**Abstract**

Nanofluids are defined as heat transfer fluids with enhanced heat transfer properties by the addition of nanoparticles. Nanofluid's stability, nanoparticles' type and their chemical compatibility with the base fluid are essential not only to increase the nanofluid's thermophysical properties but also to ensure a longlasting and thermal efficient use of the equipment in which it is used. Some of these aspects are discussed in this chapter. Likewise, the improvement in terms of the heat transfer capacity (thermal resistance) that the use of nanofluids has on the heat pipes-thermosyphons is shown. On the other hand, the improvement in energy efficiency that nanofluid causes in a vapor compression system is also presented.

**Keywords:** nanofluid, heat pipe, vapor compression, battery refrigeration

#### **1. Introduction**

In an increasingly digitized society with a growing trend in the interconnection of things (IoT and AI), the volume of information circulating through the network and to be processed is constantly growing. This information must be processed in high-speed processing and storage servers, which means that the density of heat to be dissipated has increased considerably in recent decades. This heat flux increase, together with technological advances that allow the miniaturization of electronics, forces thermal engineers to seek advanced solutions in heat dissipation. Advances in the field of electronics, and in particular power electronics, have resulted in a significant increase in heat flux density at the component level. Meeting component temperature requirements and ensuring maximum system performance requires more efficient, lower-volume cooling technologies. As a result, thermal management is becoming increasingly important and critical to the electronics industry. The need for thermal management has increased over the past decade and the prediction is that a steeper increase is yet to come in the coming years.

In parallel, other applications have demanded an increasing thermal management capability that were not even considered less than a decade ago. The advent of electric vehicles with the use of Li-Ion batteries has become a new edge for the development of reliable and high-performance thermal management systems. Due to the fact that this type of battery can be charged within minutes and present a high density of energy that can be delivered to the vehicle's systems, overheating became an issue that can potentially cause accidents, which unfortunately have

already been reported in some applications. This type of issue is generally caused by heat concentration in specific areas of the battery resulting in temperature overshooting with consequent potential fire and loss of the device. Such an issue has been reported with more frequency as new vehicles that utilize electric propulsion are gaining interest from different markets, which require proper addressing using reliable thermal management systems. As a potential solution for this issue, temperature homogenization can be applied in order to minimize heat concentration, which also contributes to increasing the battery's lifetime.

On the other hand, conventional vapor compression refrigeration has, in recent years, suffered from the consequences of international environmental legislation relating to fluorinated refrigerants "HFCs". In this regard, Europe has adopted the "F-GAS" regulation, which establishes deadlines for the use of these refrigerants due to their negative impact on the climate. The climate impact of a substance is commonly expressed as the global warming potential (GWP). The lower the GWP, the more climate-friendly the substance. Most of the HFCs have a very high GWP and are hence potent greenhouse gases. Most of the HFCs are used as refrigerants in refrigeration and air conditioning. To mitigate emissions of substances with a high GWP and comply with the F-Gas Regulation, each sector needs to find solutions to quickly switch to low GWP refrigerants. The F-gas regulation is committed to so-called clean refrigerants (hydrocarbons, CO2, HFOs) due to their zero or very low GWP. However, the use of these refrigerants often implies a reduction in the efficiency of the refrigerators as well as an extra effort to redesign them.

Under this scenario, thermal and refrigeration engineers are forced to find solutions, not only in terms of the type of refrigerant (more respectful with the environment) but also in terms of new refrigeration technologies (acoustic, thermocaloric, thermoelectric, nanofluids …) that meet new challenges in heat dissipation and cooling. Nanofluids are envisioned as one of these solutions. Although there is little bibliography at this regard, recent works show the interest of nanofluids as key enabling technology to meet the environmental challenges vapor compression systems must face. For example, Gokulnath G [1] presents an analysis of the effect of different nano-refrigerants on a domestic refrigerator performance. Haque [2] analyzes the behavior of a domestic refrigerator when using a polyolester-based nano-lubricant.

Nanofluids are defined as heat transfer fluids with enhanced heat transfer properties by the addition of nanoparticles. When formulating a nanofluid, a fundamental aspect to consider is its stability, since its thermophysical properties pretty much depend on it. Adding dispersants in the two-phase systems is an easy and economic method to enhance the stability of nanofluids. Although surfactant addition is an effective way to enhance the dispersibility of nanoparticles, surfactants might cause several problems [3]. In this chapter an analysis of the effect of nanoparticles not only on the stability of the nanofluid but also on its thermal conductivity is carried out.

The use of nanofluids is already being seen in different applications - technologies, in this chapter some application cases are shown.

## **2. Nanofluids**

Nanofluids [4] are a type of fluid made up of a base fluid to which naoparticles (<100 nm) are added in order to increase its thermophysical properties.. Nanoparticles manipulation and in turn nanofluid formulation requires high security measures and therefore must be handled in controlled environments, **Figure 1**.

**149**

charge change.

AL2O3 and TiO2).

*Nanofluid as Advanced Cooling Technology. Success Stories*

Metallic nanoparticles are among the most interesting ones due to their high thermal conductivity. This nanoparticles addition makes the nanofluid thermal conductivity increase [5, 6] as well as its viscosity which is a negative effect as far as

Despite the amount of research carried out so far, which shows that the use of nanofluids increase the heat transfer coefficients, there is still much to understand in the area of nanofluids, for example, depending on which cooling technology (LHP, HP) the nanofluid is used in, other forces (capillarity) apart from the viscous and gravitational forces come into play requiring a better fluid–structure interaction understanding [7]. This interaction is given, among others, by the surface tension and the contact angle between the fluid and the porous medium. Since the contact angle is affected by the addition of nanoparticles [8–10] the capillary forces are altered and with them the LHP capillary pumping. From a theoretical point of view, the phenomena that take place at the nanoparticle level (Brownian movement, plasma, …) that make the heat transfer coefficients improve are not clear. In the bibliography there are several theoretical models [11–19] that try to shed light on the matter but their predictions differ from the experimental values [20–22]. This theoretical field requires a greater research effort to be able to give answers to

Nanoparticles not only increase the thermal conductivity of the base fluid but also act as sources of bubble generation in boiling processes, thus increasing the

The addition of nanoparticles to a base fluid, as mentioned above in the section, basically alters its viscosity and its thermal conductivity. These alterations depend pretty much on the nanoparticle size and concentration as shown in the following sections. This influence is reflected in the following analysis carried out for the base fluid polyol-ester when it is doped with different types of nanoparticles (CuO,

Nanoparticles stability [25, 26] in the fluid is key to have a nanofluid that ensures an enhancement of the device thermal performance over time. Different techniques are used for such purpose: surfactant addition, sonication and surface

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

pressure drop is concerned.

*Nanoparticles handling laboratory.*

**Figure 1.**

the real behavior of nanofluids.

boiling coefficients, important in LHPs and HPs [23, 24].

*Nanofluid as Advanced Cooling Technology. Success Stories DOI: http://dx.doi.org/10.5772/intechopen.96247*

**Figure 1.** *Nanoparticles handling laboratory.*

*Heat Transfer - Design, Experimentation and Applications*

which also contributes to increasing the battery's lifetime.

already been reported in some applications. This type of issue is generally caused by heat concentration in specific areas of the battery resulting in temperature overshooting with consequent potential fire and loss of the device. Such an issue has been reported with more frequency as new vehicles that utilize electric propulsion are gaining interest from different markets, which require proper addressing using reliable thermal management systems. As a potential solution for this issue, temperature homogenization can be applied in order to minimize heat concentration,

On the other hand, conventional vapor compression refrigeration has, in recent years, suffered from the consequences of international environmental legislation relating to fluorinated refrigerants "HFCs". In this regard, Europe has adopted the "F-GAS" regulation, which establishes deadlines for the use of these refrigerants due to their negative impact on the climate. The climate impact of a substance is commonly expressed as the global warming potential (GWP). The lower the GWP, the more climate-friendly the substance. Most of the HFCs have a very high GWP and are hence potent greenhouse gases. Most of the HFCs are used as refrigerants in refrigeration and air conditioning. To mitigate emissions of substances with a high GWP and comply with the F-Gas Regulation, each sector needs to find solutions to quickly switch to low GWP refrigerants. The F-gas regulation is committed to so-called clean refrigerants (hydrocarbons, CO2, HFOs) due to their zero or very low GWP. However, the use of these refrigerants often implies a reduction in the

efficiency of the refrigerators as well as an extra effort to redesign them.

Under this scenario, thermal and refrigeration engineers are forced to find solutions, not only in terms of the type of refrigerant (more respectful with the environment) but also in terms of new refrigeration technologies (acoustic, thermocaloric, thermoelectric, nanofluids …) that meet new challenges in heat dissipation and cooling. Nanofluids are envisioned as one of these solutions.

Although there is little bibliography at this regard, recent works show the interest of nanofluids as key enabling technology to meet the environmental challenges vapor compression systems must face. For example, Gokulnath G [1] presents an analysis of the effect of different nano-refrigerants on a domestic refrigerator performance. Haque [2] analyzes the behavior of a domestic refrigerator when using a polyol-

Nanofluids are defined as heat transfer fluids with enhanced heat transfer properties by the addition of nanoparticles. When formulating a nanofluid, a fundamental aspect to consider is its stability, since its thermophysical properties pretty much depend on it. Adding dispersants in the two-phase systems is an easy and economic method to enhance the stability of nanofluids. Although surfactant addition is an effective way to enhance the dispersibility of nanoparticles, surfactants might cause several problems [3]. In this chapter an analysis of the effect of nanoparticles not only on the stability of the nanofluid but also on its thermal conductivity is car-

The use of nanofluids is already being seen in different applications - technologies,

Nanofluids [4] are a type of fluid made up of a base fluid to which naoparticles (<100 nm) are added in order to increase its thermophysical properties.. Nanoparticles manipulation and in turn nanofluid formulation requires high security measures and therefore must be handled in controlled environments, **Figure 1**.

