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Airflow distribution in an apple storage room
Journal Pre-proof Airflow distribution in an apple storage room Ulrike Praeger, Reiner Jedermann, Marc Sellwig, Daniel A. Neuwald, Nico Hartgenbusch, Mykhailo Borysov, Ingo Truppel, Holger Scaar, Martin Geyer PII:
S0260-8774(19)30390-5
DOI:
https://doi.org/10.1016/j.jfoodeng.2019.109746
Reference:
JFOE 109746
To appear in:
Journal of Food Engineering
Received Date: 17 May 2019 Revised Date:
29 August 2019
Accepted Date: 28 September 2019
Please cite this article as: Praeger, U., Jedermann, R., Sellwig, M., Neuwald, D.A., Hartgenbusch, N., Borysov, M., Truppel, I., Scaar, H., Geyer, M., Airflow distribution in an apple storage room, Journal of Food Engineering (2019), doi: https://doi.org/10.1016/j.jfoodeng.2019.109746. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
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Airflow distribution in an apple storage room
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Ulrike Praeger1*, Reiner Jedermann2, Marc Sellwig3, Daniel A. Neuwald3, Nico Hartgenbusch2, Mykhailo Borysov2, Ingo Truppel1, Holger Scaar1, Martin Geyer1
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Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max‐Eyth‐Allee 100, Potsdam 14469, Germany; upraeger@atb‐potsdam.de; itruppel@atb‐potsdam.de; hscaar@atb‐potsdam.de; mgeyer@atb‐potsdam.de 2
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Institute for Microsensors, ‐actuators and –systems (IMSAS), University Bremen, Otto‐Hahn‐Allee NW1, 28359 Bremen, Germany; [email protected]‐bremen.de; [email protected]‐ bremen.de; [email protected]‐bremen.de
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Competence Centre for Fruit Growing—Lake Constance (KOB), Schumacherhof 6, 88213 Ravensburg, Germany, marc.spuhler@kob‐bavendorf.de; neuwald@kob‐bavendorf.de
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*Correspondence Author
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Abstract
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In refrigerated stores of fruit and vegetables, cooling air is circulated by air coolers attached to the ceiling. Uniform airflow and even temperature distribution in the product stacks is important for quality maintenance. However, the air speed close to the produce inside the bins in industrial cold stores is unknown. Airflow distribution was measured with newly developed sensors at different ventilation levels inside bins and in vertical gaps between the bins in a common apple storage room. The air speed between the fruit was low (≤ 0.3 m/s) compared to the average air velocity in the neighboring gap (1.15 m/s) at 100 % fan power. In the bins of the upper stack area, the air speed was about 7 times higher than that in the bins at the bottom. The airflow pattern in the vertical gaps showed the formation of an air roll with relatively uniform air velocity across the height of the bin stack. Reducing the fan power immediately lowered the airflow between the fruit and in the gaps. However, airflow was detected at all measuring positions, even when the fan power was reduced to 44 %.
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Keywords: cold store, airflow distribution, fruit bin, air speed, airflow sensor, fan revolution
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1. Introduction
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In cold stores of fruit and vegetables, air circulation is essential to remove field and respiration heat of the produces and to minimize temperature gradients in the rooms. Maintenance of homogenous temperature and humidity adapted to the requirements of the produces prevents quality loss due to respiration, water loss, or infestation with pathogens. In refrigerated stores, air coolers are fixed overhead at the ceiling. Coolers are fitted with fans, which blow the cooled air over the bin stacks. The fan operation typically use up to 30‐40 % of the total energy requirement of an apple CA store (Kittemann et al., 2015; Koca and Hellicson, 1993). During the initial cooling phase, fans are running continuously with full power. After the produces had cooled down, the fan operation is limited to about 6 to 8 hours per day related to the operation of the cooling unit.
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For maintenance of stable temperatures in the stores, the cooling unit usually operates with a differential gap between 0.5 and 1.5 K of the air inlet temperature at the cooler. During long‐term storage, fan operation is the major source of heat load in an apple cold store (Ambaw et al., 2016). The authors pointed out the energy saving potential by reduced operation time of fans and cooling units and by variable temperature set points, which enhances temperature fluctuations of the stored products within limited range.
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In CA storage, slightly increased temperatures only minimally affect fruit quality (East et al., 2013). Commonly, fans are running with constant revolution. Although electrically commutated (EC) fans are increasingly used for condensers at the heat removal side of the cooling circuit in industrial stores they are rarely applied for evaporators inside storage rooms. The recommended air exchange rate referred to the volume of the empty room is about 40/h during the initial cooling phase and can be reduced to approximately 20/h during long‐term storage (Gasser and Höhn, 2012).
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The demand for airflow studies aiming to optimize the design of facilities for precooling with forced air, transport and of storage rooms for fruit and vegetable storage has been largely increasing during the last 20 years. Several authors performed air velocity measurements in refrigeration facilities to validate CFD models for airflow simulation (Ferruah and Singh, 2009; Moureh et al., 2009; Dehghannya et al., 2010; Ambaw et al., 2013a). So far, numerical simulation of airflow in big industrial storage rooms of fruit and vegetables has not been realized yet without simplification of the bin layout (Ambaw et al. 2016, Scaar et al. 2017). Airflow in cold stores was mainly studied in experimental chambers of small volume (< 50 m3). These chambers were either empty or filled with few bins or boxes stacked on pallets with stable air circulation of the fans. Airflow velocity in gaps between bins or between bins and the wall were measured with either directional hot wire anemometers by turning them to record values in two directions (Duret et al., 2014, Scaar et al., 2017) or with omnidirectional thermal anemometers (Hoang et al., 2000). The vertical air velocity profiles in storage chambers were rather uniform with values in a range between 0.5 m/s and 1.5 m/s directly at the level of bins and with higher velocity (≥ 2 m/ s) in the space above the bins (Duret et al., 2014, Hoang et al., 2000; Kolodziejczyk et al., 2016). The formation of air rolls in the chambers depended on the respective loadings (Nahor et al., 2005; Delele et al., 2009). Applying air velocity measurements and CFD‐modeling, Bhanderi (2016) analyzed the relation between air velocity at the outlet of the air cooler and temperature variations in the stacks of an experimental 900 m3 apple storage room. Neuwald et al. (2015) investigated the effect of room modifications on airflow distribution measured in gaps between bins in industrial CA‐storage rooms for apples (40 t). Using a 2
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sealing‐off below the evaporator increased the air velocity at the bottom of the room, which improved airflow uniformity in the room.
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Knowledge about airflow properties close to the produces is essential for the development of techniques that improve air distribution uniformity in cooling rooms. It is also necessary for the optimization of the bin design or the stacking layout in cold stores and, thus, the reduction of energy consumption and produce losses. Airflow in packages close to the produces was analysed by CFD simulation (Delele et al., 2013; Han et al., 2015) or by heat transfer determination using heated measuring spheres (Alvarez and Flick, 2007; Moureh et al., 2009; Duret et al. 2014). Alvarez and Flick (1999) measured air velocity inside bins between produce dummies with a common hot wire anemometer, but for the installation of the sensor, the removal of some produce dummies was necessary. Ambaw et al. (2013b) used omnidirectional thermal anemometers for measurement of air velocity next to two bins and between fruit dummies inside the bins in a container of 0.5 m3. They measured air velocity for validation of a CFD model for distribution of the gas 1‐MCP in the ventilated container. Recently, an omnidirectional speed sensor was developed by Geyer al. (2018) for airflow measurement at very low speed (< 1.5 m/s) between fruit in a bin or bulk with random stacking.
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In order to provide a detailed analysis of the airflow pattern in the gaps between bin stacks, it is necessary to measure the angle of airflow in addition to its magnitude. The sensor resolution has to be high enough to measure airflow down to 0.1 m/s. Several 2‐dimensional (2D) airflow sensors had been developed in the past, but most available 2D sensors were only tested for airflow higher than 1 m/s, e.g. the device from Van Oudheusden and Huijsing (1991). They reported an average error of 1% without cover, which is increased to a value between 5% and 10% if the cover to protect the sensor is mounted. Piotto et al. (2011) presented a device that is able to measure airflow down to 0.5 m/s with a maximum error of 8%. Cubukcu et al. (2010) showed that it is feasible to measure airflow down to less than 0.01 m/s under laboratory conditions if the air is directly conducted to the sensor element by a small channel at a certain airflow angle. The reduction of the sensor resolution by the necessary housing to fix the sensor in the target environment was not part of their study. A more detailed survey of available 2D sensors was presented in Jedermann et al. (2018).
