High Temperature Nanofluids Based on Therminol 66 for Improving the Heat Exchangers Power in Gas Refineries

Journal Pre-proofs High Temperature Nanofluids Based on Therminol 66 for Improving the Heat Exchangers Power in Gas Refineries Abbas Safaei, Alireza HosseinNezhad, Alimorad Rashidi PII: DOI: Reference:

S1359-4311(19)34918-X https://doi.org/10.1016/j.applthermaleng.2020.114991 ATE 114991

To appear in:

Applied Thermal Engineering

Received Date: Revised Date: Accepted Date:

17 July 2019 25 December 2019 22 January 2020

Please cite this article as: A. Safaei, A. HosseinNezhad, A. Rashidi, High Temperature Nanofluids Based on Therminol 66 for Improving the Heat Exchangers Power in Gas Refineries, Applied Thermal Engineering (2020), doi: https://doi.org/10.1016/j.applthermaleng.2020.114991

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High Temperature Nanofluids Based on Therminol 66 for Improving the Heat Exchangers Power in Gas Refineries

Abbas Safaei a, Alireza HosseinNezhad a,1, Alimorad Rashidi b aDepartment bNano

of Mechanical Engineering, University of Sistan and Baluchestan, Zahedan, Iran Technology Research Center, Research Institute of Petroleum Industry, Tehran, Iran

Abstract One of the problems that we face in many industries and research projects is the need for heat transfer in a short time and with high intensity. Most of the previous studies have been conducted on the low-temperature nanofluids (T ≤ 100 ̊C) such as water and various oils, and the hightemperature fluids are largely neglected. In this research, therminol 66 as a high-temperature oil was selected as the base fluid. Therminol 66 is used in the oil and gas industry for heat transfer in heat exchangers. In this research, SiO2 and Al2O3 nanoparticles were added at the concentration of 0.1 wt% to the base fluid. The basic thermophysical properties, including density, viscosity, and specific heat capacity of the samples, were measured. A high-temperature laboratory system was employed to evaluate the performance of nanofluids in the temperature range of 280-320 ̊C. The results showed that addition of nanoparticles at the concentration of 0.1 wt% did not lead to a considerable change in the density and viscosity of the base fluid, but the specific heat capacity of the nanofluid at high temperatures was improved compared to the base fluid. The results of the heat exchanger test also showed that the use of nanoparticles considerably improved the exchanger efficiency, such that it was increased at one state up to 88% compared to the base fluid. Keywords: Therminol 66, high-temperature nanofluid, heat exchanger efficiency, specific heat capacity, SiO2 nanoparticles, Al2O3 nanoparticles

1Corresponding

author: Mechanical Engineering Department, University of Sistan and Baluchestan

Email address: [email protected]

1

Nomenclature 𝐶𝑝 𝑞 𝑈 𝐴 T1 T2 t1 t2 F R P 𝑚

Specific heat (J/g.K) Heat flux (J/s) Overall heat transfer coefficient (J/m2.K) Heat transfer surface (m2) Hot fluid inlet temperature (̊C) Hot fluid outlet temperature (̊C) Cold fluid inlet temperature (̊C) Cold fluid outlet temperature (̊C) Geometric correction factor Heat transfer rate ratio Temperature effectiveness Fluid flow (kg/s)

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1. Introduction The research in the field of nanotechnology is being developed in many aspects and it seems to affect the dynamics of many of the largest industries such as oil [1] and gas [2, 3], theram engineering [4-7], agriculture [8]. With regard to the increasing in energy demand in industrial systems and recent efforts to increase the efficiency of energy systems [9-12], a special attention has been paid to the application of nanofluids in heat exchangers. The metal and metal oxides nanoparticles have been among the first particles used to produce nanofluids. These nanoparticles have a very high thermal conductivity coefficient compared to that of the base fluids. For example, the thermal conductivity coefficient of copper is 700 times of the thermal conductivity coefficient of water and 3000 times of that of engine oil. Moreover, the thermal conductivity coefficient of aluminum oxide is about 60 times of the thermal conductivity coefficient of water [13]. Therefore, it is expected that the fluids containing metal nanoparticles, metal oxide, carbon nanotube, graphene, and a hybrid of these particles would show better thermal properties than pure fluids. Theoretically, it has been indicated that the heat transfer surface would be increased by reducing the particle size. As a result, the thermal efficiency of suspended particles as a function of the heat transfer surface is increased as the particle size decreases [13]. In general, the researchers consider four main factors in the significant increase in the conduction of nanofluids [14], as follows: 1. Brownian motion of the nanoparticles, 2. Nano-layers formed on the boundary of nanoparticles and base fluid, 3. Nature of heat transfer in nanoparticles, 4. Effect of clustering of nanoparticles. Lee et al. (1999) [13] showed that CuO and Al2O3 nanoparticles in the base fluid of water or ethylene glycol had very high thermal conductivity, such that an approximate 20% increase in thermal conductivity coefficient was observed in 4 vol% of the 35nm particles in ethylene glycol. Vasheghani et al. [15] investigated the effect of Al2O3 phases on increasing the thermal conductivity and viscosity of engine oil. They observed that, with the addition of 3 wt% of nanoparticles α-Al2O3 and β-Al2O3 to the engine oil, the thermal conductivity was increased by 37% and 31%, respectively. Also, the viscosity of the above nanofluids was increased by 36% and 38%, respectively.

