Indoor thermal comfort assessment using PCM based storage system integrated with ceiling fan ventilation: Experimental design and response surface approach

Accepted Manuscript

Indoor Thermal Comfort Assessment using PCM based Storage System Integrated with Ceiling Fan Ventilation: Experimental Design And Response Surface Approach M. Alizadeh , S.M. Sadrameli PII: DOI: Reference:

S0378-7788(18)33271-7 https://doi.org/10.1016/j.enbuild.2019.02.020 ENB 9043

To appear in:

Energy & Buildings

Received date: Revised date: Accepted date:

22 October 2018 3 February 2019 17 February 2019

Please cite this article as: M. Alizadeh , S.M. Sadrameli , Indoor Thermal Comfort Assessment using PCM based Storage System Integrated with Ceiling Fan Ventilation: Experimental Design And Response Surface Approach, Energy & Buildings (2019), doi: https://doi.org/10.1016/j.enbuild.2019.02.020

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Indoor Thermal Comfort Assessment using PCM based Storage System Integrated with Ceiling Fan Ventilation: Experimental Design And Response Surface Approach M. Alizadeh11, S. M. Sadrameli1,*,

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1- Chemical Engineering Department, Tarbiat Modares University,P. O. Box 14115-114, Tehran, -Iran

Abstract

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The integration of Phase Change Materials (PCMs) in buildings as a potential method to improve indoor thermal comfort can be achieved via free cooling/heating approach. This paper presents the results of a study on indoor thermal comfort and energy efficiency regarding the PCM’s positive role when applied to new constructive solutions, inside a building with a ceiling fan-assisted ventilation system. The scope was driven to investigate the potential of the solution for overheating/overcooling mitigation. The thermal performance of proposed system was experimentally evaluated by comparing the behaviour of a prototype test room (including PCM panel), with the behaviour of a similar prototype test room, in which no PCM was added. First the experiments are conducted in an artificial climate inside laboratory environment chamber which is controlled by harmonic and linearly rising/falling temperature changing processes. Experiments were performed based on 5 level RSM CCD method to quantify the potential effects of using PCM panels and to determine individual/interactive effect of parameters on thermal discomfort index, PPD. Results indicate that minimum discomfort level can be achieved when inlet air temperature and humidity, fan rotating speed and PCM slab height and thickness were set to 29, 48%, 115rpm, 31 cm and 2.6 cm, respectively. PPD was obtained 4.1% in optimized condition. Then optimised tests rooms were subjected to realistic daily temperature profiles during winter and summer. In summer case, the experiments proved that the PCM application in one of the rooms lead to an overheating reduction of 13.83% representing a PCM efficiency of 56%. Under the winter condition during two months, the experiments showed proposed hybrid system can averagely reduce discomfort level around 1

Corresponding Author: Process Engineering Department, Faculty of Chemical Engineering, Tarbiat Modares University, P. O. Box 14115-114 Tehran, Iran [email protected]

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2.61% corresponding a PCM efficiency of about 35.49%. Based on the results, proposed system have the potential to shift cooling/heating energy demand away from peak hours.

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Keywords: Free cooling/heating, phase change material, ceiling fan, thermal comfort, response surface methodology 1- Introduction

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Residential and commercial buildings are among the few sectors that possess large energy saving potential by means of renewable energy utilization, green building concepts and building energy management[1]. The increasing demand for energy along with worldwide environmental threat has drawn the attention of researchers to devise the necessary steps for energy efficiency and sustainability in buildings. In order to reduce the energy consumption and to address the global environmental issues in buildings, more importance is given toward the implementation of energy efficient passive cooling technologies[2-5]. Passive cooling technology adopts the principle of supplying cool air to the buildings with minimal electricity consumption by avoiding the energy intensive mechanical type air conditioning systems[6, 7]. Although passive cooling is energy efficient, this technique has limitations regarding the controlling of thermal comfort conditions, architectural restrictions of the building envelope and security requirements due to facade openings. Those disadvantages of passive cooling could be abolished by free cooling ventilation systems[1, 8-10].

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The main principle of free cooling is to either receive or release an adequate amount of cooling energy during phase transition at constant temperature with low amplitude of temperature[1, 9]. Free cooling technology requires a storage unit which stores the thermal energy either by varying the internal energy of the storage medium (sensible heat storage) or by varying the phase of storage material (latent heat storage) or by both these processes[2]. When the phase change materials (PCMs) loses its cool energy, it gets discharged and to charge it again, cool ambient air is allowed to pass through it during the night or early morning hours. Advantage of free cooling over other ventilative cooling is that the accumulated cold can be extracted whenever it is needed by circulating ambient or room air through storage unit[11, 12]. For the free cooling, three main criteria need to be satisfied (i) the air outlet temperature (air supply temperature to the building) should meet the thermal comfort conditions in the building (ii) cooling time (i.e.

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discharging time) should be equal or more than the cooling period demand during the day time and (iii) the charging of the PCMs should be completed (meeting the daytime thermal energy) during night-time (i.e. charging time)[1].

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The consolidated review on the experimental, numerical investigations carried out exclusively on PCM based free cooling applications by several reviewers[1, 2, 811, 13, 14]. Inard et al. [15] analysed 14 office rooms in low-energy buildings to evaluate energy savings by free cooling by enhanced night-time ventilation. Zhou et al.[16] and Raj et al. [14]analyzed the heat transfer process between HTF and PCM by developing a modular heat exchanger for the free cooling application. Wang et al.[17-19] analyzed the charging and discharging process of a free cooling system for hot and dry climatic conditions. Panchabikesan et al.[9] presented the first pilot scale experimental work reporting the thermal performance of the PCM based free cooling system under real ambient conditions in a hot – dry climate. The impact of HTF mass flow rate/temperature, PCM plate thickness, melting front and cooling power was numerically investigated by Darzi et al.[20]. Thambidurai et al. [21]experimentally investigated the potential of free cooling application in reducing the room temperature during day hours using an inorganic PCM with the phase change temperature of 29 ◦C. The performance of PCM-based free cooling system with RT 27 as PCM was experimentally and numerically studied by Rajagopal et al. [22, 23]. Osterman et al. [24] numerically analyzed the functioning of a stand-alone hybrid system comprised of PCM (RT22 HC) based TES tank and solar air heater on an annual basis for year round thermal management of a building space.