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The relationship between the airflow at the outlet of the cooler and the airflow close to the products in bins within industrial fruit and vegetable storage rooms is still unknown. Thus, the presented study aimed to comprehensively evaluate the airflow distribution in an industrial apple storage room in the gaps both between and inside bins during common and during reduced fan power. This investigation also targeted to analyze the minimum fan revolution still allowing for undisturbed airflow and air rolls in the room. In a practical apple store, the airflow distribution was measured in the gaps between bins and between fruit inside the bins at stepwise reduction of fan power.
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Newly developed sensors measured the two‐dimensional air velocity in the gaps and determined the omnidirectional airspeed between fruit. For the study of airflow between fruit inside large bins, only the variation of air volume at constant ambient temperature was considered. Disturbing effects of temperature fluctuations and of heat production by stored produces on airflow and the sensor measurements, relevant in actual storage situations, should be minimized (section 2.1; 2.2).
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2. Material and Methods
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2.1 Cold room facility and stacking layout In March 2017, tests for airflow analyses were performed at the Competence Centre for Fruit Growing ‐ Lake Constance (KOB) in an apple store with a storage capacity of 67 tons. For these studies, only the airflow in the room produced by the fans was examined at a constant temperature without considering cooling effects. In a CA‐storage room of apples with low temperature (1‐4°C) the thermal effect on airflow, e.g. due to heat production of the fruit (about 10 W/t, Osterloh, 1996), is marginal compared to the air circulation due to the fans. Therefore, four fans without evaporators were fixed on a track, laterally moveable below the ceiling with 45 cm distance to the wall (Figure. 1). The axial flow fans (type AxiCOOL EC W3G450‐SC28‐35, ebm‐papst, Mulfingen GmbH & Co. KG, Mulfingen, Germany) had a cross‐section of 45 cm and were fitted with an air guiding rectifier each. The revolution speed could be steplessly varied by a joint control voltage between 0 ‐ 10 V with a maximum revolution of 1300 rpm. An adjustable side wall was installed covering the original air coolers in the room. This room arrangement offers the possibility to examine different row‐ and fan‐ distances for tests described later.
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In the present study, the room had a volume of 292 m3 with 7.75 m depth, 5.70 m width and 6.6 m height. Standard bins for apple storage with a size of 120 cm x 100 cm x 78 cm (CargoPlast GmbH, Salem, Germany) with opening area proportion of walls and bottom of 7 % for approximately 300 kg fruit were used for building the stacks of 214 bins with the short side of the bins (100 cm) in the direction of flow. The bins were stacked in 4 rows, 7 bins deep and eight bins high, except for two stacks directly behind the door, which could only be loaded up to the 4th bin. The distances from the bin stacks to the sidewalls were 30 cm, to the wall opposite the fans it was 30 cm, to the wall below the fans 45 cm and between the rows 10 cm (Figure 1).
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Figure 1: Scheme of fully loaded store during airflow measurements
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Earlier investigations in a wind tunnel (Praeger et al., 2016) showed that, compared to empty bins, the bin fillings did not influence the airflow around single bins (air speed in the gap above the bin and next to the side wall). Therefore, only the uppermost bins directly exposed to the flow of the fans were filled with apples as well as the bins fitted with air speed sensors (Figures 5, 6).
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2.2 Airflow sensors
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For the characterization of the airflow in the bins, sensors specially developed for the omni‐ directional measurement of the low air speed (0‐1.5 m/s) between fruit were used (Air speed Logger – ASL). The term ‘air speed’ is used because air movement with unknown direction is quantified in contrast to ‘air velocity’. The sensor consists of four interconnected spheres (diameter 80 mm) with tetrahedron‐shaped layout, simulating neighboring fruit in a bulk. Air speed is measured by a calorimetric principle with temperature comparison of heated and unheated diodes, fixed with wires in the space between the spheres. The data recorded by the ASL are temperature‐compensated, but rapid temperature changes may cause measurement errors, since temperature gradients arise in the measuring arrangement due to thermal inertia. The sensitivity of the sensor increases with decreasing speed values (resolution of 2 µm/s near 0 mm/s). The device is a self‐contained 4
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measuring system with rechargeable lithium batteries and an internal data memory with adequate capacity for continuous measurement for up to 28 h (Geyer et al., 2018).
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The airflow measurements in the gaps were performed with newly developed wireless anemometers (WAMs) (Jedermann et al. 2018). Due to difficulties to install wires during transport of bins to the warehouse by forklift, a wireless solution was preferred. The housing form factor had to fit into gaps of 10 cm width. Furthermore, the sensor element had to be mechanically protected by a cover. The WAMs are based on a new sensor chip of size 2 mm × 2 mm for two‐dimensional air velocity measurement. The chip consists of a resistive heater, surrounded by 4 thermopiles (Hartgenbusch et al. 2018). Airflow creates a temperature difference between two diametrical thermopiles according to the calorimetric principle. The chip is glued into a printed circuit board for analogue and digital signal processing by low power electronics (Hartgenbusch et al., 2017). The cylindrical housing of 65 mm diameter and a height between 45 mm and 50 mm also includes a radio board for wireless transmission of the measurements. The airflow is measured inside the slit between main part and cover of the housing (Figure 2).
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The measurement tolerance and temperature dependency of the WAMs was verified by wind tunnel tests at different temperatures. The wind tunnel was calibrated with a Kimo VT200 Anemometer as reference. The calibration of the VT200 was verified with a Laser Doppler Velocity meter (LDV) (flowPoint fp50HeNe, Intelligent Laser Applications GmbH, Jülich, Germany).
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The average error was estimated to ±10% for 1 m/s. For the lowest velocity, the error increased to 19% at 0.1 m/s. Two variants of the housing were used during the tests, showing different errors at higher velocities ≥ 1.5 m/s. For the first variant with mounting posts of 3 mm diameter, the error increased to ±17% at high velocities due to turbulences behind the mounting posts. The mounting posts were later replaced by 0.6 mm needles (Figure 2), thus reducing the error to 8.7%.
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Figure 2: WAM with needles as mounting posts, holding the cover to protect the sensor element (A); scheme of WAM components (B)
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2.2.1 Preliminary test
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For finding the optimal positions of the sensors in the stacks and the number of ASL sensors per bin, a preliminary test was carried out in a refrigerated storage room of 40 t capacity filled with 163 apple bins stacked in 3 rows. The room was fitted with an air cooler with 5 fans (type Helpman, LFX 256‐7 230‐E4, 5 fans, Alfa Laval Corporate AB, Lund, Sweden, air volume rates of 14000 m3/h). Deviations of air speed in the hollow space between the apples of a bin should be determined by measurement at 5 different positions inside a bin at 4 different relative fan power levels (100 %, 75 %, 50 %, 25 %).
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Therefore 5 sensors (Figure 3) were placed in each of two bins about 20 cm below the surface of the apple filling, one in the centre and 4 about 20 cm from the corners. The two bins were placed at different tiers in the middle bin row of the storage room (at the 3rd and 7th tier from the floor).
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Figure 3: Preparation of measurements with 5 ASL-sensors in a preliminary test (A) and positions of the two bins fitted with sensors in the middle row of an apple storage room (B)
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The deviation of the actual from the average air speed values at five positions inside one box was up to 40 %. However, the air speed in the upper bin was on average 2.5 times higher than that at the related positions in the bin below (section 3.1.1). Therefore, the influence of the bin positions was 5
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regarded as more important than the sensor position inside one bin. The ASL sensors were placed in a large variety of bin positions during the subsequent main tests, but with only one sensor per bin.
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2.2.2 Main test
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For preparation of the main test, 24 bins were filled with apples for airflow measurements between the fruit with the ASL. In each bin, one sensor was placed in the center between the fruit about 20 cm below the surface of the apple filling (Figure 4).
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Figure 4: Positioning of the ASL between the apple fruit in the bin
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The scanning rate of the ASL sensors was 1 s. The air speed data were stored internally together with ambient temperature data.
