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Drying of sweet basil with solar air collectors
Renewable Energy 93 (2016) 77e86
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Renewable Energy journal homepage: www.elsevier.com/locate/renene
Drying of sweet basil with solar air collectors Fevzi Gulcimen a, Hakan Karakaya b, *, Aydın Durmus c a
Tunceli University, Department of Mechanical Engineering, 62020 Tunceli, Turkey Batman University, Department of Energy Systems Engineering, 72060 Batman, Turkey c Ondokuz Mayıs University, Department of Mechanical Engineering, 55139 Samsun, Turkey b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 August 2015 Received in revised form 7 February 2016 Accepted 10 February 2016 Available online xxx
In this study, sweet basil was dried and its drying parameters were investigated experimentally and theoretically by using newly developed solar air collectors. Proper temperatures were chosen to dry sweet basil and experiments were carried out at different flow rates. At the end of drying experiments, it was determined that total mass of sweet basil decreased from 0.250 kg to 0.029 kg. In drying sweet basil, dimensionless moisture ratios were decreased rapidly to 300 min for 0.012 kg/s, 360 min for 0.026 kg/s, and 450 min for 0.033 kg/s. It was observed that the efficiency of collector was increased at the same rate with air flow changed between 29 and 63%. Among the models in the literature, Page Model was found to suit best for drying sweet basil. Furthermore, a novel mathematical model rendering more valid results for sweet basil and leafy products was developed. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Sweet basil Solar drying Mathematical modelling
1. Introduction Temporary and permanent preservation methods have been implemented in order to store foods for centuries. Temporary methods can be outlined as cooling foods or storing them in fridges or isolating them from moisture and air. On the other hand, drying is the best example for permanent or long lasting preservation method. Drying is the procedure that was defined as removing water or moisture from substances. Food drying is also a process to make fruits and vegetables last longer time by reducing the amount of water they contain from 80e90% to 10e20%. Therefore, drying can be defined as decreasing the amount of moisture since this process reduces the amount of moisture in products to such a level that they can be preserved against decay. Today, of the driers used commercially, none provides completely the most economical and the best quality for drying facilities altogether. Each method has some limitations and deficiencies in terms of power consumption, drying cost and quality variables in products. Todays' commercial driers are designed to use one or a few methods such as contact drying, convective drying, drying with radiation, dielectric drying, and freeze drying, osmotic
* Corresponding author. E-mail addresses: [email protected], (H. Karakaya). http://dx.doi.org/10.1016/j.renene.2016.02.033 0960-1481/© 2016 Elsevier Ltd. All rights reserved.
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drying and vacuum drying. Among drying methods, today, the most commonly used one is the convective drying method carried out with the help of air flow. To heat the air in dryers, various types of energy sources (electric, LPG, fuel oil) are still being used in industry. Since utilizing commercial power sources in heating air increases the expenses of drying, this method is mostly not economic in drying fruits and vegetables in rural areas. For this reason, in many parts of the world, for heating air, solar power dryers have been developed utilizing solar energy in order to dry vegetables and fruits. Drying method by means of solar power is divided into two major groups as passive and active method according to air circulation technique in dryer. In passive dryers, air circulation is activated by means of thermal power (according to the “Principle of Convection”). In active dryers, air circulation is provided by means of an electric fan. Although active dryers facilitate a faster drying compared to passive dryers, they cannot be used in places where there is no electricity, which necessitates an additional cost. Active dryers should be preferred when product to be dried is in a large amount; and when the drying period is short. Solar power dryers are classified as direct, indirect and combined types according to the forms of exposing to solar radiations [1]. The products dried by researchers can be categorized into two groups. While, in the first group, the leafy products such as mints, basils, vine leaves having thin structures and containing less moisture take place, in the second group, fleshy products such as apples, apricots, mulberries, potatoes containing more moisture
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Nomenclature I L Me Mo Mt Mw n (EF) (RMSE) k t m_ MR WT Wt Ww WV
Total radiation coming on tilted plane (W/m2) thickness of dried product (m) Dry mass of product (kg) Initial mass of product (kg) Mass of the drying product at a time t (kg) Water mass in product (kg) Coefficient number in model used Sufficiency parameters () The root mean square error () Drying constant (1/s) Time (s) Mass flow rate of air (kg/s) Moisture ratio () Total error stemming from heat measurement ( C) Total error stemming from time measurement (min.) Total error stemming from loss of weight (gr) Total error stemming from speed measurement (m/s)
take place. When these two groups of products are compared, fleshy products have disadvantages in decaying not only in terms of time but also in quality of product (colour, texture etc.). Researchers have designed various solar air power collectors to dry these products more efficiently. A. Hobbi studied various passive heat enhancement devices that include twisted strip, coil-spring wire and conical ridges. The comparison did not produce any tangible differences in the heat flux of the collector fluid [2]. B.M. Ramani proposed double pass counter flow solar air collector with porous material in the second air passage which is one of the most significant and remarkable design improvements that has ever been offered to better the thermal performance. Comparison results reveal that the thermal efficiency of double pass solar air collector with porous absorbing material is 20e25% and 30e35% higher than that of a double pass solar air collector without porous absorbing material and single pass collector respectively [3]. A.M. El-Sawi carried out an experimental study of two types of flatbed solar air collectors with flat plate and chevron pattern absorbers to investigate their performance over a wide range of operating conditions [4]. Designing different collectors, Durmus et al. performed several experiments on drying [5,6]. In a study that Akbulut conducted, he dried mulberries in Elazıg region and investigated drying parameters [7]. In another study, Akbulut investigated energy and exergy analyses of redpeppers dried in thin layers [8]. Koua et al. investigated the behaviour of thin layer drying of plantain, banana, mango and cassava experimentally in a direct solar dryer, and secondly performed mathematical modelling by using thin layer drying models present in the literature [9]. Doymaz studied the effects of air temperature, air-flow rate and sample thickness on drying kinetics of carrot cubes. In the studies he carried out, convective air drying characteristics of carrot cubes were evaluated in a cabinet dryer [10]. A.Kouchakzadeh tested a new approach of ultrasoundassisted sun drying. In this study, he used a flatbed as product support and two extensional piezoelectric Bolt-clamped 20 kHz transducer elements. Wet unshelled pistachios with mono layer were dried under the sun by applying 500 and 1000 W power ul€ trasound [11]. Ozdemir and Devres tried to explain the drying characteristics of hazelnut on a thin layer between the temperature clearances of 100 Ce1600 C [12]. Akpınar investigated thin-layer drying characteristics of mint leaves in solar dryer with reinforced
WM WP
Total error stemming from moisture measurement (rH) Total error stemming from pressure measurement (mbar)
Subscripts c,i Drier inlet c,o Drier outlet cr Crop e environment exp experimental i inlet m mean(Average) n number of experiments nk number of constants in the model o outlet s surface of collector t time the theoretical
convection; and under the sun with natural convection with the purpose of carrying out energy and exergy analysis of solar drying process of mint leaves [13]. Yaldız and Ertekin modelled drying of the seedless sultana raisins as thin layers by means of solar power dryers. Drying air is heated with the help of solar power air heater; and drying process was conducted by allowing the heated air to pass among the product on the shelf in drying chamber [14]. Togrul investigated the effect of drying temperatures on drying ratios of apple slices at different temperatures. When drying temperatures were increased from 500 C0 to 800 C, he determined that drying ratios also increased almost twice [15]. Tripathy proposed a methodology for determination of temperature dependent drying parameters, which are drying constant and lag factor of the experimental drying kinetic curves of food product [16]. The drying systems were evaluated thermodynamically by researchers, and also energy and exergy analyses were carried out [17e20]. During the drying process, a constant mass and heat transfer occur. It is very important that the parameters of this complex process be understood better in terms of engineering. Mathematical modelling of drying process can be used both for designing and improving new drying systems and for controlling drying process. The parameters such as drying air temperature and speed used in these models directly depend on drying conditions. In order to define drying processes, a number of mathematical models were developed and many products were examined [21e24]. In this study, a solar air power cabin dryer collector was designed in order to dry sweet basil, frequently used in soup, salad, meals and beverages in daily life healthily, without damaging its physical properties. A cabin type dryer was designed in the study with authentic solar air collectors in order to benefit from sun more efficiently. It has low first investment expenses and is capable of eliminating drying defects on a large scale. After the experiments at different flow rates and specified temperatures in accordance with sweet basil, drying parameters were investigated experimentally and theoretically; and the obtained results were compared to the literature. In addition, the convenient model for sweet basil was determined after this model was compared to drying models previously developed; and a novel mathematical model was developed to be able to use for drying leafy products.
