Numerical simulation of integrating an air conditioner with an evaporative air cooler

During the summer, air conditioning is increasingly used in commercial and residential structures to provide thermal comfort. The elevated condenser pressure caused by high ambient temperatures has led to a significant increase in electricity consumption in dry, hot climates. Therefore, this article presents the results of a numerical simulation investigation into the feasibility of enhancing the performance of a conventional air conditioning unit by applying a direct evaporative cooling system. The objective is to increase the cooling capacity while decreasing power consumption. The program used a small window-type air conditioner configured to simulate various weather conditions. The numerical findings indicate that incorporating evaporative cooling aids improved the system's ability to overcome numerous obstacles, resulting in a 10–20% increase in refrigeration capacity. Additionally, power consumption was reduced by approximately 3%, and the discharge temperature fell by 6–10°C. The predicted mean vote standard (PMV) for thermal conditions for human occupants yielded favorable outcomes (normal-type). Despite the challenging climate conditions prevailing during the five sweltering summer months, water production demonstrated good results, particularly in September.


Introduction
Energy is vital for a country's economy to grow.As energy consumption continues to rise, saving it becomes increasingly important.Many engineering fields are striving to optimize energy utilization or reduce consumption [1][2][3].Reducing energy usage can lower dependence on costly oil and gas, significantly impacting a country's economy [4].Conserving energy plays a crucial role in mitigating global warming.
Using more energy enables a more comfortable lifestyle.Air conditioners, refrigerators, and water heaters consume around 30% of total power requirements [5].Air conditioners in homes and businesses account for nearly half of all electricity usage [6].Experts predict a 71% surge in energy demand between 2003 and 2030 due to population growth and expanding economies [7].Therefore, optimizing energy usage, especially in cooling buildings, is crucial to global energy conservation efforts.
Efficient cooling systems help conserve energy.Strategies include reducing compressor power usage, enhancing heat rejection in the condenser, or minimizing pressure differences between the condenser and evaporator.Elevated condenser temperatures increase compressor workload, potentially reducing efficiency and lifespan.In high temperatures, most air-cooled systems' efficiency drops to around 2.2-2.4 [8].Extended exposure to extreme heat, like temperatures surpassing 45°C, can cause air conditioners to malfunction due to excessive condenser pressure.
In some Middle Eastern nations, summer temperatures soar beyond 40 -45°C.The air conditioner's constant operation in such conditions escalates electricity consumption and reduces system efficiency [9].Employing evaporative condensers to cool the air before reaching the coil lowers condenser temperature and pressure.Evaporative condensers can mitigate high outdoor temperatures, especially in regions with drastic dry and wet temperature differences during peak periods [10].Despite lower airflow and heat transfer area [11], these condensers efficiently reduce energy consumption and alleviate pressure on power systems [12], [13].Ongoing research aims to enhance evaporative-cooled condensers' heat transfer for more efficient cooling systems.This paper examines the functionality of evaporative condensers, the energy consumption of residential cooling systems, and the fundamental principles, regulations, and theory underlying the heat removal process of evaporative condensers, crucial for facilitating heat transfer from the refrigerant during its transition from a gaseous to a liquid state.Condensers are indispensable components of cooling systems, with vapor, water, and air condensers being among the various types available.Smaller refrigeration systems, like chillers, typically utilize air-cooled condensers up to about 20 tons [14], [15].Heat transfer in air-cooled condensers occurs between coils and the ambient air, operating based on the principles of thermal transfer governed by air physics.However, their effectiveness might be affected by weather conditions.Air-cooled models are most common, as they do not rely on water, although they tend to be noisier due to their high ventilation requirements.Despite being more cost-effective in production and operation, alternative condensers consume less energy.Air-cooled systems must maintain a condensing temperature of approximately 15-20°C higher than ambient air [16].An alternative method involves using adjacent water to eliminate heat, which is then converted to heated air by a tower [17], [18].
Although this condenser type is smaller and more efficient in heat transfer compared to air-cooled units, it necessitates water and a larger initial investment [19] [20], requiring a pump for water circulation.Chemical treatment is essential to prevent coil fouling, and regular monitoring and maintenance are necessary.If the distance between the compressor and the heat release point is substantial for pushing the refrigerant vapor, only the water-cooled condenser should be used, typically handling from half to ten thousand tons of refrigeration (TR).Water-cooled condensers are primarily employed in heat pumps and specialized equipment [21].
Next, let's discuss the evaporative condenser.In larger non-residential settings requiring substantial cooling, evaporative cooling effectively removes heat more efficiently than air-cooled systems.These compact heat exchangers facilitate the exchange of air and water for cooling.They transfer sensible and latent heat between the air and water, where the water transforms into vapor, subsequently cooling the air.Unlike air -cooled systems, these condensers require smaller fans and motors, resulting in reduced air demand.Additionally, they necessitate fewer chemicals and water pumps compared to water-cooled condensers.Both water-cooled and evaporative condensers can only cool to the outside wet bulb temperature, which is typically lower than the dry bulb temperature.
These condensers play a role in cooling the refrigeration system, consequently reducing electricity consumption.They offer improved efficiency and enhanced cooling capabilities compared to air -cooled condensers.Evaporative condensers consume less water than water-cooled counterparts with cooling towers, despite utilizing similar amounts for each refrigeration unit.The water system for evaporative condensers is entirely contained within the unit.As they are smaller and have fewer components, they are more cost-effective than water-cooled condensers.However, their planning and installation can be more complex than water and air-cooled condensers due to the water evaporating into the air during operation.