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The preparation of the apple bins with the sensors was done at ambient temperature of about 10°C in March outside the building. Before stowing the bins filled with apples into the room, they were placed in front of the measuring room to adapt them to the temperature inside the warehouse building. The bins with the ASL‐sensors were placed in row 1 and 2 of the stack at the positions shown in Figure 5.
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Figure 5: Positions of ASL-Sensors inside the bins of row 1 and 2 (green bins) and positions of WAMs attached to the bins on both sides of row 1 (U=USB WAMs, R= Radio WAMs)
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A total of 31 WAMs were installed on the sides of the bins of the first row, half of them in the gap towards row 2 and the other half on the opposite side facing the wall (Figure 6, 7). Half of the WAMs per side were equipped with a radio interface (R). The radio WAMs measured the air velocity every 30 s. The average of 6 measurements was transmitted to a gateway every 3 minutes and finally recorded by a laptop. For a more detailed analysis, the remaining 8 WAMs per side were programmed to measure 5 times per second. They were directly connected over a USB interface (U) to transmit the full signal curve to a laptop.
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Figure 6: Attachment of the WAMs to the bin walls in the gap between row 1 and 2 (before stacking of the bins of row 2-4)
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Airflow was measured at 4 fan speeds by adjusting control voltage to 10, 7.5, 5 and 2.5 V. The revolution speed of the 4 fans was measured with a stroboscope. Not all fan speed controls worked properly and only two fans (1 and 3) run with stepwise decreased fan speed while speed of the other fans was reduced to only a lesser extent (Figure 7). Therefore the resulting total air volume rate was not reduced linearly at the four voltage steps with 21772 m3/h (100 %), 19743 m3/h (90 %), 16640 m3/h (76 %), 9584 m3/h (44 %) respectively (Figure 7) corresponding to an air exchange rate between 70/h and 33/h. The air velocity measured with a hand‐held hot wire anemometer (Testo 435‐2, Testo GmbH Austria, Wien, Austria; measuring range 0‐20 m/s), about 1 m in front of the 4 fans at the air outlet was in average about 10.5 m/s, 8 m/s, 5.5 m/s and 2.5 m/s for the 4 steps of voltage control.
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Figure 7: Effect of control voltage on revolution of individual fans and total air volume rate
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The airflow in the gaps and inside the bins was measured over 15 min. The fans were switched off for at least 5 min before each change of fan control voltage. During these periods, the temperature dependent zero offsets were measured and corrected for the USB‐WAMs. Distortion by convective airflow was manually measured to maximum 0.1 m/s when the fans were switched off. The first 6
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generation of Radio‐WAMs did not allow remote correction of zero offsets. Tests with the Radio‐ WAMs at lower fan speed and thus higher sensitivity towards temperature drifts were excluded from the further evaluation.
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For the presentation of the results of airflow measurements with the ASL sensors and the WAMs the average speed values of 15 min period were calculated. For characterization of the uniformity of the flow distribution in the bin rows and in the gaps an uniformity index (Zhang et al. 2017, Guhan et al. 2016) based on deviation from the average velocity was calculated by:
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is a dimensionless index between 0 and 1, expressing a high degree of uniformity when the value is near 1, is the speed at each observation point, is the average speed in the measurement
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section,
is the measuring point number.
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3. Results
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3.1 Air speed between fruit
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3.1.1 Dependency in regard to sensor position inside bin
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The preliminary test (section 2.2.1) in two bins with five sensors per bin showed deviations of air speed measurements of up to 40 % from the average value at different fan speed settings. In the bin in tier 3 the minimum air speed was 0.015 m/s and maximum air speed 0.036 m/s measured by five sensors at 100 % fan revolution (14000 m3/h). Inside the bin in tier 7 the air speed was between 0.06 and 0.13 m/s at 100 % fan revolution (Figure 8). With stepwise reduced fan revolution, the average air speed decreased relatively stronger in the bin at tier 7 than in tier 3.
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Figure 8: Air speed at five positions inside each of two bins at a low and a high bin position in a stack of stored apples (average of five positions with standard deviation (A, C); each measurement position at 100 % fan power (B, D); main airflow direction along the depth (1 m) of the bins)
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3.1. 3.1.2 Temporal air speed course
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Figure 9 shows exemplary single airspeed courses of the main test measured with the ASL inside four bins at different positions, two at stack 5/tier 6 and two at stack 1/tier 1 in row 1 and 2 respectively. Stepwise reduction of the fan revolution immediately changed the air speed between the fruit. The air speed decreased in most of the bins, except in some bins near to the floor, where even air speed slightly increased (Figure 9, position stack 1/ tier 1, row 1). The airflow speed between the apples in stack 5/tier 6 fluctuated with deviation of about 10 % from the average values but was highly constant at a certain fan revolution. The deviation was much higher (about 80 % from the average) at the position in stack 1/tier 1 near the floor. Temperature ranged between 10°C and 13°C with difference of about 1 C° between periods of fan operation and without ventilation. Temperature 7
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fluctuation was low in the bin in row 2 near the floor with very low airflow between fruit compared to the other positions.
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Figure 9: Examples of continuous air speed measurements with the ASL at four bin positions in the stack. Values were recorded for 15 min at each fan power setting and interruption of 5 min
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3.1.3 Summary of timetime-averaged air speed inside bins
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In the bins between apple fruit, the air speed was very low (≤ 0.3 m/s; average of all 24 positions 0.1 m/s) compared to the air speed at the outlet of the fans (ca. 10 m/s) at maximum total air volume rate of 21772 m3/h (Figure 10). At most bin positions of row 2, lower air speed was measured than in row 1 nearby the wall at corresponding positions resulting in average air speed (12 sensors) in row 2 of 0.07 m/s and 0.12 m/s in row 1, respectively. Air speed was highest in the bins of tier 8 and the bins of tier 6 and 4 of stack 5 and 7, situated near the fans.
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At all sensor positions and all fan power settings, airspeed values could always be recorded which were distinguishable from the status without ventilation when the fans were switched off. Air speed inside a bin was lowest (0.0006 m/s) at the position stack3/tier3 in row 2 at the fan power of 44 %. The stepwise reduction of the fan power decreased the air speed stronger between fruit inside bins at higher position in the whole stack than in the low tiers.
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Figure 10: Air speed inside bins at all measuring positions of row 1 and 2 at different fan power settings levels (bars indicate standard deviation of air speed values of each sensor during 15 min measurement period)
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3.2 Magnitude and direction of air flow inside gaps
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At 100 % fan power, air velocity in the gap between row 1 and 2 was much higher (1.15 m/s, average of 16 WAMs) than inside the bins between fruit (Figure 11). The airflow pattern in the gap between row 1 and the wall was very similar with average velocity of 1.17 m/s. At reduced fan power (< 100%), the values of the radio sensors were excluded because the measurement was not reliable. At some measuring positions, flow direction changed with decreased air velocity in both gaps, mainly in the medium and upper tiers of the stack.
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Figure 11: Air velocity and flow direction in the gap between row 1 and 2 at different fan power settings (Radio Sensors only shown for maximum fan power)
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3.3 Comparison of airflow in bins and gaps
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3.3.1 Influence of fan revolution
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Figure 12 (A) shows average air speed measured by the ASL‐sensors inside the bins of both rows and the WAMs in both gaps considering only the 15 USB‐sensors (Figure 5). Air velocity in the gaps was about 10 times higher than air speed in the bins. The reduction of air volume rates resulted in almost linear diminution of air velocity in the gaps and air speed between fruit inside the bins. In the gaps, 8
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air velocity decrease was stronger between row 1 and 2 than at the wall. Air speed inside the bins was higher in row 1 next to the wall than in the bins of row 2.
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The reduction of the maximum air speed in the bins of both rows and in both gaps was greater than that of the minimum air speed values with reduced air volume rate (Figure 12, B) resulting in a small difference between maximum and minimum speed values at low fan power compared to high fan power.
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Figure 12: Relation of air volume rate to average speed (A) and to minimum and maximum speed values inside the bins and in the gaps (B) (Radio WAMs excluded )
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3.3.2 Influence of bin position
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Inside the bins, highest air speed was measured in the upper area of the bin stack at the sensor positions of tier 8. There, air speed was on average 7 times higher than in the lowest tier 1 at 100 % fan power. This relation was smaller with reduced air volume rate to 16640 m3/h (Figure 13, A).
