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 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 59, 2017 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.aidic.it/cet 

Guest Editors: Zhuo Yang, Junjie Ba, Jing Pan 
Copyright © 2017, AIDIC Servizi S.r.l. 
ISBN 978-88-95608- 49-5; ISSN 2283-9216 

Study on Cooling Characteristics of Water-based Carbon 

Nanotube Nanofluids for Internal Combustion Engines  

Haichao Liua, b, Xiaona Songb, Yongwei Gaoa, b 

aSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China 
bSchool of Mechanical Engineering, North China University of W ater Resource and Electric Power, Zhengzhou 450046, 

China 

dahai9915@163.com 

In the cooling system of internal combustion engines, traditional cooling water is replaced by the water-based 

carbon nanotube nanofluids. To cope with the overall method of six cylinder diesel engine, the cooling system 

and the solid components of internal combustion engine are seen as a coupling, and the fluid solid boundary 

become an internal real-time boundary of nanofluids in internal combustion cooling system. In addition, heat 

transfer characteristics are studied in this paper. On the influence of law, different types, different volume 

fraction and different particle size of nanofluids have different effects on the heat transfer of internal 

combustion engine cooling system, which gives the coolant flow, the cooling water jacket of the heat transfer 

coefficient, pressure field and accurate temperature distribution. Thus, the thermal stress calculation for the 

internal combustion engine using water-based carbon nanotube nanofluids has laid a theoretical foundation in 

the application of diesel engine cooling water cavity. In this paper, the X-Y function can record the 

determination curve of aqueous carbon nanotube nanofluids. And then we discuss the effect of carbon 

nanotube content and temperature on the cooling characteristics of water carbon nanotube nanofluids. Finally, 

the results of experiments show that the maximum cooling rate of nanofluids increases gradually with the 

increase of CNT content, and the cooling performance of nanofluids decreases with the increase of quenching 

temperature. 

1. Introduction 

Adding the metal and non-metal the polymer solid particles in the liquid is an effective method to improve the 

heat transfer ability of the liquid. Based on this theory, Argonne National Laboratory firstly proposed that 

adding a small amount of nano particles, namely "nanofluids" concept, to improve the heat transfer 

performance of refrigerant comparing to the base fluid. The thermal conductivity of nanofluids increases 

obviously and the heat transfer ability is enhanced, while the flow resistance in the flow do not significantly 

increase. The enhancement of the nano fluid heat transfer mechanism can significantly improve the thermal 

conductivity, which can also produce heat diffusion in nano fluid so as to enhance heat transfer. In the 

literature, the mechanisms of thermal conductivity of nanofluids are studied, but many researches dosen’t 

focus on the mechanism of the nano fluid flow process (Oliveira et al., 2017). Although the flow and heat 

transfer of nanofluids scholars carried out experimental research and got some heat transfer data, it is difficult 

to establish the corresponding correlation for convection criterion due to the lack of experimental data for nano 

fluid finishing methods and the lack of detailed analysis of the mechanism. Some scholars of nanofluids in 

engine cooling system were applied to do the preliminary study (Esfe et al., 2017). The vehicle based nano 

fluid heat radiator was studied and analyzed about the heat transfer enhancement of the nano fluid 

mechanism. Then the parameter test with nano fluid thermal properties was replaced by the original cooling 

refrigerant, CFD numerical simulation on the application of nano fluid in the cooling system of the engine. And 

they found that the nano fluid heat transfer performance of engine cooling system had a very good 

strengthening effect, however, the thermal parameters only replaced the original cooling refrigerant without 

considering the nanoparticles micro motion and heat diffusion mechanism, which reflected the strengthening 

effect of nano fluid on the cooling system of internal combustion engine. In addition, it was necessary to carry 

                               
 
 

 

 
   

                                                 
DOI: 10.3303/CET1759180

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Please cite this article as: Haichao Liu, Xiaona Song, Yongwei Gao, 2017, Study on cooling characteristics of water-based carbon nanotube 
nanofluids for internal combustion engines, Chemical Engineering Transactions, 59, 1075-1080  DOI:10.3303/CET1759180   

1075



out nano fluid of engine cooling system based on flow strengthening mechanism. The process flow diagram of 

preparation of water-based carbon nanotube CNT nanofluids is given in Figure 1 (Rasheed et al., 2016; 

Nizamani et al., 2017). 