**148**

ried out.

**2. Nanofluids**

ester-based nano-lubricant.

in this chapter some application cases are shown.

Metallic nanoparticles are among the most interesting ones due to their high thermal conductivity. This nanoparticles addition makes the nanofluid thermal conductivity increase [5, 6] as well as its viscosity which is a negative effect as far as pressure drop is concerned.

Despite the amount of research carried out so far, which shows that the use of nanofluids increase the heat transfer coefficients, there is still much to understand in the area of nanofluids, for example, depending on which cooling technology (LHP, HP) the nanofluid is used in, other forces (capillarity) apart from the viscous and gravitational forces come into play requiring a better fluid–structure interaction understanding [7]. This interaction is given, among others, by the surface tension and the contact angle between the fluid and the porous medium. Since the contact angle is affected by the addition of nanoparticles [8–10] the capillary forces are altered and with them the LHP capillary pumping. From a theoretical point of view, the phenomena that take place at the nanoparticle level (Brownian movement, plasma, …) that make the heat transfer coefficients improve are not clear. In the bibliography there are several theoretical models [11–19] that try to shed light on the matter but their predictions differ from the experimental values [20–22]. This theoretical field requires a greater research effort to be able to give answers to the real behavior of nanofluids.

Nanoparticles not only increase the thermal conductivity of the base fluid but also act as sources of bubble generation in boiling processes, thus increasing the boiling coefficients, important in LHPs and HPs [23, 24].

Nanoparticles stability [25, 26] in the fluid is key to have a nanofluid that ensures an enhancement of the device thermal performance over time. Different techniques are used for such purpose: surfactant addition, sonication and surface charge change.

The addition of nanoparticles to a base fluid, as mentioned above in the section, basically alters its viscosity and its thermal conductivity. These alterations depend pretty much on the nanoparticle size and concentration as shown in the following sections. This influence is reflected in the following analysis carried out for the base fluid polyol-ester when it is doped with different types of nanoparticles (CuO, AL2O3 and TiO2).

### **2.1 Nanoparticles size - viscosity**

As mentioned above, nanofluid viscosity [27] is an important property as far as thermal performance and fluid flow are concerned. As shown by the rheological analyzes carried out by different researchers [28, 29]. Among the several works regarding oil based nanofluids, Resiga et al. [30] investigated the rheological properties of highly concentrated transformer oil-based magnetic nanofluids; the results confirmed that the nanofluids were Newtonians in all concentrations except at the highest concentration of 20.8 vol%. Murshed et al. [31] experimentally studied the viscosity of silicone oil (SO) based TiO2 and SiO2 nanofluids confirming the nanofluids' Newtonian nature. Chen and Xie. [32] reached the same conclusion for carbon nanotubes (TCNT)-nanofluids. At low shear rates, Newtonian behavior of silicone oil (Syltherm 800) based diamond-graphene nanofluid was observed by Yang et al. [33]. The same authors [34] investigated the effects of multi-walled carbon nanotubes (MWCNT) loading, surfactant concentration and dispersion energy (ultrasonication) on the thermal conductivity and steady shear viscosity of oil (PAO6)- based-nanofluids. Polyisobutene succinimide (PIBSI) was used as surfactant. The results showed that at low shear conditions the nanofluid viscosity was governed by the PIBSI, observing a 0.1 to 0.07 Pa shear stress decrease. They also analyzed the concentration of CNT versus viscosity, it was observed that the viscosity increased for any concentration other than 3% by weight.

Heris et al. [35] studied the rheological properties of ZnO nanoparticles dispersed in mineral oil (MO) based lubricant as a function of the volume fraction in the range 0.01–0.6% and temperature from 0 to 60 °C. The results showed that the investigated nanolubricants were found to behave as yield stress fluids as mineral oil and the viscosity ratio was increased by the nanoparticle loadings. The effects of the temperature were noticeable at high temperature and concentration.

Kole and Dey [36] dispersed 40 nm diameter CuO nanoparticles at a volume fraction higher than 0.005 in gear oil and concluded that for a 10–50 °C temperature range the nanofluid shear rate was below 30 s − 1. For ultra-low concentration, it was observed a viscosity increase with increasing volume fraction.

Moreover, Saeedinia et al. [37] investigated the viscosity of CuO/oil-based nanofluids with 50 nm nanoparticle for weight fraction ranging from 0.2% to 2%. Newtonian nature was noticed in the shear rate range of 0–15 s − 1 for all the investigated temperatures and concentrations.

When analyzing the Ti2O3 nanoparticles size on the 1 wt%. polyol-ester nanofluid, **Figure 2**, it is observed that viscosity increases with the increase of NP size. This increase becomes steeper for a specific size (180 nm). This result agrees with other researchers' work [38, 39]. Although, it could be expected that viscosity would decrease with increasing NP size [40], this performance depends to a great extent on the NP concentration, which can cause a decrease or an increase in viscosity as the size of the NPs increases [41].

In any refrigeration application, the nanofluid must be pumped to flow through the pipe and this pumping work is greater the higher the viscosity. In terms of efficiency, this work must be as low as possible and consequently the nanofluid viscosity.

#### **2.2 Thermal conductivity**

The enhancement of the thermal conductivity of the base fluid is the primarily objective of the addition of nanoparticles. The literature showed that the thermal conductivity of nanofluids is higher compared to the base fluids; this is confirmed also in the case of oil-based nanofluids. Nonetheless, just a few works were devoted to investigate the thermal conductivity of this kind of nanofluids.

**151**

increased by 49%.

**Figure 2.**

*Nanofluid as Advanced Cooling Technology. Success Stories*

of the more uniform of nanoparticles dispersion.

*Influence of NPs size on viscosity. 1 wt% nanofluid of Ti2O3 NPs in polyol-ester.*

Saeedinia et al. [37] investigated the thermal conductivity of CuO/oil nanofluid. The authors, measured the thermal conductivity at different temperatures ranging between 24 and 70 °C and at two concentrations of 1 wt% and2 wt. %. The results showed a remarkable enhancement in the thermal conductivity of the studied nanofluid with temperature. With increasing the temperature, the agglomeration of nanoparticles is hindered, and thus the thermal conductivity is enhanced because

Wang et al. [42] studied the effects of temperature and solid concentration on the thermal conductivity of oil-based nanofluids containing graphite nanoparticles. The results highlighted that when adding 1.36%vol. of graphite a 36% enhancement in the thermal conductivity was achievable. The authors also found that the thermal conductivity enhancement was not linear with nanoparticle concentration. The temperature showed a weak effect on the thermal conductivity enhancement but

Aberoumand et al. [43] experimentally investigated the thermal conductivity of silver/heat transfer oil nanofluid at different values of concentration and temperatures. The authors found that while the thermal conductivity of the base fluid showed a decreasing trend as the temperature increased that of the nanofluid increased with the temperature. This trend has been found for all the investigated concentrations. The authors stated that this phenomenon can be explained considering the Brownian motion which are enhanced when increasing temperature. Aberoumand et al. [44] experimentally demonstrated that for a nanofluid composed of 1% wt CuO nanoparticles on engine oil, the thermal conductivity

Colangelo et al. [45] The effect of adding a different amount of Oleic Acid surfactant toAl2O3/diathermic oil NF on the thermal conductivity, in different temperatures (30 to 50 °C) and three concentrations of 0.3, 0.7, and 1 vol.%, has been investigated by. Their results showed that adding surfactant does not affect the thermal conductivity of the NF. Moreover, increasing the solid concentration of the surfactant has also no effect on the thermal conductivity enhancement. They reported the maximum enhancement of 4% at the solid concentration of 1 vol. %. **Figure 3** shows the thermal conductivity variation with variation in nanoparticle concentration from 0.1 wt% to 1.1 wt% at ambient temperature. It is apparent from

when increasing temperature, the thermal conductivity also increased.

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

*Nanofluid as Advanced Cooling Technology. Success Stories DOI: http://dx.doi.org/10.5772/intechopen.96247*

*Heat Transfer - Design, Experimentation and Applications*

As mentioned above, nanofluid viscosity [27] is an important property as far as thermal performance and fluid flow are concerned. As shown by the rheological analyzes carried out by different researchers [28, 29]. Among the several works regarding oil based nanofluids, Resiga et al. [30] investigated the rheological properties of highly concentrated transformer oil-based magnetic nanofluids; the results confirmed that the nanofluids were Newtonians in all concentrations except at the highest concentration of 20.8 vol%. Murshed et al. [31] experimentally studied the viscosity of silicone oil (SO) based TiO2 and SiO2 nanofluids confirming the nanofluids' Newtonian nature. Chen and Xie. [32] reached the same conclusion for carbon nanotubes (TCNT)-nanofluids. At low shear rates, Newtonian behavior of silicone oil (Syltherm 800) based diamond-graphene nanofluid was observed by Yang et al. [33]. The same authors [34] investigated the effects of multi-walled carbon nanotubes (MWCNT) loading, surfactant concentration and dispersion energy (ultrasonication) on the thermal conductivity and steady shear viscosity of oil (PAO6)- based-nanofluids. Polyisobutene succinimide (PIBSI) was used as surfactant. The results showed that at low shear conditions the nanofluid viscosity was governed by the PIBSI, observing a 0.1 to 0.07 Pa shear stress decrease. They also analyzed the concentration of CNT versus viscosity, it was observed that the

viscosity increased for any concentration other than 3% by weight.

temperature were noticeable at high temperature and concentration.

it was observed a viscosity increase with increasing volume fraction.

investigated temperatures and concentrations.

ity as the size of the NPs increases [41].