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Thermal comfort depends on many factors, in which, temperature, humidity, and air speed are among the most important ones. In cooling scenarios, although low temperature is the first choice for comfort control, moderate air speed as a breeze can enhance thermal comfort at higher temperature by wind chill effect[25-27]. In residential and commercial buildings, temperature control is achieved by using air conditioners, while air speed can be increased by using ceiling fans[25]. The proper use of a ceiling fan in an air-conditioned space can result in better thermal comfort and energy savings[28-31]. Most fan studies have focused on the air flow volume induced by ceiling fans, but not on the room air movement distribution, and particularly not on the distribution in the occupied zone. Laboratory [3035]and field [36]studies compared energy efficiency index and indoor airflow distributions from different fan speeds and blade diameters. The studies indicated that the vertical temperature difference decreases with increasing fan speed, and

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that wider fan blades increase airflow coverage with increased energy efficiency [37], and that fans with a larger diameter and lower rotation speed reduce noise [38]. There has been considerable effort to improve the design of the fan blades in order to increase the flow volume, uniformity along the fan radius, and to increase the air movement coverage area. Adeeb et al. [39] focused on the number of blades and found that increasing the number of blades resulted in a higher flow volume. Afaq et al. [30] measured the effect of rake angles on the flow volume and found that a 6° upward rake angle (fan blades tilted above the horizontal level) provided the highest flow volume. Jain et al. [34]found that introducing winglets and spikes on the blade tip increased flow volume. However ceiling fans do not provide real ventilation, as there is no introduction of fresh air[28, 29, 40, 41]. Ceiling fans only circulate air within a room for the purpose of reducing the perceived temperature by method of evaporation of perspiration on the skin of the occupants[25]. Alizadeh and Sadrameli performed a numerical CFD model to study ceiling fan effect on thermal comfort inside the room. They simulated a large office room and optimized its performance using RSM method. Based on above mentioned literature, ceiling fan can only increase thermal comfort by wind chilling effect but cannot improve indoor temperature. The use of phase change materials (PCMs) may be a suitable solutions linked to the ceiling fan for overheating reduction and to provide better indoor thermal comfort.

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The aim of the research was to investigate the effectiveness of PCM in reducing the zone air temperature and improving thermal comfort in an experimental room under running ceiling fan. Two identical test rooms were considered for cooling application. One test room was used as the control while the other was used as a retrofit room containing PCM storage medium. Two series of experiments were performed. The first one was carried out in a fully laboratory conditions and second series of tests was performed for more realistic conditions. For laboratory conditions, response surface method was used to evaluate and optimize proposed system performance. The second series of tests were performed for more realistic conditions. This study was focused on the Summer and Winter season of Tabriz (Iran) area. In each experiment, indoor thermal comfort was recorded and compared with control case.

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2- Methodology 2.1. PCM selection

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In the building applications, the PCMs with a phase change temperature (18–30 °C) are preferred to meet the need of thermal comfort [27]. In this study, commercial available PCM S27 was used because of its little volume expansion during melting process (lesser than 4%) and suitable temperature range for air conditioner between 22 °C and 24 °C (Table 1). 2.2. Experimental setup

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The tests were performed using two identical fully instrumented test rooms with interior dimensions of 1.2m×1.2m×1.5 m and designed to operate independently [40]. The test rooms are located at University of Tarbiat Modares, Iran (see Fig. 1). Both rooms were elevated 0.5 m above the ground and insulated using 0.1 m thick pink glass wool in the walls and ceiling and 0.06 m of wood plastic composite under the floor to reduce heat loss from the rooms [39]. The first, room referred to as R1, is used as the base case for all experiments throughout this study and has ordinary ceiling fan. In second room, referred to as R2, PCM containers installed 3cm above the ceiling fan. Each Room was equipped with an AC unit to provide cooling demand as required and a power meter to monitor the electricity consumption. An axial 3-blade ceiling fan (Maker: Aramis; Model: 3215) was installed in the middle of the ceiling with the mid-plane of the blades 30 cm below the ceiling. The fan measures 45 cm in diameter with blades that are 20 cm long, 2mm thick and have width of 7 cm at the base and 9 cm at the tip. The pitch angle of the blades is 6 and the deflection of their tips due to gravity is 1 cm relative to the base. Fan power was 20W and equipped with a DC inverter to provide different rotating direction. A programmable logic controller (PLC) Siemens model S7224CPU was used to change fan rotating direction during day (7 Am – 10 Pm) and night (10Pm-7Am). 3 Aluminum PCM slabs with dimension of 20cm × 10 cm were installed between the ceiling and fan. The directions of the airflow by ceiling fan were the upward and downward directions. Fig. 2 shows the airflow measurement points. The air velocity measurement was conducted by a threedimensional ultrasonic anemometer (Aramis, AN360). T type thermocouples were used for all temperature measurements inside and outside the experimental rooms. All thermocouples were calibrated against a reference thermometer (Ebro TFX430) from 0 to 60 oC. A light bulb was installed on the wall and connected to a dimmers and digital timer. This arrangement simulated a full daily cycle (day and night) for

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total of 24 hours. Temperature was collected using the data logging system(Agilent 34970A). It collected temperatures in 20 second increments. Inlet air supply and outlet air exhaust were provided to introduce fresh air inside the rooms. Inlet air specifications including air velocity, temperature and humidity were measured using Lutron Anemometer model Am-4205.