 

 

Figure 1: Process flow diagram of preparation of water-based carbon nanotube CNT nanofluids 

Once the nanofluids are used as the heat transfer medium for the piston to cool the oil chamber, the gas-liquid 

two-phase flow becomes the solid-liquid H-phase flow and the heat transfer, whose process is more 

complicated (Ahammed et al., 2016). Apart from the above problems, we also face with the following 

difficulties: (1) At present, the numerical simulation of nano-fluid research is mostly based on the traditional 

solid-liquid two-phase flow or single-phase flow theory. However, the surface effect and the quantum scale 

effect make the behaviour close to the liquid molecules due to the small size effect of the nanoparticles, which 

is not the same as the molecules (Azwadi et al., 2016). (2) Under the reciprocating motion condition of the 

piston, the nanometre fluid is fixed into the solid gas solution with the air, and the mathematical model of the 

flow and heat transfer of the nanometer fluid is still to be further studied and perfected. (3) The presence of 

nanoparticles has an additional impact on the wall, and it is necessary to simplify the treatment of 

nanoparticlesin the process of reciprocating shock, separation and reattachment of the nanofluids, which will 

result in a violent oscillation of the wall attachment layer (Hussein et al., 2016). (4) When the water-based 

nanometer fluid is used to cool the piston, it is necessary to distinguish the phase of the nanometer fluid in the 

numerical simulation process, and the interaction mechanism between the nanometer particles and the wall 

surface needs further study, (Sekhar et al., 2016). The water-based carbon nanotube nanofluids are studied in 

this paper, which can artificially reach fluid turbulent flow to improve the cooling performance of internal 

combustion engines due to the special structure of the wave shaped wave wall. And the test equipment is 

reduced sharply. The results are easily observed, and the most important thing is to reflect on the flow of 

nanofluids. 

2. Mathematical and physical models of nanofluids 

In this section, we firstly introduce the mathematical model of nano-fluid and the tracking model in the CFD 

numerical simulation, and the mathematical expressions of different models are given in details. In the model, 

since the nanoparticles are regarded as a cleavage fluid, it is necessary to specify the faint viscosity in solving 

the conservation equation. The commonly particle viscosity models are based on the gas-solid two-phase flow 

at high concentrations. However, the large particle sizes may not be suitable for nanofluids such as low 

concentrations, small particle sizes and Liquid-solid two-phase flow. In this section, the virtual viscosity model 

which is suitable for the nanoparticles is deduced from the N-S equation of the basic fluid and the 

nanoparticles. In the subsequent calculation, the empirical formula based water-based fluidized bed is 

compared with the formula based on molecular motion theory, which highlights the advantages of the new 

model and provides theoretical support for the numerical simulation. And then we introduce the geometric 

reconstruction algorithm and the local compressible algorithm based on the limiting factor. The interface 

between the gas-liquid two-phase flow and the solid-liquid flow is used in the reciprocating oscillation condition. 

2.1 Single-phase flow model 

The single-phase flow model is a relatively simple continuous model. In the Euler coordinate system, the 

nanofluids are used as a single-phase fluid to calculate the physical parameters, such as density, viscosity, 

thermal conductivity, of the nanofluids, and then the empirical formula can be obtained. Compared with the 

basic fluid, the single-phase flow model only considers the change of the physical properties of the nanofluids, 

which does not consider the interaction between the nanoparticles and the basic liquid. In this paper, we 

ignore the phase of the momentum exchange and energy exchange process, but the impact of nano-particles 

on the flow field is applied into a physical parameter of the change. Finally, the conservation equations for the 

single-phase flow model are expressed as follows (Sidik et al., 2017). 

The quality equation: 

1076



  0V
t





  

   (1) 

Momentum equation: 

   V VV p g
t
   


      


  (2) 

The quality equation: 

       eff effE V E p k T V
t
  


        

   (3) 

Where ρ is the density of the nanofluids, V is the velocity of the nanofluids, g is the gravitational acceleration, 

p is the static pressure, 𝜏̿ is the stress tensor, E is the total energy, keff is the effective thermal conductivity of 

the nanometre and T is the temperature. 