**2.2 Thermal conductivity**

Heris et al. [35] studied the rheological properties of ZnO nanoparticles dispersed in mineral oil (MO) based lubricant as a function of the volume fraction in the range 0.01–0.6% and temperature from 0 to 60 °C. The results showed that the investigated nanolubricants were found to behave as yield stress fluids as mineral oil and the viscosity ratio was increased by the nanoparticle loadings. The effects of the

Kole and Dey [36] dispersed 40 nm diameter CuO nanoparticles at a volume fraction higher than 0.005 in gear oil and concluded that for a 10–50 °C temperature range the nanofluid shear rate was below 30 s − 1. For ultra-low concentration,

Moreover, Saeedinia et al. [37] investigated the viscosity of CuO/oil-based nanofluids with 50 nm nanoparticle for weight fraction ranging from 0.2% to 2%. Newtonian nature was noticed in the shear rate range of 0–15 s − 1 for all the

When analyzing the Ti2O3 nanoparticles size on the 1 wt%. polyol-ester nanofluid, **Figure 2**, it is observed that viscosity increases with the increase of NP size. This increase becomes steeper for a specific size (180 nm). This result agrees with other researchers' work [38, 39]. Although, it could be expected that viscosity would decrease with increasing NP size [40], this performance depends to a great extent on the NP concentration, which can cause a decrease or an increase in viscos-

In any refrigeration application, the nanofluid must be pumped to flow through the pipe and this pumping work is greater the higher the viscosity. In terms of efficiency, this work must be as low as possible and consequently the nanofluid viscosity.

The enhancement of the thermal conductivity of the base fluid is the primarily objective of the addition of nanoparticles. The literature showed that the thermal conductivity of nanofluids is higher compared to the base fluids; this is confirmed also in the case of oil-based nanofluids. Nonetheless, just a few works were devoted

to investigate the thermal conductivity of this kind of nanofluids.

**2.1 Nanoparticles size - viscosity**

**150**

**Figure 2.** *Influence of NPs size on viscosity. 1 wt% nanofluid of Ti2O3 NPs in polyol-ester.*

Saeedinia et al. [37] investigated the thermal conductivity of CuO/oil nanofluid. The authors, measured the thermal conductivity at different temperatures ranging between 24 and 70 °C and at two concentrations of 1 wt% and2 wt. %. The results showed a remarkable enhancement in the thermal conductivity of the studied nanofluid with temperature. With increasing the temperature, the agglomeration of nanoparticles is hindered, and thus the thermal conductivity is enhanced because of the more uniform of nanoparticles dispersion.

Wang et al. [42] studied the effects of temperature and solid concentration on the thermal conductivity of oil-based nanofluids containing graphite nanoparticles. The results highlighted that when adding 1.36%vol. of graphite a 36% enhancement in the thermal conductivity was achievable. The authors also found that the thermal conductivity enhancement was not linear with nanoparticle concentration. The temperature showed a weak effect on the thermal conductivity enhancement but when increasing temperature, the thermal conductivity also increased.

Aberoumand et al. [43] experimentally investigated the thermal conductivity of silver/heat transfer oil nanofluid at different values of concentration and temperatures. The authors found that while the thermal conductivity of the base fluid showed a decreasing trend as the temperature increased that of the nanofluid increased with the temperature. This trend has been found for all the investigated concentrations. The authors stated that this phenomenon can be explained considering the Brownian motion which are enhanced when increasing temperature. Aberoumand et al. [44] experimentally demonstrated that for a nanofluid composed of 1% wt CuO nanoparticles on engine oil, the thermal conductivity increased by 49%.

Colangelo et al. [45] The effect of adding a different amount of Oleic Acid surfactant toAl2O3/diathermic oil NF on the thermal conductivity, in different temperatures (30 to 50 °C) and three concentrations of 0.3, 0.7, and 1 vol.%, has been investigated by. Their results showed that adding surfactant does not affect the thermal conductivity of the NF. Moreover, increasing the solid concentration of the surfactant has also no effect on the thermal conductivity enhancement. They reported the maximum enhancement of 4% at the solid concentration of 1 vol. %.

**Figure 3** shows the thermal conductivity variation with variation in nanoparticle concentration from 0.1 wt% to 1.1 wt% at ambient temperature. It is apparent from

#### **Figure 3.**

*Influence of NPs concentration on thermal conductivity for different NPs (CuO, Ti2O3 and Al2O3) and concentrations. Polyol-ester as base fluid.*

**Figure 3** that thermal conductivity increases with increasing the NPs concentration [46]. However, in the cases of Al2O3 and TiO2, the thermal conductivity increase is less the higher the concentration. The "CuO" nanofluid exhibits a linearly increasing behavior with concentration.

The effect of the type of nanoparticle is clearly observed in **Figure 3**. Al2O3 nanoparticles provide the largest thermal conductivity increase compared to the other two.

#### **3. Application cases**

#### **3.1 Passive cooling devices**

Nanofluids can be potentially applied as working fluids in active (mechanically driven) and passive (capillary action, slug/plug dynamics) systems. Thermal management devices employing either concepts can benefit from the advantages of using nanofluids in order to enhance their heat transport capabilities.

Liquid cooling systems use a pump to drive the liquid to the heat source (or sources) in contact with a dedicated heat exchanger (or multiple heat exchangers). Heat is then absorbed by the working fluid and transported by the lines to a condenser (one or multiple), where the heat is rejected to a medium (environmental air, liquid reservoir, etc) with low temperature. Since the liquid cooling system is a closed circuit, the working fluid operates in a cycle absorbing and rejecting heat. As a necessity from its design, liquid cooling systems require a reservoir used to self-control the working fluid being used by the system, which will be determined by the flow rate at which it is operating. **Figure 4a** presents an schematics of a liquid cooling system.

As a promising technology for complex thermal management systems, Pulsating Heat Pipe (PHPs), also known as Oscillating Heat Pipes (OHPs) can potentially use nanofluids as their working fluids, due to the fact that they do not present a wick structure that could compromise their overall thermal performance. Their simple construction based on a meandering tube bent in several parallel curves operate by means of liquid slugs and vapor plugs motion [46], transporting the heat absorbed

**153**

evaporator [52, 53].

*Nanofluid as Advanced Cooling Technology. Success Stories*

from a source and rejecting it in a sink. This kind of device can be considered a special type of heat pipe and was introduced by Akachi [47]. There are several applications in thermal control systems that PHPs can be utilized, from structures to electronics cooling, as well as thermal management of sensitive equipment such as those related to aerospace and surveillance. Given the potential use of PHPs as an effective thermal control device, investigations have been carried out towards the improvement of their overall efficiency, which leads to the search of alternative and more effective working fluids. In this case, the addition of solid nanoparticles in the working fluid has shown important improvements in its thermal conductivity that

*(a) schematic, and (b) CAD representation of the thermal control system arrangement.*

Another thermal control device that can benefit from the improvements given by nanofluids is called Loop Heat Pipe (LHP). Given its architecture, LHPs are high efficient thermal control devices that can transport heat over long distances. It is built with a capillary evaporator responsible for generating capillary pressure that drives the working fluid throughout the loop. It is directly connected to a heat source where it absorbs the heat transferring it to the working fluid causing its evaporation. Due to the presence of a fine pore structure (wick), it generated capillary pressure that pushed the vapor towards the condenser, where it condenses back to liquid phase. By the capillary pressure action, liquid is sent back to the evaporator to complete the cycle. A compensation chamber (or reservoir) present at the capillary evaporator's inlet, which is hydraulically connected to the evaporator's core, will supply or drain the working fluid depending on the heat loads that are applied [49]. Depending of the level of accuracy needed to control the heat source, the LHP can present a pressure control regulator that sets the device's operation temperature with great precision [50, 51]. The potential in applying nanofluids in LHPs has been presented, showing a considerable enhancement in their performance. However, since the pressure drop increases with the use of nanofluids, the overall performance can be compromised due to limitations in the capillary pressure generation by the

Due to the potential in using nanofluids in thermal control devices, PHPs have been designed and integrated in a hybrid thermal management system installed in a surveillance system. This hybrid thermal management system was composed of a liquid cooling loop that connected several heat sources by heat exchangers, where PCBs were directly attached, in order to keep their electronic components within the required levels of temperature. A magnetic pump with variable flow rate was

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

can potentially benefit PHPs [48].

**Figure 4.**

*Nanofluid as Advanced Cooling Technology. Success Stories DOI: http://dx.doi.org/10.5772/intechopen.96247*

*Heat Transfer - Design, Experimentation and Applications*

ing behavior with concentration.

*concentrations. Polyol-ester as base fluid.*

other two.

**Figure 3.**

**3. Application cases**

**3.1 Passive cooling devices**

**Figure 3** that thermal conductivity increases with increasing the NPs concentration [46]. However, in the cases of Al2O3 and TiO2, the thermal conductivity increase is less the higher the concentration. The "CuO" nanofluid exhibits a linearly increas-

*Influence of NPs concentration on thermal conductivity for different NPs (CuO, Ti2O3 and Al2O3) and*

The effect of the type of nanoparticle is clearly observed in **Figure 3**. Al2O3 nanoparticles provide the largest thermal conductivity increase compared to the

Nanofluids can be potentially applied as working fluids in active (mechanically driven) and passive (capillary action, slug/plug dynamics) systems. Thermal management devices employing either concepts can benefit from the advantages of

Liquid cooling systems use a pump to drive the liquid to the heat source (or sources) in contact with a dedicated heat exchanger (or multiple heat exchangers). Heat is then absorbed by the working fluid and transported by the lines to a condenser (one or multiple), where the heat is rejected to a medium (environmental air, liquid reservoir, etc) with low temperature. Since the liquid cooling system is a closed circuit, the working fluid operates in a cycle absorbing and rejecting heat. As a necessity from its design, liquid cooling systems require a reservoir used to self-control the working fluid being used by the system, which will be determined by the flow rate at which it is operating. **Figure 4a** presents an schematics of a liquid

As a promising technology for complex thermal management systems, Pulsating Heat Pipe (PHPs), also known as Oscillating Heat Pipes (OHPs) can potentially use nanofluids as their working fluids, due to the fact that they do not present a wick structure that could compromise their overall thermal performance. Their simple construction based on a meandering tube bent in several parallel curves operate by means of liquid slugs and vapor plugs motion [46], transporting the heat absorbed

using nanofluids in order to enhance their heat transport capabilities.