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Askari et al. [16] examined the rheological and thermophysical properties of the kerosenebased nanofluids and iron/graphene hybrid nanoparticles. In order to stabilize nanoparticles in the base fluid, they used oleic acid for the functionalization of nanoparticles. They reported that the produced nanofluids were completely stable for more than 5 months without any sediment. Their results showed that viscosity and volumetric mass of the nanofluid were slightly increased compared to the base fluid. Also, the thermal conductivity of the nanofluid was improved by about 31% compared to base fluid at the temperature of 50 ̊C. They used a laboratory system to examine the convection heat transfer. Their results indicated 66% improvement in the convection heat transfer coefficient in the sample nanofluid at the concentration of 0.3 wt% in Reynolds number of 4553 compared to the base fluid. Sandia et al. [17] investigated the improved performance of water-ethylene glycol mixture as the heat transfer fluid in the vehicle radiator using the titanium oxide nanoparticles. They used 60% water, 40% ethylene glycol, and nanoparticles at the concentrations of 0.1, 0.3 and 0.5 wt% for the production of nanofluid samples. All the tests were conducted in the Reynolds number range of 4000 to 15000 using a laboratory system equipped with a vehicle radiator. Their results showed that the heat transfer rate in the vehicle radiator was improved by almost 37% using the nanofluid compared to the base fluid. Behrangzade et al. [18] implemented Ag/water nanofluid to study the efficiency improvement of a plate heat exchanger. Their findings revealed that the overall heat transfer coefficient increase from 6.18 to 16.79% by adding nano-silver in nanofluid (with concentration of 100 ppm). They also reported that implementation of nanofluids caused no significant pressure drop. Shahsavani et al. [19] performed a research to estimate the influence of functionalized multi walled carbon nanotubes (f-MWCNT) on heat transfer and pressure drop of water/ethylene glycol-based nanofluid in a heat exchanger. They reported the relative values of pressure drop and heat transfer coefficient experimentally and by a correlation they proposed at temperature lower than 50 ̊C. Accordin g to their finding, the relative pressure drop declined with the increase in shear rate and increased with nanoparticles volume load and temperature increment. They reported that the aforementioned nanofluid can be used efficaciously at higher shear rates and