2.2 Multiphase flow model 

In this paper, the multiphase flow model takes into account the velocity difference between discrete and 

continuous phases and the interaction between them. And the flow and heat transfer processes of nanofluids 

are calculated by solving the conservation equation of the mixed phase, the volume fraction equation of the 

solid phase and the velocity slip. In general, the mixture model is more reasonable than the single-phase flow 

model, because it takes into account the temperature difference between the base fluid and the solid particles, 

additionally, and the speed slip is closer to the actual situation. In the conservation equation, the conservation 

of the physical parameters is the volume mean of each phase, the velocity field and the temperature field, 

which are no longer shared by the solid-liquid two-phase. In this paper, the conservation equation of the 

multiphase flow model is shown as follows (Sidik et al., 2017). 

The quality equation: 

  0m m mV
t





  


  (4) 

Momentum equation: 

      , ,
1

n
T

m m m m m m m m m k k dr k dr k

k

V V V p V V g F V V
t
     



  
                 


  (5) 

The quality equation:  

      
1 1

n n

k k k k k k k eff

k k

E V E p k T
t

   
 


     


 

 (6) 

The multiphase model introduces the concept of algebraic slip and defines the algebraic relation of relative 

velocity between two phases. On a shorter space length scale, the local balance should be achieved and the 

relative velocity can be expressed as follows, 

 p mp
pq

drag p

V a
f

 






 (7) 

Where 𝜌𝑘  is the density of the k-phase,  𝑉𝑘 is the velocity of the k-phase, 𝛼𝑘 is the volume fraction of the k-th 

phase,n is the number of phases, F is the volume force, 𝜌𝑚 is the average density of the mixed phase, 𝜇𝑚 is 
the volume average viscosity of the mixed phase, Vm is the average velocity of the sea phase is the velocity of 

the particle phase, keff is the effective thermal conductivity, Ek is the total energy for the first phase, and T is 

the temperature for the temperature, 𝜏𝑝 is the relaxation time, dp is the particle size of the particle. fdrag is the 

drag force function, 𝜌𝑝 is the density of the particle phase, a is the acceleration.  

2.3 Thermophysical Properties of Nanofluids 

The thermal conductivity of nanofluids was measured experimentally before 2003. In recent years, many 

scholars have successfully established an effective theoretical model to predict the thermal conductivity, 

density, specific heat capacity and viscosity of nanofluids. The thermo physical properties of the nanofluids 

used in the numerical simulation are determined by the formulas (8) to (11) 

Thermal conductivity is expressed as follows (Solangi et al., 2015), 

1077



      
    

3 3 3 3

1

3 3 3

1 1

2 1 2

2 1

p lr lr p lr lr f f

nf

p lr p lr

k k k k k k k k
k

k k k k

    

   

           


         (8) 

Density is shown as, 

 1nf f p     
 (9) 

Specific heat capacity is the following equation, 

      1p p p
nf f p

c c c   
 (10) 

Viscosity is shown as follows, 

𝜇𝑛𝑓 = 𝜇𝑓
1

(1−∅)2.5
, 𝛽 = 1 + 𝛾, 𝛽1 = 1 +

𝛾

2
, 𝛾 =

ℎ

𝑎
, 𝑘𝑙𝑟 = 2𝑘𝑓 (11) 

Where h is the thickness of the interface layer, a is the particle radius, k is the thermal conductivity, φ is the 

volume fraction of the nanoparticles, ρ is the density, c is the specific heat capacity,


is the viscosity, 

respectively. 

3. Cooling characteristics of water-based carbon nanotubes nanofluids in internal 
combustion engines 

Table 1: Main technical parameters of internal combustion engine 

Item Name Index 

Model CA6DE2-23 

Type inline six-cylinder, four-stroke, water-cooled, direct jet type 

Bore (mm) 106 

Compression ratio 17.5:1 

Piston stroke (mm) 125 

Calibration power (KW) 180 

Calibrated power speed (rmin-1) 2300 

Maximum torque (Nm) 900 

Maximum torque speed (rmin-1)  1400 

 

As shown in Table 1, main technical parameters of internal combustion engine are given in details. SEM 

morphology of water-based carbon nanotube CNT nanofluids with SDBS adding is shown in Figure 2. We can 

find that the visible carbon nanotubes in the nano-fluid dispersion are better and it do not see the reunion of 

CNT particles. 