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
2. Experimental setup In this study, drying an agricultural crop with the help of renewable energy sources was handled under climatical conditions of Elazig. Solar energy was used as the renewable energy source. For this purpose, an authentic solar air collector was designed. It has the fixed fins that have three different angles in air direction. Basically, the experimental setup consisted of three main parts. These are heating unit, drying unit and measurement&control unit. Heating unit contains of solar air collectors. Drying unit consists of cabinet type drying (conditioning) part. And measurement and control unit is divided into two sections as measurement and control parts. Measurement unit contains a data collector and in connection with this, it has heat, speed, pressure, moisture and mass probes. And control unit consists of a fan for mass flow rate, an adjustable AC frequency converter and a Pentium IV computer. Schematic view of experimental setup is shown in Fig. 1. Solar air collectors were used so as to heat the air in the drying unit. The solar air collectors were produced in standard collector size (0.93 1.93 m2) (Fig. 2). Collector flow channel is 10 cm and it was designed in such a way that the fins were fixed in at the same hight and with 30 , 45 and 60 angles. The distance between fins is 10 cm. Collector surface was manufactured from galvanized metal sheet with 0.6 mm thickness. Glass with 4 mm thickness was used as transparent layer in order to prevent heat loss from the collector surface. Underneath and sides of the collector were covered with standard isolation material of 10 cm fiberglass. Collector surface was painted in mat black. The images of solar air collector and flow channel are given in Fig. 2. The positions of fins fixed inside the flow channel with angle are also clearly presented. The height of cabinet type dryer unit manufactured as conditioning chamber is 1.5 m from the ground. The base of conditioning chamber is square and has a width of 0.74 m. The heated air entering into the conditioning chamber from a circular cross-section (D ¼ 20 cm) opened in mid underneath part is disposed outside from cross-section square with
Fig. 2. Dimensions and photos of flow field.
Fig. 1. Schematic display of cabinet type dryer with solar air collector.
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dimensions 20 20 cm. The conditioning chamber was meticulously isolated due to thermal difference to prevent the heat loss of dry air entering into the conditioning chamber and the density of the air in the conditioning chamber. During the process while drying procedure was going on, a double glazed window was mounted in front of the cabinet to permit the researchers to observe the drying crop. Drying chamber was manufactured considering the optimum efficiency to measure homogenous air distribution, heat and mass change (Fig. 3). Measurement unit consists of measurement probes and an Almemo 5990-0 model data collector that can record measurements from a number of points where these probes are mounted. Experimental study was performed in two stages as collector efficiency and drying experiments. Initially, collector efficiency experiments were conducted. Solar air collectors were manufactured as standard collector chassis with the dimensions of 0.93 1.93 m, and with a modified flow channel. Fins at the height of flow channel and having three different angles (30 , 45 and 60 ) were fixed inside the flow channel. Predominantly, the efficiency of fins on collector was investigated. In collector experiments, it was determined that most efficient air collector type was that of having 30 fin angle and this type was used in drying experiments. Collector efficiency and drying experiments were carried out at three different air mass flow rates (0.012 kg/s, 0.026 kg/s and 0.033 kg/s). In the experiments, relatively dry and hot air entering to the lower part of the conditioning chamber left the chamber from the upper part of the chamber passing over wet crops on the tray. And sweet basil drying process was compared with both leaving the crops in the natural environment to dry and drying them by means of air collector. Mass change in sweet basil left to dry in natural environment was recorded after weighing it with a sensitive scale. This process lasted approximately for three days. In natural drying process, sweet basil was put into the conditioning chamber after closing its entrance and exit channels during the hours when there was no day-light. As a result, initial values were nearly the same with the next day values. When drying process was carried out by means of solar air collector, mass change in the crop was measured with the help of K25 type FKA0251 model tension and pressure sensor. The tension-pressure sensor was connected to the trays by means of a hook. After the crop was dried spread and placed on the trays, the fan was activated; and the necessary mass flow rate was adjusted. While the system was running under these conditions, after resetting the gadget, the weight values read on the tensionpressure sensor were recorded. Afterwards, mass change was measured in regard with time. Temperature values at three different points in the conditioning chamber for drying experiments were measured together with mass change and average air
Fig. 3. Photo of drying chamber.
speed. The parameters were measured in 15 min intervals and recorded into Pentium IV computer. At the end of drying experiments, it was found out that the total mass of the sweet basil decreased from 0.250 kg to 0.029 kg. During the drying process, great care was paid in measuring and evaluating all parameters. Once the approximately equal conditions existed, the validity of the experimental data was to adjust the related parameters by repeating the same experiments for a few times. 3. Analyses 3.1. Error analyses It is widely known that the errors stemming from fixed, manufacture and random errors are effective during temperature measurement, speed, weight loss, time and air moisture in drying experiments conducted via cabinet type solar air collector. The total error value can be calculated by taking fixed, manufacture, and random errors into consideration in order to determine the total error in any parameters whose measurements are carried out [6]. If the amount of error with each variable effecting the measurement is defined as x, total error can be written as follows:
i1=2 h Wth ¼ ðx1 Þ2 þ ðx2 Þ2 þ ………ðx∞ Þ2
(1)
Total errors in measurement carried out in solar air collector with cabinet type are determined as shown in Table 1. 3.2. Efficiency analysis In the experimental study, solar air collectors were used to heat the air. As it is known, the air inlet-outlet temperature differences in solar air collectors (DT) change as in the following function:
ðDTÞ ¼ fðV; I; Ac ; ta; FR ; UL Þ
(2)
However, bound and free variables given in equation (2) change in connection with different parameters on their own. In this study, in order to increase collector efficiency, guiding fins were used on the surface area of collector, and by extending flow way, the efficiency was tried to be increased by means of passive method without using additional energy. Collector efficiency in connection with variables is expressed as
Table 1 Total values of errors made in drying experiments. Parameters causing errors in experiments Total error WT,I WT,o WT,s WTc,i WTc,o WTm WTe Total error Wt Total error Wwdry Wwwet Total error WV Total error WM Total error WP
Unit
Total error
C C C C C C C
±0.173 ±0.173 ±0.173 ±0.173 ±0.173 ±0.173 ±0.173
min
±0.141
gr gr
±0.212 ±0.014
m/s
±0.104
r.H.
±0.200
mbar
±0.0025
stemming from heat measurement
stemming from time measurement stemming from loss of weight
stemming from speed measurement stemming from moisture measurement stemming from pressure measurement
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follows:
h¼
Qu F IðtaÞ FR UL ðTi To Þ ¼ R I I Ac
(3)
The useful energy employed in determination of collector efficiency, Qu, can be calculated via following equation:
_ p ðTo Ti Þ Qu ¼ mC
(4)
3.3. Drying analyses It is possible to calculate the moisture content of crop being dried at any t time as follows:
Moisture content ¼
Mt Me Me
(5) Fig. 4. Alterations in radiation values of days drying experiments were conducted according to time of day.
In drying process, dimensionless moisture ratio (MR) is one of the most important parameters while examining drying and dryer parameters. While calculating dimensionless moisture ratio, measurement time, moisture content, initial moisture content and balance moisture content are taken into consideration.
MR ¼
Mt Me Mi Me
4. Results and discussions The days with approximately equal radiation are preferred in order to compare drying experiments conducted between the dates of 24 August and 6 September. As can be seen in Fig. 4, the radiation values change between 440 and 490 W/m2 during morning hours and increase from 720 to 750 W/m2 gradually. After 16.00 o'clock, the radiation value decreases till it reaches to 200 W/m2. At these radiation values, drying experiments were carried out at three different mass flow rates (0.012 kg/s, 0.026 kg/s, 0.033 kg/s). As mentioned before, fins having a ¼ 30 , 45 and 60 angles were mounted inside the air flow way in order to increase the efficiency of the collector. As known, mounting the fins inside the flow environment extends the flow way preventing formation of boundary layer in flow channel. Furthermore, extended surface influence occurs because of the impact of fins and, as a result, outlet temperature of the air increases. Before starting drying experiments, the most convenient collector was identified to determine collector activities for drying experiments. For this aim, heat transfer experiments were initially done at three different mass flow rates for all collectors. As a result of the experiments, it was witnessed that the smaller the angle of the fin, the higher the instant efficiency of the collector was. This case showed the importance of fixing way of the fins placed in the collector flow channel. Namely, the more the fins'
(6)
Moisture ratio (MR) models are given in the literature after being developed for drying process. Khi-square (X2), sufficiency parameters (EF) and root mean square error (RMSE) values are obtained for correlations calculated by means of multi regression.
c2 ¼
2 Pn i¼1 MRexp;i MRthe;i n nk
(7)
2 Pn Pn i¼1 MRthe;i MRthe;m i¼1 MRexp;i MRexp;m EF ¼ Pn i¼1 MRexp;i MRexp;m
RMSE ¼
"Pn #1=2 i¼1 MRthe;i MRexp;i n
(8)
(9)
Drying constant is determined utilizing experimental data according to dried crop and drying conditions. To explain the drying curves, semi theoretical and empirical models were developed by some researchers. These models are presented in Table 2 [6].
Table 2 Drying curve models present in the literature. Model name
Model equation
Ref.