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lower temperature. Furthermore, they showed that the relative heat transfer coefficient improved (up to 44%) with nanoparticles volume load (1.0 vol%) and temperature (50 ̊C). Bhanvase et al. [20] also used a vertical helically coiled tube heat exchanger to study the heat transfer improvement by using nanofluid of water/PANI (polyaniline nanofibers, prepared by means of ultrasound assisted emulsion polymerization method) at nanofibers' concentration range of 0.1–0.5 vol%. They studied the effect of nanofibers concentration and Reynolds number on heat transfer coefficient. They showed that the heat transfer coefficient of distilled water (basefluid) and nanofluid with vol% PANI concentration was found to be 304 and 515.8 W/m2.̊C, respectively. They also found that 10.52 and 69.62% improvement in heat transfer coefficient was correspondence to nanofluid with PANI nanofibers concentrations of 0.1 and 0.5 vol%, respectively. Esfe et al. [21] used Ag/water nanofluid to investigate the heat transfer enhancement in a double tube heat exchanger using an artificial neural network. The findings revealed the ability of neural network to estimate the experimental data with excessive deviation and scatters. Also, the results indicated that with the increase of nanoparticle volume fraction from 0.15 to 1.9 vol% the values of relative heat transfer coefficient increased 9.3% at Re=31000. Other similar works have been conducted for further improvement of the heat transfer systems in the vehicles by other researchers, including Nieh et al. [22] for reducing heat loss in the radiator using alumina and titanium oxide nanoparticles, Hussein et al. [23] for examining heat transfer performance of the vehicle cooling system using SiO2 nanoparticles, Elias et al. [24] for laboratory examination of the nanofluid thermophysical properties based on radiator water and alumina nanoparticles, Muhammad Ali et al. [25] for laboratory examination of the improvement in the convection heat transfer in the vehicle radiator system using ZnO/H2O nanofluid, and by M'hamed et al. [26] for laboratory study of the heat transfer performance of the Toyota Prado radiator system using the multi-wall carbon nanotubes. Studies on thermosphysical and heat transfer properties of nanofluids, carried out by the researchers, have mostly been focused on low-temperature water-based nanofluids [27-29], ethylene glycol [30-32], and a variety of low-temperature working oils [33-35]. However, an important issue which has been neglected is the effect of nanoparticles in high-temperature fluids and efforts to improve their performance. Hence, in the gas refineries, absorbent beds usually 5

become resuscitation using hot gases exhausted from adsorbent system. Although a wide range of studies have been carried out on investigating the effect of nanoparticles on heat transfer coefficient at nominal range of temperature, no comprehensive conclusions have been reported on the effect of nanoparticles on heat transfer coefficient in heat exchanger at high temperatures. Indeed, it is expected that the effect of nanoparticles on fluids’ hydrodynamic (as a one negative factor on heat transfer) will be insignificant and the effect of nanoparticles and the relative mechanisms on heat transfer will be more tangible at high temperature. For this purpose, a shell and tube heat exchanger containing therminol 66 was used. So, increasing heat transfer ability of therminol 66 using nanoparticles leads to increase the temperature of resuscitation gas. The final result of this process is the reducing energy consumption in the gas refineries. In this research for first time the high temperature nano fluids based on therminol 66 were used in the absorbent regeneration systems. Nano fluids lead to the enhancement of heat transfer rate, so regeneration time in the bed will be decreased. Therminol 66 is one of the most used fluid high-temperature working oils. This oil is capable of being pumped at low temperature and shows high stability at high temperatures. It can also be applied at temperatures up to 345 ̊C. In order to examine the actual performance of high-temperature nanofluids, a laboratory system was built. The nanofluid samples were made based on fresh and used oil of therminol 66 containing SiO2 and Al2O3 nanoparticles at the concentration of 0.1 wt%. Initially, the thermophysical properties of the samples, including density, viscosity, specific heat capacity, and thermal conductivity were measured. Finally, the nanofluid heat transfer capability was examined using the simulated laboratory system.

2. Experimental procedure All the stages of synthesis of nanoparticles, nanofluid preparation, measurement of thermophysical properties, manufacturing of the heat exchanger and performing thermal tests are presented in this section.

2.1. Synthesis of nanoparticles

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For the synthesis of silica nanoparticles, 70 g of

Sodium Metasilicate Nonahydrate

(Na2SiO3.9H2O, Merck) was dissolved in 450 g of distilled water at the room temperature (25C). At the same time, in another bottle, 1.4763 liter (1401.995 g) of Dimethylformamide (C3H7NO, Merck) and 54.66 g of N-cetyl-N,N,N-trimethyl ammonium bromide (CTAB surfactant ,Merck) were dissolved in 400 g of distilled water while being stirred for 15 min. In the second stage, the CTAB and C3H7NO solutions were added to the transparent silicate solution at the room temperature. Immediately after mixing these two solutions, the initially transparent silicate solution was darkened. The reaction mixture was kept at the temperature of 25 ̊C for 3 h. After filtering the products and rinsing with water and ethanol, the remaining white substance was dried in the oven at 80 ̊C for 2 h. The surfactants were eliminated by calcination at 570 ̊C for 8 h [36]. The schematic process for silica nanoparticles preparation are shown in Fig.1.

Figure 1. process for preparation of silica nanoparticles.