 

Figure 2: SEM morphology of water-based carbon nanotube CNT nanofluids with SDBS adding 

The temperature probe material of cooling performance is the 45 steels with the size 20mm×40mm. And 

probe thermocouple is chosen as the armoured nickel-chromium - nickel silicon thermocouple, which has the 

wire diameter φ 0.3mm and response time 0. 1s. And the thermocouple is located in the geometric center of 

the probe. In this paper, a vertical resistance furnace is used to heat the cooling temperature probe with the 

temperature control accuracy of± 5 °C. The temperature of the cooling test is placed in a resistance furnace, 

which is heated to 850 °C for 10 min. Then, the temperature probe is quickly quenched into the nano-fluid, 

while the initial temperature of the nano-fluid is 25 °C, and the nano-fluid with different CNT content is 

measured of the cooling characteristics for internal combustion engines. 

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In this paper, the measured temperature of the cooling curve of the probe is shown in Figure 3 (a), while the 

water is treated as a reference liquid of different CNT content of nano-fluid quenching medium, and the initial 

temperature is 25 °C. The differential curve of the temperature probe in the temperature is given in Figure 3 

(a). 

   

Figure 3: (a) Cooling rate of temperature transmitter overall grid CNT content (b) Inline six cylinder cooling 

water flow in each cylinder (c) The percentage of total 

Table 2: Cooling capacity of temperature probe in different CNT content water based CNT nanofluids 

Test temperature Probe cooling temperature 

>800 same 

800-400 0.2wt%CNT >water >0.4wt%CNT >0.8wt%CNT 

400-300 0.2wt%CNT >0.4wt%CNT >water >0.8wt%CNT 

<300 0.2wt%CNT >0.4wt%CNT >water >0.8wt%CNT 

 

As shown in Figure 3 (a), we can find that all curves are almost coincident at all temperatures above 800°C, 

which indicates that the cooling rate of all quenching media including water is substantially the same. When 

the probe temperature drops below 800°C, the cooling rate in the nanofluids begins to change. And in Figure 

3 (b), we give the inline six cylinder transmitter overall grid. And the Cooling capacity of temperature probe in 

different CNT content water based CNT nanofluids is given in Table 2. From Figure 3 (c), the percentage of 
total cooling water flow in each cylinder can be obtained in details. It can be explained that the low content of 

CNT nanofluids in the study range is better than that of CNTs with high content of CNT under the condition of 

natural convection, and the heat dissipation capacity of water is higher than that of high CNT of the nanofluids. 
The cooling rate of water-based carbon nanotubes nanofluids changes with different quenching medium 

temperatures as shown in Figure 6. It can be seen that the cooling rate of nano-fluid at different temperatures 

is basically the same at 630°C, and the cooling rate of nanometer fluid decreases with the increase of 

temperature of nanometer fluid quenching at 630°C. And we find that the cooling performance of nanofluids 

decreases gradually with the increase of nanometer fluid temperature. At different temperatures of quenching 

fluid, the cooling rate of nanometer fluid changes little at high temperature and changes greatly at low 

temperature. 

Nano-fluid quenching fluid canbroaden the scope of application of quenching medium, and it will not produce 

flue gas pollution and avoid the risk of fire without mineral oil, nitrite and other harmful substances, while it can 

ensure the operator and the safety of the equipment. Due to the presence of nanoparticles, the bursting of the 

bubbles is accelerated and the stage of the vapour film is shortened. Thus, the different parts of the work 

piece can enter the boiling stage at the same time and the cooling rate is faster. The main drawbacks of 

water-based carbon nanotubes nanofluids quenching fluids are: the water-based carbon nanotubes quenching 

fluid is still mostly better than the water, while the water is seen as a quenching medium. And the cooling rate 

will be greatly reduced in a high temperature, in addition, the liquid also inherits the shortcoming. The 

concentration of the changes is more sensitive to the requirements of the concentration of quenching fluid; 

And the degree of agitation is very strict, while the work-piece quenching area of the degree of mixing should 

be uniform to ensure the adequate strength, while the uniform mixing is used to ensure that the temperature 

concentration and cooling uniform. Compared with the quenching oil, quenching liquid is easier to produce 

pollution and needs careful maintenance. 

1079



 

Figure 6: Effect of cooling medium temperature on cooling rate of nanometer fluid 

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