**152**

cooling system.

**Figure 4.** *(a) schematic, and (b) CAD representation of the thermal control system arrangement.*

from a source and rejecting it in a sink. This kind of device can be considered a special type of heat pipe and was introduced by Akachi [47]. There are several applications in thermal control systems that PHPs can be utilized, from structures to electronics cooling, as well as thermal management of sensitive equipment such as those related to aerospace and surveillance. Given the potential use of PHPs as an effective thermal control device, investigations have been carried out towards the improvement of their overall efficiency, which leads to the search of alternative and more effective working fluids. In this case, the addition of solid nanoparticles in the working fluid has shown important improvements in its thermal conductivity that can potentially benefit PHPs [48].

Another thermal control device that can benefit from the improvements given by nanofluids is called Loop Heat Pipe (LHP). Given its architecture, LHPs are high efficient thermal control devices that can transport heat over long distances. It is built with a capillary evaporator responsible for generating capillary pressure that drives the working fluid throughout the loop. It is directly connected to a heat source where it absorbs the heat transferring it to the working fluid causing its evaporation. Due to the presence of a fine pore structure (wick), it generated capillary pressure that pushed the vapor towards the condenser, where it condenses back to liquid phase. By the capillary pressure action, liquid is sent back to the evaporator to complete the cycle. A compensation chamber (or reservoir) present at the capillary evaporator's inlet, which is hydraulically connected to the evaporator's core, will supply or drain the working fluid depending on the heat loads that are applied [49]. Depending of the level of accuracy needed to control the heat source, the LHP can present a pressure control regulator that sets the device's operation temperature with great precision [50, 51]. The potential in applying nanofluids in LHPs has been presented, showing a considerable enhancement in their performance. However, since the pressure drop increases with the use of nanofluids, the overall performance can be compromised due to limitations in the capillary pressure generation by the evaporator [52, 53].

Due to the potential in using nanofluids in thermal control devices, PHPs have been designed and integrated in a hybrid thermal management system installed in a surveillance system. This hybrid thermal management system was composed of a liquid cooling loop that connected several heat sources by heat exchangers, where PCBs were directly attached, in order to keep their electronic components within the required levels of temperature. A magnetic pump with variable flow rate was

responsible for driving the working fluid throughout the loop, in order to guarantee that the heat generated would be properly absorbed and rejected. However, some PCBs were located far from the heat exchangers, which required the use of PHPs to connect the PCBs to them in order to transport the heat generated by the electronics to be properly rejected in a heat sink, while keeping their temperature according to the project's requirements. Due to the complexity of the system, along with the presence of hundreds of PCBs, several PHPs were designed, built and integrated to their dedicated heat sink, which were connected to the liquid cooling system. All the heat generated by the PCBs was transported to a condenser, responsible for dissipating it to the environmental air. According to the project's requirements, the hybrid system had to operate between +5 and + 50 °C of ambient temperature for a maximum humidity level of 95%. The schematics of such arrangement is presented by **Figure 4a** and **b** presents the hybrid setup where the pulsating heat pipe and the heat sink are connected [54].

The nanofluid selected for this application was composed of de-ionized water as the base fluid and CuO nanoparticles, since this combination presents a stable chemical compatibility. The solid nanoparticles presented an average diameter of 29 nm with 98% of purity. The nanoparticles concentration varied from 3.5 wt% to 20 wt%, which were used to compare their effects on the system's thermal performance while operating in real conditions.

As mentioned before, several PHPs were designed, built and integrated in this surveillance system, which showed to be a very complex thermal management problem to be solved. The PHPs had different configurations regarding their total effective length, number of turns, etc. all due to the fact that they were operating under different heat loads. The different designs for the PHPs are shown in **Figure 5** with the representation of their integration with their respective PCB [54]. The PHPs were charged with a nanofluid formed with de-ionized water (base fluid) and CuO (nanoparticles), with the same characteristics as the ones applied to the liquid cooling system. The nanoparticles concentration ranged from 2.0 wt% to 3.5 wt%. Due to the PHPs requirements towards the temperature homogenization of all their related PCBs, the heat dissipation capabilities of the entire thermal management system could be optimized.

Due to the thermal management characteristics at which a given device must operate, such as those found in heavy duty processing demands of computer clusters, as well as some electronics found in avionics, etc., a specific design is required. For high heat densities, PHPs are not indicated as thermal control devices due to their limitation in transporting the heat, which can generate concentrated heat loads and an eventual device's failure. In this case, LHPs are the most indicated to be applied as they can efficiently remove the heat from concentrated areas, being known to operate in applications where the heat flux in the heat source can be as

**Figure 5.**

*PHPs with nanofluids applied to the thermal control of PCBs. (a) low, (b) medium, (c) high thermal load configuration.*

**155**

**Figure 6.**

*Loop heat pipes applied to computer clusters thermal control.*

*Nanofluid as Advanced Cooling Technology. Success Stories*

, or even above that. There are different architecture configura-

tions for LHPs destined to the thermal control of high heat density electronics, being able to operate with a regular working fluid or with a nanofluid, such as

order to not compromise its performance and cause a system's failure.

Nanofluids have been reported to increase by up to 20% the heat transport capability in LHPs, even though they were facing higher pressure drops as nanofluids present a higher viscosity when compared to the base fluid's only. In this case, a better assessment regarding the LHP's thermal characteristics must be well balanced in

A subject that is commonly neglected by some researchers and manufacturers is related to the degree of chemical compatibility between the base fluid, the solid nanoparticles and the material used to build a PHP and a LHP, since they operate with their working fluid at saturation conditions. This is a key factor to ensure instant operation of those devices as soon as heat is administrated to their evaporator, being promptly absorbed by latent heat. If chemical incompatibility is found between the working fluid, solid nanoparticles and other materials used to build the device, the working fluid will begin its degradation resulting in the generation of non-condensable gases (NCGs). The velocity at which the degradation will occur will depend on the materials and working fluid involved, as well as with the operational temperature. Incompatible materials and fluids, such as water and aluminum, ammonia and copper, etc., will present a degradation much faster than known compatible materials and fluids, such as water and copper, ammonia and

The NCGs generated during the base fluid's degradation will be accumulated at the coldest part of the PHP/LHP (condenser), being accumulated there during the device's operation. Since more NCG will be accumulated, the device will lose its condensation capability, compromising the heat rejection by the system that will end up causing an increase in the evaporator's temperature and, finally, the device's failure due to a dryout caused by the lack of liquid returning to the

A process that has been often neglected by many professionals working with PHPs/LHPs and heat pipes, as well as with nanofluids, is called *aging*. This process forces the system to generate as much NCG as possible under controlled conditions that will eventually guarantee that the device will operate for a long time without

As part of the manufacturing processes of any device like PHPs, LHPs and heat pipes, the aging process will be executed after the vacuum/charging procedure applied to those devices. The vacuum/charging procedure is of great importance and must be carefully controlled in order to ensure that the device will properly operate under the designed requirements. In this case, the device must reach a vacuum level that is adequate for its operation, which is also applied as a final cleaning process and moisture removal to any device. Prior to transferring the working fluid to the device, it needs to go through a process called *outgassing* that

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

much as 100 W/cm2

aluminum.

evaporator.

the effect of NCGs [55].

shown by **Figure 6** [52–54].

*Heat Transfer - Design, Experimentation and Applications*

heat sink are connected [54].

system could be optimized.

mance while operating in real conditions.

responsible for driving the working fluid throughout the loop, in order to guarantee that the heat generated would be properly absorbed and rejected. However, some PCBs were located far from the heat exchangers, which required the use of PHPs to connect the PCBs to them in order to transport the heat generated by the electronics to be properly rejected in a heat sink, while keeping their temperature according to the project's requirements. Due to the complexity of the system, along with the presence of hundreds of PCBs, several PHPs were designed, built and integrated to their dedicated heat sink, which were connected to the liquid cooling system. All the heat generated by the PCBs was transported to a condenser, responsible for dissipating it to the environmental air. According to the project's requirements, the hybrid system had to operate between +5 and + 50 °C of ambient temperature for a maximum humidity level of 95%. The schematics of such arrangement is presented by **Figure 4a** and **b** presents the hybrid setup where the pulsating heat pipe and the

The nanofluid selected for this application was composed of de-ionized water as the base fluid and CuO nanoparticles, since this combination presents a stable chemical compatibility. The solid nanoparticles presented an average diameter of 29 nm with 98% of purity. The nanoparticles concentration varied from 3.5 wt% to 20 wt%, which were used to compare their effects on the system's thermal perfor-

As mentioned before, several PHPs were designed, built and integrated in this surveillance system, which showed to be a very complex thermal management problem to be solved. The PHPs had different configurations regarding their total effective length, number of turns, etc. all due to the fact that they were operating under different heat loads. The different designs for the PHPs are shown in **Figure 5** with the representation of their integration with their respective PCB [54]. The PHPs were charged with a nanofluid formed with de-ionized water (base fluid) and CuO (nanoparticles), with the same characteristics as the ones applied to the liquid cooling system. The nanoparticles concentration ranged from 2.0 wt% to 3.5 wt%. Due to the PHPs requirements towards the temperature homogenization of all their related PCBs, the heat dissipation capabilities of the entire thermal management

Due to the thermal management characteristics at which a given device must operate, such as those found in heavy duty processing demands of computer clusters, as well as some electronics found in avionics, etc., a specific design is required. For high heat densities, PHPs are not indicated as thermal control devices due to their limitation in transporting the heat, which can generate concentrated heat loads and an eventual device's failure. In this case, LHPs are the most indicated to be applied as they can efficiently remove the heat from concentrated areas, being known to operate in applications where the heat flux in the heat source can be as

*PHPs with nanofluids applied to the thermal control of PCBs. (a) low, (b) medium, (c) high thermal load*

**154**

**Figure 5.**

*configuration.*

much as 100 W/cm2 , or even above that. There are different architecture configurations for LHPs destined to the thermal control of high heat density electronics, being able to operate with a regular working fluid or with a nanofluid, such as shown by **Figure 6** [52–54].