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Thermal Comfort Datalogger-HD32.2 PCE Instruments was used for measuring and recording the room indoor environmental parameters such as operative temperature, relative humidity, air velocity in order to derive predicted mean vote (PMV/PPD). Three external sensors were connected to the device which was placed in middle of room, at height 0.4m as recommended by ASHRAE [13]. The data values were measured and recorded every minute and the average of each 15 minutes was determined and is presented in the results section. 2.3. Design of experiment

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y  f (x 1 , x 2 ,..., x k )

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Design of experiments is a systematic approach for distinguishing the importance of process variables, their interaction and controlling them toward the optimum response. There are four classes of experimental designs: mixture experiments, factorial design, combined design, and response surface . Response surface methodology (RSM) is applied for multivariate optimization with the minimum number of experiments. The accomplishment of experiments with reduced runs leads to less consumption of material and time, likewise less laboratory work. If all variables are assumed measurable, the response surface can be expressed as follows: (1)

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The aim is to optimize y. It is assumed that the independent variables are continuous and controllable by experiments with negligible errors. It is mandatory to find an appropriate approximation for the true functional relationship between independent variables and the response surface. Second order polynomial is usually considered as a full model in RSM: k

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y  0   i x i  ii x ii2  ij x i x j  

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where y is the response (PPD), βs are regression coefficients, xi is a coded independent variable, ε is the error and k is the number of factors . The most common response surface methodology is the central composite design [13]. In

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this design each variable has 5 levels; a center point, two factorial points with the distance of 1 unit from center point, and two star points that allow estimation of curvature and have the distance of a from center point. Four selected control factors and their levels are shown in Table 2. The relation between the coded and actual values is as following equation: x i  x cp

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x i

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Xi 

where Xi is the coded value of each factor; xcp is the value of the xi at the center point obtained from the preliminary experiments; and Δxi presents the step change.

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As the last step, Analysis of Variance (ANOVA) was used through a statistical analysis software (Design Expert 8.0.5b) for graphical analyses of the data to obtain the interaction between the process variables and the responses. The statistical significance was checked by the Fisher F-test, and model terms were evaluated by the p-value (probability) with 95% confidence level. The quality of the fit polynomial model was expressed by the coefficient of determination R2 and adjusted R2 in the same program. The process variables investigated were inlet air temperature(X1), humidity(X2), fan speed (X3), distance between ceiling and fan(X5) and PCM slab thickness(X4). Three responses was PPD % as mentioned above.

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2.4. Experimental procedure

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Two series of experiments were performed. The first one was carried out in a fully laboratory conditions, i.e. inlet air temperature (which can be treated as an independent variable) was set by means of an air conditioning system, according to arbitrary chosen temporal characteristic. The required humidity in each experiment was provided by a humidifier (Ultrasonic 600 Hirad Co.). In addition, a fan with 20W power was used to create appropriate air velocity. In each test, indoor temperature, PMV and PPD were recorded every 20s. Experiments were performed for 3 hours. The second series of tests was performed for more realistic conditions, i.e. air was taken from the outside of a laboratory building and daily variations of air temperature were closer to ambient air temperature variations. The experiment was done from June 1st to 5th in summer and December 1th to 5th in Winter case. The weather station records hourly outdoor dry bulb temperature, outdoor humidity, rain rate, solar radiation, wind speed and direction and barometric pressure. Indoor air temperature were recorded every 10 min. This

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study was focused on the summer and Winter season of Tabriz area. During summer time of the year, the daily average maximum outdoor temperature is 28.9 ◦ C and the daily average minimum outdoor temperature is 20.2 ◦C. During Winter, the daily average maximum outdoor temperature is 18.5 ◦C and the daily average minimum outdoor temperature is 7 ◦C This large temperature variation should allow PCM to melt completely during discharging period and solidify during charging process, and thus work efficiently. For winter cases, a heater with input power of 150W was provided to keep room temperature above 18 oC. 3- Results and discussion 3.1. Velocity measurement results Upward airflow

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In first case, anemometer was set at 10 cm above the ceiling fan. Based on the Fig.3, the airflow pulled up by the ceiling fan sweeps along the ceiling. As the distance between ceiling and fan increases, air velocity in X direction becomes smaller. This can be attributed to the decreasing outward air velocity from the ceiling fan. The air, discharge by ceiling fan, is spread over the ceiling of the room and as the distance increases, ceiling surface effect on air movement decreases. The maximum value of velocity in X direction is located at x= 20cm. In addition, maximum air speed increases toward the center of ceiling and reaches to its maximum value in fan blade span. This means that maximum speed occurs at blade tip. The maximum value also increases with decreasing the distance. This can be explained by accelerating suction flow when the ceiling surface is closer to ceiling fan. In the case of Z direction, the velocity decreases as moving away from the fan. The highest value of velocity in Z direction observed when the distance between the ceiling fan and ceiling surface increases. Higher distance between the fan and ceiling increases suction air volume and as result, increases air velocity. In all cases, no significant differences for velocity component were observed at Z =10 cm. For downward airflow at Z = +10 cm, the results are in the same trend as upward air flow (Fig. 4). At Z = -10 cm, velocity component in x direction becomes larger toward the fan center and reducing the distance increases the intensity of it. It can be explained by increasing rate of the wind flowing toward the ceiling fan rotational center. The highest velocity in Z direction happens nearer to the ceiling fan rotating circle and its maximum becomes smaller as reducing the distance. In smaller distance, air converges around the ceiling fan rotating circle and

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accelerates in the horizontal direction. Based on the figures, significant results can be obtained for the distance smaller than 30 cm.

3.2. Temperature measurement results

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Vertical profile of temperature was shown in Fig.5 at different fan speed and height. Based on the figure, 0.1 ~ 2.1 oC difference in temperature was observed when ceiling fan was turned off. Temperature variation was reduced by increasing fan speed and its distance from ceiling surface. The higher rotational speed, the more beneficial to moderate the vertical temperature difference. Increasing fan speed required more power to rotate and as a result, room temperature slightly increased.

