Simulation of vapour compression air conditioning system using Al2O3 based nanofluid refrigerant

Abstract

Keywords: Nanorefrigerants; Air Conditioning System; Energy Saving; Net Refrigeration Effect (NRE); Vapour Compression Cycle

Introduction

The most critical issue is to improve the performance of the vapour compression cycle in a refrigeration and air conditioning framework leading to minimizing the cooling-related greenhouse gas (GHG) emissions. This can be accomplished by selecting low Global Warming Potential

(GWP) refrigerants [1–4]. Despite its high global warming potential (GWP100) of 2090, the refrigerant R410a having non-depleting potential is the replacement for R22 in medium and high-temperature applications [5,6]. Due to its similarities in thermophysical properties with R410a, R32 has been used as a low-GWP and low-LCCP

*Corresponding author. *E-mail address: adnan@nitsri.ac.in This paper was recommended for publication in revised form by Regional Editor Omid Mahian Published by Yıldız Technical University Press, İstanbul, Turkey Copyright 2021, Yıldız Technical University. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

alternative to R410a [7–9]. The R32 refrigerant has low lubricant-refrigerant miscibility, a high discharge temperature and pressure, chemical stability, and low flammability [10]. Nevertheless, R32 has certain advantages like high latent heat of vaporization, less refrigerant charge and high thermal conductivity compared to R410a [9]. The use of nanoparticles in R32 helps in lowering compressor discharge temperature thereby keeping the compressor cool which leads to a higher COP, energy-saving and reduction in GHG emissions [11–14]. According to a recent United Nations report, the use of air conditioners worldwide is the main cause of Global Warming even though able to maintain cool interiors. In a recent report by the International Energy Agency, improving air conditioning efficiency is critical for the conservation of energy. More than 3.6 billion cooling appliances in the form of refrigerators, freezers, and air-conditioners are used for HVAC-related applications for thermal comfort, food storage, dry preservative and various other essential services. With the use of new technologies and innovations. It is estimated that by 2050 14 billion AC units will be in operation worldwide [15]. Nano additives with enhanced thermophysical properties improve the solubility of compressor lubricant in pure ozone-friendly refrigerants with low GWP (Typically nano-additives in compressor oil are called nanorefrigerant or nanolubricant). The enhancement in properties depend upon the loading fraction, operation temperature and size of nanoparticles [16]. In addition, there is a marked decrease in the compressor discharge temperature accompanied by an increase in COP and corresponding power saving. Refrigerant with nano additives (nanolubricant) prevents direct contact between the piston and cylinder in motion and improves rolling, mending and polishing effects which increases the life span of moving parts and reduces the friction coefficient of the compressor shown in Figure 1 [17–21].

Figure 1. Lubrication mechanisms by the use of nanofluid in machining. According to EU directives 2037/2000 and 842/2006, the use of HCFC-based refrigerants with a high greenhouse effect should be phased out permanently and replaced with low-GWP HFC-based refrigerants [22]. The best replacement of R410a with R32 refrigerant for air conditioning units has a zero ODP and a low GWP, as illustrated in Figure 2 and it requires less refrigerant charge [23]. The use of nanofluids in refrigeration, air conditioning, and heat pump (RACHP) systems may increase efficiency. “Efficiency rating” a term commonly used for performance refers to the ratio of the heat removed from a space to the amount of energy required to condition it. The higher the energy-efficiency rating, the more efficient the machine. Climate-weighted efficiency rating indicators vary by country, as illustrated in Figure 3 [24]. According to the literature, nanorefrigerants are prepared using two distinct techniques. The first method involves dispersing the nanoparticles into the refrigerant. The second method involves dispersing the nanoparticles into the compressor oil. However, researchers assert that the final products from both these approaches result in

Figure 2. ODP versus GWP and lifetime of HFCs, HCFCs, CFCs (Circles).