Nanofluids have been reported to increase by up to 20% the heat transport capability in LHPs, even though they were facing higher pressure drops as nanofluids present a higher viscosity when compared to the base fluid's only. In this case, a better assessment regarding the LHP's thermal characteristics must be well balanced in order to not compromise its performance and cause a system's failure.

A subject that is commonly neglected by some researchers and manufacturers is related to the degree of chemical compatibility between the base fluid, the solid nanoparticles and the material used to build a PHP and a LHP, since they operate with their working fluid at saturation conditions. This is a key factor to ensure instant operation of those devices as soon as heat is administrated to their evaporator, being promptly absorbed by latent heat. If chemical incompatibility is found between the working fluid, solid nanoparticles and other materials used to build the device, the working fluid will begin its degradation resulting in the generation of non-condensable gases (NCGs). The velocity at which the degradation will occur will depend on the materials and working fluid involved, as well as with the operational temperature. Incompatible materials and fluids, such as water and aluminum, ammonia and copper, etc., will present a degradation much faster than known compatible materials and fluids, such as water and copper, ammonia and aluminum.

The NCGs generated during the base fluid's degradation will be accumulated at the coldest part of the PHP/LHP (condenser), being accumulated there during the device's operation. Since more NCG will be accumulated, the device will lose its condensation capability, compromising the heat rejection by the system that will end up causing an increase in the evaporator's temperature and, finally, the device's failure due to a dryout caused by the lack of liquid returning to the evaporator.

A process that has been often neglected by many professionals working with PHPs/LHPs and heat pipes, as well as with nanofluids, is called *aging*. This process forces the system to generate as much NCG as possible under controlled conditions that will eventually guarantee that the device will operate for a long time without the effect of NCGs [55].

As part of the manufacturing processes of any device like PHPs, LHPs and heat pipes, the aging process will be executed after the vacuum/charging procedure applied to those devices. The vacuum/charging procedure is of great importance and must be carefully controlled in order to ensure that the device will properly operate under the designed requirements. In this case, the device must reach a vacuum level that is adequate for its operation, which is also applied as a final cleaning process and moisture removal to any device. Prior to transferring the working fluid to the device, it needs to go through a process called *outgassing* that

**Figure 6.** *Loop heat pipes applied to computer clusters thermal control.*

will bring the working fluid to its saturation condition at the local temperature. Along with this, the *outgassing* will eliminate any dissolved gases present in the working fluid that will certainly contribute to the NCG generation and compromise the device's performance. This is not a complex process to be executed and can be done as presented by **Figure 7**. The technician needs to pay attention to the valves sequence to ensure that the device will be properly evacuated at the required vacuum level, as well as the adequate outgassing of working fluid prior to transfer it to the device. In order to perform the vacuum in the device, valves V1 and V3 must be open, keeping V2 closed. Upon reaching the required vacuum level and no leaks have been detected, the working fluid is outgassed by opening V1 and V2 keeping V3 closed. Once the outgassing has been completed, the technician can transfer the working fluid to the device by closing V1 while opening V2 and V3, ensuring that the required inventory of working fluid is properly transferred to the device [55].

When using low pressure working fluids, such as water, methanol, and acetone, it is possible to watch the entire outgassing process when using a clear glass bottle. During this process, all dissolved gases that will be removed from the working fluid will present a "boiling" pattern, indicating that the vacuum pump is bringing the internal volume to the working fluid's saturation condition. **Figure 8** presents the outgassing process being executed for deionized water. In the case of a nanofluid, due to the addition of solid nanoparticles, the resulting working fluid can result in a dark substance that can present some difficulties to see the outgassing occurring. A trained technician can overcome this issue and perform the outgassing as needed, as shown by **Figure 9** for the case of CuO-deionized water nanofluid (concentration of 2 wt%).

The outgassing process will be over once the bubbles stop appearing in the working fluid. This is the time when the working fluid can be transferred to the device. Nanofluids present a faster outgassing process due to the presence of solid nanoparticles. The working fluid volume that needs to be transferred to the device will determine the time required for the outgassing process, as well as the vacuum pump's speed.

**157**

*Nanofluid as Advanced Cooling Technology. Success Stories*

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

**3.2 Active cooling -vapor compression**

*released; (c) intense release of dissolved gases.*

pressor lubrication improvement [59, 60].

and whose characteristics are listed in **Table 1**.

the refrigerator, as shown in **Figure 11**.

pared to liquid cooling.

**Figure 8.**

**Figure 9.**

*(c) intense release of dissolved gases.*

are shown in **Table 2**.

Another potential application for nanofluids is vapor compression refrigeration "VCS". In these systems, the working fluid is circulated actively through a compressor. The compressor generates the pressure difference necessary for the refrigerant to circulate. During its journey, the refrigerant undergoes a cyclical phase change, condensation-evaporation, which gives it a greater heat transport capacity com-

*Outgassing process for the CuO- water nanofluid: (a) beginning of the process; (b) dissolved gases being*

*Outgassing process for the de-ionized water: (a) beginning of the process; (b) dissolved gases being released;*

The coefficient of performance "COP" of the VCS systems can be improved in two ways: firstly, by increasing heat abstraction rate in evaporator, and secondly, by reducing the work done in a compressor The use of nanoparticles to increase the COP of vapor compression systems is something that has already been confirmed, as evidenced by the research works on the matter [54, 55]. Some works are more focused on the increase of heat transfer rates [56–58] while others are on the com-

The present work aims to provide more scientific information about nano-lubricants and how they influence the COP of a vapor compression system. The refrigeration system used for determining the COP values was built in-house, **Figure 10**

The Polyol ester lubricant is doped at 1.5% by weight with two types of nanoparticles (Cu and CuO). Both the clean lubricant and the two formulated nano-lubricants are tested on the bench in order to record the corresponding COP. The results

The level of lubricant in the refrigerant circuit also has its effect on the COP of

**Figure 7.**

*Charging process of a heat pipe operating at saturation conditions.*

#### **Figure 8.**

*Heat Transfer - Design, Experimentation and Applications*

will bring the working fluid to its saturation condition at the local temperature. Along with this, the *outgassing* will eliminate any dissolved gases present in the working fluid that will certainly contribute to the NCG generation and compromise the device's performance. This is not a complex process to be executed and can be done as presented by **Figure 7**. The technician needs to pay attention to the valves sequence to ensure that the device will be properly evacuated at the required vacuum level, as well as the adequate outgassing of working fluid prior to transfer it to the device. In order to perform the vacuum in the device, valves V1 and V3 must be open, keeping V2 closed. Upon reaching the required vacuum level and no leaks have been detected, the working fluid is outgassed by opening V1 and V2 keeping V3 closed. Once the outgassing has been completed, the technician can transfer the working fluid to the device by closing V1 while opening V2 and V3, ensuring that the required inventory of working fluid is properly transferred to the

When using low pressure working fluids, such as water, methanol, and acetone, it is possible to watch the entire outgassing process when using a clear glass bottle. During this process, all dissolved gases that will be removed from the working fluid will present a "boiling" pattern, indicating that the vacuum pump is bringing the internal volume to the working fluid's saturation condition. **Figure 8** presents the outgassing process being executed for deionized water. In the case of a nanofluid, due to the addition of solid nanoparticles, the resulting working fluid can result in a dark substance that can present some difficulties to see the outgassing occurring. A trained technician can overcome this issue and perform the outgassing as needed, as shown by **Figure 9** for the case of CuO-deionized water nanofluid (concentration

The outgassing process will be over once the bubbles stop appearing in the working fluid. This is the time when the working fluid can be transferred to the device. Nanofluids present a faster outgassing process due to the presence of solid nanoparticles. The working fluid volume that needs to be transferred to the device will determine the time required for the outgassing process, as well as the vacuum

**156**

**Figure 7.**

*Charging process of a heat pipe operating at saturation conditions.*

device [55].

of 2 wt%).

pump's speed.

*Outgassing process for the de-ionized water: (a) beginning of the process; (b) dissolved gases being released; (c) intense release of dissolved gases.*

**Figure 9.**

*Outgassing process for the CuO- water nanofluid: (a) beginning of the process; (b) dissolved gases being released; (c) intense release of dissolved gases.*

#### **3.2 Active cooling -vapor compression**

Another potential application for nanofluids is vapor compression refrigeration "VCS". In these systems, the working fluid is circulated actively through a compressor. The compressor generates the pressure difference necessary for the refrigerant to circulate. During its journey, the refrigerant undergoes a cyclical phase change, condensation-evaporation, which gives it a greater heat transport capacity compared to liquid cooling.

The coefficient of performance "COP" of the VCS systems can be improved in two ways: firstly, by increasing heat abstraction rate in evaporator, and secondly, by reducing the work done in a compressor The use of nanoparticles to increase the COP of vapor compression systems is something that has already been confirmed, as evidenced by the research works on the matter [54, 55]. Some works are more focused on the increase of heat transfer rates [56–58] while others are on the compressor lubrication improvement [59, 60].

The present work aims to provide more scientific information about nano-lubricants and how they influence the COP of a vapor compression system. The refrigeration system used for determining the COP values was built in-house, **Figure 10** and whose characteristics are listed in **Table 1**.

The Polyol ester lubricant is doped at 1.5% by weight with two types of nanoparticles (Cu and CuO). Both the clean lubricant and the two formulated nano-lubricants are tested on the bench in order to record the corresponding COP. The results are shown in **Table 2**.

The level of lubricant in the refrigerant circuit also has its effect on the COP of the refrigerator, as shown in **Figure 11**.