Also, for the synthesis of alumina nanoparticles, the hydrothermal method was used. For this purpose, initially, pure gibbsite (Gibbsite 99.99%), ammonium bicarbonate, and 3 to 5 ml of deionized water were mixed. The weight ratio of gibbsite to ammonium bicarbonate was about 7

25-45%. Then, the above mixture was placed in the Teflon autoclave at 75 to 85 ̊C for 10 h. After the end of the reaction process, the product was cooled at the room temperature for 30 min while being stirred. Finally, in order to produce the nanogamma alumina particles, the prepared mixture underwent calcination for 60 min at 450 ̊C under thermal decomposition conditions. The schematic process for silica nanoparticles preparation are shown in Fig.2.

Figure 2. process for preparation of alumina nanoparticles.

2.2. Preparing the nanofluids based on therminol 66 In this research, the oil of therminol 66 (Heat Transfer Fluid-Eastman Chemical Company, Belgium) was selected as the base fluid. A probe ultrasonic device (ultrasonic homogenizer Y9211n-syclan, china) was used to disperse the nanoparticles into the base fluid. For further stability, BenzAlkonium Chloride (BAC surfactant) at the concentration of 1:1 to nanoparticles was used. SiO2 and Al2O3 nanoparticles were added at high concentration to the fresh and used oil and received ultrasound waves for 10 min along with BAC surfactants. Indeed, after preparation of nanofluid with high concentration, a mechanical mixer was used to produce a high 8

volume of nanofluid to work with the laboratory system, with further details presented in the relevant section. It should also be noted that the fresh oil of therminol 66 was purchased from the factory and the used oil of therminol 66 was sampled from the heat exchanger of a gas refinery in south of the Iran.

2.3. Thermophysical properties measurement Thermophysical properties, including density, viscosity and specific heat capacity (𝐶𝑝), were measured respectively based on ASTM-D4052, ASTM-D445 and ASTM-E1269-11 standards for base fluids and nanofluid samples. Also, for studying the heat transfer capability of the samples, the laboratory heat exchanger system was used. For this purpose, the heat exchanger efficiency was measured for all the samples at the temperature of 320 ̊C.

2.4. Design and fabrication of laboratory heat exchanger The initial design of the heat exchanger was carried out using Aspen Exchanger Design and Rating (EDR) software. The specifications of the designed exchanger are presented in Table 1. Then, in order to develop the exchanger, a three-dimensional design was drawn in Solidwork software, as shown in Fig.3.

Table 1. Heat Exchanger Specification Sheet. Shell side

Tube side

Air

Therminol 66

0.007

0.0309

Temperature In/Out (̊C)

49.9/293.3

315.6/287.8

Absolute pressure (bar)

1.5

1.5

Tube/Shell number

1

24 Us

Number passes per shell

1

2

Fluid allocation Total fluid quantity (kg/s)

9

Tube sheet-Stationary Tube length (mm)

SS 304

SS 304

1000

1000

Figure 3. Heat exchanger design in Solidwork software.

The laboratory system designed in this research consisted of three main parts. The first part was the shell-tube heat exchanger, the second part was the set of hot oil pump and electromotor, and the third part was the storage tank and oil heater. As demonstrated in Fig.4, each part was individually made and, then, assembled. Afterwards, electronic equipment and precise tools, including electric control panel, inverter, oil flow meter, air flow meter, safety valve, temperature sensors, pressure gauge and heaters, were installed on the system. The schematic view of the final system is shown in Fig.5. 10

Figure 4. Heat exchanger and assembled system.

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Figure 5. Schematic view of the constructed laboratory system.

2.5. Measuring the heat exchanger efficiency using the laboratory system According to the calculations, the total required oil for the laboratory system was about 38 kg. Therefore, the required nanofluid was initially produced in sufficient volume. For this purpose, a mechanical mixer was used. The oil of therminol 66 along with nanoparticles and BAC surfactant was poured into the mixer tank based on the formulations of Table 2, and the mixing process was performed at 1420 rpm for 2 h. The samples had excellent stability and uniformity. The fresh oil of therminol 66 refers to an oil purchased from the factory that has not yet been used. Moreover, the used oil of therminol 66 refers to an oil that has already been used in the heat exchanger of the refinery for a specified period of time (about one year).