India (ISEER) Best Available India (ISEER) Market Available India (ISEER) Minimum Available

Figure 3. Efficiency ratings of available AC units by regional metric. nanorefrigerants. Although few researchers distinguish the products from the first procedure as nanorefrigerants and the second technique as nanolubricants. The use of nanorefrigerants or nanolubricants will improve heat transfer and tribological performance leading to an increase in compressor efficiency. According to the manufacturer of HVAC products, approximately 50% of compressor oil is contained within the compressor, while the rest is in the evaporator, condenser, hoses, and drier [25,26]. Senthilkumar et al. [27] carried experimental investigation of CuO-SiO2 hybrid nanolubricant in R600a refrigeration system. There was an improvement in COP by 35% and cooling capacity by 18%. This resulted in reduced power consumption of 75 W using 0.4 g/L nanolubricant with 60 g of R600a. HudaElsam et al. [28] has investigated Cerium Oxide nanoparticle as a single material and as a blend with copper oxide to verify the feasibility of this oxide to increase nanolubricant stability and enhanced thermal characteristics. Pritam and Bijan [29] carried study on the performance enhancement of a shell and tube evaporator using Al2O3/ R600a nanorefrigerant. A multi-object optimization has been carried out for cooling the right combination for maximizing heat transfer and minimizing power requirements. 5 times above that of a base refrigerant at a concentration of 5 wt.% nanoparticles. Suraj et al. [30] observed the effect of Aluminum oxide of 20-30 nm nanoparticles used in hydrocarbon refrigerant at various mass concentrations of nanoparticles are 0.20 gm, 0.30 gm and 0.40 gm respectively. The addition of nanoparticles to the refrigerant improved the thermophysical properties and heat transfer characteristics of the refrigeration system. It is observed that there are more temperature reductions have been reported for the nanorefrigerant (14.4

– 20%) compared with pure refrigerant R600a. Similarly, evaporator temperature a gain of 2.33- 5.55% and also improved in COP by 3.68 - 11.05% respectively. Desai and Patil [31] observed that nano-additives possess significant properties that enhanced the thermophysical properties of refrigerant compressor oil. The optimal COP increases by approximately 14% and power saving by approximately 12.30% using R-134a and POE/SiO2 at a concentration of 2% (by mass). Krishnan et al. [32] investigated enrichment in the coefficient of performance of the refrigerator by adding various nanoparticles such as Al2O3, SiO2, ZrO2, and CNT in pure Polyolester oil. Attributed the use of nano lubricants for COP improvement at various concentrations (0.1, 0.2, and 0.3% w/v). The coefficients of performance of POE/Al2O3 at 0.3% (w/v), POE/SiO2 at 0.1% (w/v), POE/ZrO2 at 0.1% (w/v), and POE/CNT at 0.1% (w/v) were 1.59, 1.73, 1.505, and 1.49 as compared to the base lubricant at (1.42). Deokar and Cremaschi [33] used R-410 as the refrigerant and found that dispersing Al2O3 and ZnO nanoparticles in POE oil leads to a 15% increase in heat transfer coefficient (HTC) over ZnO nano oil, as well as improved vapour quality and greater refrigeration effect. The deposition of nanoparticles on the inner wall of smooth copper tubes increases nucleates boiling thereby increasing heat dissipation and frictional pressure drop. Marcucci et al. [34] investigated the use of R-410a as a refrigerant by dispersing diamond nanoparticles in pure POE (32-3MAF) oil at two different concentrations (0.1 and 0.5% mass). The study concentrated on key performance indicators, such as energy savings, increased cooling capacity, and lower oil sump and discharge temperature. Another study reported improved tribological performance in terms of wear and friction with R32 refrigerant instead of R-410a [35].