Theoretical model and methodology
The 3D Navier-Stokes approach via ANSYS simulated the airflow, dehumidification, and condensation processes within a room.This simulation involved calculations related to interior conditions, such as temperature, velocity, and humidity.Additionally, it evaluated the turbulent flow emanating from the room's duct outlet and accounted for the non-uniform heat flow originating from the walls.The experimental model underwent numerical solution using CFD (Computational Fluid Dynamics) software fluent within ANSYS 22 R1.This approach, based on vectors, resolves conservation equations for mass, momentum, energy, and species in stable three-dimensional flows.

Governing equations
The flow and energy equations are derived from the fundamental equations of fluid dynamics, namely continuity, momentum, and energy equations.The Navier-Stokes equations specifically describe the motion of fluids and are often likened to Newton's second law of motion applied to fluids.

Momentum conservation equations
The direction of the X-axis (U-momentum): (μ) = fluid viscosity of dynamic.Replacing U, V, and W by the time-mean and fluctuating components and assuming a pressure expression that is comparable to integrating and averaging with time .The terms −ρu′c′, −ρv′c′, and −ρw′c′ are the turbulent diffusion fluxes, J.C.

Modeling turbulent production in the k-models
: Component of the gravitational vector in i-direction : Thermal expansion coefficient

Effects of buoyancy on turbulence in the k-models
When a non-zero gravity field and temperature gradient are present, the k-epsilon (k-) models in Fluent software account for the generation of 'k' due to buoyancy in Equation 3.11 and the corresponding contribution to the production of 'epsilon' in Equation 3.12.The generation of turbulence due to buoyancy is given by: Where 〖Pr〗_t is the turbulent Prandtl number for energy, and g is the component of the gravitational vector in the I th direction.For the standard (k-ε) models, the default value of 〖Pr〗_t is 0.85.The coefficient of thermal expansion is defined as: ) (3.17 ANSYS Fluent consists of four software modules that take geometry and mesh and pass the info rmation required to perform a CFD analysis, as shown in Fig. 1.

Model description by using ANSYS 22/R1
The tester room at Al Najaf Hospital measures 4m in length, 3m in width, and 2.5m in height.The construction features walls made of hollow concrete blocks, and the roof consists of galvanized Kirby corrugated iron, with an internal secondary ceiling made of gypsum board.Conditioned air is provided through an inner rectangular supply air duct located on the northern wall.The measuring duct, measuring 2m in length, 0.3m in width, and 0.6m in height, comprises three slots; slot 1 delivers air at a velocity of 4m/s with a temperature of 28°C from the evaporative air cooler device, slot 3 supplies air at a velocity of 1.5m/s and a temperature of 16°C from the air conditioner, and slot 2 is a mix of the two airflow streams.The room's geometry was designed using ANSYS Fluent 22/R1.Figures 2 and 3 illustrate the room's dimensions and layout.Designing the interior and exterior walls posed the most significant challenges during modeling.The roof was exposed to daily environmental fluctuations, especially in May, June, September, and October, which affected both the outer and inner walls.These fluctuations in daily temperatures led to changes in the results within the room, such as increased inner wall temperatures and variations in relative humidity and temperature levels.Moreover, a return air duct enables the room's air to circulate back to the air conditioner, enhancing air quality and producing clean water.The heat transfer boundary conditions for all walls, except the floor, are adjusted to account for the varying climatic conditions.The tester room features a single door located at a height of two meters from the base, measuring one meter in width, along with two windows positioned at an elevation of 1.5 meters and with a width of 1 meter.