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Fig.6 shows PCM temperature at different fan rotation speed. It is expected that the higher rotation speed can enhance convection flow heat transfer and thus speed melting process. From experimental results, at each fan speed, the PCM starts to transit phase from solid to liquid by absorbing heat from the air. From heat transfer point of view, due to the phase change involved, the heat transfer coefficient on the PCM is greatly improved such that the PCM side is not the main thermal resistance. Therefore due to the flow rate increase, the heat transfer enhancement on the air side can significantly affect the overall heat transfer and thus greatly reduce the completion time of phase change. Once the PCM is liquefied, the PCM temperature increases.

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Fig.7 shows inlet air temperature effect on PCM temperature during melting process. Based on the figure, the significant temperature difference between air and PCM and small sensible heat transfer involved, the PCM can all quickly approach to transition temperature point. After that, at each inlet temperature, the PCM starts to transit phase from solid to liquid by absorbing air heat. The higher air temperature can enhance the overall heat transfer during the phase change period and therefore speed up the charging process. Although the higher fan speed can speed up melting process, the temperature difference between PCM and inlet air seems to dominate.

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3.3. RSM Results

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As discussed in the method section, the studied variables which affected thermal comfort inside the test rooms were inlet air speed, temperature, humidity, fan rotation speed, ceiling fan height and PCM thickness. CCD was conducted to identify the simple and combined effects of operating parameters on PPD. Three major steps involved in this process: performing the statistically designed experiments, estimating the coefficients in the proposed model and predicting the response of process, and checking the validity of the model. Different models were tested to find the best fitting model. The mathematical modeling was developed in a way that it would fit the data to the highest order polynomial. Table 3 shows the results of analysis of variance (ANOVA) of the models which were fitted to responses. The significance of each model was checked using p-value. It was observed that only Quadratic model fitted models is significant in 95% confidence level (pvalue<0.05). The following response equations were used to correlate removal efficiencies and independent variables n terms of coded factors regardless of the significance of coefficients: PPD  9.68  3.45A  1.15B  0.96C  1.57D  2.32E

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 0.56A 2  1.57B 2  0.80C 2  0.25D 2  0.37E 2  0.63AB  0.15AC  0.015AD  0.48AE  0.28BC  0.0068BD  0.028BE  0.055CD  0.03CE  0.022DE

(4)

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Analysis of variance (ANOVA) was used to evaluate the model (Table 4). F-value is a useful tool to determine the statistical significance of the regression model. It is measurement of variance of data about the mean, based on the ratio of mean square of group variance due to error. Good prediction of the experimental data can be achieved when the tabulated Fvalue becomes smaller than calculated F-value. The “Model F-value” of 40.3 shows that the model is highly significant. The associated p-value was employed to predict whether the F-statistics were large enough to indicate statistical significance. p-values less than 0.05 indicate significance. P value was obtained <0.0001 which implies there is only a 0.001% chance that a “Model F-Value” with this magnitude could occur due to noise and the model is strongly significant over the 95% confidence interval. The Lack of Fit F-value of 0.51 implies the Lack of Fit is significant. There is only a 68% chance that a Lack

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of Fit F-value this large could occur due to noise. The non-significance of lack-offit is favorable and it specifies the high predictability of the model.

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Model summary statistic is listed in Table5. The coefficient of determination (R2) of the model for response was noted as 0.96 suggested that the fitted polynomial equations had a significant degree of fit of the model and only about 4% of the total variation cannot be explained by the fitted model. The pred R-squared of 0.91 was in reasonable agreement with the “adj Rsquared” of 0.94 because the difference between these values is within 0.01 which confirmed good predictability of the model. Moreover, the standard deviation for the model was 1.12 and it has been confirmed that smaller the value of standard deviation the better is the model because the predicted value obtained will be found closer to the actual value for the response. Adequate precision is a measure of the signal to noise ratio and a value greater than or equal to 4 is always desirable. In the present analysis, a value of 26.1 indicated sufficient model discrimination. On the other hand, a relatively lower value of the coefficient of variation (CV = 9.42%) indicated dependability and reproducibility of the model. Predicted versus actual plot of the response was presented in Fig. 8. The values predicted by the model (from Eq. (4)) and the results obtained by the experiments are distributed uniformly around a 45◦ line. Normal Probability Plots for is shown in Fig 9. The normal probability plot is a graphical technique for assessing whether or not a data set is approximately normally distributed. The data are plotted against a theoretical normal distribution in such a way that the points should form an approximate straight line. Departures from this straight line indicate departures from normality. The points on plots form a nearly linear pattern, which indicates that the normal distribution is a good model for this data set.

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The significance of the parameter coefficients and the associated standard error of each term in Eq. (4) are presented in Table 4. According to p-values (<0.05 is significant) A,B, C,D, E, AB, AC, AE, A2, B2, C2, are the significant model terms. It is remarkable that, although BC,CE and E2 terms have a p-value slightly greater than 0.05, they are kept in the relevant correlations. The ANOVA results reveal that the significance of PPD parameters is (the most to the least significant): inlet air temperature > PCM thickness> inlet air humidity>fan rotating speed> fan distance from ceiling. The highest F-value (475.13) and the lowest p-value (<0.0001) is assigned to the inlet air temperature among other variables. This result indicates the inlet air temperature is the most important variable in PPD evaluation under the current circumstances. Among the interactions, the simultaneous

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influence of the inlet air temperature and humidity has the highest significance (Fvalue (12.7), pvalue (0.0036)).

The effects of the parameters on PPD

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Perturbation plots are illustrated in Fig. 10 for both responses. This figure shows how the responses change as each factor moves from the chosen reference point, with all other factors held constant at the reference value. The reference value is the coded zero level of each factor. As it mentioned before and Fig.10 approves that, factor D produces a relatively small effect on PPD as it changes from the reference point. It also shows the direct nonlinear dependence of PPD on A,B and C.