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Number

Table 2. Nanofluids specifications. Components Sample formulation

abbreviation

Therminol 66

Nanoparticles BAC surfactant

name

(kg)

(gr)

(gr)

1

Pure oil (Therminol 66)

TH

38

-

-

2

Pure oil+Alumina

TH+Al2O3

37.924

38

38

3

Pure oil+Silica

TH+SiO2

37.924

38

38

4

Used oil

UTH

38

-

-

5

Used oil+Alumina

UTH+Al2O3

37.924

38

38

6

Used oil+Silica

UTH+SiO2

37.924

38

38

In order to measure the efficiency of the exchanger using the laboratory system, the following method was used. In the first stage, the air in the entire system (reservoir, pump, tubes and fittings) was completely depleted using nitrogen gas. To this end, the nitrogen gas (with the pressure of 1.5 bar) was injected into the system and the air was depleted from the highest point of the system. This process lasted for about 5 min. Then, the nitrogen valve and the air outlet valve were closed. In the second stage, the nanofluid was injected through the inlet funnel into the system and, at the same time, the pump was turned on at the frequency of 25-35 Hz. In the third stage, using the nitrogen line and for improving the pump performance, the pressure of 1.5 bar was applied to the oil tank. In the fourth stage, the heaters were turned on for oil heating and reaching the desired temperature of 320 ̊C. The time required for oil temperature to reach 320 ̊C was about 24 h. In the fifth stage, after the temperature of reservoir oil reached 320 ̊C, the data collection process began. Before the data collection, using the flow meters embedded on the system, the oil and inlet air flows were adjusted according to the corresponding values. After 20 min and the stability of the system conditions, the oil and air inlet and outlet temperatures were read and recorded using the sensors embedded on the exchanger. Subsequently, using the existing relationships, the value of the exchanger efficiency was calculated. Since the oil flow is effective for the exchanger efficiency, therefore, the data collection process was carried out in different oil flows. The inlet air flow was also considered 22 𝑚3 ℎ based on the system design conditions for all the samples. This process was performed for all the samples in Table 2.

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Figure 6. Flow diagram for performing experimentation.

3. Result and discussion In this section, the results of the synthesis and characterization of nanoparticles and the measurement of the thermophysical properties of the nanofluids will be discussed and examined. The results of the exchanger efficiency measurement are also presented.

3.1. Characterization of nanoparticles and preparing nanofluids Fig.7 and 8 show X-Ray Diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM) analyses of synthesized gamma alumina nanoparticles, respectively. The structure of alumina and silica nanoparticles was characterized using XRD analysis. As shown in Fig.7 a, the broad peaks of 38, 46 and 66 at 2 angles were related to surfaces (311), (400) and (440), respectively, which was significantly compatible with the standard structure of gamma alumina nanoparticles [36]. In addition, a broad peak ranging from 20 to 30 at 2 angles in Fig.7 b represents the amorphous structure of silica nanoparticles with high purity [37]. 14

Fig.8 also shows the FESEM image of alumina nanoparticles. As specified, the alumina nanoparticles had a spherical-shape structure and the average sizes of alumina nanoparticles were ranged from 20 to 50 nm. a

b

Figure 7. XRD analysis of a, gamma alumina and b, silica nanoparticles.

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The Scanning Electron Microscope (SEM) image of the nanoporous silica particles is also shown in Fig.9. The silica nanoparticles were almost spherical in shape and porous and the average sizes of silica nanoparticles were ranged from 60 to 120 nm [38]. The stability and the formation of nanoparticles agglomeration should be studied in basefluid environment due to the fact that the intra-particles forces depend on the basefluid types as well as the method of dispersion and nanofluid preparation process significantly [16, 30, 39, 40]. The nanoparticles were dispersed in ethanol and then they were introduced to the SEM test after full evaporation of this solvent. It has been reported in previous researches that the dispersion of silica nanoparticles in hydrophilic solvent such as water and ethanol lead to the formation of nanoparticles clusters [6]; therefore, the formation of nanoparticles’ agglomeration and the observation of these clusters in the SEM and FESEM images is expected. However, implementation of BAC surfactant in Therminol 66 leads to higher stability of nanoparticles in basefluid. In fact, alumina and Silica nanoparticles are hydrophobic and they can be dispersed in therminol 66 well. Furthermore, the addition of BAC surfactant in nanofluids enhance the hydrophobicity of the nanoparticles and BAC molecules act as surface modifiers over nanoparticles’ surface [41]. In addition, the size distribution of nanoparticles in basefluid can be determined by using Dynamic Light Scattering and the morphology of nanoparticles can be determined by using Transmission Electron Microscope. However, the implementation of SEM analysis can be used in order to determine the morphology and sizes of nanoparticles’ clusters. The size distributions of nanoparticles were measured by using Image J software and the average sizes of nanoparticles were obtained at different fractions.

