductivity ratio vs. fullerene atomic ratio in MD simulation box. As depicted in this figure, the thermal conductivity of H2O-fullerene nanofluid reach to the final ratio after t= 10 ns. The results listed in Table 2 were averaged over the simulation box directions to get the accurate ratio. The calculated results show that the fullerene and doped fullerene with 4% atomic ratio effectively improve the thermal behavior of H2O molecules, resulting from a large contact surface between the fullerene nanoparticle and base-fluid atoms. This procedure detected in previous researches and verified our computational technique in current research [45-48]. Nonoparticles aggregation process in nanofluid structures is an important parameter for heat and mass transfer process. Physically, by fullerene nanoparticles insertion to H2O base fluid with high atomic ratio, the atomic mobility of nanostructures would increase and the aggregation process is detected in shorter MD time. As reported in table 2, by the use of nanoparticles in MD box with 4% atomic ratio, the contact surface between various nanoparticles was decreased and the aggregation process was detected after t= 5.32 ns. Through this mechanism, the energy transition rate in simulated structure was enlarged and finally the MD time for various physical phenomenon such as heat and mass transfer was decreased. By estimating thermal power of simulated nanofluid inside the nanostructures (nanochannels), one can estimate these atomic structures’ behavior as cooling systems in various actual applications such as nuclear engineering-based systems. The thermal power is another important parameter which can be described via thermal behavior of simulated structures. Thermal power of the fuel rods is determined with the help of power peaking factors presented [49-51].
The MD outputs indicated that by nanoparticles adding to pristine fluid, the thermal power of atomic structure was increased. The use of 4% fullerene nanoparticles inside MD box caused an increase of total system thermal power from 3000 to 3881 MW. Physically, phonon vibration increasing inside pristine fluid by adding nanoparticles to them cause heat flux ratio which transferred inside MD box increased and thermal conductivity of modeled nanofluid improved. The computational results indicated that water-fullerene nanofluid can be used in coolant systems in the nuclear engineer industry. Furthermore, simulation results indicated by using nanoparticles with more than 4% ratio, some inappropriate phenomenon such as aggregation of nanoparticles occur in lesser simulation time and thermal efficiency of modeled samples decreased. In another modeled sample in current computational research, by adding nanoparticles with 20% ratio, thermal conductivity dropped to 0.73 W/m.K.
Also, coolants could be replaced by hybrid-nanofluids, particularly fluids that work at very high temperatures. Our results show that thermal-conductivity in hybridnanofluid increases and improve heat transfer performance (table 2).
Figure 5 illustrates the thermal power variation of simulated systems as a function of nanoparticles ratio. As can be seen in this figure, by nanoparticles addition to base fluid by >4% atomic ratio, the thermal power of simulated structures was decreased. This decrease arises from the nanoparticles aggregation process.
Figure 4. The thermal conductivity of H2O-fullerene nanofluid variation as a function of nanoparticle ratio and MD simulation time.
Figure 5. The thermal power of H2O-fullerene nanofluid variation as a function of nanoparticle ratio.
Table 2. The thermal conductivity, aggregation time, and thermal power of H2O-fullerene nanofluid /hybrid nanofluid as a function of nanoparticles atomic ratio.
Atomic Ratio of Fullerene Nanoparticles(%) | Thermal Conductivity(W/m.K) | Atomic Aggregation Time(ns) | Thermal Power(MW) |
1 | 0.68/0.81 | 7.08 | 3122/3241 |
2 | 0.74/0.85 | 6.83 | 3208/3312 |
3 | 0.78/0.89 | 6.59 | 3459/3570 |
4 | 0.82/0.92 | 5.84 | 3881/3988 |
10 | 0.79/0.89 | 5.49 | 3661/3780 |
Thermal behavior improvement of simulated nanofluid by the increase of nanoparticles ratio can be effected via the heat flux ratio calculation. Figure 6 represents this parameter variation as a function of nanoparticle ratio and MD time. By adding greater amount of fullerene nanoparticles to base fluid, the ratio atoms’ mobility would increases. So, more thermal energy and heat flux would flow inside the MD box. Numerically, by an increase of 1 to 5% ratio of fullerene nanoparticles, the net heat flux would vary from 1661 W/m2 to 2019 W/m2, respectively (as shown in Table 3 and figure 7). The temperature variation of simulated structures cause thermal behavior variations in them. For this purpose, the temperature of simulated nanofluid in presence of 1% nanoparticle was set to 352 ̊C. The ratios and thermal conductivity of final atomic structures have been reported in this section. This ratio is the operating temperature of common reactors in the nuclear engineering industry systems. By initial temperature increasing in atomic nanofluid, the fluctuations’ amplitude would increase against higher temperature. This atomic procedure would cause heat flux increasing inside the MD box. After equilibration phase of nanofluid detection at T0=352 ̊C, the heat flux which flows in atomic nanofluid would reach to 2405 KW/m2. This heat flux increase in simulated models, the thermal conductivity of pristine atomic systems would reach to larger ratios and would converge to 4003 W/m.K. Computationally, the heat flux in the current study was calculated by using Green-Kubo method.