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In order to reach a complete understanding of the thermal comfort inside the room, along with the two-dimensional contours, three-dimensional response surface plots are essential. These plots presents two factors influence on response while other factors are kept constant at the central point. Figs. 11-17 show the simultaneous influence of considered parameters on PPD. The significance of the investigated interactions can be found by the elliptical shape of the contour plots. When the contour lines become parallel with either of the axes, it can be concluded that no interaction would exist between the two variables.

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The simultaneous influence of inlet air temperature and humidity on PPD was illustrated in Fig 11. based on the figure at a constant air humidty, increasing air temperature increases PPD. The parameters for air temperature include the mean interior temperature and the criteria for horizontal and vertical temperature distribution in order to reduce area s of local thermal discomfort to minimum. The air temperature inside the room is in nearly homogeneous due to the installed ceiling fan. Higher inside air temperature implies higher cooling loads which results in melting PCM faster (Fig. 12). Although this will temporarily reduce the discomfort level, it will not allow to the use of phase change material for a longer time period. Consequently, despite the improvement of the PPD for a short time, the overall PDD for the considered period will increase. Based on the results, better comfort level can be assessed at higher temperature providing that PCM section be considered inside the room. It must be noted that keeping air velocity in a constant value while increasing air temperature is another reason for higher discomfort level.

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Humidity has a minor role to play in PPD variation, except for certain extreme conditions[32]. With lower inlet air temperature, thermal perception and skin temperature and wettedness are generally not affected much by humidity. However, indoor environments with humidity higher than 70%, preventing the evaporation of sweat from the skin, make it very difficult to cool down. At operative temperatures beyond the upper comfort limit of temperature, higher humidity prevents the evaporation of sweat from the skin, which is the main way to cool down. This results in increasing discomfort level. Therefore, higher inlet temperature needs to keep down humidity level.

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Fig. 13 show the interaction between inlet air temperature and fan rotation speed. At a higher inlet air temperature, fan speed slightly increased thermal comfort; however, it has a more pronounced effect at lower levels for inlet air temperature. The faster the air movement, the greater the exchange of heat between the person and air. As an illustration, greater air velocity can compensate for rise in temperature, improve air quality perception [43] and ensure performance level in warmer environment. Moving air in warm or humid conditions can increase heat loss through convection without any change in air temperature. As said before, increasing inlet air temperature rises temperature gradient vertically inside the room. This will reduce cooling effect of higher speeds. Higher fan speed will pull warm air around the fan motor and under the ceiling down. Ceiling fans, in contrast to air conditioners, do not lower air temperature or air humidity in rooms. Ceiling fans cool the bodies, but they do this only by increasing the air movement or airflow in the room. With increased air movement, the body sweat evaporates easier. And as sweat evaporates, it takes away some of body heat; thus, cooling persons.

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Fig. 14 show the interaction between inlet air temperature and fan distance with ceiling surface. As can be seen, discomfort level decrease with increasing ceiling fan distance. As said before, the maximum value of air velocity becomes closer to the center of the ceiling fan and the maximum value is smaller when the ceiling fan is closer to the ceiling surface. Increasing air velocity will improve thermal comfort by creating a wind-chill effect. However beyond a value, increasing the distance creates inappropriate conditions for thermal discomfort at higher temperature. Higher distance can result in poor airflow in the room and increase discomfort level. For lower temperatures, the distance does not show a significant effect on PPD.

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Fig. 15 show the simultaneous influence of fan rotation speed and humidity. Based on the figure, when the relative humidity is above 80%, high airflow velocities would again work against thermal comfort. In hot and humid environments where the relative humidity varies from 50% to 100%, increasing the airflow velocity will accelerate the evaporation of sweat by moving the saturated air away from the skin and replacing it with unsaturated air. Furthermore, at a relative humidity of 20% (dry conditions), the airflow velocity will accelerate moisture removal at the skin surface increasing cooling due to evaporative processes. Above 80% relative humidity (humid conditions) there is very little evaporative potential as the ambient air is already close to saturation, making air movement relatively ineffective.

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The interaction of fan speed and PCM thickness was presented in Fig. 16 . Higher air velocity will increase heat transfer rate into the PCM section and decrease room air temperature sharply. As a result, higher air velocity together with lower air temperature will not improve thermal comfort. On the contrary, lower fan speed makes PCM melt slowly and the required temperature gradients was not provided to create favorable conditions. Larger PCM thickness will results in better thermal comfort for time period. The presence of phase change material results in thermal comfort assessment at lower fan rotating speed compared to the cases without PCM.

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Finally, the interaction between PCM thickness and inlet air humidity was presented in Fig 17. Based on the figure, the presence of PCM reduces for higher humidity discomfort compared to the case without storage unit. Optimization and validation

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To determine the optimum conditions for the proposed systems, the optimization tool of DesignExpert® 7.0.0 was utilized. The program strategy was to optimize the response via the maximization of an objective function named the desirability function ranging from zero to one. When desirability functions became one, the program searched for the conditions in which desirability reached a maximum level. To achieve the optimum conditions, all the factors were selected based on Tabriz weather condition while PPD was defined as minimum. However, a comprehensive optimization is the one that accounts the economic aspects of a process along with maximizing its efficiency. Accordingly, the optimum process variables and the related response are presented in Table 6. In order to check the accuracy of the optimization, the model was validated by performing thermal

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experiments in test room B under the optimum condition. The minimized PPD was. These indicated that RSM was an effective approach for obtaining desired operating conditions in proposed system during discharging process. 3.4. Thermal comfort assessment in real condition

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To test the effectiveness of PCM incorporation into the ceiling fan, series of tests was performed for more realistic conditions, i.e. air was taken from the outside of a laboratory building and daily variations of air temperature were closer to ambient air temperature variations. In this step, the room without PCM unit was optimized separately using RSM results. PLC program was used to change fan rotating direction during day and night periods. A 5 days period from 1/06/2017 to 5/06/2017 was used to perform the tests. Temperature variation inside the rooms was recorded and compared.