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Figure 8. a, FESEM image and b, size distribution of gamma alumina nanoparticles. 17

Figure 9. a, SEM image and b, size distribution of silica nanoparticles. 18

3.2. Thermophysical properties Viscosity and density are among the most important parameters to determine the quality of heat transfer in fluids. In this research, the viscosity and density of all the samples (according to Table 2) were measured at 50, 60, 70, 80 and 90 ̊C. The results are shown in Fig.10 and 11. As can be seen, the trend of variations in density and viscosity was descending in all the samples as the temperature increased, which was normal. The notable point is the very slight variations in the density and viscosity of nanofluid samples compared to the base fluid. In other words, the results showed that the addition of alumina and silica nanoparticles at the concentration of 0.1 wt% did not lead to significant variations in the density and viscosity of the base fluid, which was a positive result.

Figure 10. Density changes with temperature.

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Figure 11. Viscosity changes with temperature. The specific heat capacity (𝐶𝑝) determines the heating and cooling rate of the material and is an important property in heat transfer. Since the heat capacity of the material is directly related to its atomic structure, the heat capacity measurement as a function of temperature can determine the structural properties of nanomaterials. The research on nanofluids has been mainly focused on thermal conductivity and convection heat transfer. Differential scanning calorimetry (DSC) is a powerful tool for measuring the heat capacity of nanofluids. In this research, the specific heat capacity of all the samples (according to Table 2) was measured using the exact DSC test based on ASTM-E1269-11 standard. The heat flow was measured for all the samples from ambient temperature up to 320 ̊C at the heating rate of 20 ̊C/min. Results of the DSC test are shown in Fig.12.

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Figure 12. 𝐶𝑝variations with temperature for all samples. In general, the heat capacity of the nanofluid can be increased or decreased compared to the base fluid. This trend depends on the type and concentration of the nanoparticles, temperature and type of base fluid. Results of this research showed that the heat capacity of the nanofluid samples reached to the maximum value at higher temperatures than the base fluid, indicating the positive effect of nanoparticles on preventing the formation of free carbon and coke for the degradation of Therminol 66 components. Increasing the nanofluid temperature leads to degradation of basefluid components and formation of free carbon during a chemical reaction. These free carbons decrease the nanofluid’s specific heat capacity compared to pure basefluid (the specific heat capacity of carbon is lower than that of therminol 66). The heat capacity of the nanoparticles and the base fluid affect the heat capacity of the nanofluid. If the heat capacity of the nanoparticles is less than that of the base fluid, the heat capacity of the suspension will be decreased; otherwise, it will be increased. The liquid-solid interfacial free energy varies upon 21

mixture. Due to the larger surface area of nanoparticles, the free surface energy is more compatible with system capacity, which affects the specific heat capacity of composite materials. In general, where rapid temperature changes are required, it is appropriate to use a fluid with less heat capacity. Besides, where a large temperature range is required, nanofluids with high heat capacity can be used. Therefore, with regard to the working range of oil in gas refineries, i.e. 280-320 ̊C, it can be said that the samples containing SiO2 nanoparticles had better performance in heat transfer. Furthermore, for the UTH-SiO2 sample, which refers to the used oil of therminol 66 containing silica nanoparticles, the amount of 𝐶𝑝 was not reduced up to the temperature of 320 ̊C and kept its ascending trend. Also, in order to investigate the effect of nanoparticles on other nanofluids thermosphysical properties, the value of thermal conductivity (as the most influential parameter on heat transfer rate) were measured at various nanoparticles mass concentrations (wt%). To do so, a thermal analyzer device (KD2 Pro. Decagon, USA) was implemented and the values of thermal conductivities were measured by using Transient Hot Wire approach. A quartz probe (with length of 60 mm and diameter of 2 mm containing three different thermometers) was used for producing heat and measuring the cooling laps. The values of thermal conductivities were measured at temperature of 25 ̊C after preparation of nanofluids with nanoparticles concertation of 0.05, 0.1, 0.3, 0.5, and 1 wt%. The results presented in Fig.13 shows that with the increase of nanoparticles mass load the value of thermal conductivity increase for both nanofluid. It is due to the increase in number of Brownian motion caused by nanoparticles [42]. According to the previous researches [4, 7, 42, 43], higher intensities and number of Brownian motion leads to increase the microconvection within the nanofluid. Therefore, a unique conclusion has been reported by previous scholar that addition of nanoparticles to basefluid enhances the thermal conductivity of nanofluid. However, this results showed that for Al2O2 (3.95 g/cm3)-loaded nanofluid the values of nanofluid thermal conductivity were observed higher than SiO2 (2.65 g/cm3)-loaded nanofluid about 1.6% at any nanoparticles mass loads. This results can be attributed to the nanoparticles density (higher density produce microconvection with higher intensities [4, 5, 7, 42, 43]). In this study the results showed the value of basefluid thermal conductivity was found to be 0.116 W/m.K and the value of thermal conductivity for highlyconcentrated alumina and silica-based nanofluid was 12.1 and 10.7% higher than those of pure basefluid, respectively 22