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In contrast to the speed values inside the bins, the average velocity measured in the gaps varied at different heights (tier) between 0.8 and 1.5 m/s at 100% fan power but there was no gradient from the highest to the lowest tier. The average air velocity for lower fan power is not shown in Figure 13 (A) because the values of the radio sensors were excluded (Figure 11).
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Figure 13: Average air speed in bins at different tiers (A) and average air velocity in both gaps at different tiers (B)
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The closer the bin stacks were to the fans, the higher the air speed was in the bins (Figure 14, A). Average air velocity in the gaps of different stacks ranged between 0.8 m/s and 1.3 m/s at 100 % fan power similar to the average values of different tiers. Lowest air velocity was measured at stack 1 and 2 far away from the fans and at stack 7 next to the fans (Figure 14, B).
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Figure 14: Average air speed in bins in different stacks (A) and average air velocity in both gaps at different stacks (B)
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The vertical gradient of air speed within the bins is reflected by less uniform speed distribution compared to the gaps. The uniformity of speed in bins and gaps was similar with usual ventilation (100 %) and reduced fan power settings (table 1).
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Table 1: Uniformity of airflow in bins and gaps Fan power setting
100 %
90 %
76 %
44 %
Uniformity index Bins in row 1
0.64
0.62
0.66
0.58
Bins in row 2
0.55
0.53
0.52
0.44
Gap between wall and row 1
0.87
0.89
0.93
0.93
Gap between row 1 and row 2
0.88
0.91
0.91
0.93 9
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4. Discussion
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Airflow in the gaps and between fruit in plastic storage bins in an apple storage room was measured with specific, newly developed and calibrated flow sensors. The exemplary temporal courses of airflow measurements inside the bins between the apples showed fluctuations in speed values which were highly constant at a certain fan power setting. These speed fluctuations occurred due to flow turbulences between the fruit. It can be excluded that the fluctuations are caused by the noise of the ASL sensors, because the comparison of the air speed values inside the bins in tier 6 and tier 1 (Figure 9) showed higher fluctuations at lower average speed. A test measurement during the development of the ASL device in a closed chamber showed a peak‐to‐peak noise of about 0.5 mm/s (Geyer et al. 2018).
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The average air speed inside the bins between the apple fruits was much lower than in the vertical gaps. For infiltration of airflow in the apple bulk the air must cross the barrier of the bin walls. Standard plastic storage bins cause high air resistance due to a small opening area of about 10 % of the walls and bottom. Thus, wall porosity is considerably lower than porosity of the apple bulk with a hollow space content of 41 % (Scaar et al., 2018). Delele et al. (2009) showed air velocity simulations in the porous region inside small vented boxes with fruit dummies stacked on one single pallet. The velocity values inside the boxes were also very low but in contrast to the present study higher at the bottom with 0.16 m/s than at the top (0.03 m/s). The simulation showed an air roll in front of the stack in the empty space of the store causing higher air velocity in the lower area of the store.
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Ambaw et al. (2017) performed an airflow simulation through a single bin situated on the floor in a ventilated empty storage room apart from this single bin. In the model the bin wall and apple bulk was differentiated and a similar air exchange rate of 80/h was assumed as in this study. The air velocity in the porous region inside the bin was in agreement with the present results below 0.1 m/s, because the circulating air bypassed the bin.
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In the vertical gaps of the bin stack in discharge direction of the fans, the flow direction measured with the WAMs (arrows Figure 10) and the calculation of the uniformity index showed that at 100 % fan power an air roll has formed over the entire stack height with relatively uniform velocity. Duret et al. ( 2014) measured similar air velocities (0.5 to 1 m/s) in gaps between apple bin stacks on pallets of a small apple cold store with 29 m3 volume. At low air velocities, only half of the WAMs were available. Their velocity and direction measurements indicate that the air roll in the gaps did not break down even at 44 % fan revolution.
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In contrast to the relatively uniform flow pattern in the vertical gaps, the bin position had a strong influence on air speed between the apples. Air speeds in the upper bins were about 7‐fold higher compared to the positions at the store ground. The flow direction inside the bins is not determined with the ASL sensors. High air velocity above the bin stack might cause an air sucking effect through the upper bins, which does not affect the bins in the low tiers in the stack. In tier 1, airflow in the gap below the bins is limited by the ground of the floor with small distance between the bottom of the bin and the floor.
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Ambaw et al. (2016) showed an airflow simulation in a similar apple cold store room with wooden bins and similar air exchange rate of 75/h, corresponding to the rate in the present study at 100 %. 10
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The volume averaged superficial air velocity per bin was in the same range as in this study (<0.6 m/s), but the gradient from the bins on the top to the bottom was less pronounced. The reason of lower speed values in this study in the low tiers might be low opening area portion of the plastic bins and an overestimation of speed values by the flow simulation because porosity of fruit bulk and bin wall was not distinguished.
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Air speed in the bins and gaps decreased almost linearly with reduced air volume rate generated by the fans. In the 30 cm wide gap near the wall, the airflow at 100 % fan power was very similar to the flow in the gap between the bin rows 1 and 2. With reduced fan power the air velocity in the 30 cm wide gap next to the bins decreased to a lesser extent than in the small gap of 10 cm width between the bin rows. Probably, higher velocities were measured in the wider gap, because the air is flowing in the direction of lowest resistance. Due to the turbulent flow regime in the gap (Reynolds number > 20.000), it could be assumed that the air velocity in the center of the 30 cm wide gap is in the same range as the measured air velocity with the WAM near the bin wall.
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The highest fan power setting (air volume rate of 21772 m3/h) corresponds to a common air exchange rate (70/h) in practical ventilated storage rooms (Ambaw et al. 2016). The calculation of the uniformity index shows that uniformity in bins and gaps is not affected by the air volume rate. Reduction of fan power up to 44 % still provided airflow in the bins at all measuring positions, but in the bins at the bottom air movement was hardly measurable, i.e. the recorded values of the sensor were only slightly higher than the noise signal. In single bins near the ground air speed even increased with reduced air volume in the store. Reduction in total air volume may cause local changes in airflow direction and thus local increase of air speed. These results do not permit a clear conclusion about a minimum tolerable air volume rate during long time storage without impairment of fruit quality. Airflow at the fruit surface affects heat and mass transfer, which were analyzed for precooling of apples and storage situations with common ventilation (Gaffney et al. 1985, Han et al. 2017, Duret et al. 2014). The impact of fast air speed changes with very low average (<0.1 m/s) on heat and mass transfer at the fruit surface has not yet been investigated.
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5. Conclusions
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A comprehensive study of airflow distribution was performed in a standard industrial apple cold store. Recently developed flow sensors allowed 2‐dimensional air velocity measurements in the vertical gaps between bin stacks and omnidirectional speed determination between the fruit in the bins.
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The accuracy of the WAMs was not fully satisfactory with an average error between 8.7% and 17% of the measured values. Nevertheless, their accuracy was sufficient to evaluate the magnitude and spatial pattern of typical airflow inside the gaps and its dependency on air volume rates. Values of several WAMs were averaged and thus the error reduced. For future tests, a new generation of improved WAMs can be used (Jedermann et al., 2018). Distortions of the airflow inside the WAM housing were reduced by replacing the mounting posts by a high number of evenly distributed fins. The temperature stability of the electronics was also improved.
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The ASL sensors allowed the determination of air speed fluctuations with very low average values (<0.05 m/s) between the fruit within the storage bins. Such measurements could not be determined 11
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before with available flow sensors. The presented results of air speed close to the product enable exact validation of numerical simulations of airflow in the porous region inside the bins in cold stores with complex geometry of bin stacks. The validated simulations can be used for further studies on the effect of modified room layout on airflow distribution.
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The velocity distribution in the vertical gaps was relatively uniform compared to the speed distribution in the bins, which showed a clear vertical gradient over stack height. An option to enhance the uniformity of speed in the bins could be to increase bin wall porosity. The fan power reduction up to 44 % showed that there is significant potential for energy saving with lower revolutions, because low fan power did not affect flow uniformity in bins and gaps and still provides for airflow close to the fruit. In order to find a tolerable limit for flow reduction near the fruit the effects of temperature and humidity have to be included.