Newton
M t M e ¼ expðktÞ MR ¼ M 0 M e
[25]
Page
M t M e MR ¼ M ¼ MR ¼ expðktn Þ 0 M e
[26]
Modified page
M t M e MR ¼ M ¼ expððktÞn Þ 0 M e
[27]
Henderson and Pabis
M t M e MR ¼ M ¼ a expðktÞ 0 M e
[28]
Logarithmic
M t M e MR ¼ M ¼ a expðktÞ þ c 0 M e
Wang and Singh
MR ¼
Fick’ s diffusion
MR ¼
Diffusion
MR ¼
Modified page II
MR ¼
Midilli and Kucuk
MR ¼
M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e
[29] [30]
2
¼ 1 þ at þ bt
¼ MR ¼ aexpðcðt=L ÞÞ
[31]
¼ aexpðktÞ þ ð1 aÞexpðkbtÞ
[32]
¼ expðkðt=L2 Þn Þ
[31]
¼ aexpðktn Þ þ bt
[33]
2
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surfaces fixed in the flow direction were vertical to the flow direction, the more efficient the collectors were. When fin angle was 30 , maximum efficiency was obtained. Therefore, this type of collector was used in drying experiments. In Fig. 5, the efficiencies at different mass flow rates were given with a ¼ 30 for the most efficient collector type. The air flow is directly proportional to collector efficiency. _ ¼ 0.012 kg/s, while collector In regard to radiation values, for m efficiency is 29% at 9.00 o'clock, it rises to 42% at 13.00 o'clock. The _ ¼ 0.012 kg/s, 51% for maximum efficiency value is 42% for m _ ¼ 0.026 kg/s and 63% for m _ ¼ 0.033 kg/s. When fin angle is m a ¼ 45 and while maximum efficiency value is 38% for _ ¼ 0.012 kg/s, it is 45% for m _ ¼ 0.026 kg/s and 55% for m _ ¼ 0.033 kg/s. When fin angle is a ¼ 60 , the maximum collector m _ ¼ 0.033 kg/s. efficiency is 47% for m In Fig. 6a, the changes according to drying time of dimensionless moisture ratio for sweet basil can be observed. Naturally, when t is 0, the dimensionless moisture ratio of crop is found as 1. Dimensionless moisture ratio decreases rapidly to 300 min for 0.012 kg/s; 360 min. 0.026 kg/s; 450 min for 0.033 kg/s in drying sweet basil. This slows down after time elapses. The change in moisture content for sweet basil is given in Fig. 6b according to drying time. Maximum moisture content for sweet basil is 7.62 kg-water. As the moisture content increases, the effect of flow rate on the change of moisture content also increases according to data obtained as a result of experimental study carried out for sweet basil. To determine the drying speed, derivative of moisture content is taken according to time. The change in drying speed for sweet basil according to drying time is given in Fig. 6c. For all mass flow rates, as the drying time increases, the effect of moisture content on drying speed decreases. At the start of drying process, moisture content has more effect on drying speed. This speed lasts during all drying process though it gradually loses its effect. As is seen, the effect of mass flow on dimensionless moisture is significant. Furthermore, drying speed until 0.026 kg/s of sweet basil is more influential on dimensionless moisture compared to mass flow. When mass flow rate increases to 0.033 kg/s, the effect of mass flow rate on dimensionless moisture increases, as well. Several experimental equations were developed for drying process. Moisture ratio change obtained for all drying processes conducted was later compared to these equations. Equation coefficient (R) is high, while comparison requires X2 and RMSE values to
Fig. 6. a) Alteration of dimensionless moisture ratio according to drying time. b) Alteration of moisture content according to drying time. c) Alteration of drying rate according to drying time.
Fig. 5. Instant collector efficiency alterations according to time of day for a ¼ 30 .
be low. In this study, moisture ratio values obtained for sweet basil were compared to those equations given in the literature. If the diversity of agricultural crops and if each crop is considered to be different with its physical properties and dimensions, it will obviously be seen that the mass change in each crop is different
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
during drying process. This change in mass during drying may not only occur with regard to physical properties of crop but also it may change with regard to drying environment and the properties of dryer. For instance, it is aimed to reduce the moisture amount in the crop by means of drying process. However, it is required that the product should be hygienic and should not lose its flavour and nutrition value. In this study, solar energy and drying parametres were examined for sweet basil. After the obtained data were applied to frequently used model equations, a convenient model for sweet basil was constituted. Nevertheless, it was found out that some equations commonly used in the literature were not convenient models for drying leafy products. Relying on the data obtained, it was determined that Fick Diffusion Model, Two-Term Model and Midilli Model were not convenient equations for drying leafy products. It was observed that all three models did not give correlation coefficient in regression analysis carried out. Therefore, coefficient table, experimental and theoretical graphics were not given for these models. In drying sweet basil, moisture ratio change is clearly logarithmical. In respect with this, odd numbered logarithmical and second level parabolical equations are obtained as a more convenient model for drying sweet basil. While developing a convenient model for drying processes, only correlation coefficient or X2 and RMSE are not taken into consideration. These parametres should be evaluated as a whole. When data obtained for sweet basil drying were evaluated within this model equations (Table 3), Wang and Singh Models containing second level parabol equation were calculated as the best models (Fig. 7). When all related parametres are taken into consideration, Page Model seems to be the best model for sweet basil drying. In Fig. 8, the comparison of experimental and theoretical values is given for sweet basil obtained for Modified Page 1 Model. X2 and RMSE exist in levels of 108 and 105 (Table 3). This ratio is an acceptable one. For Modified Page 1 Model, correlation coefficient changes between 0.992 R 0.997. The fact that correlation coefficient meets experimental values with a value of 99% shows that experimental
83
Fig. 7. Change in theoretical values according to experimental values for sweet basil (Wang and Singh Model).
studies and equations produced are quite in concordance and are required values. One of the most suitable models in drying sweet basil is Newton Model. As mentioned above, the most suitable correlations for mint and sweet basil are those of second stage parabola and odd numbered logarithmical ones. Newton Model is one of them. In this model, correlation coefficient changes between 0.972 R 0.993 (Table 3). As it is seen in Fig. 9, theoretical and experimental values for sweet basil meet each other within the boundaries of ±20%. Page model is one of the most appropriate equations (Table 3). With regard to correlation coefficient change between 0.989 R 0.999 theoretical and experimental values meet each other with a good percentage as ±10%. This change is obviously seen for sweet basil in Fig. 10.
Table 3 Relevant parameter values for different models. Model name
The drying air mass flow rate (kg/s)
Drier inlet-outlet temperature difference
Wang and Singh
0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033
13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423
Modified page I
Newton
Page
Modified page II
Henderson and Papis
Diffusion
This study
a 0.002 0.003 0.005 e e e e e e e e e 0.333 1.519 1.256 1.321 1.118 1.082 201.9 192.1 97.3 0.910 1.189 1.092
B
c
k
n
RMSE
X2
EF
R
0.000001 0.000003 0.000007 e e e e e e e e e e e e 0.005 0.006 0.007 0.990 0.996 0.991 1.387 1.407 1.123
e e e e e e e e e e e e 0.61 0.0004 0.0003 e e e e e e e e e
e e e 1.703 1.554 1.113 0.003 0.005 0.007 0.0002 0.0003 0.0004 e e e e e e 0.007 0.011 0.013 0.0003 0.0004 0.002
e e e 0.000001 0.000003 0.000007 e e e 1.441 1.486 1.119 0.0004 0.394 0.411 e e e e e e e e e
3.5E6 3.1E6 4.2E6 1.3E5 7.8E5 1.7E5 5.3E5 1.8E5 1.1E5 2.3E6 1.8E6 8.83e5 8.3E1 2.7E2 1.7E3 2.6E5 1.9E5 1.9E6 2.3E6 1.8E6 8.8E5 1.2E6 8.81E7 9.3E7
3.9E8 4.2E8 4.3E8 7.8E7 4.5E8 9.3E7 1.8E8 1.5E8 1.1E8 1.98E8 6.6E8 1.3E8 4.8E2 4.4E2 8.3E3 1.2E8 3.3E8 2.2E8 1.9E8 6.6E8 1.3E8 8.8E8 9.5E8 9.3E8
0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999
0.993 0.996 0.994 0.992 0.998 0.993 0.972 0.981 0.993 0.989 0.998 0.992 0.566 0.861 0.903 0.987 0.981 0.996 0.998 0.994 0.997 0.991 0.994 0.995
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Fig. 8. Change in theoretical values according to experimental values for sweet basil (Modified Page 1 Model).
Fig. 10. Change in theoretical values according to experimental values for sweet basil (Page Model).
Fig. 9. Change in theoretical values according to experimental values for sweet basil (Newton Model). Fig. 11. Change in theoretical values according to experimental values for sweet basil (Modified Page II Model).