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The recorded temperature were presented in Fig18. for rooms A and B. During day time, the temperature in room A (without PCM) is higher than Room B. On the contrary, Room B possess higher temperature during nighttime. Moreover, Room B temperature peak time lag behind those of the Room A. Comparison of peak temperatures between Room A and Room B was presented in Table 7. Based on the table, Room A peak temperature is higher of 2.5 oC than in the Rom B; while , the minimum temperature of Room B is higher 2.3 oC than that of the Room A. This can be explained by discharging PCM heat into the room during nighttime. An interesting point is that the indoor temperature fluctuation is smaller when PCM was employed which shows its advantage for smoothing temperature difference of day and night.

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The tests were continued for two months. The results presented in Fig.19. Obviously, Room B has a lower indoor temperature than Room A without PCM unit. In summer period, the Room A average temperature during the day is 6.3 oC higher than that of Room B. This is due to the PCM storage ability which prevent temperature increment by absorbing heat from the room. Mostly, higher temperature for Room B happened outside the operation time (nighttime). This is a proof for significant potential of building energy efficiency. The completely or significant portion of required energy for space cooling can be shifted to off-peak period to cool the interior of the room which would bring significant economic benefits on both energy demand and supply. This shifting technique is achieved through the storing off-peak periods energy and utilizing it during peak period.

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To test the applicability of proposed system during the cold days, both rooms were operated in Winter weather condition. The recorded temperature for 5 days was presented in Fig.20. For rooms A and B. Room B possess lower temperature during the day. Ceiling fan creates an updraft and will push air down with lower temperature. At first glance, one may conclude that discomfort level will be increase in this situation. Taking a deeper look into the process shows that PCM only uses extra heat load which employed to make the room warmer. During the night, ceiling fan sucks cool air up and rises its temperature through PCM solidifying. Based on the figure, the peak temperature in Room B is lower of 1.9 oC than that in the Room A. Contrary to the above results, the minimum temperature of PCM room is higher 0.9 oC than that of the room without PCM.

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The tests were continued for two months. The results presented in Fig.21. Based on the figure, Room B temperature was apparently higher than Room A during nighttime. Based on the results, Room B can bring larger temperature drop during winter day and larger temperature rise during winter night.

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Standard EN 15251was used to investigate the indoor comfort assessment for summer period. Based on the figure, periods of overheating exists for both rooms. This was concluded from extensive period above the upper limit for the indoor air temperature (Fig. 22) . In terms of overheating, it is possible to observe the period of overheating of 24.37% for the Room A and 10.54% for the Room B. For the corresponding period evaluated in the room with PCM, discomfort rate was reduced 13.83% for the cooling season. This results indicates a PCM efficiency of 56%.

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Indoor air temperature was represented for the heating period in Fig. 23 From the figure, it can be concluded that overheating exists for both the rooms. For room A, a large cloud of points for indoor air temperatures monitored which found below the lower limit defined by the standard. This means that higher discomfort rate during the heating season was occurred. Comparing Room A and Room B discomfort level shows a reduction of discomfort for the heating season of 2.61%. This reduction shows PCM efficiency of 35.49% (relative percentage), between results of discomfort time of the room with and without PCM. Analyzing discomfort time for heating and cooling season proved that PCM provides a potential thermal regulation effect by reducing the discomfort level. This was concluded by reducing temperature swing.

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Conclusion

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The paper presents results of the experimental tests of thermal performance characteristics of special ceiling fan, which aims to improve the free cooling in the building. The experiments were performed in both laboratory and real weather condition. Air velocity profile was investigated at different fan distance from the ceiling surface. The results showed that increasing distance will increase air velocity in vertical direction. It was confirmed that the ceiling fan is beneficial to moderate the vertical temperature difference, and the higher rotational speed, the more beneficial to improve the vertical temperature stratification. In order to investigate PCM unit performance together with ceiling fan, as a new free cooling system, two tests room were built. The only difference between the rooms was PCM unit. RSM design of experiment method was employed to evaluate individual/interactive influences of parameters (including inlet air temperature and humidity, fan rotating speed, fan distance from ceiling surface and PCM slab thickness) on thermal comfort inside the rooms. RSM with an 50-run CCD design was performed and second-order regression models were generated. ANOVA was conducted to validate the significant consistency between experimental values and predicted ones. The fundamental objective of this work was to determine the most important parameter of the mentioned process. The ANOVA results enunciated that the significance of the parameters is as follows (the most to the least significant): inlet air temperature > PCM thickness> inlet air humidity>fan rotating speed> fan distance from ceiling. The 3D surface graphs were generated to investigate parameters effect on PPD. The results proved that including PCM unit together with ceiling fan decrease temperature negative effect on PPD. Analysis of Variance (ANOVA) showed a satisfactory agreement of the predicted and experimental data. High values of the determined R2 coefficients of the model (>0.99) confirm that the proposed equation fits the experimental data accurately. The obtain desired operating conditions to minimize PPD were inlet air temperature of 29, humidity of 48%, fan rotating speed of 115rpm, fan height of 31 cm and PCM thickness of 2.6 cm. PPD was obtained 4.1% in optimized condition. The second series of tests was performed for more realistic conditions. Tests rooms were adjusted to optimized conditions. This study was focused on the summer and Winter season of the Tabriz area. The room with PCM was cooler than the room without PCM, and the peak temperature was also delayed by PCM. The peak time shifting and peak temperature reducing indicated the application of PCM used in building can benefit the indoor thermal comfort and building energy efficiency.

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For summer case, Room A(without PCM) peak temperature is higher of 2.5 oC than in the Rom B (with PCM); while , the minimum temperature of Room B is higher 2.3 oC than that of the Room A. Comparing Room A and Room B discomfort level shows a reduction of discomfort for the heating season of 2.61%. This reduction shows PCM efficiency of 35.49% (relative percentage), between results of discomfort time of the room with and without PCM.