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The knowledge gained about the air speed close to the product and its fluctuations in an actual industrial cold store can be used for targeted investigations of the mass and heat transfer at the surface of produces in bulks and resulting quality maintenance.
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Acknowledgements
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The ‘COOL’ project was supported by the Federal Ministry for Economic Affairs and Energy on the basis of a decision by the German Bundestag (grant number VP2050828CL4). The authors thank in particular the company ebm‐papst Mulfingen GmbH & Co. KG, Germany, for providing the fans, Daniel Dadej (KOB), Christian Regen und Stefan Elwert (ATB) for their support during the experiment and sheme preparation for the manuscript.
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Highlights • • • • •
Airflow distribution was determined in big bins and in gaps of an apple store New sensors were used for air speed inside bins and air velocity in the gaps The air speed in the bins was 7 times higher on top than on bottom of the bin stack The air velocity in the gaps was quite uniform across the height of the stacks Reduction of fan power to 44 % still provides for airflow in the whole room
Declarations of interest: none
S0260-8774(19)30390-5
DOI:
https://doi.org/10.1016/j.jfoodeng.2019.109746
Reference:
JFOE 109746
To appear in:
Journal of Food Engineering
Received Date: 17 May 2019 Revised Date:
29 August 2019
Accepted Date: 28 September 2019
Please cite this article as: Praeger, U., Jedermann, R., Sellwig, M., Neuwald, D.A., Hartgenbusch, N., Borysov, M., Truppel, I., Scaar, H., Geyer, M., Airflow distribution in an apple storage room, Journal of Food Engineering (2019), doi: https://doi.org/10.1016/j.jfoodeng.2019.109746. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
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Airflow distribution in an apple storage room
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Ulrike Praeger1*, Reiner Jedermann2, Marc Sellwig3, Daniel A. Neuwald3, Nico Hartgenbusch2, Mykhailo Borysov2, Ingo Truppel1, Holger Scaar1, Martin Geyer1
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1
Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max‐Eyth‐Allee 100, Potsdam 14469, Germany; upraeger@atb‐potsdam.de; itruppel@atb‐potsdam.de; hscaar@atb‐potsdam.de; mgeyer@atb‐potsdam.de 2
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Institute for Microsensors, ‐actuators and –systems (IMSAS), University Bremen, Otto‐Hahn‐Allee NW1, 28359 Bremen, Germany; [email protected]‐bremen.de; [email protected]‐ bremen.de; [email protected]‐bremen.de
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3
Competence Centre for Fruit Growing—Lake Constance (KOB), Schumacherhof 6, 88213 Ravensburg, Germany, marc.spuhler@kob‐bavendorf.de; neuwald@kob‐bavendorf.de
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*Correspondence Author
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Abstract
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In refrigerated stores of fruit and vegetables, cooling air is circulated by air coolers attached to the ceiling. Uniform airflow and even temperature distribution in the product stacks is important for quality maintenance. However, the air speed close to the produce inside the bins in industrial cold stores is unknown. Airflow distribution was measured with newly developed sensors at different ventilation levels inside bins and in vertical gaps between the bins in a common apple storage room. The air speed between the fruit was low (≤ 0.3 m/s) compared to the average air velocity in the neighboring gap (1.15 m/s) at 100 % fan power. In the bins of the upper stack area, the air speed was about 7 times higher than that in the bins at the bottom. The airflow pattern in the vertical gaps showed the formation of an air roll with relatively uniform air velocity across the height of the bin stack. Reducing the fan power immediately lowered the airflow between the fruit and in the gaps. However, airflow was detected at all measuring positions, even when the fan power was reduced to 44 %.
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Keywords: cold store, airflow distribution, fruit bin, air speed, airflow sensor, fan revolution
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1. Introduction
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In cold stores of fruit and vegetables, air circulation is essential to remove field and respiration heat of the produces and to minimize temperature gradients in the rooms. Maintenance of homogenous temperature and humidity adapted to the requirements of the produces prevents quality loss due to respiration, water loss, or infestation with pathogens. In refrigerated stores, air coolers are fixed overhead at the ceiling. Coolers are fitted with fans, which blow the cooled air over the bin stacks. The fan operation typically use up to 30‐40 % of the total energy requirement of an apple CA store (Kittemann et al., 2015; Koca and Hellicson, 1993). During the initial cooling phase, fans are running continuously with full power. After the produces had cooled down, the fan operation is limited to about 6 to 8 hours per day related to the operation of the cooling unit.
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For maintenance of stable temperatures in the stores, the cooling unit usually operates with a differential gap between 0.5 and 1.5 K of the air inlet temperature at the cooler. During long‐term storage, fan operation is the major source of heat load in an apple cold store (Ambaw et al., 2016). The authors pointed out the energy saving potential by reduced operation time of fans and cooling units and by variable temperature set points, which enhances temperature fluctuations of the stored products within limited range.
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In CA storage, slightly increased temperatures only minimally affect fruit quality (East et al., 2013). Commonly, fans are running with constant revolution. Although electrically commutated (EC) fans are increasingly used for condensers at the heat removal side of the cooling circuit in industrial stores they are rarely applied for evaporators inside storage rooms. The recommended air exchange rate referred to the volume of the empty room is about 40/h during the initial cooling phase and can be reduced to approximately 20/h during long‐term storage (Gasser and Höhn, 2012).
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The demand for airflow studies aiming to optimize the design of facilities for precooling with forced air, transport and of storage rooms for fruit and vegetable storage has been largely increasing during the last 20 years. Several authors performed air velocity measurements in refrigeration facilities to validate CFD models for airflow simulation (Ferruah and Singh, 2009; Moureh et al., 2009; Dehghannya et al., 2010; Ambaw et al., 2013a). So far, numerical simulation of airflow in big industrial storage rooms of fruit and vegetables has not been realized yet without simplification of the bin layout (Ambaw et al. 2016, Scaar et al. 2017). Airflow in cold stores was mainly studied in experimental chambers of small volume (< 50 m3). These chambers were either empty or filled with few bins or boxes stacked on pallets with stable air circulation of the fans. Airflow velocity in gaps between bins or between bins and the wall were measured with either directional hot wire anemometers by turning them to record values in two directions (Duret et al., 2014, Scaar et al., 2017) or with omnidirectional thermal anemometers (Hoang et al., 2000). The vertical air velocity profiles in storage chambers were rather uniform with values in a range between 0.5 m/s and 1.5 m/s directly at the level of bins and with higher velocity (≥ 2 m/ s) in the space above the bins (Duret et al., 2014, Hoang et al., 2000; Kolodziejczyk et al., 2016). The formation of air rolls in the chambers depended on the respective loadings (Nahor et al., 2005; Delele et al., 2009). Applying air velocity measurements and CFD‐modeling, Bhanderi (2016) analyzed the relation between air velocity at the outlet of the air cooler and temperature variations in the stacks of an experimental 900 m3 apple storage room. Neuwald et al. (2015) investigated the effect of room modifications on airflow distribution measured in gaps between bins in industrial CA‐storage rooms for apples (40 t). Using a 2
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sealing‐off below the evaporator increased the air velocity at the bottom of the room, which improved airflow uniformity in the room.
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Knowledge about airflow properties close to the produces is essential for the development of techniques that improve air distribution uniformity in cooling rooms. It is also necessary for the optimization of the bin design or the stacking layout in cold stores and, thus, the reduction of energy consumption and produce losses. Airflow in packages close to the produces was analysed by CFD simulation (Delele et al., 2013; Han et al., 2015) or by heat transfer determination using heated measuring spheres (Alvarez and Flick, 2007; Moureh et al., 2009; Duret et al. 2014). Alvarez and Flick (1999) measured air velocity inside bins between produce dummies with a common hot wire anemometer, but for the installation of the sensor, the removal of some produce dummies was necessary. Ambaw et al. (2013b) used omnidirectional thermal anemometers for measurement of air velocity next to two bins and between fruit dummies inside the bins in a container of 0.5 m3. They measured air velocity for validation of a CFD model for distribution of the gas 1‐MCP in the ventilated container. Recently, an omnidirectional speed sensor was developed by Geyer al. (2018) for airflow measurement at very low speed (< 1.5 m/s) between fruit in a bin or bulk with random stacking.