Equations containing dimensions of crop do not provide drying parametres in drying and modelling of leafy products. Yet, Modified Page Model gives a bad value correlation coefficient as 0.566 R 0.903. Therefore, theoretical and experimental values meet each other at the boundaries of ±60% for sweet basil (Fig. 11). X2 and RMSE exist at the levels of 102. Handerson and Papis Model and Diffusion Model are appropriate correlations for many different kinds of crops (Figs. 12e13). When credible parameters given in Table 3 are considered, it will be seen that both correlations are appropriate for sweet basil. Apart from different models available in the literature for modelling drying processes, it is needed to develop a novel moisture content model (MR). The model correlation developed can be obtained as follows:
MR ¼
Mt Me ¼ exp kðt a Þ k t b M0 Me
(10)
According to the correlation developed, correlation coefficient for sweet basil is obtained at a very high level as 99% for all mass
flow rates. Moreover, X2 and RMSE appear at rather low levels such as 109 and 107 for obtained correlations (Table 4). Fig. 14 gives theoretical and empirical results of change in sweet basil. As seen, theoretical and empirical values are obtained at highly appropriate clearance as ±5%. In determining diffusion coefficient for sweet basil, Arrhenius function is preferred. The mass flow rate of drying air and collector inlet-outlet temperature difference are used [34].
DF ¼ a1 $m_ a2 $exp
a 3
DT
(11)
Diffusion coefficient obtained for sweet basil at three different mass flow rates is given in Table 5. When diffusion coefficients are carefully inspected, it will be seen that the equation of theoretical diffusion correlation and empirical diffusion correlation are quite close to each other.
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
Fig. 12. Change in theoretical values according to experimental values for sweet basil (Henderson and Papis Model).
Fig. 13. Change in theoretical values according to experimental values for sweet basil (Diffusions Model).
Table 4 Relevant parameter values for correlation designed for this study. The drying air flow (kg/s)
0.012
0.026
0.033
Drier inlet-outlet temperature difference A B K RMSE X2 EF R
13.211 0.910 1.387 0.0003 1.2E-6 8.8E-8 0.9999 0.991
8.613 1.189 1.407 0.0004 8.81E-7 9.5E-8 0.9999 0.994
7.423 1.092 1.123 0.002 9.3E7 9.3E8 0.9999 0.995
5. Conclusion In the drying process, deterioration of physical properties of the dried product, hygiene of drying environment, continuity of the drying process, efficient operation of the dryer model, usability of the dryer model, low cost of the drier manufacturing and drying
85
Fig. 14. Change in theoretical values according to experimental values for sweet basil (This study).
process are the primary requirements. The main advantages of the drying process by solar energy are; using renewable energy sources as the energy supply, low installation costs, complying with the climate conditions, providing drying in a hygienic environment that does not require chemical processing. In this type of systems, there are two major problems. The first one is to failure to take advantage of solar energy effectively. The other is to unabling benefit from solar energy during the day along and therefore enabling to meet the energy requirements continuously. This study aims to bring a solution to the problems mentioned at first. Furthermore, by using obtained drying parameters, the comparisons were made for drying mathematical models in the literature and a new model was proposed for Reyhan drying. In this study, drying parametres of sweet basil were determined empirically in a cabinet type dryer under climatical conditions of Elazig province with the help of newly designed solar air collectors. By employing these drying parameters obtained, a comparison was carried out for mathematical drying models given in literature. Furthermore, a novel drying model was developed for the handled crop. The obtained results of the study are given below: - The mass flow rate of the air is directly proportional to collector efficiency. In respect to the radiation values, while collector efficiency is 29% at 09.00 a.m. for 0.012 kg/s, it rises upto 42% at _ ¼ 0.012 kg/s, 13.00. The maximum efficiency value is 42% for m _ ¼ 0.026 kg/s and 63% for m _ ¼ 0.033 kg/s. Should and 51% for m classical plane surface solar air collector efficiency values, changing between 20 and 25%, be considered, the efficiency values for collectors that we developed appear to have increased significantly. - Before starting the drying process via solar air collectors, drying was applied to sweet basil in natural environment. As can easily be seen from the correlation between mass changes and drying time for sweet basil, mass change became zero after nearly 1320 min in natural environment. According to these data, it was found out that sweet basil dried approximately in three days. At the beginning of each day, mass and moisture content changed slowly. In this, it attracts attention that morning radiation values and environment temperature were low to bring crop to a regime. Drying moisture content was approximately 10e12%.
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Table 5 Diffusion coefficient at different mass flow rates for sweet basil. The drying air flow (kg/s)
0.012 0.026 0.033
Drier inlet-outlet temperature difference
13.21 8.61 7.42
- In the solar air collectors, drying time for 0.012 kg/s sweet basil is 600 min. However, it is 420 min for 0.033 kg/s. 0.250 kg sweet basil decreases to 0.029 kg dry product losing 88% water content. 0.221 kg water in 0.250 kg sweet basil dries in 420e600 min depending on mass flow rate of air. Eventually, the solar energy was effectively utilized by the designed collector with a new model. During the development and implementation of this study, the mentioned problems can be solved by alternative methods such as the use an additional source of energy, energy storage, etc. Acknowledgement The authors would kindly like to thank to Firat University Research Foundation (FUNAF) (FUNAF-1038) for financial contribution. Furthermore, we would like to express our highly gratitudes to the experienced English lecturer Ihsan Pilatin of Batman University for his contributions in checking the paper throughly and making all necessary corrections. References [1] O.V. Ekechukwu, B. Norton, Review of solar energy drying systems II: an overview of solar drying technology, Energy Convers. Manag. 40 (1999) 615e655. [2] A. Hobbi, K. Siddiqui, Experimental study on the effect of heat transfer enhancement devices in flat-plate solar collectors, Int. J. Heat Mass Transf. 52 (2009) 4650e4658. [3] B.M. Ramani, A. Gupta, R. Kumar, Performance of a double pass solar air collector, Sol. Energy 84 (2010) 1929e1937. [4] A.M. El-Sawi, A.S. Wifi, M.Y. Younan, E.A. Elsayed, B.B. Basily, Application of folded sheet metal in flat bed solar air collectors, Appl. Therm. Eng. 30 (2010) 864e871. [5] I. Kurtbas, A. Durmus, Efficiency and exergy analysis of a new solar air heater, Renew. Energy 29 (2004) 1489e1501. [6] H. Karakaya, A. Durmus, Investigation of efficiency and exergy loss in plate heat exchangers having spiral surface profiles, Energy Educ. Sci. Technol. 28 (2) (2012) 577e590. [7] A. Akbulut, A. Durmus, Energy and exergy analyses of thin layer drying of mulberry in a forced solar dryer, Energy 35 (4) (2010) 1754e1763. [8] E.K. Akpinar, Y. Biçer, C. Yildiz, Thin layer drying of red pepper, J. Food Eng. 55 (2003) 99e104. [9] K.B. Koua, W.F. Fassinou, P. Gbaha, S. Toure, Mathematical modelling of the thin layer solar drying of banana, mango and cassava, Energy 34 (2009) 1594e1602. [10] I. Doymaz, Convective air drying characteristics of thin layer carrots, J. Food Eng. 61 (2004) 359e364. [11] A. Kouchakzadeh, The effect of acoustic and solar energy on drying process of pistachios, Energy Convers. Manag. 67 (2013) 351e356. [12] M. Ozdemir, Y.O. Devres, The thin layer drying characteristics of hazelnuts
Eq. (11). R ¼ 0.82
a1 ¼ 0.0000001 a2 ¼ 0.188 a3 ¼ 0.101
Diffusion coefficient Exp.
The.