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Reference

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Alizadeh, M. and S.M. Sadrameli, Development of free cooling based ventilation technology for buildings: Thermal energy storage (TES) unit, performance enhancement techniques and design considerations - A review. Renewable and Sustainable Energy Reviews, 2016. 58: p. 619-645. Zeinelabdein, R., S. Omer, and G. Gan, Critical review of latent heat storage systems for free cooling in buildings. Renewable and Sustainable Energy Reviews, 2018. 82: p. 2843-2868. Saffari, M., et al., Passive cooling of buildings with phase change materials using whole-building energy simulation tools: A review. Renewable and Sustainable Energy Reviews, 2017. 80: p. 1239-1255. Akeiber, H., et al., A review on phase change material (PCM) for sustainable passive cooling in building envelopes. Renewable and Sustainable Energy Reviews, 2016. 60: p. 1470-1497. Souayfane, F., F. Fardoun, and P.H. Biwole, Phase change materials (PCM) for cooling applications in buildings: A review. Energy and Buildings, 2016. 129: p. 396-431. Alam, M., et al. A Comparative Study on the Effectiveness of Passive and Free Cooling Application Methods of Phase Change Materials for Energy Efficient Retrofitting in Residential Buildings. in Procedia Engineering. 2017. Geetha, N.B. and R. Velraj, Passive cooling methods for energy efficient buildings with and without thermal energy storage - A review. Energy Education Science and Technology Part A: Energy Science and Research, 2012. 29(2): p. 913-946. Osterman, E., V. Butala, and U. Stritih, PCM thermal storage system for 'free' heating and cooling of buildings. Energy and Buildings, 2015. 106: p. 125-133. Thambidurai, M., et al., Review on phase change material based free cooling of buildings-The way toward sustainability. Journal of Energy Storage, 2015. 4: p. 74-88. Kamali, S., Review of free cooling system using phase change material for building. Energy and Buildings, 2014. 80: p. 131-136. Waqas, A. and Z. Ud Din, Phase change material (PCM) storage for free cooling of buildings - A review. Renewable and Sustainable Energy Reviews, 2013. 18: p. 607-625. Brun, A., et al., Summer comfort in a low-inertia building with a new free-cooling system. Applied Energy, 2013. 112: p. 338-349. Iten, M., S. Liu, and A. Shukla, A review on the air-PCM-TES application for free cooling and heating in the buildings. Renewable and Sustainable Energy Reviews, 2016. 61: p. 175-186. Raj, V.A.A. and R. Velraj, Review on free cooling of buildings using phase change materials. Renewable and Sustainable Energy Reviews, 2010. 14(9): p. 2819-2829. Inard, C., J. Pfafferott, and C. Ghiaus, Free-running temperature and potential for free cooling by ventilation: A case study. Energy and Buildings, 2011. 43(10): p. 2705-2711. Zhou, G., Y. Yang, and H. Xu, Energy performance of a hybrid space-cooling system in an office building using SSPCM thermal storage and night ventilation. Solar Energy, 2011. 85(3): p. 477485. Waqas, A., M. Ali, and Z. Ud Din, Performance analysis of phase-change material storage unit for both heating and cooling of buildings. Int J Sustain Energy, 2015: p. 1-19. Waqas, A. and S. Kumar, Thermal performance of latent heat storage for free cooling of buildings in a dry and hot climate: An experimental study. Energy and Buildings, 2011. 43(10): p. 2621-2630. Waqas, A. and S. Kumar, Utilization of latent heat storage unit for comfort ventilation of buildings in hot and dry climates. International Journal of Green Energy, 2011. 8(1): p. 1-24.

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19.

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Darzi, A.A.R., et al., Numerical investigation of free-cooling system using plate type PCM storage. International Communications in Heat and Mass Transfer, 2013. 48: p. 155-163. Thambidurai, M., et al., Experimental investigation of free cooling using phase change materialfilled air heat exchanger for energy efficiency in buildings. Adv Build Energy Res, 2016: p. 1-11. Rajagopal, M., et al., Investigation on phase change material-based flat plate heat exchanger modules for free cooling applications in energy-efficient buildings. Adv Build Energy Res, 2016: p. 1-23. Rajagopal, M., et al., Free cooling potential and technology options for thermal energy management of a commercial building in Bangalore City, India. Energy Engineering: Journal of the Association of Energy Engineering, 2014. 111(2): p. 11-24. Osterman, E., et al., Parametrical analysis of latent heat and cold storage for heating and cooling of rooms. Applied Thermal Engineering, 2015. 84: p. 138-149. Alizadeh, M. and S.M. Sadrameli, Numerical modeling and optimization of thermal comfort in building: Central composite design and CFD simulation. Energy and Buildings, 2018. 164: p. 187202. Zhang, S., et al., Optimization of room air temperature in stratum-ventilated rooms for both thermal comfort and energy saving. Applied Energy, 2017. 204 p. 420-431. Djamila, H., Indoor thermal comfort predictions: Selected issues and trends. Renewable and Sustainable Energy Reviews, 2017. 74: p. 569-580. Chen, W., et al., Experimental and numerical investigations of indoor air movement distribution with an office ceiling fan. Building and Environment, 2018. 130 p. 14-26. Zhai, Y., et al., Human comfort and perceived air quality in warm and humid environments with ceiling fans. Building and Environment, 2015. 90: p. 178-185. Afaq, M.A., et al. Study on the design improvement of an indoor ceiling fan. in Proceedings of 2014 11th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2014. 2014. Bassiouny, R. and N.S. Korah, Studying the features of air flow induced by a room ceiling-fan. Energy and Buildings, 2011. 43(8): p. 1913-1918. Parker, D.S., T. Zambrano, and T. Kiceniuk, High Efficiency Twisted Leaf Blade Ceiling Fan. 2008. Koschenz, M. and B. Lehmann, Development of a thermally activated ceiling panel with PCM for application in lightweight and retrofitted buildings. Energy and Buildings, 2004. 36(6): p. 567578. Jain, A., et al. Experimental investigation of the flow field of a ceiling FAN. in Proceedings of the ASME Heat Transfer/Fluids Engineering Summer Conference 2004, HT/FED 2004. 2004. Volk, S.J., Propeller Breeze Enhancing Blades for Conventional Ceiling Fans. 1990. Lin, S.C. and M.Y. Hsieh, An integrated numerical and experimental analysis for enhancing the performance of the hidden ceiling fan. Advances in Mechanical Engineering, 2014. 2014. Sonne, J. and D. Parker, Measured ceiling fan performance and usage patterns: Implications for efficiency and comfort improvement. ACEEE Summer Study on Energy Efficiency in Buildings, 1998. 1: p. 335-341. Aynsley, R., Fan size and energy efficiency. The International Journal of Ventilation, 2002. 1(1): p. 33-38. Adeeb, E., et al. Shape optimization of non-linear swept ceiling fan blades through RANS simulations and Response Surface Methods. in Proceedings of 2015 12th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2015. 2015. Babich, F., et al., Transient three-dimensional CFD modelling of ceiling fans. Building and Environment, 2017. 123: p. 37-49.