Jwo et al. [36] has investigated the possibility of replacing the POE lubricant and R-134 refrigerant with mineral oil (MO) and hydrocarbon refrigerant. Aluminium oxide nanoparticles dispersed in MO at various concentrations (0.05, 0.1, and 0.2 wt%) have been used to improve the lubrication and heat dissipation rates. The obtained results indicate that R-134a at 0.1 wt% nanoparticles, was the optimal choice for lower power consumption and increased coefficient of performance. Adelekan et al. [37] studied the effects of different mass of charge (40, 60, and 80g) of R-600a refrigerant and graphene nanoparticles dispersed in mineral oil (MO) at concentrations of 0.2, 0.4, and 0.6 g/L. The highest power per tonne of refrigeration (PPTR) value of 5.22 was obtained. The maximum coefficient of performance (COP) of 0.76 at 0 g/L concentration with 70 g of refrigerant charge. Sanukrishna and Prakash [38] investigated the refrigeration system using TiO2 nanoparticles. The optimal concentration was 0.4% volume fraction, and the results obtained in an increase in thermal conductivity, viscosity, or rheological properties. Sendil and Elansezhian [39] studied the R152 refrigeration system using PAG/ZnO nanolubricants. The optimum volume concentration of 0.5% gave an improved COP value of 3.56 resulting in power savings and a reduction in both suction and discharge temperature to 10.5%. Abdur and Ahamed [40] has investigated the drop replacement of R22-POE with a mixture of R22 and R600a (80:20) by mass of refrigerant, with TiO2-MO as a lubricant (0.1% -0.4%). The experimental results indicated that both exergetic and energetic performance was improved; the compressor discharge temperature was reduced by 15oC for the mixture

Material And Methods

Theoretical Formulation and Simulation Model of R32/ Al2O3 And R410a/Al2O3 for Vapour Compression Air Conditioning System The vapour compression air conditioning framework comprises four major components namely, compressor, condenser, expansion valve, (or capillary tube) and the evaporator as shown in Figure 4. The figure illustrates a simple cycle with no superheating or undercooling.

containing 0.4% MO/TiO2 nano-oil, and the compressor coefficient of performance was increased by 10-19.5%. Kumar et al. [41] studied the effect of copper oxide (CuO) nanolubricant on the performance and characteristics of LPG nanorefrigerant and observed improvement in the viscosity which leads to a significant decrement in friction coefficient. The coefficient of the performance was enhanced by 46% and power saving by 7%. It is clear that scanty literature is available on the enhancement of the refrigeration effect accompanied by reduced power consumption using eco-friendly and low GWP HFC refrigerants. Adding alumina nanoparticles at various volume concentrations in such cases may lead to further enhancement in the performance of HFC-32 (Low GWP-675) systems. The novelty of the work stems from the fact that this is one of its kind Matlab simulation-based analysis of nanorefrigerants. Furthermore, a detailed comparison has been made between the refrigerants to arrive at the best alternative based on sustainable development goals, which is in itself a peculiarity of this work.

Figure 4. T-s diagram for pure and Al2O3 nanorefrigerant cycle (R32).

¾ Process (1-2) Isentropic Compression in compressor ¾ Process (21-3) Constant pressure heat dissipation in a condenser ¾ Process (3-4) Isenthalpic throttling process in an expansion device. ¾ Process (4-1) Constant pressure heat extraction in an evaporator The enthalpy and other properties of the nanorefrigerants are evaluated using a density of the refrigerant [42]. Mollier chart is used to evaluate the properties of pure and nanorefrigerants. The density of nanorefrigerant (ρNR) at points 1 and 3 is calculated from Equation 1 given by Pak and Cho [43]. This research study uses Al2O3 (Alumina) nanoparticle having density and thermal conductivity of 3.9 g/cm3 and 40 W/m-k [44]. The use of R32 and R410a refrigerants with various volume concentrations of Alumina nanoparticles (0.06, 0.08, 0.1, 0.12, and 0.14%). A sample of

calculations for NRE, COP, power-saving and reduction in discharge temperature of R32/R410a/Al2O3 are presented in Table 1 and Table 2 using Alumina at the volume concentration of 0.14%. (1) (2) where, ρNR = Density of nanorefrigerant in g/m3, ρNP = Density of nanoparticle in g/m3, ρPR = Density of pure refrigerant in g/m3, ϕ = volume concentration (%), mp = mass of nanoparticle in grams, ρp = Density of particle in g/m3, mR = mass of refrigerant in grams, ρR = Density of refrigerant in g/m3.