## **Figure 10.**

*VC system to test nano-lubricant effects on COP.*

#### **Table 1.**

*Components' technical characteristics.*

#### **Table 2.**

*COP improvement.*

**159**

**Author details**

and Juncal Estella1

\*, Roger R. Riehl2

4 UPV-University of Basque Country, Bilbao, Spain

\*Address all correspondence to<EMAIL_ADDRESS>
provided the original work is properly cited.

, Simone Mancin3

1 NAITEC-Research Center for Automotive and Mechatronics, Pamplona, Spain

2 National Institute for Space Research – INPE/DMC, São José dos Campos, Brazil

3 Department of Management and Engineering University of Padova, Padova, Italy

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Jesús Mª Blanco4

, Maite Aresti1

Jesús Esarte1

*Nanofluid as Advanced Cooling Technology. Success Stories*

cooling management in the immediate future.

• In view of what is stated in this chapter, it can be concluded that: nanofluids is a promising science to improve the heat transfer capacity of different

• Nanofluid stability continues to be a challenge and therefore an open door to

• A greater understanding of the causes that make the thermophysical properties of nanofluid improve is still necessary, more theoretical research is required

• The large amount of experimental research work carried out to date positions nanofluids as a key enabling technology for the advancement of thermal and

• It is applicable to different sectors with minimal investment cost

*DOI: http://dx.doi.org/10.5772/intechopen.96247*

**4. Conclusion**

technologies

research

**Figure 11.** *Effect of the 1.5%Cu nano-lubricant on the VCS's COP.*


*<IP_ADDRESS> Multi-piping systems*

#### *A. Three-pipe systems*

**Disadvantages of fan coil unit**s

*Low-temperature Technologies*

optional air ventilation duct systems.

*2.2.2 Types of all water systems*

*<IP_ADDRESS> Single piping systems*

the return water.

**Figure 15.**

**14**

coil units, into two types [1–5], namely:

*A. Single piping system (reversed return)*

*B. Single piping system (direct return)*

return water from each fan coil unit.

1.Do not provide good control of room air humidity.

2.Require maintenance within the air-conditioned places.

3.Provide suitable medium for bacteria grow in water pipes.

4.The ventilation of the rooms is affected by the speed of wind and rain and insect leakage through the wall openings and cracks which are associated with

The all water systems are classified based on water pipe connections to the fan

In this system, there are two pipes, one pipe to feed either the cold or hot water to the fan coil unit and another pipe for returning the water back to the chiller or boiler (see **Figure 15**). In these systems the supplied water is in counterflow with

In this system, there are two pipes, one pipe to feed either the cold or hot water to the fan coil unit and another pipe for returning the water back to the chiller or boiler (see **Figure 16**). In these systems the supplied water is flowing in a pipe which is connected directly to the chiller or boiler, where the same pipes receive the

*A schematic diagram of a fan coil unit, two-pipe system of reversed return. Redrawn from [2].*

In these systems, there are two pipes for providing hot and cold water to the fan coil unit and one pipe for return water (three-pipe system). **Figure 17** shows a three-pipe all-water-type system.

#### *B. Four-pipe systems*

In these systems, there are two pipes for providing hot and cold water to the fan coil unit and two pipes for return, one for cold water return and one for hot water return (four-pipe system). These systems are considered as the best system as the use of two return pipes can maintain efficient energy performance. **Figure 18** shows a four-pipe all-water-type system.

### **2.3 Air-water systems**

In these systems both air and water produce heating and cooling effects. Usually induction or fan coil units can be used in air-water systems. The following section will describe the induction unit systems and fan coil system [1–5].

*A schematic diagram of a fan coil unit of four-pipe system. Redrawn with modification from [2].*

generally used in multiroom buildings such as hotels, hospitals, and apartments

Advantages of these systems over induction units are the quite operation and the means to control required condition as fan speed can be usually controlled. But the initial cost of fan coil unit which is higher than induction units makes the induction units more preferred. **Figure 20** shows a schematic diagram of a fan coil unit with

This chapter reviews the types of central air conditioning systems. Specifically, the types and applications of all-air, all-water, and air-water systems are provided. In addition, this chapter gives further insight to all systems through several developed schematic diagrams as various components and working principles of these diagrams and systems can be identified and figured out, respectively. Moreover, the differences

among the given systems can be easily distinguished through this chapter.

where the operating mode can be switched to work in cold season.

*A schematic diagram of a fan coil unit system. Readapted with modification from [5].*

*Central Air Conditioning: Systems and Applications DOI: http://dx.doi.org/10.5772/intechopen.89455*

its components [1–5].

**3. Conclusion**

**17**

**Figure 20.**

#### **Figure 19.**

*A schematic diagram of an induction unit system. Readapted from [5].*

#### *2.3.1 Induction unit system*

Induction unit systems in air-water central air condition are used in building of multi-surrounding rooms such as offices, hotels, hospital patient rooms, as well as apartments. These systems are used where higher thermal loads are present. In addition, these systems are suitable where some rooms require cooling, while the next other rooms require heating. Besides that, these systems are suitable for buildings such as skyscrapers where the spaces are limited. **Figure 19** shows a schematic view of induction unit system which uses primary air and external air. Return air can be used if all primary air is greater than the minimum ventilation requirements [1–5].

#### *2.3.2 Primary air fan coil systems*

The working principle of primary air fan coil systems is very similar to the induction unit system. The main difference is the use of fan. These systems are *Central Air Conditioning: Systems and Applications DOI: http://dx.doi.org/10.5772/intechopen.89455*

generally used in multiroom buildings such as hotels, hospitals, and apartments where the operating mode can be switched to work in cold season.

Advantages of these systems over induction units are the quite operation and the means to control required condition as fan speed can be usually controlled. But the initial cost of fan coil unit which is higher than induction units makes the induction units more preferred. **Figure 20** shows a schematic diagram of a fan coil unit with its components [1–5].


**6. Conclusion**

A new algorithm for the detection and delineation of surface water bodies based on high spatial resolution airborne VNIR imaging spectroscopy data has been developed. In contrast to existing methods the proposed approach does not require *a priori* knowledge nor user input, manual thresholding or fine-tuning of input parameters and is able to automatically detect and delineate surface water bodies with a very high accuracy. Thus, the developed algorithm is suitable for implementation in automated processing chains. The algorithm was tested on different sensor data (AISA Eagle and HyMap), works for different types of landscapes (tested: urban, rural and coastal) and is not influenced by different atmospheric correction methods (tested: ATCOR-4 (Richter, 2011), MIP (Heege & Fischer, 2004), ACUM-R (unpublished in-house development by K. Segl), the method of L. Guanter et al. (Guanter *et al.*, 2009), and empirical line correction). Future issues will be to improve the detection of small and narrow water bodies, the detection of white water and of water under shadow. Furthermore, the proposed method will be tested on hyperspectral VNIR satellite data.


**1. Introduction**

Urbanisation is a growing concern in the present world. With over 55% of the world's population living in urban areas [1], urban expansion has dramatically influenced the change in urban land use. Land use change due to urbanisation results in more impervious surfaces that have considerable impacts on urban hydrology [2]. Urban expansion leads to large impervious surfaces that reduces rainwater infiltration, generating high surface runoff and peak flow, thus increasing the risks of urban flooding and waterlogging [3]. Urban development is one of the major causes of urban pluvial flooding, aggravated by poor urban drainage systems that become more severe with increasing frequency and

**Citation:** Shrestha, S.; Cui, S.; Xu, L.; Wang, L.; Manandhar, B.; Ding, S. Impact of Land Use Change Due to Urbanisation on Surface Runoff Using GIS-Based SCS–CN Method: A Case Study of Xiamen City, China. *Land* **2021**, *10*, 839. https:// doi.org/10.3390/land10080839

Academic Editors: Matej Vojtek, Andrea Petroselli and RaffaelePelorosso

Received: 14 July 2021 Accepted: 9 August 2021 Published: 11 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

magnitude of extreme precipitations as a consequence of climate change, affecting the urban population, infrastructure, and economy [4–6].

The effect of land use change on surface runoff depends on many factors such as spatial characteristics of land use, rainfall, and soil [7]. The effect is most prominent in areas undergoing rapid urbanisation where natural vegetation has been removed and replaced by constructed land [8]. Removal of trees and vegetation and construction of commercial and residential buildings, streets, and parking lots alters the water balance of an area by changing the balance between rainfall, infiltration, evapotranspiration, and runoff [9,10]. Constructed areas such as concrete buildings, roofs, paved roads, and sidewalks lead to an increase in impervious surfaces, which reduces the time of concentration for runoff, leading to higher storm runoff and peak discharges [11,12]. As a result, flooding and waterlogging are common issues in highly urbanised areas [13].

The effect on hydrological processes, particularly surface runoff characteristics, of land use change due to urbanisation has been studied by many researchers [14–16]. Specifically, Hu, Fan, and Zhang [2] investigated the impact of land use change on the distribution of surface runoff in the highly urbanised city of Beijing. Results indicated that the change in surface runoff is strongly associated with change in impervious areas. Chen et al. [17] showed that non-uniform urban expansion and intensification are the major driving forces for changing surface runoff. The studies mentioned above indicate that changes in urban land use with more impervious surfaces reduce the ability to intercept rainfall and exacerbate surface runoff process.

The SCS–CN method, developed by the Natural Resources Conservation Service (NRCS), U.S. Department of Agriculture (USDA), is one of the most widely used methods in many hydrological studies, particularly for estimating surface runoff, accounting several factors such as soil, land use treatment, and topographical features, and incorporating these factors into a single CN parameter [18–21]. However, the conventional method is more time consuming and error prone. Remote sensing (RS) and a geographic information system (GIS) can be used effectively to manage spatial and non-spatial databases that represent the hydrologic characteristics of the watershed [22]. Therefore, the application of GIS and remote sensing with hydrological models yield results with high reliability and accuracy over conventional methods [23]. Many hydrological studies are being conducted with the integration of GIS and RS techniques for simulating surface runoff. For instance, Shadeed and Almasri [24] demonstrated that the integration of GIS with SCS–CN for simulating runoff volume proved to be an effective tool in arid to semi-arid catchments [24]. Similarly, Liu and Li [25] used a GIS-based SCS model for runoff generation in Loess plateau of China and found that the calculated and observed runoff processes were well correlated.