2.2E13 9.8E11 2.3E11
1.6E14 6.8E11 1.3E11
during roasting, J. Food Eng. 42 (1999) 225e233. [13] E.K. Akpinar, Drying of mint leaves in a solar dryer and under open sun: modelling, performance analyses, Energy Convers. Manag. 51 (2010) 2407e2418. [14] O. Yaldiz, C. Ertekin, H.I. Uzun, Mathematical modeling of thin layer solar drying of sultana grapes, Energy 26 (2001) 457e465. [15] I. Turktogrul, D. Pehlivan, Mathematical modelling of solar drying of apricots in thin layers, J. Food Eng. 55 (2002) 209e216. [16] P.P. Tripathy, S. Kumar, Determination of temperature dependent drying parameters for potato cylinders and slices during solar drying, Energy Convers. Manag. 49 (2008) 2941e2948. [17] A. Midilli, H. Kuçuk, Energy and exergy analyses of solar drying process of pistachio, Energy 28 (2003) 539e556. [18] K. Sopian, M.Y. Othman, M.H. Ruslan, Energy and exergy analyses of solar drying system of red seaweed, Energy Build. 68 (2014) 121e129. [19] G. BoroumandJazi, S. Mekhlif, M. Jameel, Exergy analysis of solar energy applications, Renew. Sustain. Energy Rev. 16 (1) (2012) 350e356. [20] D. Alta, E. Bilgili, C. Ertekin, O. Yaldiz, Experimental investigation of three different solar air heaters: energy and exergy analyses, Appl. Energy 87 (10) (2010) 2953e2973. [21] A.A. El-Sebaii, S.M. Shalab, Experimental investigation of an indirect-mode forced convection solar dryer for drying thymus and mint, Energy Convers. Manag. 74 (2013) 109e116. [22] T.Y. Tunde-Akintunde, Mathematical modeling of sun and solar drying of chilli pepper, Renew. Energy 36 (2011) 2139e2145. [23] I. Ceylan, M. Aktas, H. Dogan, Mathematical modeling of drying characteristics of tropical fruits, Appl. Therm. Eng. 27 (2007) 1931e1936. [24] A.A. El-Sebaii, S. Aboul-Enein, M.R.I. Ramadan, H.G. El-Gohary, Empirical correlations for drying kinetics of some fruits and vegetables, Energy 27 (2002) 845e859. [25] A.S. Mujumdar, Handbook of Industrial Drying, Marcel Dekker, New York, 1987. [26] G.E. Page, Factors Influencing the Maximum Rates of Air Drying Shelled Corn in Thin Layers (Unpublished masterthesis), Purdue University, Lafayette, IN, USA, 1949. [27] G.M. White, I.J. Ross, R. Ponelert, Fully exposed drying of popcorn, Trans. Am. Soc. Agric. Eng. 24 (1981) 466e468. [28] M.S. Chinnan, Evaluation of selected mathematical models for describing thin layer drying of in-shell pecans, Trans. Am. Soc. Agric. Eng. 27 (1984) 610e615. [29] A. Yagcioglu, A. Degirmencioglu, F. Cagatay, Drying characteristics of laurel leaves under different conditions, in: A. Bas Cetincelik (Ed.), Proceedings of the Seventh International Congress on Agricultural Mechanization and Energy, 26e27 May, Adana, Turkey, Faculty of Agriculture, Cukurova University, 1999, pp. 565e569. [30] C.Y. Wang, R.P. Singh, A Single Layer Drying Equation for Rough Rice, American Society of Agricultural Engineers, 1978. Paper no. 3001. [31] L.M. Diamante, P.A. Munro, Mathematical modeling of hot air drying of sweet potato slices, Int. J. Food Sci. Technol. 26 (1991) 99e107. [32] A.S. Kassem, Comparative studies on thin layer drying models for wheat, in: 13th International Congress on Agricultural Engineering, Morocco; 2e6 February, 1998. [33] A. Midilli, H. Kucuk, Z. Yapar, A new model for single layer drying, Dry. Technol. 20 (2002) 1503e1513. [34] F. Gulcimen, Drying of the Mint and Sweet Basil with New Desıgned Air Collectors and Determining of the Drying Parameters, Firat University, Elazig, PhD Thesis, 2008.
Contents lists available at ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
Drying of sweet basil with solar air collectors Fevzi Gulcimen a, Hakan Karakaya b, *, Aydın Durmus c a
Tunceli University, Department of Mechanical Engineering, 62020 Tunceli, Turkey Batman University, Department of Energy Systems Engineering, 72060 Batman, Turkey c Ondokuz Mayıs University, Department of Mechanical Engineering, 55139 Samsun, Turkey b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 August 2015 Received in revised form 7 February 2016 Accepted 10 February 2016 Available online xxx
In this study, sweet basil was dried and its drying parameters were investigated experimentally and theoretically by using newly developed solar air collectors. Proper temperatures were chosen to dry sweet basil and experiments were carried out at different flow rates. At the end of drying experiments, it was determined that total mass of sweet basil decreased from 0.250 kg to 0.029 kg. In drying sweet basil, dimensionless moisture ratios were decreased rapidly to 300 min for 0.012 kg/s, 360 min for 0.026 kg/s, and 450 min for 0.033 kg/s. It was observed that the efficiency of collector was increased at the same rate with air flow changed between 29 and 63%. Among the models in the literature, Page Model was found to suit best for drying sweet basil. Furthermore, a novel mathematical model rendering more valid results for sweet basil and leafy products was developed. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Sweet basil Solar drying Mathematical modelling
1. Introduction Temporary and permanent preservation methods have been implemented in order to store foods for centuries. Temporary methods can be outlined as cooling foods or storing them in fridges or isolating them from moisture and air. On the other hand, drying is the best example for permanent or long lasting preservation method. Drying is the procedure that was defined as removing water or moisture from substances. Food drying is also a process to make fruits and vegetables last longer time by reducing the amount of water they contain from 80e90% to 10e20%. Therefore, drying can be defined as decreasing the amount of moisture since this process reduces the amount of moisture in products to such a level that they can be preserved against decay. Today, of the driers used commercially, none provides completely the most economical and the best quality for drying facilities altogether. Each method has some limitations and deficiencies in terms of power consumption, drying cost and quality variables in products. Todays' commercial driers are designed to use one or a few methods such as contact drying, convective drying, drying with radiation, dielectric drying, and freeze drying, osmotic
* Corresponding author. E-mail addresses: [email protected], (H. Karakaya). http://dx.doi.org/10.1016/j.renene.2016.02.033 0960-1481/© 2016 Elsevier Ltd. All rights reserved.
[email protected]
drying and vacuum drying. Among drying methods, today, the most commonly used one is the convective drying method carried out with the help of air flow. To heat the air in dryers, various types of energy sources (electric, LPG, fuel oil) are still being used in industry. Since utilizing commercial power sources in heating air increases the expenses of drying, this method is mostly not economic in drying fruits and vegetables in rural areas. For this reason, in many parts of the world, for heating air, solar power dryers have been developed utilizing solar energy in order to dry vegetables and fruits. Drying method by means of solar power is divided into two major groups as passive and active method according to air circulation technique in dryer. In passive dryers, air circulation is activated by means of thermal power (according to the “Principle of Convection”). In active dryers, air circulation is provided by means of an electric fan. Although active dryers facilitate a faster drying compared to passive dryers, they cannot be used in places where there is no electricity, which necessitates an additional cost. Active dryers should be preferred when product to be dried is in a large amount; and when the drying period is short. Solar power dryers are classified as direct, indirect and combined types according to the forms of exposing to solar radiations [1]. The products dried by researchers can be categorized into two groups. While, in the first group, the leafy products such as mints, basils, vine leaves having thin structures and containing less moisture take place, in the second group, fleshy products such as apples, apricots, mulberries, potatoes containing more moisture
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Nomenclature I L Me Mo Mt Mw n (EF) (RMSE) k t m_ MR WT Wt Ww WV
Total radiation coming on tilted plane (W/m2) thickness of dried product (m) Dry mass of product (kg) Initial mass of product (kg) Mass of the drying product at a time t (kg) Water mass in product (kg) Coefficient number in model used Sufficiency parameters () The root mean square error () Drying constant (1/s) Time (s) Mass flow rate of air (kg/s) Moisture ratio () Total error stemming from heat measurement ( C) Total error stemming from time measurement (min.) Total error stemming from loss of weight (gr) Total error stemming from speed measurement (m/s)
take place. When these two groups of products are compared, fleshy products have disadvantages in decaying not only in terms of time but also in quality of product (colour, texture etc.). Researchers have designed various solar air power collectors to dry these products more efficiently. A. Hobbi studied various passive heat enhancement devices that include twisted strip, coil-spring wire and conical ridges. The comparison did not produce any tangible differences in the heat flux of the collector fluid [2]. B.M. Ramani proposed double pass counter flow solar air collector with porous material in the second air passage which is one of the most significant and remarkable design improvements that has ever been offered to better the thermal performance. Comparison results reveal that the thermal efficiency of double pass solar air collector with porous absorbing material is 20e25% and 30e35% higher than that of a double pass solar air collector without porous absorbing material and single pass collector respectively [3]. A.M. El-Sawi carried out an experimental study of two types of flatbed solar air collectors with flat plate and chevron pattern absorbers to investigate their performance over a wide range of operating conditions [4]. Designing different collectors, Durmus et al. performed several experiments on drying [5,6]. In a study that Akbulut conducted, he dried mulberries in Elazıg region and investigated drying parameters [7]. In another study, Akbulut investigated energy and exergy analyses of redpeppers dried in thin layers [8]. Koua et al. investigated the behaviour of thin layer drying of plantain, banana, mango and cassava experimentally in a direct solar dryer, and secondly performed mathematical modelling by using thin layer drying models present in the literature [9]. Doymaz studied the effects of air temperature, air-flow rate and sample thickness on drying kinetics of carrot cubes. In the studies he carried out, convective air drying characteristics of carrot cubes were evaluated in a cabinet dryer [10]. A.Kouchakzadeh tested a new approach of ultrasoundassisted sun drying. In this study, he used a flatbed as product support and two extensional piezoelectric Bolt-clamped 20 kHz transducer elements. Wet unshelled pistachios with mono layer were dried under the sun by applying 500 and 1000 W power ul€ trasound [11]. Ozdemir and Devres tried to explain the drying characteristics of hazelnut on a thin layer between the temperature clearances of 100 Ce1600 C [12]. Akpınar investigated thin-layer drying characteristics of mint leaves in solar dryer with reinforced
WM WP
Total error stemming from moisture measurement (rH) Total error stemming from pressure measurement (mbar)
Subscripts c,i Drier inlet c,o Drier outlet cr Crop e environment exp experimental i inlet m mean(Average) n number of experiments nk number of constants in the model o outlet s surface of collector t time the theoretical
convection; and under the sun with natural convection with the purpose of carrying out energy and exergy analysis of solar drying process of mint leaves [13]. Yaldız and Ertekin modelled drying of the seedless sultana raisins as thin layers by means of solar power dryers. Drying air is heated with the help of solar power air heater; and drying process was conducted by allowing the heated air to pass among the product on the shelf in drying chamber [14]. Togrul investigated the effect of drying temperatures on drying ratios of apple slices at different temperatures. When drying temperatures were increased from 500 C0 to 800 C, he determined that drying ratios also increased almost twice [15]. Tripathy proposed a methodology for determination of temperature dependent drying parameters, which are drying constant and lag factor of the experimental drying kinetic curves of food product [16]. The drying systems were evaluated thermodynamically by researchers, and also energy and exergy analyses were carried out [17e20]. During the drying process, a constant mass and heat transfer occur. It is very important that the parameters of this complex process be understood better in terms of engineering. Mathematical modelling of drying process can be used both for designing and improving new drying systems and for controlling drying process. The parameters such as drying air temperature and speed used in these models directly depend on drying conditions. In order to define drying processes, a number of mathematical models were developed and many products were examined [21e24]. In this study, a solar air power cabin dryer collector was designed in order to dry sweet basil, frequently used in soup, salad, meals and beverages in daily life healthily, without damaging its physical properties. A cabin type dryer was designed in the study with authentic solar air collectors in order to benefit from sun more efficiently. It has low first investment expenses and is capable of eliminating drying defects on a large scale. After the experiments at different flow rates and specified temperatures in accordance with sweet basil, drying parameters were investigated experimentally and theoretically; and the obtained results were compared to the literature. In addition, the convenient model for sweet basil was determined after this model was compared to drying models previously developed; and a novel mathematical model was developed to be able to use for drying leafy products.