Figure 5 (a). Air Conditioning Framework used R32/Al2O3 Nanorefrigerant in Simulink.

Compi hg vs T, kJ/kg T Sg [Tevp] R410a Vapor Compression Sg vs T, kJ/kgoC AC Cycle [Tcond]

Figure 5 (b). Air Conditioning Framework used R410a/Al2O3 Nanorefrigerant in Simulink. A MATLAB/Simulink model has been developed to assess the performance of the air conditioning framework in terms of properties of refrigerants/nanorefrigerants through the density of nanorefrigerant by using Equation 1, to evaluate NRE, COP, and power consumption as depicted in Figures 5(a) and 5(b). The schematics of the algorithm used in Simulink of Matlab for R32/Al2O3 and R410a/ Al2O3 are illustrated in Figures 5(a), 5(b), and 6 in terms of block diagrams and flowchart. Theoretical Formulation Used as Coding in MATLAB The results of R32/Al2O3 nanorefrigerant have been analysed and compared with the performance of R410a/ Al2O3 in the system using Equations (3)-(9). Cooling capacity (Qevap) is given by (3) The compressor power (kW) input is given by

Refrigerant mass flow rate is given by (6) Coefficient of performance (7) Effective thermal conductivity (keff ),

where h1 is the enthalpy of saturated vapour (kJ/kg), h2 is the enthalpy of superheated vapour (kJ/kg), h3 is the

Input Operating conditions Design various signals, gauges and other parameters

Set temperatures/pressures According to densities of pure and nanorefrigerants

Compressor coding’s (Power, mass flow rate and outlet conditions)

Solving temperature and pressure drops between compressor and condenser

Condenser Coding’s (Outlet conditions such as condenser and fan power, pressure drop, condenser area and HTC etc)

Evaporator Coding’s (Outlet conditions such as pressure drop, vapour quality and HTC etc.)

Conditions of inlet to compressor Run Calculate power consumption and COP

enthalpy of saturated liquid (kJ/kg), m is the mass flow rate (kg/s). where ϕ, is the volume concentration of nanoparticles. keff is the effective thermal conductivity of the nanorefrigerant. kf and kp are the thermal conductivities of pure refrigerant and nanoparticles respectively. µbf, is the viscosity of base fluid and µnf is the viscosity of nanofluid.

Assumptions The important assumptions for leading this kind of theoretical model-based study are.

Pressure losses at the compressor inlet and outlet ports are neglected. Pipelines pressure losses are neglected. Heat losses and heat gains from or to the system are ignored. Isentropic, mechanical and electric motor compressor efficiencies are considered. Degree of undercooling and superheating before compression are neglected. No deposition of nanoparticles at the solid wall.

Results And Discussion

The results are presented using MATLAB graphs. Figures 7(a-f) shows the time response of compressor power, condenser power, mass flow rate, steam quality and condenser cooling air mass flow rate variations up and down according to the load at a various volume concentration of (0, 0.06, 0.08, 0.1, 0.12 and 0.14%) Al2O3 in R410a and R32 refrigerants at reference temperature respectively. The maximum reduction in compressor and condenser power at 0.14%vol concentration and improved vapour quality of nanorefrigerant. Figure 7 (c) indicates that fluctuation

in mass flow rate according to the controlling cooling load and temperatures. The simulation data in Figure 8 (a) shows that a maximum reduction in compressor discharge temperature of 6.7% takes place in R410a/Al2O3 compared to a reduction of 18% in R32/ Al2O3 on increasing the nanoparticle content of Al2O3 in the respective refrigerants. The addition of alumina nanoparticles to the refrigeration system boosted cooling capacity and COP, while the discharge and oil sump temperatures of the compressor have been reduced. The reduction in the discharge temperature and pressure leads to an increase in COP and power-saving [34].