Recently, the GIS-based SCS–CN method has been used widely to study the impacts of land use change and urban growth on surface runoff [2,14,26]. For example, Jahan et al. [27] investigated the impacts of suburban growth on surface runoff using GIS-based SCS–CN, and concluded that the integrated approach is useful for land use change detection and analysis of impact of suburban growth on surface runoff. Furthermore, Vojtek and Vojtekova [14] applied the SCS–CN method in a GIS environment to study the impact of land use change on surface runoff. Results indicated that the method is suitable for spatial modelling of runoff characteristics of a basin where few data are available. Therefore, GIS and remote sensing in the SCS–CN model is a more efficient and cost-effective method that produces adequate results without using complex data in analysing the impact of land use change and urban growth [27–30]. In this study, the GIS and SCS–CN method is integrated to analyse the effect of land use change, and examine the spatial-temporal variation in surface runoff at an urban scale.

Firstly, the study assessed land use change in Xiamen city from 1980 to 2015 by analysing land use images in GIS environment. Then, surface runoff depth was estimated using SCS–CN method. We used GIS-based SCS–CN method to evaluate the effect of land use change on surface runoff. The main objective of this research is to identify the characteristics of land use change from 1980 to 2015 and analyse the impact of land use

change due to urbanisation on the temporal and spatial distribution of surface runoff under the rainfall return periods of 5, 10, 20, and 50 years.

#### **2. Materials and Methods**

*2.1. Study Area*

Xiamen City is located on the west coast of the Taiwan Strait, composed of the mainland area along Xiamen Bay, Xiamen Island, Gulangyu, and other islands, including 6 administrative districts: Huli, Siming, Haicang, Jimei, Tong'an, and Xiang'an, as shown in Figure 1. The city has a total land area of 1699 km2 and a sea area of 324 km2. The study area is predominantly flat, low relief, with medium-low mountains, plains, and tidal flats. The slope of the terrain descends from northwest to southeast. The northwest part is mountainous, with the highest elevation of 1175 m above sea level, located on Yunding mountain [31]. Xiamen has a subtropical monsoon climate, with humid and mild climates throughout the year. According to the *Xiamen Statistical Yearbook*, annual average temperature and rainfall are approximately 21 ◦C and 1200 mm, respectively, with most rainfall in June, July, and August, accounting for more than half of the annual rainfall. Xiamen is one of the special economic zones in China and has experienced a rapid economic development and urbanisation [31]. According to Xiamen Municipal Bureau of Statistics [32], urban built-up area of the city has expanded from 38.5 km2 in 1985 to 348.23 km2 in 2017. The permanent population of the city was 4.29 million in 2019 [32]. As of 2019, the urbanisation rate of the population in Xiamen is 89.2% [33]. Xiamen has experienced several natural disasters, especially flooding and waterlogging induced by sea-level rise and storm surges, which is further intensified by rapid urban growth in past decades. Hence, there is an urgent need for mitigation of the potential hazards induced by urban development and climate change.

**Figure 1.** Location of study area with administrative boundary and catchment divisions.

Figure 2 shows the overall methodology of the study conducted for analysing impact of land use change on surface runoff with the application of GIS and SCS–CN method. The GIS environment was used to build and intersect land use and HGS shapefiles. The land use and soil complex were used to obtain the weighted CN. The CN value of each polygon was estimated using the USDA table. Finally, raster calculator in the GIS was used to calculate runoff depth from CN values for the four rainfall return periods. The methodology was applied to four different years of 1980, 1990, 2005, and 2015, respectively.

**Figure 2.** Flowchart showing the methodology of the study.

#### *2.2. Data Source and Methods*

#### (a) Land use data

Multispectral satellite images from Landsat 3 MSS, Landsat 5 TM, and Landsat 7 ETM+ were obtained to create a land use map of the study area for 1980, 1990, 2005, and 2015. The images were downloaded from Centre for Earth Observation and Digital Earth (CEODE), Chinese Academy of Sciences, and the United States Geological Survey (USGS) [34]. Images were georeferenced to the UTM, Zone 50 North, WGS-84 projection, and Beijing 1954 coordinate systems. The spatial resolution is set to 30 m. The land use was classified according to the National Land Cover Data Sets (NLCD) of China generated by Liu et al. [35] in the construction of the *China 20th Century LUCC Spatio-temporal Platform*. The method of unsupervised classification with Iterative Self Organizing Data Analysis Technique Algorithm (ISODATA) was used for image classification. Based on the national land use data product by Geographical Information Monitoring Cloud Platform, the land use was initially classified as six first level categories and twenty-five second level categories, which were reclassified into eight classes for the study. High resolution satellite imagery from Google Earth was used for visual interpretation and accuracy assessment. The overall accuracy and kappa coefficient of classified land use types is more than 85%. The high overall accuracy and kappa coefficient suggests a good relationship between classified image and reference image. The detailed descriptions of land use classes are given in Table 1. ArcGIS 10.5 and ENVI 5.3 software were used to generate various layers and land use maps.

**Table 1.** Land use classes and their description.

#### (b) Soil data

Soil data were obtained from Harmonized World Soil Database (HWSD) and Food and Agriculture Organization (FAO). Soil information for Xiamen city was obtained from 1:1 million soil map of China with a resolution of 1 km (30 × 30 arc seconds) [36]. Hydrological soil groups are classified into A, B, C, and D on the basis of water transmission and infiltration rate of soil when the soil is thoroughly wetted [29]. Soil group A has a high infiltration rate and the lowest runoff potential. These soils consist of sands or gravels that have a high rate of water transmission. Group B and C soils have moderate runoff potential and infiltration rate with a slower rate of water transmission. Soil group D has the lowest infiltration rate and highest runoff potential composed of clay or clayey loam soils with a very slow rate of water transmission [29]. Based on soil texture and soil type, the study area is classified into three HSG types, B, C, and D, as can be seen in Figure 3, which mostly contribute to large surface runoff and less infiltration.

(c) Rainfall data

Long-time series rainfall data from 1985 to 2015, collected at the Xiamen meteorological stations, were acquired from the China Meteorological Data Service Centre of the China Meteorological Administration. The rainfall amount for the return periods of 5, 10, 20, and 50 years were obtained from maximum daily rainfall data for the hydrological analysis, as seen in Table 2. The rainfall for corresponding return periods was determined by using Log Pearson Type III distribution, which is the common probability distribution method used in China [37]. The study assumed that the climatic and soil conditions are constant. To investigate spatial heterogeneity, the study required uniformly distributed station data, which are not available. Therefore, for the temporal analysis of rainfall from the stations, the station with the most complete data was selected as a representative of the study area's rainfall. Furthermore, the study area is small, and changes in rainfall variation is considered insignificant.

(d) Digital Elevation Model (DEM)

A digital elevation model (DEM) with a 30 m resolution was downloaded from the USGS website. Using hydrology tools in ArcGIS 10.8, 19 catchments were obtained, as seen in Figure 1. The sinks in the DEM data were filled, water flow direction was estimated, and flow accumulation was set with a threshold of 10,000 and 60,000 to obtain the catchments. As the study area has short streams and not many large rivers, areas in the southwest do not have adequate streams to obtain a catchment. Hence, runoff obtained from these areas

was not significant, and only those areas with enough streams within the threshold are selected as catchments for runoff analysis.

**Figure 3.** Soil type and hydrological soil group in Xiamen.

**Table 2.** Rainfall depth for 24 h maximum daily rainfall in different return periods.

Source: Xiamen Meteorological Bureau.

#### *2.3. SCS–CN Method*

The SCS–CN method is the most commonly used empirical hydrological method developed by the NRCS, USDA, and is widely used to simulate runoff [19,29]. The curve number method has been successfully adopted in many ungauged watersheds and has expanded its scope of application in urbanised catchments and forested watersheds [29]. The surface runoff model uses the curve number approach of the US Soil Conservation Service [29], based on combinations of land use, hydrological soil group, and antecedent moisture condition (AMC) for the estimation of runoff. The amount of runoff was estimated using the SCS–CN method in presence of GIS and RS. The curve number is the most important factor in determining runoff via the SCS based method. The runoff of the soil and land use complex is represented by CN, which is a function of soil type, moisture conditions, and land use type [38].

The SCS–CN model is based on the water balance equation as shown in the Equations (1)–(3).

 −

$$P = Ia + F + Q \tag{1}$$

$$\frac{Q}{P - Ia} = \frac{F}{S} \tag{2}$$

$$Ia = \lambda \times \mathcal{S} \tag{3}$$

where *P* is the rainfall depth (mm), *Ia* is the initial abstraction of the rainfall (mm), *F* is infiltration, *Q* is surface runoff depth (mm), *S* is the potential maximum soil retention, and *λ* is abstraction coefficient that ranges between 0.0 to 0.2 or 0.05 for urbanised catchments [39]. The value of 0.2 as mentioned by Natural Resources Conservation Service (NRCS) was used in the study [29]. The runoff depth can be obtained for two conditions from the Equations (1) and (2):

For *P* > *Ia* and

$$Q = \frac{\left(P - Ia\right)^2}{P - Ia + S} \tag{4}$$

 If *P* < *Ia*, *Q* = 0 and *Q* from Equation (4) is expressed as follows:

$$Q = \frac{\left(P - 0.2S\right)^2}{P + 0.8S} \tag{5}$$

In Equation (5), *S* was obtained from the dimensionless parameter *CN*. *CN* is runoff curve number that ranges from 0 to 100.

$$S = \frac{25,400}{\text{CN}} - 254\tag{6}$$

In the SCS–CN method, curve number plays an important role in determining the surface runoff of an area, and its value depends on the corresponding soil type and AMC. AMC is antecedent moisture condition present in the soil at the beginning of the rainfall. Areas with a higher curve number represent higher runoff generated from the surface. In our study, we chose B, C, and D as three hydrological soil groups (HSG) present in the study area, and the soil moisture condition (AMC II) was set as moderate according to average runoff condition. A combined map of land use and HSG was generated by combining land use and soil maps in ArcGIS using overlay analysis. Then, the CN values were assigned for each polygon based on the information of land use and soil. The CN values for each land use type under AMC II is obtained from the TR-55 lookup Table 3 [29,40].