Table 3. The heat flux of H2O-fullerene nanofluid as a function of nanoparticles atomic ratio.
Atomic Ratio of Fullerene Nanoparticles(%) | Heat flux (W/m2) |
1 | 1661 |
2 | 1752 |
3 | 1893 |
4 | 2019 |
10 | 1903 |
Figure 6. The heat flux of H2O-fullerene nanofluid variation as a function of nanoparticle ratio.
Figure 7. The thermal conductivity of H2O-fullerene nanofluid at T0=625.15 ̊C variation as a function of MD simulation time.
To more analayzing of thermal conductivity in defined nanofluid , interaction energy inside MD box calculated in this step. As shown in figure 8, by nanoparticle ratio enlarging to 4%, interation energy inside MD box reached to -91.25 eV. By more nanoparticles ratio increasing, interatomic distance inside box decreases and replusive force between them convergd ti higher value. Numerically, by nanoparticle ratio setting to 10%, interaction energy converged to -74.31 eV. Structurally, figure 9 indicated the atomic position of atoms in as a function of MD time. As shown in this figure various parts, nanoparticles don’t aggregated before t=5 ns. This time evolution indicated appropriate behavior of fullerene nanoparticles as thermal improved parameter for heat transfer applications at high temperature and pressure condition.
Figure 8. The interaction energy between various atoms as a function of nanoparticles inside MD box.
Figure 9. Atomic evolution of H2O-fullerene nanofluid at: a) t=0 ns, b) t=2 ns, c) t= 5ns, and d) t= 10 ns.
The atomic evolution of H2O-fullerene nanofluid is defined by their density, velocity, and temperature profiles inside the atomic channel. For this calculation, the simulation box is divided into 122 bins in z direction. The calculated results show that the density profile of H2O-fullerene nanofluid converge a maximum ratio at initial and final bins. Numerically, the maximum value of the density profile changes from 0.019 atom/Å3 to 0.032 atom/Å3 values by 1% to 10% nanoparticles adding to water base-fluid, respectively (as depicted in figure 10). This atomic behavior arises from the absorption force from atomic channel inside MD simulation box. Inserting this attraction force into the simulated nanofluid restricted the atomic evolution of H2O-fullerene nanofluid particles in the vicinity of atomic walls. Furthermore, atomic evolution of defined compounds inside MD box affected by nanoparticles aggregation process and should be condidered in actual cases. Atomic representaionao of aggragation process depicted in figure 11.
Figure 10. Density profile of H2O-fullerene nanofluid with 4% nanoparticle in MD simulation box after t=10 ns.
Figure 11. Atomic arrangement of H2O and fullerene molecules, before and after of aggregation process.
The velocity profile of H2O-fullerene nanofluid as a function of nanoparticle atomic ratio depicted in figure 12 a. Computationally, this atomic parameter indicated the time evolution of H2O-fullerene nanofluid particles in MD box. Our results show that nanofluid particles velocity converged to maximum ratio in the middle union of simulation box. Furthermore, this parameter converged a minimum value in the initial and final bins. Numerically, the maximum velocity of H2O-fullerene nanofluid particles changes from 0.013 Å/ps to 0.004 Å/ps by nanoparticles ratio varies from 1% to 10%, respectively. Also, temperature profile of simulated nanofluid particles has similar manner, as shown in figure 12 b. This physical profile converged the maximum value in the middle union of simulation box and reached to a minimum value in initial and final bins. The numerical ratio of this physical parameter listed in Table 4. The results obtained from this part of the study show that the atomic mobility of simulated nanofluid reach to maximum value by 4% nanoparticle adding to base-fluid which this calculation show the best thermal behavior of H2O-fullerene nanofluid by 4% fullerene inserting to pristine base-fluid.
Figure 12. a) Velocity and b)temperature profile of H2O-fullerene nanofluid with 4% nanoparticle in MD simulation box after t=10 ns.