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
2. Experimental setup In this study, drying an agricultural crop with the help of renewable energy sources was handled under climatical conditions of Elazig. Solar energy was used as the renewable energy source. For this purpose, an authentic solar air collector was designed. It has the fixed fins that have three different angles in air direction. Basically, the experimental setup consisted of three main parts. These are heating unit, drying unit and measurement&control unit. Heating unit contains of solar air collectors. Drying unit consists of cabinet type drying (conditioning) part. And measurement and control unit is divided into two sections as measurement and control parts. Measurement unit contains a data collector and in connection with this, it has heat, speed, pressure, moisture and mass probes. And control unit consists of a fan for mass flow rate, an adjustable AC frequency converter and a Pentium IV computer. Schematic view of experimental setup is shown in Fig. 1. Solar air collectors were used so as to heat the air in the drying unit. The solar air collectors were produced in standard collector size (0.93 1.93 m2) (Fig. 2). Collector flow channel is 10 cm and it was designed in such a way that the fins were fixed in at the same hight and with 30 , 45 and 60 angles. The distance between fins is 10 cm. Collector surface was manufactured from galvanized metal sheet with 0.6 mm thickness. Glass with 4 mm thickness was used as transparent layer in order to prevent heat loss from the collector surface. Underneath and sides of the collector were covered with standard isolation material of 10 cm fiberglass. Collector surface was painted in mat black. The images of solar air collector and flow channel are given in Fig. 2. The positions of fins fixed inside the flow channel with angle are also clearly presented. The height of cabinet type dryer unit manufactured as conditioning chamber is 1.5 m from the ground. The base of conditioning chamber is square and has a width of 0.74 m. The heated air entering into the conditioning chamber from a circular cross-section (D ¼ 20 cm) opened in mid underneath part is disposed outside from cross-section square with
Fig. 2. Dimensions and photos of flow field.
Fig. 1. Schematic display of cabinet type dryer with solar air collector.
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F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
dimensions 20 20 cm. The conditioning chamber was meticulously isolated due to thermal difference to prevent the heat loss of dry air entering into the conditioning chamber and the density of the air in the conditioning chamber. During the process while drying procedure was going on, a double glazed window was mounted in front of the cabinet to permit the researchers to observe the drying crop. Drying chamber was manufactured considering the optimum efficiency to measure homogenous air distribution, heat and mass change (Fig. 3). Measurement unit consists of measurement probes and an Almemo 5990-0 model data collector that can record measurements from a number of points where these probes are mounted. Experimental study was performed in two stages as collector efficiency and drying experiments. Initially, collector efficiency experiments were conducted. Solar air collectors were manufactured as standard collector chassis with the dimensions of 0.93 1.93 m, and with a modified flow channel. Fins at the height of flow channel and having three different angles (30 , 45 and 60 ) were fixed inside the flow channel. Predominantly, the efficiency of fins on collector was investigated. In collector experiments, it was determined that most efficient air collector type was that of having 30 fin angle and this type was used in drying experiments. Collector efficiency and drying experiments were carried out at three different air mass flow rates (0.012 kg/s, 0.026 kg/s and 0.033 kg/s). In the experiments, relatively dry and hot air entering to the lower part of the conditioning chamber left the chamber from the upper part of the chamber passing over wet crops on the tray. And sweet basil drying process was compared with both leaving the crops in the natural environment to dry and drying them by means of air collector. Mass change in sweet basil left to dry in natural environment was recorded after weighing it with a sensitive scale. This process lasted approximately for three days. In natural drying process, sweet basil was put into the conditioning chamber after closing its entrance and exit channels during the hours when there was no day-light. As a result, initial values were nearly the same with the next day values. When drying process was carried out by means of solar air collector, mass change in the crop was measured with the help of K25 type FKA0251 model tension and pressure sensor. The tension-pressure sensor was connected to the trays by means of a hook. After the crop was dried spread and placed on the trays, the fan was activated; and the necessary mass flow rate was adjusted. While the system was running under these conditions, after resetting the gadget, the weight values read on the tensionpressure sensor were recorded. Afterwards, mass change was measured in regard with time. Temperature values at three different points in the conditioning chamber for drying experiments were measured together with mass change and average air
Fig. 3. Photo of drying chamber.
speed. The parameters were measured in 15 min intervals and recorded into Pentium IV computer. At the end of drying experiments, it was found out that the total mass of the sweet basil decreased from 0.250 kg to 0.029 kg. During the drying process, great care was paid in measuring and evaluating all parameters. Once the approximately equal conditions existed, the validity of the experimental data was to adjust the related parameters by repeating the same experiments for a few times. 3. Analyses 3.1. Error analyses It is widely known that the errors stemming from fixed, manufacture and random errors are effective during temperature measurement, speed, weight loss, time and air moisture in drying experiments conducted via cabinet type solar air collector. The total error value can be calculated by taking fixed, manufacture, and random errors into consideration in order to determine the total error in any parameters whose measurements are carried out [6]. If the amount of error with each variable effecting the measurement is defined as x, total error can be written as follows:
i1=2 h Wth ¼ ðx1 Þ2 þ ðx2 Þ2 þ ………ðx∞ Þ2
(1)
Total errors in measurement carried out in solar air collector with cabinet type are determined as shown in Table 1. 3.2. Efficiency analysis In the experimental study, solar air collectors were used to heat the air. As it is known, the air inlet-outlet temperature differences in solar air collectors (DT) change as in the following function:
ðDTÞ ¼ fðV; I; Ac ; ta; FR ; UL Þ
(2)
However, bound and free variables given in equation (2) change in connection with different parameters on their own. In this study, in order to increase collector efficiency, guiding fins were used on the surface area of collector, and by extending flow way, the efficiency was tried to be increased by means of passive method without using additional energy. Collector efficiency in connection with variables is expressed as
Table 1 Total values of errors made in drying experiments. Parameters causing errors in experiments Total error WT,I WT,o WT,s WTc,i WTc,o WTm WTe Total error Wt Total error Wwdry Wwwet Total error WV Total error WM Total error WP
Unit
Total error
C C C C C C C
±0.173 ±0.173 ±0.173 ±0.173 ±0.173 ±0.173 ±0.173
min
±0.141
gr gr
±0.212 ±0.014
m/s
±0.104
r.H.
±0.200
mbar
±0.0025
stemming from heat measurement
stemming from time measurement stemming from loss of weight
stemming from speed measurement stemming from moisture measurement stemming from pressure measurement
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
81
follows:
h¼
Qu F IðtaÞ FR UL ðTi To Þ ¼ R I I Ac
(3)
The useful energy employed in determination of collector efficiency, Qu, can be calculated via following equation:
_ p ðTo Ti Þ Qu ¼ mC
(4)
3.3. Drying analyses It is possible to calculate the moisture content of crop being dried at any t time as follows:
Moisture content ¼
Mt Me Me
(5) Fig. 4. Alterations in radiation values of days drying experiments were conducted according to time of day.
In drying process, dimensionless moisture ratio (MR) is one of the most important parameters while examining drying and dryer parameters. While calculating dimensionless moisture ratio, measurement time, moisture content, initial moisture content and balance moisture content are taken into consideration.