Mesh design
While assessing grid dependency, the conclusions' accuracy was verified by increasing network density.The air ducts located along the north wall and positioned below the ceiling underwent testing to analyze primary flow or heat distribution.Figure 5 illustrates the incremental mesh refinement in these zones and their surroundings until achieving network independence.Irregular grid layouts were implemented in complex sections to tackle the challenges posed by 3D physics, while standard grid layouts were u tilized in geometric areas due to limitations in cube and microscopic sizes.Despite the considerable space in the room allowing for a restricted grid, which might prolong the precision of findings for several days or more in each case, it does not compromise the accuracy.These equations calculate the PMV and relate to the ASHRAE thermal sensation scale, which spans from -3 to 3 as shown in Figure 6.

The cooling process
The cooling system involves two primary heat transfer methods.Firstly, in the evaporative cooler, water evaporation cools and humidifies the hot outside air.This process is governed by the convective heat transfer coefficient and the temperature difference between the exterior air and the evaporative cooler.Secondly, the air conditioning device cools and dehumidifies the mixed return air from the test room, facilitating heat transfer.
The heat transmission in this process is influenced by the temperature difference between the outside air and the air conditioning unit, along with the convective heat transfer coefficient.
Water evaporation humidifies the outside air in the evaporative cooler, regulated by the convective mass transfer coefficient and the humidity difference between the room air and the evaporative cooler.In the air conditioning unit, the process of dehumidifying indoor air involves mass transfer, which is affected by the convective mass transfer coefficient and the humidity difference between the outside air and the air conditioning unit, as depicted in Figure 7.In this study, as a first step, the appropriateness of the ANSYS 22 R1 program is validated against the results reported by [21].The governing equations (mass conservation, momentum, energy, and concentration) for turbulent airflow inside a room with dimensions of 6 meters in length, 4 meters in width, and 2.4 meters in height are generated, aligning with the dimensions used in the aforementioned researcher's work.The flowing air was contaminated with particles at varying concentrations.A model akin to the one presented in [21] is constructed using the ANSYS 17 program, and the aforementioned governing equations are solved using the same program, ANSYS/CFD/CFX-17.
The current model closely resembles Model Number 1, which operates exclusively with an evaporative air cooler, enabling a detailed analysis of its thermal performance.The primary objective of this verification study is to ensure the accuracy and reliability of the existing code.Any discrepancies between the two results are then quantified.In the horizontal plane, the researcher's air velocity range is 0-1.00 m/s, while verification case 1 exhibits a range of 0-0.99 m/s.In the vertical plane, the researcher's air velocity range spans 0-3.2 m/s, whereas verification case 1 shows an air velocity range of 0-3.02 m/s.These differences indicate an acceptable level of convergence between the two sets of results.To comprehensively compare both research types, the results were plotted in Chart 1, and their differences were calculated.The maximum and minimum percentage error values are tabulated in Table 2. It's worth noting that the generally accepted range of difference falls between 10% and 20%, as commonly reported in indoor airflow measurements and simulations, as summarized in Table 3.To delve deeper into this analysis, specific points in Figure 12 were examined, particularly near the E.C. levels and the surrounding area.

Verification case 2
A verification study was conducted for case 2, previously investigated by Begdouri et al. [22].The analysis utilized the ANSYS-17/CFD/Fluent program, focusing on the room's thermal performance by examining temperature, velocity, and relative humidity distributions.In this configuration, the room was conditioned solely by the window-type air conditioner.The dimensions of this designed room were chosen to match the model studied by the researcher [27], who conducted numerical and experimental studies using the CFD/Fluent-FIDAP program.The specified dimensions for this case were 4.8 x 4 x 2.7 cubic meters.The detailed boundary conditions for case 2, examined by the researcher, and verification case 2 are presented in  Figure 14.The drawing created by (a) design modeler 3D and (b) vector plane for a verification case [22] Table 5. Measured and numerical values of air velocities and temperatures at selected domain points for the primary case [22] V Error % V R with V c-w Error % T R with T c-w 1.
6.11 12.5 Chart 2. Comparison of measured and numerical values of temperature and velocity of the domain points a) researcher [22] and verification case 2

Grid independence study
Mesh quality significantly impacts the accuracy and stability of numerical computations.If there are issues with grid quality, ANSYS will generate a warning message in the console, highlighting problems identified with the mesh.The geometry was created using ANSYS Design Modeler (DM) within the ANSYS program and later transferred to ANSYS Meshing for the meshing process.Various types of meshes were employed to achieve the necessary mesh quality that ensures accurate resolution for solving the problem.For each type of mesh, there are three stages of mesh size: course mesh, medium, and fine mesh.As Table 7 shows, Mesh 2 is the best in the current study when transferring from Mesh 6 to Mesh 7 because Mesh 6 has less error.