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In order to provide a detailed analysis of the airflow pattern in the gaps between bin stacks, it is necessary to measure the angle of airflow in addition to its magnitude. The sensor resolution has to be high enough to measure airflow down to 0.1 m/s. Several 2‐dimensional (2D) airflow sensors had been developed in the past, but most available 2D sensors were only tested for airflow higher than 1 m/s, e.g. the device from Van Oudheusden and Huijsing (1991). They reported an average error of 1% without cover, which is increased to a value between 5% and 10% if the cover to protect the sensor is mounted. Piotto et al. (2011) presented a device that is able to measure airflow down to 0.5 m/s with a maximum error of 8%. Cubukcu et al. (2010) showed that it is feasible to measure airflow down to less than 0.01 m/s under laboratory conditions if the air is directly conducted to the sensor element by a small channel at a certain airflow angle. The reduction of the sensor resolution by the necessary housing to fix the sensor in the target environment was not part of their study. A more detailed survey of available 2D sensors was presented in Jedermann et al. (2018).
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The relationship between the airflow at the outlet of the cooler and the airflow close to the products in bins within industrial fruit and vegetable storage rooms is still unknown. Thus, the presented study aimed to comprehensively evaluate the airflow distribution in an industrial apple storage room in the gaps both between and inside bins during common and during reduced fan power. This investigation also targeted to analyze the minimum fan revolution still allowing for undisturbed airflow and air rolls in the room. In a practical apple store, the airflow distribution was measured in the gaps between bins and between fruit inside the bins at stepwise reduction of fan power.
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Newly developed sensors measured the two‐dimensional air velocity in the gaps and determined the omnidirectional airspeed between fruit. For the study of airflow between fruit inside large bins, only the variation of air volume at constant ambient temperature was considered. Disturbing effects of temperature fluctuations and of heat production by stored produces on airflow and the sensor measurements, relevant in actual storage situations, should be minimized (section 2.1; 2.2).
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2. Material and Methods
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2.1 Cold room facility and stacking layout In March 2017, tests for airflow analyses were performed at the Competence Centre for Fruit Growing ‐ Lake Constance (KOB) in an apple store with a storage capacity of 67 tons. For these studies, only the airflow in the room produced by the fans was examined at a constant temperature without considering cooling effects. In a CA‐storage room of apples with low temperature (1‐4°C) the thermal effect on airflow, e.g. due to heat production of the fruit (about 10 W/t, Osterloh, 1996), is marginal compared to the air circulation due to the fans. Therefore, four fans without evaporators were fixed on a track, laterally moveable below the ceiling with 45 cm distance to the wall (Figure. 1). The axial flow fans (type AxiCOOL EC W3G450‐SC28‐35, ebm‐papst, Mulfingen GmbH & Co. KG, Mulfingen, Germany) had a cross‐section of 45 cm and were fitted with an air guiding rectifier each. The revolution speed could be steplessly varied by a joint control voltage between 0 ‐ 10 V with a maximum revolution of 1300 rpm. An adjustable side wall was installed covering the original air coolers in the room. This room arrangement offers the possibility to examine different row‐ and fan‐ distances for tests described later.
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In the present study, the room had a volume of 292 m3 with 7.75 m depth, 5.70 m width and 6.6 m height. Standard bins for apple storage with a size of 120 cm x 100 cm x 78 cm (CargoPlast GmbH, Salem, Germany) with opening area proportion of walls and bottom of 7 % for approximately 300 kg fruit were used for building the stacks of 214 bins with the short side of the bins (100 cm) in the direction of flow. The bins were stacked in 4 rows, 7 bins deep and eight bins high, except for two stacks directly behind the door, which could only be loaded up to the 4th bin. The distances from the bin stacks to the sidewalls were 30 cm, to the wall opposite the fans it was 30 cm, to the wall below the fans 45 cm and between the rows 10 cm (Figure 1).
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Figure 1: Scheme of fully loaded store during airflow measurements
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Earlier investigations in a wind tunnel (Praeger et al., 2016) showed that, compared to empty bins, the bin fillings did not influence the airflow around single bins (air speed in the gap above the bin and next to the side wall). Therefore, only the uppermost bins directly exposed to the flow of the fans were filled with apples as well as the bins fitted with air speed sensors (Figures 5, 6).
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2.2 Airflow sensors
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For the characterization of the airflow in the bins, sensors specially developed for the omni‐ directional measurement of the low air speed (0‐1.5 m/s) between fruit were used (Air speed Logger – ASL). The term ‘air speed’ is used because air movement with unknown direction is quantified in contrast to ‘air velocity’. The sensor consists of four interconnected spheres (diameter 80 mm) with tetrahedron‐shaped layout, simulating neighboring fruit in a bulk. Air speed is measured by a calorimetric principle with temperature comparison of heated and unheated diodes, fixed with wires in the space between the spheres. The data recorded by the ASL are temperature‐compensated, but rapid temperature changes may cause measurement errors, since temperature gradients arise in the measuring arrangement due to thermal inertia. The sensitivity of the sensor increases with decreasing speed values (resolution of 2 µm/s near 0 mm/s). The device is a self‐contained 4
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measuring system with rechargeable lithium batteries and an internal data memory with adequate capacity for continuous measurement for up to 28 h (Geyer et al., 2018).
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The airflow measurements in the gaps were performed with newly developed wireless anemometers (WAMs) (Jedermann et al. 2018). Due to difficulties to install wires during transport of bins to the warehouse by forklift, a wireless solution was preferred. The housing form factor had to fit into gaps of 10 cm width. Furthermore, the sensor element had to be mechanically protected by a cover. The WAMs are based on a new sensor chip of size 2 mm × 2 mm for two‐dimensional air velocity measurement. The chip consists of a resistive heater, surrounded by 4 thermopiles (Hartgenbusch et al. 2018). Airflow creates a temperature difference between two diametrical thermopiles according to the calorimetric principle. The chip is glued into a printed circuit board for analogue and digital signal processing by low power electronics (Hartgenbusch et al., 2017). The cylindrical housing of 65 mm diameter and a height between 45 mm and 50 mm also includes a radio board for wireless transmission of the measurements. The airflow is measured inside the slit between main part and cover of the housing (Figure 2).
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The measurement tolerance and temperature dependency of the WAMs was verified by wind tunnel tests at different temperatures. The wind tunnel was calibrated with a Kimo VT200 Anemometer as reference. The calibration of the VT200 was verified with a Laser Doppler Velocity meter (LDV) (flowPoint fp50HeNe, Intelligent Laser Applications GmbH, Jülich, Germany).
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The average error was estimated to ±10% for 1 m/s. For the lowest velocity, the error increased to 19% at 0.1 m/s. Two variants of the housing were used during the tests, showing different errors at higher velocities ≥ 1.5 m/s. For the first variant with mounting posts of 3 mm diameter, the error increased to ±17% at high velocities due to turbulences behind the mounting posts. The mounting posts were later replaced by 0.6 mm needles (Figure 2), thus reducing the error to 8.7%.
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Figure 2: WAM with needles as mounting posts, holding the cover to protect the sensor element (A); scheme of WAM components (B)
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2.2.1 Preliminary test
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For finding the optimal positions of the sensors in the stacks and the number of ASL sensors per bin, a preliminary test was carried out in a refrigerated storage room of 40 t capacity filled with 163 apple bins stacked in 3 rows. The room was fitted with an air cooler with 5 fans (type Helpman, LFX 256‐7 230‐E4, 5 fans, Alfa Laval Corporate AB, Lund, Sweden, air volume rates of 14000 m3/h). Deviations of air speed in the hollow space between the apples of a bin should be determined by measurement at 5 different positions inside a bin at 4 different relative fan power levels (100 %, 75 %, 50 %, 25 %).
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Therefore 5 sensors (Figure 3) were placed in each of two bins about 20 cm below the surface of the apple filling, one in the centre and 4 about 20 cm from the corners. The two bins were placed at different tiers in the middle bin row of the storage room (at the 3rd and 7th tier from the floor).
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Figure 3: Preparation of measurements with 5 ASL-sensors in a preliminary test (A) and positions of the two bins fitted with sensors in the middle row of an apple storage room (B)
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The deviation of the actual from the average air speed values at five positions inside one box was up to 40 %. However, the air speed in the upper bin was on average 2.5 times higher than that at the related positions in the bin below (section 3.1.1). Therefore, the influence of the bin positions was 5
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regarded as more important than the sensor position inside one bin. The ASL sensors were placed in a large variety of bin positions during the subsequent main tests, but with only one sensor per bin.