Figure 13. Thermal conductivity measurement for SiO2 and Al2O3–loaded nanofluid.

3.3. Thermal performance factor of heat exchanger Performance factor of the heat exchanger was measured and calculated for all the samples (as shown in Table 2). In this research, the log-mean temperature difference (LMTD) method was used to calculate the performance factor of the exchanger. This method is more common in the cases, in which the inlet and outlet temperatures of the cold and hot fluid were measured. Eq.1 holds in heat exchangers, in which the temperature of inlet and outlet hot fluid is respectively shown by T1 and T2, and the temperature of inlet and outlet cold fluid is shown by t1 and t2, respectively. Also, the parameter q is the transferred heat,

U

is the total heat transfer coefficient

of the exchanger and A is the total heat transfer surface in the exchanger. q  U  A  F  LMTD

(1)

23

T  LMTD    T1   T2  / ln  1  T2  

T1 T1 t2 T2 T2 t1 In this equation, (F<1) is the geometric correction factor, which depends on the geometry of the heat exchanger, and inlet and outlet temperatures of hot and cold fluids. In fact, the factor F is a criterion for examining the behavior of the heat exchanger compared to the ideal exchanger behavior. In Fig.14, values of the correction factor F are represented based on parameters P (temperature effectiveness) and R (heat transfer rate ratio). According to Eq.2 and 3, the dependence of the correction factor F on the inlet and outlet temperatures of the hot and cold fluids per P and R is quite obvious.

𝑃= 𝑅=

(𝑇2 ― 𝑇1)

(2)

(𝑡1 ― 𝑇1) (𝑡1 ― 𝑡2)

(3)

(𝑇2 ― 𝑇1)

Figure 14. Correction factor F. 24

In this research, in order to calculate the exchanger performance, the experimental data obtained from the laboratory system were used. In experimental experiments, the data collection process was performed with three repetitions in different oil flows. Initially, the numerical values of LMTD were calculated in accordance with Eq.1 based on the inlet and outlet temperatures for all the samples. Then, parameters P and R were calculated based on Eq.2 and 3, and the values of factor F were determined using the diagram in Fig.14. Afterwards, the values of the parameter q in Eq.1, which is equivalent to the heat exchange between two fluids in the exchanger, was calculated using the first law of thermodynamics. Assuming the insignificance of heat losses, the



equation m.C p T



air

  m.C p T 

oil

holds, where m . is fluid flow (kg/s), 𝐶𝑝 is specific heat

capacity 𝑘𝑗 𝑘𝑔.℃, and T is the difference in the temperature of inlet and outlet flows (oil or air) per ̊C. Finally, using Eq.1, the UA values were calculated as the performance factor of heat exchanger for all the samples. The LMTD values for all the samples are shown in Fig.15. The LMTD parameter in the calculations related to the heat exchangers indicated a thermal driving force in the heat transfer from hot to cold fluid. A higher numerical value for this quantity indicated higher heat transfer in the exchanger. As shown in Fig.15, the LMTD values for all the nanofluid samples were higher than those of the base fluids. On the other hand, the highest value of LMTD was related to the samples containing silica nanoparticles. In the 175 kg/h flow, the LMTD was 115 and 96 for THSiO2 and TH samples, and 105 and 91 for UTH-SiO2 and UTH samples, respectively. Therefore, it can be said that value of LMTD for nanofluids containing silica nanoparticles in the fresh oil and used oil was increased by 20 and 15%, respectively, compared to the base fluid. According to the data presented in Fig.12, it can be concluded that the maximum values of specific heat capacity for TH-SiO2 is much higher than other nanofluids and basefluid. In addition, due to the fact that SiO2 nanoparticles contain silanol (Si-OH) groups on its surface [6] and Therminol 66 contain modified therphenyl with the polar molecular structure (Fig.16) [44], a significant surface interaction can be seen between the nanoparticles’ surface and basefluid molecular components thanks to their polar structures and lower surface energy [6]. Therefore, SiO2 nanoparticles can be easily dispersed in basefluid and increases the heat transfer rates as well as the nanofluid thermal conductivity by using random Brownian motion as a result [6]. Furthermore, this results were not observed for alumina loaded nanofluids owing to the fact that these nanoparticles might form clusters and agglomeration which leads to decrease the alumina 25