Theoretical results and discussions
This chapter presents the findings of an extensive study conducted over five months from May to October 2021-2022.It investigates the impact of various parameters on the thermal comfort of a specially designed test room cooled by an evaporative air cooler and a window air conditioner.These parameters encompass relative humidity, air temperature, and air velocity.Comprehensive records of external variables were maintained to comprehend their influence on internal conditions.The analysis involved performing calculations using ANSYS 22/R1 software.The numerical results were obtained using the ANSYS 2022/R1 Species Transport software tool.These simulation studies are essential for validating the results, comparing them with experimental data, and presenting findings that explore the relationship between outdoor climate conditions and the conditions within the conditioned room, considering factors such as temperature, air velocity, humidity, and weather conditions.

Analysis and study of the present case by using ANSYS 22/R1
The study involved utilizing the ANSYS 22/R1 Fluent program to operate both cooling systems.Various horizontal and vertical planes and lines were employed to assess specific locations in the room, as detailed in Table 8.These evaluations encompassed measuring relative humidity, temperature, and air velocity, as illustrated in Figure 15.Data collection was performed on the 14th day of four hot summer months (May, June, September, and October) at 1:30 p.m., and the results are depicted in Figures 16, 17   In Charts 11 to 20, variations in relative humidity are observed across four months: May, June, September, and October.These differences are most noticeable in September, corresponding to the changing external conditions associated with the onset of the autumn season.This external shift directly impacts the internal relative humidity levels within the room.The most significant relative humidity increase is noted near the air supply vent of the window-type air conditioner, particularly within the heights of Y=1.5 m to 2.5 m and within the Z=2 m to 2.5 m range.Conversely, relative humidity decreases as the cooler air moves closer to the room's walls.In the holy city of Najaf, interior temperatures undergo significant variations during the summer, spanning from May to mid-October.The temperatures gradually rise from May, peak in September, and then improve in October.Environmental shifts play a significant role in these temperature changes.Analyzing Table 10, it is observed that indoor relative humidity increased from 38.6% in May to 41.2% in June, decreased in September, and then rose again in October.The data was generally well-maintained, highlighting the importance of maintaining the circulation of exterior air to prevent moisture accumulation.The relationship between temperature and humidity is dynamic: higher temperatures reduce the air's moisture-holding capacity, thereby decreasing humidity while cooling the air increases humidity.In essence, higher temperatures can accommodate more moisture without a significant increase in humidity.Conversely, lower temperatures can elevate humidity levels.Using both cooling devices simultaneously can improve humidity and cooling conditions.
Evaporative air coolers effectively lower temperatures in dry, hot areas with low humidity.However, their usage in high-humidity conditions might lead to discomfort and dew formation.Combining a desert air cooler

Predicted mean votes
The PMV serves as an initial step in assessing room comfort.It relies on equations derived from theoretical principles, delineating comfort levels by differentiating cooling and heating gradients, denoted by negative and positive numbers, respectively.The internal conditions observed on the 14 th day of summer testing at 1:30 p.m., as presented in Table 11, depict fluctuations in interior temperature and relative humidity.Despite these variations, the results were deemed acceptable.

Water production efficiency
Water productivity from the return of humid, cool air during summer is particularly notable in managing hot and dry outdoor conditions.Table 12 illustrates that closing the louver air vent can elevate internal humidity, leading to the intake of humid, cool return air.As a result, this process amplifies moisture production, particularly noticeable in June, September, and October in comparison to May.By taking into account these factors and refining water extraction processes, it's plausible to enhance the efficiency of dehumidification systems, especially in coping with hot and dry outdoor conditions.