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2.2.2 Main test
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For preparation of the main test, 24 bins were filled with apples for airflow measurements between the fruit with the ASL. In each bin, one sensor was placed in the center between the fruit about 20 cm below the surface of the apple filling (Figure 4).
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Figure 4: Positioning of the ASL between the apple fruit in the bin
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The scanning rate of the ASL sensors was 1 s. The air speed data were stored internally together with ambient temperature data.
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The preparation of the apple bins with the sensors was done at ambient temperature of about 10°C in March outside the building. Before stowing the bins filled with apples into the room, they were placed in front of the measuring room to adapt them to the temperature inside the warehouse building. The bins with the ASL‐sensors were placed in row 1 and 2 of the stack at the positions shown in Figure 5.
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Figure 5: Positions of ASL-Sensors inside the bins of row 1 and 2 (green bins) and positions of WAMs attached to the bins on both sides of row 1 (U=USB WAMs, R= Radio WAMs)
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A total of 31 WAMs were installed on the sides of the bins of the first row, half of them in the gap towards row 2 and the other half on the opposite side facing the wall (Figure 6, 7). Half of the WAMs per side were equipped with a radio interface (R). The radio WAMs measured the air velocity every 30 s. The average of 6 measurements was transmitted to a gateway every 3 minutes and finally recorded by a laptop. For a more detailed analysis, the remaining 8 WAMs per side were programmed to measure 5 times per second. They were directly connected over a USB interface (U) to transmit the full signal curve to a laptop.
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Figure 6: Attachment of the WAMs to the bin walls in the gap between row 1 and 2 (before stacking of the bins of row 2-4)
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Airflow was measured at 4 fan speeds by adjusting control voltage to 10, 7.5, 5 and 2.5 V. The revolution speed of the 4 fans was measured with a stroboscope. Not all fan speed controls worked properly and only two fans (1 and 3) run with stepwise decreased fan speed while speed of the other fans was reduced to only a lesser extent (Figure 7). Therefore the resulting total air volume rate was not reduced linearly at the four voltage steps with 21772 m3/h (100 %), 19743 m3/h (90 %), 16640 m3/h (76 %), 9584 m3/h (44 %) respectively (Figure 7) corresponding to an air exchange rate between 70/h and 33/h. The air velocity measured with a hand‐held hot wire anemometer (Testo 435‐2, Testo GmbH Austria, Wien, Austria; measuring range 0‐20 m/s), about 1 m in front of the 4 fans at the air outlet was in average about 10.5 m/s, 8 m/s, 5.5 m/s and 2.5 m/s for the 4 steps of voltage control.
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Figure 7: Effect of control voltage on revolution of individual fans and total air volume rate
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The airflow in the gaps and inside the bins was measured over 15 min. The fans were switched off for at least 5 min before each change of fan control voltage. During these periods, the temperature dependent zero offsets were measured and corrected for the USB‐WAMs. Distortion by convective airflow was manually measured to maximum 0.1 m/s when the fans were switched off. The first 6
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generation of Radio‐WAMs did not allow remote correction of zero offsets. Tests with the Radio‐ WAMs at lower fan speed and thus higher sensitivity towards temperature drifts were excluded from the further evaluation.
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For the presentation of the results of airflow measurements with the ASL sensors and the WAMs the average speed values of 15 min period were calculated. For characterization of the uniformity of the flow distribution in the bin rows and in the gaps an uniformity index (Zhang et al. 2017, Guhan et al. 2016) based on deviation from the average velocity was calculated by:
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is a dimensionless index between 0 and 1, expressing a high degree of uniformity when the value is near 1, is the speed at each observation point, is the average speed in the measurement
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section,
is the measuring point number.
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3. Results
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3.1 Air speed between fruit
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3.1.1 Dependency in regard to sensor position inside bin
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The preliminary test (section 2.2.1) in two bins with five sensors per bin showed deviations of air speed measurements of up to 40 % from the average value at different fan speed settings. In the bin in tier 3 the minimum air speed was 0.015 m/s and maximum air speed 0.036 m/s measured by five sensors at 100 % fan revolution (14000 m3/h). Inside the bin in tier 7 the air speed was between 0.06 and 0.13 m/s at 100 % fan revolution (Figure 8). With stepwise reduced fan revolution, the average air speed decreased relatively stronger in the bin at tier 7 than in tier 3.
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Figure 8: Air speed at five positions inside each of two bins at a low and a high bin position in a stack of stored apples (average of five positions with standard deviation (A, C); each measurement position at 100 % fan power (B, D); main airflow direction along the depth (1 m) of the bins)
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3.1. 3.1.2 Temporal air speed course
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Figure 9 shows exemplary single airspeed courses of the main test measured with the ASL inside four bins at different positions, two at stack 5/tier 6 and two at stack 1/tier 1 in row 1 and 2 respectively. Stepwise reduction of the fan revolution immediately changed the air speed between the fruit. The air speed decreased in most of the bins, except in some bins near to the floor, where even air speed slightly increased (Figure 9, position stack 1/ tier 1, row 1). The airflow speed between the apples in stack 5/tier 6 fluctuated with deviation of about 10 % from the average values but was highly constant at a certain fan revolution. The deviation was much higher (about 80 % from the average) at the position in stack 1/tier 1 near the floor. Temperature ranged between 10°C and 13°C with difference of about 1 C° between periods of fan operation and without ventilation. Temperature 7
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fluctuation was low in the bin in row 2 near the floor with very low airflow between fruit compared to the other positions.
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Figure 9: Examples of continuous air speed measurements with the ASL at four bin positions in the stack. Values were recorded for 15 min at each fan power setting and interruption of 5 min
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3.1.3 Summary of timetime-averaged air speed inside bins
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In the bins between apple fruit, the air speed was very low (≤ 0.3 m/s; average of all 24 positions 0.1 m/s) compared to the air speed at the outlet of the fans (ca. 10 m/s) at maximum total air volume rate of 21772 m3/h (Figure 10). At most bin positions of row 2, lower air speed was measured than in row 1 nearby the wall at corresponding positions resulting in average air speed (12 sensors) in row 2 of 0.07 m/s and 0.12 m/s in row 1, respectively. Air speed was highest in the bins of tier 8 and the bins of tier 6 and 4 of stack 5 and 7, situated near the fans.
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At all sensor positions and all fan power settings, airspeed values could always be recorded which were distinguishable from the status without ventilation when the fans were switched off. Air speed inside a bin was lowest (0.0006 m/s) at the position stack3/tier3 in row 2 at the fan power of 44 %. The stepwise reduction of the fan power decreased the air speed stronger between fruit inside bins at higher position in the whole stack than in the low tiers.
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Figure 10: Air speed inside bins at all measuring positions of row 1 and 2 at different fan power settings levels (bars indicate standard deviation of air speed values of each sensor during 15 min measurement period)
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3.2 Magnitude and direction of air flow inside gaps
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At 100 % fan power, air velocity in the gap between row 1 and 2 was much higher (1.15 m/s, average of 16 WAMs) than inside the bins between fruit (Figure 11). The airflow pattern in the gap between row 1 and the wall was very similar with average velocity of 1.17 m/s. At reduced fan power (< 100%), the values of the radio sensors were excluded because the measurement was not reliable. At some measuring positions, flow direction changed with decreased air velocity in both gaps, mainly in the medium and upper tiers of the stack.
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Figure 11: Air velocity and flow direction in the gap between row 1 and 2 at different fan power settings (Radio Sensors only shown for maximum fan power)
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3.3 Comparison of airflow in bins and gaps
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3.3.1 Influence of fan revolution
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Figure 12 (A) shows average air speed measured by the ASL‐sensors inside the bins of both rows and the WAMs in both gaps considering only the 15 USB‐sensors (Figure 5). Air velocity in the gaps was about 10 times higher than air speed in the bins. The reduction of air volume rates resulted in almost linear diminution of air velocity in the gaps and air speed between fruit inside the bins. In the gaps, 8
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air velocity decrease was stronger between row 1 and 2 than at the wall. Air speed inside the bins was higher in row 1 next to the wall than in the bins of row 2.