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Gao, Y., et al., Ceiling fan air speeds around desks and office partitions. Building and Environment, 2017. 124: p. 412-440.

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Fig.1 The concept of proposed system

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Fig.2 Experimental setup

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Fig.3 velocity component during upward airflow.

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Fig.4 velocity component during upward airflow.

Fig.5 Vertical profile of temperature

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Fig.6 PCM temperature variation at different fan speed

Fig.7 PCM temperature variation at different inlet air temperature

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Fig.8 Predicted versus actual plot of PPD

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Fig.9 Normal probability plot of residuals

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Fig. 10 – The perturbation plot for the PPD

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Fig.11 Effect of inlet air temperature and humidity on PPD; 3D surface graph

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Fig.12 Effect of inlet air temperature and PCM thickness on PPD; 3D surface graph

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Fig.13 Effect of inlet air temperature and fan rotation speed on PPD; 3D surface graph

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Fig. 14 Effect of inlet air temperature and fan height on PPD; 3D surface graph

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Fig. 15 Effect of inlet air humidity and fan rotation speed on PPD; 3D surface graph

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Fig.16 Effect of PCM thickness and fan rotation speed on PPD; 3D surface graph

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Fig. 17 Effect of inlet air humidity and PCM thickness on PPD; 3D surface graph

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Fig.18 Comparison of indoor temperature for Room A(without PCM) and Room B(with PCM)

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Fig.19 Comparison of indoor temperature in two month for Room A(without PCM) and Room B(with PCM)

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Fig.20 Comparison of indoor temperature for Room A(without PCM) and Room B(with PCM) (winter case)

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Fig.21 Comparison of indoor temperature in two month for Room A(without PCM) and Room B(with PCM) (winter case)

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Fig. 22. Indoor air temperature for the cooling season

Fig. 23. Indoor air temperature for the heating season

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Table 1. PCM Thermo-physical properties Density

Specific heat (kJ/kg) 2200

(kg/m3) 1530

Thermal conductivity (W/m K) 0.54

Viscosity (mm2/s) 111.1

Thermal expansion (1/K) 0.001

Latent heat of fusion (kJ/kg) 183

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Melting temperature (°C) 22-25

Table 2. Original variables in the CCD design. -1 Level 28 35 90 25 0.75

+1 Level 32 65 130 35 2.25

-α 26 20 70 20 0

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Name A: Inlet air temp. B:Inlet air humidity C:Fan rotating speed D:Fan height E:PCM thickness

PT 2 2.12 1.12 1.05

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Source Linear 2FI Quadratic Cubic

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Table 3. Model Summary Statistics

R-Squared 0.8327 0.8551 0.9653 0.9853

Adjusted Predicted R-Squared R-Squared PRESS 0.8137 0.7936 217.68 0.7912 0.8017 209.21 0.9413 0.9319 145.68 Suggested 0.9484 -0.8313 1931.83 Aliased

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Table 4. ANOVA report for the RSM model

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p-value Prob > F < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.00305 < 0.0001 0.0036 0.0471 0.547 0.0213 0.0657 0.7726 0.116 0.7839 0.081 0.9131 0.0088 < 0.0001 0.0004 0.2128 0.076

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F Value 40.3 376.13 41.99 29.43 10.75 169.77 10.05 4.18 5.00E-02 5.93 2.74 8.50E-02 1.1 0.077 2.114 0.0012 7.89 62.79 16.29 0.54 2.19

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Source Model A-A: Inlet air temp. B-B:Inlet air humidity C-C:Fan rotating speed D-D:Fan height E-E:PCM thickness AB AC AD AE BC BD BE CD CE DE A^2 B^2 C^2 D^2 E^2 Residual Lack of Fit Pure Error Cor Total

Sum of Squares 1018.26 475.13 53.04 37.17 98.6 214.46 12.7 0.75 7.20E-03 7.49 2.55 1.51E-03 0.025 0.097 0.029 0.015 9.97 79.32 20.58 2.05 4.28 36.63 36.1 0.53 1054.89

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Table 5. Model summary statistic 1.12E+00 11.93 9.42 1.46E+02

R-Squared Adj R-Squared Pred R-Squared Adeq Precision

0.9653 0.9413 0.9319 26.173

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Table 6. The optimum predicted results based on RSM-CCD Value C %

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Room A

1st 30.83 16.52 28.8 19.65

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Table 6 Comparison of peak temperatures between the PCM room B and reference room A.

2nd 35.46 17.85 32.04 20.11

3rd 31.69 18.84 29.38 20.52

4th 34.36 18.49 31.52 20.33

5th 26.13 21.04 24.11 21.77