The Thermoelectric effect is another important phenomenon, occurring in atomic structures by the atoms’ temperature fluctuations inside MD box. Physically, the thermoelectric effect is the direct conversion of temperature differences to electric voltage and vice versa via a thermocouple [52]. By using MD simulations, the atoms’ evolution and so atomic charge displacement in the modeled compounds can be estimated. In LAMMPS package these evolutions in the defined structures was estimated by using DUMP output. In final section of this computational work, we reported the thermoelectric phenomenon after t=10 ns. Figure 13a, indicated the electric voltage changes of simulated nanofluids as a function of the initial temperature. MD simulation results indicated by temperature increasing, total voltage can be detected inside box by adding fullerene nanoparticles to pristine fluid. Numerically, electric voltage which created in atomic compounds varioes from 33.11 V to 40.22 V value by adding nanoparticles with 4% atomic ratio. This phenomenon in atomic structures arises from the effective charge existence in individual atoms. So, time evolution and positions’ changes of these atoms cause effective voltage creation by the temperature/atoms fluctuations changes. Thermal stability of simulated nanofluid can be restricted actual applications of them. In the final section of current research, temperature of H2O-fullerene nanofluid set at 300, 350, 400, and 500 ̊C, and simulation time which needed to atomic compound get unstable reported. MD outputs indicated by temperature increasing inside simulation box, the stability time of the total structure decreases to 57.31 ns (see figure 13b). This thermal result arrised from atomic fluctuations amplitude increasing by temperature enlarging and attraction force decreasing between various atoms.
Figure 13. a) The effective voltage of H2O-fullerene nanofluid variation as a function of nanoparticle ratio and MD simulation time. b) The stability time of defined nanofluid as a function of initial temperature.
Table 4. the maximum value of density/velocity/temperature profile and effective voltage of H2O-fullerene nanofluid in MD simulation box (after t=10 ns).
Atomic Ratio of Fullerene Nanoparticles(%) | Maximum Density(atom/Å3) | Maximum Velocity(Å/ps) | Maximum Temperature(̊C) | Effective Voltage(V) |
1 | 0.019 | 0.013 | 452.19 | 33.11 |
2 | 0.023 | 0.011 | 401.39 | 35.28 |
3 | 0.027 | 0.008 | 388.24 | 38.01 |
4 | 0.029 | 0.005 | 321.36 | 40.22 |
10 | 0.032 | 0.004 | 315.15 | 39.03 |
4.1 Conclusion
Current Molecular Dynamics (MD) simulations described the effect of Fullerene and doped fullerene nanoparticles on the atomic/thermal evolution of Water base-fluid. Fullerenes nanoparticles were added to base-fluid by 1% to 10% atomic ratios. Technically, the Universal Force Field (UFF) and TERSOFF are appropriate interatomic potentials to describe the atomic and thermal evolution of water-fullerene nanofluid and hybrid nanofluid. The total energy of simulated nanofluids changes from -389.36 eV to -725.06 eV by fullerene nanoparticles atomic ratio changes from 1% to 10%, respectively. The MD outputs indicated that fullerene nanoparticles implementing to base-fluid with 4% atomic ratio would improve the thermal behavior of nanofluid appreciably. So, fullerene/water nanofluid was used as the heat transfer fluid to enhance the energy efficiency of the nuclearl heat exchangers.
Also, coolants could be replaced by hybrid-nanofluids. Our results show that thermal-conductivity in hybridnanofluid increases up to 20% and heat transfer performance improve. Numerically, thermal conductivity of water-fullerene nanofluid was increased to 0.82 W/m.K. Heat flux of the modeled structure reached to 2019 KW/m2 after t=10 ns. By 4% fullerene adding to water base-fluid, the aggregation time of fullerene nanoparticles converged to 5.84 ns. Also, the effective voltage was detected in simulated nanofluid after t=10 ns. Numerically, this parameter ratio reached to 40.22 V by using 4% fullerene nanoparticles inside base-fluid. Furthermore, density, velocity, and temperature profile of water-Fullerene nanofluid have affected by fullerene atomic ratio. Numerically, the maximum value of these profiles have reached to 0.029 atom/Å3, 0.005 Å/ps, and 321 ̊C by a nanoparticle atomic ratio increase to 4%.
This MD simulation has been performed at high temperature for the nuclear industry applications for the first time. Thermal power of nanofluid/hybridnanofluid can be improved by fullerenes ratio optimization inside the MD box. Numerically, by the temperature increase of nanofluid/hybridnanofluid structure to 625.15 K, thermal power of nanofluid/hybridnanofluid reache to 3881 MW/3988 after t=10 ns. The thermal efficiency can be increased by more than 30% by adding concentration of nanoparticles as low as 1–4 vol%.
Declarations
Conflicts of interest/Competing interests The authors declare that they have no conflicts of interest.
Ethics approval N/A
Consent to participate N/A
Consent for publication N/A
Availability of data and material Data available on request from the authors.
Code availability LAMMPS main inputs available on request from the authors.
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