MR ¼
Mt Me Mi Me
4. Results and discussions The days with approximately equal radiation are preferred in order to compare drying experiments conducted between the dates of 24 August and 6 September. As can be seen in Fig. 4, the radiation values change between 440 and 490 W/m2 during morning hours and increase from 720 to 750 W/m2 gradually. After 16.00 o'clock, the radiation value decreases till it reaches to 200 W/m2. At these radiation values, drying experiments were carried out at three different mass flow rates (0.012 kg/s, 0.026 kg/s, 0.033 kg/s). As mentioned before, fins having a ¼ 30 , 45 and 60 angles were mounted inside the air flow way in order to increase the efficiency of the collector. As known, mounting the fins inside the flow environment extends the flow way preventing formation of boundary layer in flow channel. Furthermore, extended surface influence occurs because of the impact of fins and, as a result, outlet temperature of the air increases. Before starting drying experiments, the most convenient collector was identified to determine collector activities for drying experiments. For this aim, heat transfer experiments were initially done at three different mass flow rates for all collectors. As a result of the experiments, it was witnessed that the smaller the angle of the fin, the higher the instant efficiency of the collector was. This case showed the importance of fixing way of the fins placed in the collector flow channel. Namely, the more the fins'
(6)
Moisture ratio (MR) models are given in the literature after being developed for drying process. Khi-square (X2), sufficiency parameters (EF) and root mean square error (RMSE) values are obtained for correlations calculated by means of multi regression.
c2 ¼
2 Pn i¼1 MRexp;i MRthe;i n nk
(7)
2 Pn Pn i¼1 MRthe;i MRthe;m i¼1 MRexp;i MRexp;m EF ¼ Pn i¼1 MRexp;i MRexp;m
RMSE ¼
"Pn #1=2 i¼1 MRthe;i MRexp;i n
(8)
(9)
Drying constant is determined utilizing experimental data according to dried crop and drying conditions. To explain the drying curves, semi theoretical and empirical models were developed by some researchers. These models are presented in Table 2 [6].
Table 2 Drying curve models present in the literature. Model name
Model equation
Ref.
Newton
M t M e ¼ expðktÞ MR ¼ M 0 M e
[25]
Page
M t M e MR ¼ M ¼ MR ¼ expðktn Þ 0 M e
[26]
Modified page
M t M e MR ¼ M ¼ expððktÞn Þ 0 M e
[27]
Henderson and Pabis
M t M e MR ¼ M ¼ a expðktÞ 0 M e
[28]
Logarithmic
M t M e MR ¼ M ¼ a expðktÞ þ c 0 M e
Wang and Singh
MR ¼
Fick’ s diffusion
MR ¼
Diffusion
MR ¼
Modified page II
MR ¼
Midilli and Kucuk
MR ¼
M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e M t M e M 0 M e
[29] [30]
2
¼ 1 þ at þ bt
¼ MR ¼ aexpðcðt=L ÞÞ
[31]
¼ aexpðktÞ þ ð1 aÞexpðkbtÞ
[32]
¼ expðkðt=L2 Þn Þ
[31]
¼ aexpðktn Þ þ bt
[33]
2
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surfaces fixed in the flow direction were vertical to the flow direction, the more efficient the collectors were. When fin angle was 30 , maximum efficiency was obtained. Therefore, this type of collector was used in drying experiments. In Fig. 5, the efficiencies at different mass flow rates were given with a ¼ 30 for the most efficient collector type. The air flow is directly proportional to collector efficiency. _ ¼ 0.012 kg/s, while collector In regard to radiation values, for m efficiency is 29% at 9.00 o'clock, it rises to 42% at 13.00 o'clock. The _ ¼ 0.012 kg/s, 51% for maximum efficiency value is 42% for m _ ¼ 0.026 kg/s and 63% for m _ ¼ 0.033 kg/s. When fin angle is m a ¼ 45 and while maximum efficiency value is 38% for _ ¼ 0.012 kg/s, it is 45% for m _ ¼ 0.026 kg/s and 55% for m _ ¼ 0.033 kg/s. When fin angle is a ¼ 60 , the maximum collector m _ ¼ 0.033 kg/s. efficiency is 47% for m In Fig. 6a, the changes according to drying time of dimensionless moisture ratio for sweet basil can be observed. Naturally, when t is 0, the dimensionless moisture ratio of crop is found as 1. Dimensionless moisture ratio decreases rapidly to 300 min for 0.012 kg/s; 360 min. 0.026 kg/s; 450 min for 0.033 kg/s in drying sweet basil. This slows down after time elapses. The change in moisture content for sweet basil is given in Fig. 6b according to drying time. Maximum moisture content for sweet basil is 7.62 kg-water. As the moisture content increases, the effect of flow rate on the change of moisture content also increases according to data obtained as a result of experimental study carried out for sweet basil. To determine the drying speed, derivative of moisture content is taken according to time. The change in drying speed for sweet basil according to drying time is given in Fig. 6c. For all mass flow rates, as the drying time increases, the effect of moisture content on drying speed decreases. At the start of drying process, moisture content has more effect on drying speed. This speed lasts during all drying process though it gradually loses its effect. As is seen, the effect of mass flow on dimensionless moisture is significant. Furthermore, drying speed until 0.026 kg/s of sweet basil is more influential on dimensionless moisture compared to mass flow. When mass flow rate increases to 0.033 kg/s, the effect of mass flow rate on dimensionless moisture increases, as well. Several experimental equations were developed for drying process. Moisture ratio change obtained for all drying processes conducted was later compared to these equations. Equation coefficient (R) is high, while comparison requires X2 and RMSE values to
Fig. 6. a) Alteration of dimensionless moisture ratio according to drying time. b) Alteration of moisture content according to drying time. c) Alteration of drying rate according to drying time.
Fig. 5. Instant collector efficiency alterations according to time of day for a ¼ 30 .
be low. In this study, moisture ratio values obtained for sweet basil were compared to those equations given in the literature. If the diversity of agricultural crops and if each crop is considered to be different with its physical properties and dimensions, it will obviously be seen that the mass change in each crop is different
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
during drying process. This change in mass during drying may not only occur with regard to physical properties of crop but also it may change with regard to drying environment and the properties of dryer. For instance, it is aimed to reduce the moisture amount in the crop by means of drying process. However, it is required that the product should be hygienic and should not lose its flavour and nutrition value. In this study, solar energy and drying parametres were examined for sweet basil. After the obtained data were applied to frequently used model equations, a convenient model for sweet basil was constituted. Nevertheless, it was found out that some equations commonly used in the literature were not convenient models for drying leafy products. Relying on the data obtained, it was determined that Fick Diffusion Model, Two-Term Model and Midilli Model were not convenient equations for drying leafy products. It was observed that all three models did not give correlation coefficient in regression analysis carried out. Therefore, coefficient table, experimental and theoretical graphics were not given for these models. In drying sweet basil, moisture ratio change is clearly logarithmical. In respect with this, odd numbered logarithmical and second level parabolical equations are obtained as a more convenient model for drying sweet basil. While developing a convenient model for drying processes, only correlation coefficient or X2 and RMSE are not taken into consideration. These parametres should be evaluated as a whole. When data obtained for sweet basil drying were evaluated within this model equations (Table 3), Wang and Singh Models containing second level parabol equation were calculated as the best models (Fig. 7). When all related parametres are taken into consideration, Page Model seems to be the best model for sweet basil drying. In Fig. 8, the comparison of experimental and theoretical values is given for sweet basil obtained for Modified Page 1 Model. X2 and RMSE exist in levels of 108 and 105 (Table 3). This ratio is an acceptable one. For Modified Page 1 Model, correlation coefficient changes between 0.992 R 0.997. The fact that correlation coefficient meets experimental values with a value of 99% shows that experimental
83
Fig. 7. Change in theoretical values according to experimental values for sweet basil (Wang and Singh Model).
studies and equations produced are quite in concordance and are required values. One of the most suitable models in drying sweet basil is Newton Model. As mentioned above, the most suitable correlations for mint and sweet basil are those of second stage parabola and odd numbered logarithmical ones. Newton Model is one of them. In this model, correlation coefficient changes between 0.972 R 0.993 (Table 3). As it is seen in Fig. 9, theoretical and experimental values for sweet basil meet each other within the boundaries of ±20%. Page model is one of the most appropriate equations (Table 3). With regard to correlation coefficient change between 0.989 R 0.999 theoretical and experimental values meet each other with a good percentage as ±10%. This change is obviously seen for sweet basil in Fig. 10.