nanoparticles’ random motion [42]. In addition, due to the formation of these clusters they can be attached to the heating surface easily and form fouling which leads to decrease the heat transfer rate as a result [45]. On the other hand, addition of SiO2 nanoparticles to Therminol 66 decreases the fouling phenomena on the heating surface leading to higher rate of heat transfer compared to alumina-loaded nanofluid and pure basefluid [46, 47].

Figure 15. LMTD values for base fluid and nanofluids in different oil flows.

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ortho-Terphenyl

meta-Terphenyl

para-Terphenyl

Figure 16. Molecular structure of modified therphenyl (Therminol 66) [44]. Also, the values of the parameter UA are presented as the exchanger performance in Fig.17 and 18 for the samples containing fresh and used oil, respectively. As seen, the value of the exchanger performance for all the nanofluids was higher than the base fluid. An increase in the exchanger performance indicated that the exchanger size can be reduced, or that the energy consumption would be significantly decreased. Since the changes in the refinery system were based on the used oil, therefore, with regard to the LMTD results and performance factor, it can be said that the UTH-SiO2 sample would have better performance in the refinery system. According to Fig.18, the value of exchanger performance was improved by 88% compared to the base fluid, using a sample containing silica nanoparticles in the flow rate of 250 kg/h, which was very significant.

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Figure 17. UA values for samples containing fresh oil of therminol 66 in different oil flows.

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Figure 18. UA values for samples containing used oil of therminol 66 in different oil flows. 4. Conclusion As previously stated, the research conducted in the field of nanofluids is mainly related to low-temperature systems. Therefore, the main objective of this study was to evaluate the heat transfer of nanofluids at high temperature. The oil of therminol 66 was selected as the hightemperature fluid. Therminol 66 is used in gas refineries as heat transfer fluid in the temperature range of 280-320 °C. SiO2 and Al2O3 nanoparticles were selected as additives to the oil. After the preparation of nanofluid samples, the thermophysical properties, including density, viscosity and specific heat capacity, were measured. In order to evaluate the heat transfer performance of the nanofluids, a laboratory system was used. Then, the exchanger performance was measured for all the nanofluid and basic fluid samples. The results of experimental tests showed that the addition of silica and alumina nanoparticles at the concentration of 0.1 wt% to the oil of therminol 66 did 29

not lead to significant changes in the density and viscosity. However, the specific heat capacity of the nanofluid samples was improved at higher temperatures than the base fluid. Also, the results of the exchanger test showed that the addition of silica and alumina nanoparticles to the therminol 66 significantly improved the exchanger efficiency. Based on the results, the heat exchanger performance was improved by 88% compared to the base fluid using UTH-SiO2 sample in the flow of 250 kg/h, which was very significant. Generally, it can be said that the increased exchanger efficiency indicated a decrease in the energy consumption.

ACKNOWLEDGMENTS The authors would like to thank Research Institute of Petroleum Industry (RIPI) for providing the necessary facilities for this research. Abbreviations CTAB BAC EDR XRD FESEM SEM DSC TH UTH LMTD

N-cetyl-N,N,N-trimethyl ammonium bromide BenzAlkonium Chloride Aspen Exchanger Design and Rating X-Ray Diffraction Field Emission Scanning Electron Microscopy Scanning Electron Microscope Differential Scanning Calorimetry Pure oil (Therminol 66) Used oil (Therminol 66) Log-Mean Temperature Difference

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Highlights: 

High temperature nanofluids used in the absorbent resuscitation systems.



Improvement of heat exchanger performance and reducing energy consumption.



High stability nanofluids based on SiO2 nanoparticles and therminol 66.



Thermal conductivity and performance factor were investigated.

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Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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