(f) Figure 7. Performance of AC system with HFC-32/Al2O3 nanorefrigerant according to cooling load with time response. Table 1. Sample Ideal calculations for pure and R410a/Al2O3 nanorefrigerant, at condenser and evaporator temperature, are T3= 38oC and T1= -20oC. S.No 1 2 3 4 5 6 7 8 9 10

ρ1 (kg/m3) ρ3 (kg/m3) Tc (oC) Tsup (oC) P2=P3 (bar) Power (kW) COP NRE (%) COPIncrease (%) Power Saving (%)

R-410a (Pure) R410a/ Al2O3 0.06% vol 15.42 987.52 38 66.89 23.10 1.181 2.978 77.73 -

Table 2. Sample calculations for pure and R32/Al2O3 nanorefrigerant, at condenser and evaporator temperature, are T3= 38oC and T1= -20oC. S.No

Figure 8 (a). Discharge temperature versus particle concentration.

In addition, figures 8(b) and 8(c) shows the corresponding variation of COP with discharge temperature at different concentrations of nanoparticles for R32/Al2O3 and R410a/Al2O3 respectively. A maximum improvement in COP of 24.4% and 46.2% are obtained for R410a/Al2O3 and R32/Al2O3 nanorefrigerants. All the data for the two refrigerants have been tabulated in Table 1 and Table 2 respectively. Figure 9 shows the graphical representation of variation in COP with particle concentration for the two refrigerants in terms of bar charts. The charts clearly show that incorporating Al2O3 in R32 improves the COP and compared to R410a. Effect of Nanoparticle Concentration on Net Refrigeration Effect (NRE) Figures 10(a) and 10(b) shows the net refrigeration effect versus evaporation temperature at various particle concentrations for R410a and R32 respectively. There is a marked increase in the net refrigeration effect with a

Method

Effect of nanoparticle concentration on thermal conductivity Figure 13 shows the thermal conductivity variation with variation in nanoparticle volume concentration from 0.06% to 0.14%. The effective thermal conductivity of spherical nanoparticles is calculated by using Equation 8 [45]. The maximum thermal conductivity of Al2O3/R32 and Al2O3/

R410a is observed by 48.1% and 47.7% at a volume concentration of 0.14%. Increased Brownian motion, as well as the improved thermal conductivity of Alumina nanoparticles, contributed to the improvement in suspension stability [46]. Effect of nanoparticle concentration on viscosity Variations of viscosity of Al2O3/R32 and Al2O3/R410a at various particle concentrations are shown in Figure 14. As particle volume concentration increases, the viscosity of nanorefrigerant also increases. The pioneering model for estimating the viscosity of nanofluids was proposed by Einstein in Eq. 9 [47]. Effect of nanoparticle concentration on density The density of R410a/Al2O3 and R32/Al2O3 nanorefrigerant is determined by using above mentioned Equation 1.

5. Ton

0 0.06 0.08 0.1 f (%) 0.12 0 0.14 0.06 0.08 90 72 74 76 78 80 82 84 86 88 0.1 Discharge Temperature, Tdisch (oC) 0.12 0.14

0 0.06 0.08 0.1 f (%) 0.12 0 0.14 0.06 0.08 63 64 65 66 67 0.1 o 0.12 Discharge Temperature, Tdisch ( C) 0.14

0 0.06 0.08 0.1 f (%) 0.12 0 0.14 0.06 0.08 23.1 23.2 23.3 23.4 23.5 23.6 0.1 Discharge Pressure, Pdisch (bar) 0.12 0.14 (c) 23.1

R410a/Al O R32/Al Figure 12 (a) and 2O3(b). Compressor work done versus discharge temperature. 2 3 Discharge Temperature, Tdisch (oC) Discharge Temperature, Tdisch (oC) 50 70 (b) (a) 52

0 0.06 0.08 0.1 f (%) 0.12 0 0.14 0.06 0.08 22.7 22.8 22.9 23.0 23.1 0.1 Discharge Pressure, Pdisch (bar)0.12 0.14 (d) 22.7

Figure 12 (c) and (d). Compressor work done versus discharge pressure 135

Figure 13. Increment of thermal conductivity of nanorefrigerants (R32/Al2O3 and R410a/Al2O3) with the increase in particle concentration.