Table 3 Relevant parameter values for different models. Model name
The drying air mass flow rate (kg/s)
Drier inlet-outlet temperature difference
Wang and Singh
0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033 0.012 0.026 0.033
13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423 13.221 8.613 7.423
Modified page I
Newton
Page
Modified page II
Henderson and Papis
Diffusion
This study
a 0.002 0.003 0.005 e e e e e e e e e 0.333 1.519 1.256 1.321 1.118 1.082 201.9 192.1 97.3 0.910 1.189 1.092
B
c
k
n
RMSE
X2
EF
R
0.000001 0.000003 0.000007 e e e e e e e e e e e e 0.005 0.006 0.007 0.990 0.996 0.991 1.387 1.407 1.123
e e e e e e e e e e e e 0.61 0.0004 0.0003 e e e e e e e e e
e e e 1.703 1.554 1.113 0.003 0.005 0.007 0.0002 0.0003 0.0004 e e e e e e 0.007 0.011 0.013 0.0003 0.0004 0.002
e e e 0.000001 0.000003 0.000007 e e e 1.441 1.486 1.119 0.0004 0.394 0.411 e e e e e e e e e
3.5E6 3.1E6 4.2E6 1.3E5 7.8E5 1.7E5 5.3E5 1.8E5 1.1E5 2.3E6 1.8E6 8.83e5 8.3E1 2.7E2 1.7E3 2.6E5 1.9E5 1.9E6 2.3E6 1.8E6 8.8E5 1.2E6 8.81E7 9.3E7
3.9E8 4.2E8 4.3E8 7.8E7 4.5E8 9.3E7 1.8E8 1.5E8 1.1E8 1.98E8 6.6E8 1.3E8 4.8E2 4.4E2 8.3E3 1.2E8 3.3E8 2.2E8 1.9E8 6.6E8 1.3E8 8.8E8 9.5E8 9.3E8
0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999 0.9999
0.993 0.996 0.994 0.992 0.998 0.993 0.972 0.981 0.993 0.989 0.998 0.992 0.566 0.861 0.903 0.987 0.981 0.996 0.998 0.994 0.997 0.991 0.994 0.995
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Fig. 8. Change in theoretical values according to experimental values for sweet basil (Modified Page 1 Model).
Fig. 10. Change in theoretical values according to experimental values for sweet basil (Page Model).
Fig. 9. Change in theoretical values according to experimental values for sweet basil (Newton Model). Fig. 11. Change in theoretical values according to experimental values for sweet basil (Modified Page II Model).
Equations containing dimensions of crop do not provide drying parametres in drying and modelling of leafy products. Yet, Modified Page Model gives a bad value correlation coefficient as 0.566 R 0.903. Therefore, theoretical and experimental values meet each other at the boundaries of ±60% for sweet basil (Fig. 11). X2 and RMSE exist at the levels of 102. Handerson and Papis Model and Diffusion Model are appropriate correlations for many different kinds of crops (Figs. 12e13). When credible parameters given in Table 3 are considered, it will be seen that both correlations are appropriate for sweet basil. Apart from different models available in the literature for modelling drying processes, it is needed to develop a novel moisture content model (MR). The model correlation developed can be obtained as follows:
MR ¼
Mt Me ¼ exp kðt a Þ k t b M0 Me
(10)
According to the correlation developed, correlation coefficient for sweet basil is obtained at a very high level as 99% for all mass
flow rates. Moreover, X2 and RMSE appear at rather low levels such as 109 and 107 for obtained correlations (Table 4). Fig. 14 gives theoretical and empirical results of change in sweet basil. As seen, theoretical and empirical values are obtained at highly appropriate clearance as ±5%. In determining diffusion coefficient for sweet basil, Arrhenius function is preferred. The mass flow rate of drying air and collector inlet-outlet temperature difference are used [34].
DF ¼ a1 $m_ a2 $exp
a 3
DT
(11)
Diffusion coefficient obtained for sweet basil at three different mass flow rates is given in Table 5. When diffusion coefficients are carefully inspected, it will be seen that the equation of theoretical diffusion correlation and empirical diffusion correlation are quite close to each other.
F. Gulcimen et al. / Renewable Energy 93 (2016) 77e86
Fig. 12. Change in theoretical values according to experimental values for sweet basil (Henderson and Papis Model).
Fig. 13. Change in theoretical values according to experimental values for sweet basil (Diffusions Model).
Table 4 Relevant parameter values for correlation designed for this study. The drying air flow (kg/s)
0.012
0.026
0.033
Drier inlet-outlet temperature difference A B K RMSE X2 EF R
13.211 0.910 1.387 0.0003 1.2E-6 8.8E-8 0.9999 0.991
8.613 1.189 1.407 0.0004 8.81E-7 9.5E-8 0.9999 0.994
7.423 1.092 1.123 0.002 9.3E7 9.3E8 0.9999 0.995
5. Conclusion In the drying process, deterioration of physical properties of the dried product, hygiene of drying environment, continuity of the drying process, efficient operation of the dryer model, usability of the dryer model, low cost of the drier manufacturing and drying
85
Fig. 14. Change in theoretical values according to experimental values for sweet basil (This study).
process are the primary requirements. The main advantages of the drying process by solar energy are; using renewable energy sources as the energy supply, low installation costs, complying with the climate conditions, providing drying in a hygienic environment that does not require chemical processing. In this type of systems, there are two major problems. The first one is to failure to take advantage of solar energy effectively. The other is to unabling benefit from solar energy during the day along and therefore enabling to meet the energy requirements continuously. This study aims to bring a solution to the problems mentioned at first. Furthermore, by using obtained drying parameters, the comparisons were made for drying mathematical models in the literature and a new model was proposed for Reyhan drying. In this study, drying parametres of sweet basil were determined empirically in a cabinet type dryer under climatical conditions of Elazig province with the help of newly designed solar air collectors. By employing these drying parameters obtained, a comparison was carried out for mathematical drying models given in literature. Furthermore, a novel drying model was developed for the handled crop. The obtained results of the study are given below: - The mass flow rate of the air is directly proportional to collector efficiency. In respect to the radiation values, while collector efficiency is 29% at 09.00 a.m. for 0.012 kg/s, it rises upto 42% at _ ¼ 0.012 kg/s, 13.00. The maximum efficiency value is 42% for m _ ¼ 0.026 kg/s and 63% for m _ ¼ 0.033 kg/s. Should and 51% for m classical plane surface solar air collector efficiency values, changing between 20 and 25%, be considered, the efficiency values for collectors that we developed appear to have increased significantly. - Before starting the drying process via solar air collectors, drying was applied to sweet basil in natural environment. As can easily be seen from the correlation between mass changes and drying time for sweet basil, mass change became zero after nearly 1320 min in natural environment. According to these data, it was found out that sweet basil dried approximately in three days. At the beginning of each day, mass and moisture content changed slowly. In this, it attracts attention that morning radiation values and environment temperature were low to bring crop to a regime. Drying moisture content was approximately 10e12%.
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Table 5 Diffusion coefficient at different mass flow rates for sweet basil. The drying air flow (kg/s)
0.012 0.026 0.033
Drier inlet-outlet temperature difference
13.21 8.61 7.42
- In the solar air collectors, drying time for 0.012 kg/s sweet basil is 600 min. However, it is 420 min for 0.033 kg/s. 0.250 kg sweet basil decreases to 0.029 kg dry product losing 88% water content. 0.221 kg water in 0.250 kg sweet basil dries in 420e600 min depending on mass flow rate of air. Eventually, the solar energy was effectively utilized by the designed collector with a new model. During the development and implementation of this study, the mentioned problems can be solved by alternative methods such as the use an additional source of energy, energy storage, etc. Acknowledgement The authors would kindly like to thank to Firat University Research Foundation (FUNAF) (FUNAF-1038) for financial contribution. Furthermore, we would like to express our highly gratitudes to the experienced English lecturer Ihsan Pilatin of Batman University for his contributions in checking the paper throughly and making all necessary corrections. References [1] O.V. Ekechukwu, B. Norton, Review of solar energy drying systems II: an overview of solar drying technology, Energy Convers. Manag. 40 (1999) 615e655. [2] A. Hobbi, K. Siddiqui, Experimental study on the effect of heat transfer enhancement devices in flat-plate solar collectors, Int. J. Heat Mass Transf. 52 (2009) 4650e4658. [3] B.M. Ramani, A. Gupta, R. Kumar, Performance of a double pass solar air collector, Sol. Energy 84 (2010) 1929e1937. [4] A.M. El-Sawi, A.S. Wifi, M.Y. Younan, E.A. Elsayed, B.B. Basily, Application of folded sheet metal in flat bed solar air collectors, Appl. Therm. Eng. 30 (2010) 864e871. [5] I. Kurtbas, A. Durmus, Efficiency and exergy analysis of a new solar air heater, Renew. Energy 29 (2004) 1489e1501. [6] H. Karakaya, A. Durmus, Investigation of efficiency and exergy loss in plate heat exchangers having spiral surface profiles, Energy Educ. Sci. Technol. 28 (2) (2012) 577e590. [7] A. Akbulut, A. Durmus, Energy and exergy analyses of thin layer drying of mulberry in a forced solar dryer, Energy 35 (4) (2010) 1754e1763. [8] E.K. Akpinar, Y. Biçer, C. Yildiz, Thin layer drying of red pepper, J. Food Eng. 55 (2003) 99e104. [9] K.B. Koua, W.F. Fassinou, P. Gbaha, S. Toure, Mathematical modelling of the thin layer solar drying of banana, mango and cassava, Energy 34 (2009) 1594e1602. [10] I. Doymaz, Convective air drying characteristics of thin layer carrots, J. Food Eng. 61 (2004) 359e364. [11] A. Kouchakzadeh, The effect of acoustic and solar energy on drying process of pistachios, Energy Convers. Manag. 67 (2013) 351e356. [12] M. Ozdemir, Y.O. Devres, The thin layer drying characteristics of hazelnuts
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1.6E14 6.8E11 1.3E11
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