**Table 3.** CN numbers for corresponding land use types.

Area weighted CN was obtained to simulate the runoff of the whole area using the initial curve numbers from the table as in Equation (8). Combining the CN values of different land use and soil complex polygons, weighted CN was calculated for each catchment. The weighted CN is calculated by taking the sum of each CN value multiplied by its fraction of the total area of each land use type [41]. The Equation is given below:

$$CNw = \frac{\sum (CNi \times Ai)}{A} \tag{7}$$

where *CNw* is the weighted curve number; *CNi* is the curve number for each land use type; *Ai* is area of land use with respective curve number; and *A* is the total area of each land use type. Finally, surface runoff depth was estimated, and runoff coefficient, i.e., the ratio of runoff to rainfall, was calculated.

#### *2.4. Analysing Impact of Land Use Change on Surface Runoff*

Impact of land use change on surface runoff was analysed by comparing the difference in runoff variables. Runoff depth and runoff coefficient was used as two variables to assess land use change on surface runoff. Surface runoff from the catchments were obtained for the different land use conditions and runoff was calculated under different rainfall return periods. The difference of runoff and runoff coefficient was obtained for the land use period of 1980–1990, 1990–2005, and 2005–2015 by using Equations (8)–(10):

$$
\Delta Q = Qa - Qb \tag{8}
$$

$$
\Delta \ll = \frac{\Delta \bar{Q}}{P} \tag{9}
$$

$$
\Delta \beta = \frac{\Delta Q}{Qb} \times 100\% \tag{10}
$$

where *Qa* and *Qb* denotes surface runoff depths (mm) of the initial and final land use, respectively, *P* is the rainfall depth (mm), Δ*Q* is the change in runoff depth between two periods of land use conditions, Δ*α* is the absolute change in the runoff coefficient, and Δ*β* represent relative change in runoff. Land use change leads to an increase in surface runoff if the values of Δ*Q* and Δ*α* are positive in the above Equation (10).

A relationship between land use and surface runoff was determined by using Pearson's product–moment correlation coefficient. A positive and larger correlation coefficient suggests that the factor is more significant in the change in surface runoff.

#### *2.5. Validation of SCS–CN Model*

For analysing the performance of the model, the model was validated using observed flow and simulated runoff between 1981 and 2015. Four statistical indices, as shown in Table 4, were used for testing the goodness of fit.

**Table 4.** Statistical indices used for model validity.

## **3. Results**

*3.1. Land Use Change in the Study Area*

Land use types for four different years can be seen in Figure 4. The spatial distribution of land use types show that the area has experienced significant change, especially due to urban expansion. There was a remarkable expansion of built-up areas from 62.85 to 307.54 km2 between 1980 and 2015. It was the largest gain, with a net increase of 244.69 km2. The largest net loss from 1980 to 2015 was observed in farmland and coastal wetlands with 218.2 km2 and 46.65 km2, respectively. However, constructed land that includes built-up land and rural settlements underwent the largest net increase. The forest area reduced substantially with a change of 23.93 km2.

**Figure 4.** Land use maps of Xiamen in 1980, 1990, 2005, and 2015.

Similarly, grassland and farmland were replaced by built-up areas in the south and south-eastern parts of the mainland and major parts of the island. It can be observed that most coastal wetlands decreased from 1980 to 1990, and built-up areas occupied most areas. The land area of Xiamen City expanded outward by reclamation and construction along the coast after the national survey of 1985, which contributed to the expansion of land area and reduced wetlands in 1990 [42]. A considerable increase in water bodies indicate some farmlands being converted to reservoirs, aqua farms, and other constructed wetlands. Table A1 shows the conversion of the land use in the form of a change matrix for the period of 1980 to 2015. There was a major conversion from farmland to constructed land. The trend of land use change from 1980 to 2015 indicates that urban development has dominated the island city, resulting in vast areas of impervious surfaces.

In Table A2, the percent and area change of each land use type is depicted from 1980 to 2015. It can be observed that farmlands have been reduced by 14.01% and built-up area has increased by 15.7%. The transfer process of land use types in between the study years can be seen from Figure 5. It can be noticed that major portion of change in farmlands in 1990 and 2005 have been replaced by built-up land. Overall, constructed land increased from 9.12% in 1980 to 26.1% in 2015. This indicates that urban impervious areas have increased considerably in the last few decades of the study period.

**Figure 5.** Transfer process of land use type during 1980–2015.

#### *3.2. Spatial Distribution of Runoff in Different Years*

The spatial distribution of runoff depth for the highest rainfall return period of 50 years is shown in Figure 6. Surface runoff depth ranges from 176.28 mm to 329.16 mm. The area covered by built up land with higher CN depicts a higher amount of runoff in the period from 1980 to 2015. Xiamen Island, particularly dominated by constructed area, shows larger areas of high runoff. The urban areas with high CN are often the areas with high runoff value.

Under the land use conditions of 1980, 1990, 2005, and 2015, the average surface runoff depth and runoff coefficient show an increasing trend as shown in Figure 7. The average surface depth of the area under four different periods differ from 117.2 to 271.6 mm, and runoff coefficient fluctuated from 0.6 to 0.8. The calculated value of average surface runoff and runoff coefficient increases as the rainfall return period increase from 5 years to 50 years. It can be observed that surface runoff and runoff coefficient significantly increase from the year 1990 to 2015. The amount of runoff percent for different land use types can be noticed in Figure 8. A major portion of runoff is contributed by built-up land and rural settlements which are the major constructed land in the study area with the rise from 38.2% to 48.4%. Runoff contributed by built-up land alone in the study area increased from 14.2% to 27.9% from 1980 to 2015. Similarly, farmlands and coastal wetlands also contribute to the significant portion of surface runoff in the study area.

**Figure 6.** Surface runoff depth in Xiamen from 1980 to 2015.

**Figure 7.** Average surface runoff depth Q (mm) and runoff coefficient (RC) under the return period of 5, 10, 20, and 50 years under the land use conditions of 1980, 1990, 2005, and 2015.

**Figure 8.** Runoff depth across different land use types.

#### *3.3. Change in Surface Runoff in Different Land Use Conditions*

Increase in urbanised area gives rise to impervious surfaces, resulting in increased surface runoff. Table 5 depicts the change in surface runoff at different stages of land use conditions for the rainfall return periods of 5, 10, 20, and 50 years. Increase in amount of runoff (ΔQ) is highest during 1990–2005 and lowest during 1980–1990. The surface runoff coefficient change (Δα) during the periods is influenced by the respective change in average surface runoff under return periods of 5, 10, 20, and 50 years.

**Table 5.** Changes in surface runoff at different stages under rainfall return periods of 5, 10, 20, and 50 years.

#### *3.4. Relationship between Surface Runoff and Land Use*

Land use exhibits a high relationship with surface runoff with a statistically significant correlation (*p* > 0.05). As shown in Table 6, farmlands (−0.97), forestland (−0.96), and grassland (−0.97) contribute negatively to the surface runoff, which indicates that increase in these land use types contribute to a decrease in surface runoff. Increase in urban built-up land (0.98) and rural settlements (0.99) corresponded to an increase in average surface runoff, while the decrease in farmland, forestland, and grassland contribute to higher runoff. Furthermore, increase in coastal wetlands contribute to a decrease in runoff, and unused land contributed positively to average runoff. The results are consistent with the common knowledge that increase in urban constructed land causes an increase in surface runoff; however, increases in farmland, grassland, forestland, and wetlands lead to a reduction in surface runoff. Water bodies are considered to have less effect on runoff depth, hence the relationship is less significant.

**Table 6.** Relationship between land use and surface runoff under rainfall return period of 50 years. t—t-statistic, *p*—*p*-value, and R2—Pearson's correlation coefficient. Areas in square kilometres.

*3.5. Rainfall-Runoff Correlation Analysis*

The correlation analysis shown in Figure 9 indicates a strong linear relationship between the SCS–CN runoff and maximum daily rainfall, with a correlation coefficient of 0.99. The study results are comparable with the findings of Rawat and Singh [43] who found a good coefficient of determination (0.91) in a small study area using the SCS–CN model. The slope of the line determines the runoff coefficient, i.e., 0.84. The resulting findings are similar to Al. Ghobari et al. [44], who came to the conclusion that the SCS–CN model has a better simulation effect on study areas with a coefficient of runoff greater than 0.5 than those with a coefficient of runoff less than 0.5. This coefficient may provide valuable information on the extent of the basin response to runoff generation.

**Figure 9.** Relationship between rainfall and SCS–CN runoff.

#### *3.6. Validation of SCS–CN*

The SCS–CN model was validated using historical observations and simulated flow from 1980 to 2015, as shown in Figure 10. Some statistical efficiency criteria are used to perform evaluation of the validation results between simulated output and observed data which are percent bias (PBIAS), correlation coefficient (r), Nash–Sutcliffe efficiency (NSE) and volumetric efficiency (VE). These statistical indices indicate the goodness of fit between

simulated and observed data. The model successfully predicts the annual flow with the high accuracy as depicted by the indices. The PBIAS, r, NSE, and VE were −5.7, 0.82, 0.64, and 0.86, respectively. Although there is an underestimation of streamflow due to static land use, annual flow statistics indicate that there is a good relationship between observed and simulated streamflow. Hence, the model performance was satisfactory and responded well in simulation of runoff.

**Figure 10.** Observed and simulated annual flow from 1981 to 2015.