Figure 14. Variation of viscosity of (R32/Al2O3 and R410a/ Al2O3) with the increase in particle concentration.

Particle Concentration, (Vol %) Figure 15 (a). Variation of density of R410a/Al2O3 with particle volume concentrations.

Figure 15 (b). Variation of density of R32/Al2O3 with particle volume concentrations.

Figures 15(a) and 15(b) demonstrates the variation of density of nanorefrigerants with various volume concentrations.

¾ The thermal conductivity of R32/Al2O3 is 40.9% more than as compared to R410a/Al2O3 nanorefrigerant at a volume concentration of 0.14%.

Conclusions

This study provides the illustrated simulated effect of alumina (Al2O3) nano additives at various volume concentrations (0.06, 0.08, 0.1, 0.12, and 0.14%) on long-term environmental-friendly and low global warming potential (GWP) refrigerant HFC-32. The results of the nanorefrigerants provide guidelines for using this as a viable alternative to HCFC-22 and R410a. A MATLAB Simulink program has been developed to measure the refrigerating effect, power saving, the density of nanorefrigerants, COP, and compressor discharge temperature of R32 and R410a nanorefrigerants. The maximum volume concentration of nano additives (R-410a/Al2O3 and HFC-32/Al2O3) of 0.14% was used. The following conclusions have come to light through this study. ¾ The COP of R410a and R32 nanorefrigerants increased by 24.38% and 46.14% respectively at a 0.14% volume concentration of alumina. ¾ The discharge temperature of R410 and R32 nanorefrigerants was reduced by 6.7% and 17.97% respectively. ¾ In addition of alumina nano additives to R410a and R32 with a volume concentration of 0.14%, the net refrigeration effect increased to 81.2% and 83.5%. ¾ Use of nano additives in the refrigerants R410a and R32 lower the power consumption of the system by 19.6% and 31.6% respectively.

Limitations

Even though with the increase of nanoparticle concentration the overall effectiveness of the system increases. However, there is a threshold limit below which the system can perform continuously. The reason for this is, that if the concentration of the nanoparticle is increased beyond this limit there is agglomeration and sedimentation associated with the nanoparticles which restrict the smooth operation of the system.

Importance And Future Research

More refrigerants (or a mixture of refrigerants) can be considered for the study Extensive experimentation can be carried out in the laboratory under controlled conditions. Hybrid nanoparticles can be employed to synthesize the effect on nanorefrigerants. Effect of surface functionalization and surfactants can be incorporated to impart stability and longevity to the nanofluids.

Data Availability Statement

The authors confirm that the data that supports the findings of this study are available within the article. Raw

data that support the finding of this study are available from the corresponding author, upon reasonable request.

Conflict Of Interest

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics

There are no ethical issues with the publication of this manuscript.

Nomenclature

Al2O3 COP NRE GWP (GWP)100 ODP Q Φ NR T H GHG Vol. mr ρ PAG POE MO LCCP CFC HFC

Aluminium oxide Coefficient of Performance Net Refrigeration effect, (%) Global Warming Potential Global Warming Potential over 100 years Ozone Depletion Potential Heat Transfer per Unit Mass, (kW) Volume Concentration, (%) Nanorefrigerant Temperature, (oC) Enthalpy of Refrigerant, (kJ kg-1) Greenhouse Gas Volume Mass flow rate of Refrigerant, (kg s-1) Density, (kg m-3) Polyalkylene Glycol Poly-Easter Oil Mineral Oil Life Cycle Climate Performance Chlorofluorocarbon Hydrofluorocarbon

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