Conclusion
This study delineated a numerical simulation investigation aimed at enhancing the performance of AC systems by integrating a window-type air conditioner with a DEC-based air conditioning unit.The simulation setup incorporated an integrated window-type air conditioning system with an evaporative air cooler, allowing for various temperature conditions to be generated.The findings highlight that the integration of DEC significantly enhances both the PMV standard and water production when saturated cold air is cycled back to the air conditioner.The combined AC and EC system results in an augmentation of the refrigeration capacity.Moreover, the compressor's electricity demand decreases with every degree of air velocity-related temperature ∇u) = −∇ + .((∇ + ()  ) the fluid velocity, p is the fluid pressure, ρ is the fluid density, and μ is the fluid dynamic viscosity.The different terms correspond to the inertial forces: (1) =  (   +  • ∇u), pressure forces (2) = −∇, viscous forces (3) = .((∇ + ()  )

1 .
The structure of ANSYS Fluent 22R1

Figure 2 .Figure 3 .
Figure 2. Geometry of the designed room by ANSYS Fluent

Figure 4 .
Figure 4. View grid of the tester roomDuring the 3D modeling process using the ANSYS program, diverse grid structures were utilized, incorporating triangular cells in complex geometric regions and quadrilaterals, tetrahedral, and hexahedral cells in cubes, geometric volumes, polyhedrons, pyramids, or wedges.The choice of mesh type relied on the specific application.For this study, a combination of tetrahedral and hexahedral grids was employed, as shown in Fig 6.

Figure 6 .
Figure 6.Schematic of a typical evaporator coil

Figure 7 .
Figure 7. Schematic of testing room top view (imaginary)

Figure 13 .
Figure13.The drawing created by (a) design modeler 3D and (b) velocity vector plane for a researcher[22]

, 1 8 ,
and 25.Lines 1, 2, 9, and 10 were strategically positioned at specific heights and distances from the air supply slots of the EC and window AC.The most precise data readings were observed within specific elevations and lengths, showcased in Figures 3 to 10, highlighting differences in air temperature during the transition from summer to the beginning of winter, particularly noticeable in October and September.Near the air supply vent of the window air conditioner, as shown inFigures 16,17,20,22, and 23, at a height range of 1.6 to 2 meters, there was a decrease in air temperature.The air velocity ranged from 1.25 to 2 m/s for the window air conditioner, while the evaporative air cooler demonstrated a higher velocity, approximately 4 m/s, resulting in cooler conditions near the air supply and relatively warmer conditions near the walls.

Figure 15 .
Figure 15.Locations of straight lines (horizontal and vertical) inside the room

Chart 9 .
Temperatures for four months m, Y=2 m Chart 10.Temperatures for four months at Z=2.55 at X=3 m, Y=2 m Chart 11.Relative humidity for four months at Z=1.65 m, Y=1.6 m Chart 12. Relative humidity for four months at Z=1.65 m, Y=2 m Chart 13.Relative humidity for four months at Z=2.5 m, X=0.85 m Chart 14.Relative humidity for four months at Z=2.5 m, X=2 m

Chart 15 .
Relative humidity for four X=0.85 m Chart 16.Relative humidity for four months at Y=2 m, months at Z=2.5 m, X=3 m Chart 17.Relative humidity for four months at Y=2 m, X=2 m Chart 18. Relative humidity for four months Y=2 m, X=3 m Chart 19.Relative humidity for four months at Z=2.5 m, Y=2 m.Chart 20.Relative humidity for four months at Z=1.65 m, Y=1.6 m.

Figure 16 .Figure 17 .Figure 18 .Figure 20 .
Figure 16.Five planes of temperatures at two inlets and one outlet air

Figure 22 .
Figure 22.One plane for relative contour in one outlet (no.1)

Table 1 .
[1]ues of boundary conditions derived from researcher case[1]and compared to verification case 1

Table 2 .
Measured and numerical values of air velocities and temperatures at selected domain points for the

Table 3 .
The comparison depends on an error in the results Chart 1.Comparison of measured and numerical values of temperature and relative humidity of the domain points a) researcher [26] and b) verification case 1

Table 4 .
Additionally, plane views of both rooms are depicted in Figures13 and 14.Validation was determined by comparing the researcher's contour with the results of the present study.For comparison, the boundary conditions for case 2, as studied by the researcher, and the verification case 2 are detailed in Table4.

Table 4 .
[2]ues of boundary conditions derived from researcher case[2]and compared to verification case 2 Figures 13 and 14 illustrate the 3D and 2D design models and vector planes studied for both the researcher's case and Verification Case 2.

Table 6 .
Comparison depends on an error in the resultsError %

Table 7 .
Convergence between Mesh 1 and Mesh 2 results

Table 8 .
Position lines (horizontal and vertical) inside the room

Table 9 .
Comparison between temperatures of straight lines on the 14 th day for four months

Table 11 .
PMV values and comparison between the months on the same day Chart 21.PMV values and comparison between the months on the same day

Table 12 .
Value of water productivity (analytically) in f our months on the same day(14 th )

out Average temp. Average RH% W1 out W2 room M water room (L/hr)
Chart 22. Values of water productivity (analytically) in four months on the same day