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The reduction of the maximum air speed in the bins of both rows and in both gaps was greater than that of the minimum air speed values with reduced air volume rate (Figure 12, B) resulting in a small difference between maximum and minimum speed values at low fan power compared to high fan power.
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Figure 12: Relation of air volume rate to average speed (A) and to minimum and maximum speed values inside the bins and in the gaps (B) (Radio WAMs excluded )
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3.3.2 Influence of bin position
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Inside the bins, highest air speed was measured in the upper area of the bin stack at the sensor positions of tier 8. There, air speed was on average 7 times higher than in the lowest tier 1 at 100 % fan power. This relation was smaller with reduced air volume rate to 16640 m3/h (Figure 13, A).
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In contrast to the speed values inside the bins, the average velocity measured in the gaps varied at different heights (tier) between 0.8 and 1.5 m/s at 100% fan power but there was no gradient from the highest to the lowest tier. The average air velocity for lower fan power is not shown in Figure 13 (A) because the values of the radio sensors were excluded (Figure 11).
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Figure 13: Average air speed in bins at different tiers (A) and average air velocity in both gaps at different tiers (B)
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The closer the bin stacks were to the fans, the higher the air speed was in the bins (Figure 14, A). Average air velocity in the gaps of different stacks ranged between 0.8 m/s and 1.3 m/s at 100 % fan power similar to the average values of different tiers. Lowest air velocity was measured at stack 1 and 2 far away from the fans and at stack 7 next to the fans (Figure 14, B).
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Figure 14: Average air speed in bins in different stacks (A) and average air velocity in both gaps at different stacks (B)
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The vertical gradient of air speed within the bins is reflected by less uniform speed distribution compared to the gaps. The uniformity of speed in bins and gaps was similar with usual ventilation (100 %) and reduced fan power settings (table 1).
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Table 1: Uniformity of airflow in bins and gaps Fan power setting
100 %
90 %
76 %
44 %
Uniformity index Bins in row 1
0.64
0.62
0.66
0.58
Bins in row 2
0.55
0.53
0.52
0.44
Gap between wall and row 1
0.87
0.89
0.93
0.93
Gap between row 1 and row 2
0.88
0.91
0.91
0.93 9
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4. Discussion
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Airflow in the gaps and between fruit in plastic storage bins in an apple storage room was measured with specific, newly developed and calibrated flow sensors. The exemplary temporal courses of airflow measurements inside the bins between the apples showed fluctuations in speed values which were highly constant at a certain fan power setting. These speed fluctuations occurred due to flow turbulences between the fruit. It can be excluded that the fluctuations are caused by the noise of the ASL sensors, because the comparison of the air speed values inside the bins in tier 6 and tier 1 (Figure 9) showed higher fluctuations at lower average speed. A test measurement during the development of the ASL device in a closed chamber showed a peak‐to‐peak noise of about 0.5 mm/s (Geyer et al. 2018).
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The average air speed inside the bins between the apple fruits was much lower than in the vertical gaps. For infiltration of airflow in the apple bulk the air must cross the barrier of the bin walls. Standard plastic storage bins cause high air resistance due to a small opening area of about 10 % of the walls and bottom. Thus, wall porosity is considerably lower than porosity of the apple bulk with a hollow space content of 41 % (Scaar et al., 2018). Delele et al. (2009) showed air velocity simulations in the porous region inside small vented boxes with fruit dummies stacked on one single pallet. The velocity values inside the boxes were also very low but in contrast to the present study higher at the bottom with 0.16 m/s than at the top (0.03 m/s). The simulation showed an air roll in front of the stack in the empty space of the store causing higher air velocity in the lower area of the store.
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Ambaw et al. (2017) performed an airflow simulation through a single bin situated on the floor in a ventilated empty storage room apart from this single bin. In the model the bin wall and apple bulk was differentiated and a similar air exchange rate of 80/h was assumed as in this study. The air velocity in the porous region inside the bin was in agreement with the present results below 0.1 m/s, because the circulating air bypassed the bin.
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In the vertical gaps of the bin stack in discharge direction of the fans, the flow direction measured with the WAMs (arrows Figure 10) and the calculation of the uniformity index showed that at 100 % fan power an air roll has formed over the entire stack height with relatively uniform velocity. Duret et al. ( 2014) measured similar air velocities (0.5 to 1 m/s) in gaps between apple bin stacks on pallets of a small apple cold store with 29 m3 volume. At low air velocities, only half of the WAMs were available. Their velocity and direction measurements indicate that the air roll in the gaps did not break down even at 44 % fan revolution.
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In contrast to the relatively uniform flow pattern in the vertical gaps, the bin position had a strong influence on air speed between the apples. Air speeds in the upper bins were about 7‐fold higher compared to the positions at the store ground. The flow direction inside the bins is not determined with the ASL sensors. High air velocity above the bin stack might cause an air sucking effect through the upper bins, which does not affect the bins in the low tiers in the stack. In tier 1, airflow in the gap below the bins is limited by the ground of the floor with small distance between the bottom of the bin and the floor.
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Ambaw et al. (2016) showed an airflow simulation in a similar apple cold store room with wooden bins and similar air exchange rate of 75/h, corresponding to the rate in the present study at 100 %. 10
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The volume averaged superficial air velocity per bin was in the same range as in this study (<0.6 m/s), but the gradient from the bins on the top to the bottom was less pronounced. The reason of lower speed values in this study in the low tiers might be low opening area portion of the plastic bins and an overestimation of speed values by the flow simulation because porosity of fruit bulk and bin wall was not distinguished.
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Air speed in the bins and gaps decreased almost linearly with reduced air volume rate generated by the fans. In the 30 cm wide gap near the wall, the airflow at 100 % fan power was very similar to the flow in the gap between the bin rows 1 and 2. With reduced fan power the air velocity in the 30 cm wide gap next to the bins decreased to a lesser extent than in the small gap of 10 cm width between the bin rows. Probably, higher velocities were measured in the wider gap, because the air is flowing in the direction of lowest resistance. Due to the turbulent flow regime in the gap (Reynolds number > 20.000), it could be assumed that the air velocity in the center of the 30 cm wide gap is in the same range as the measured air velocity with the WAM near the bin wall.
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The highest fan power setting (air volume rate of 21772 m3/h) corresponds to a common air exchange rate (70/h) in practical ventilated storage rooms (Ambaw et al. 2016). The calculation of the uniformity index shows that uniformity in bins and gaps is not affected by the air volume rate. Reduction of fan power up to 44 % still provided airflow in the bins at all measuring positions, but in the bins at the bottom air movement was hardly measurable, i.e. the recorded values of the sensor were only slightly higher than the noise signal. In single bins near the ground air speed even increased with reduced air volume in the store. Reduction in total air volume may cause local changes in airflow direction and thus local increase of air speed. These results do not permit a clear conclusion about a minimum tolerable air volume rate during long time storage without impairment of fruit quality. Airflow at the fruit surface affects heat and mass transfer, which were analyzed for precooling of apples and storage situations with common ventilation (Gaffney et al. 1985, Han et al. 2017, Duret et al. 2014). The impact of fast air speed changes with very low average (<0.1 m/s) on heat and mass transfer at the fruit surface has not yet been investigated.
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5. Conclusions
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A comprehensive study of airflow distribution was performed in a standard industrial apple cold store. Recently developed flow sensors allowed 2‐dimensional air velocity measurements in the vertical gaps between bin stacks and omnidirectional speed determination between the fruit in the bins.
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The accuracy of the WAMs was not fully satisfactory with an average error between 8.7% and 17% of the measured values. Nevertheless, their accuracy was sufficient to evaluate the magnitude and spatial pattern of typical airflow inside the gaps and its dependency on air volume rates. Values of several WAMs were averaged and thus the error reduced. For future tests, a new generation of improved WAMs can be used (Jedermann et al., 2018). Distortions of the airflow inside the WAM housing were reduced by replacing the mounting posts by a high number of evenly distributed fins. The temperature stability of the electronics was also improved.
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The ASL sensors allowed the determination of air speed fluctuations with very low average values (<0.05 m/s) between the fruit within the storage bins. Such measurements could not be determined 11
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before with available flow sensors. The presented results of air speed close to the product enable exact validation of numerical simulations of airflow in the porous region inside the bins in cold stores with complex geometry of bin stacks. The validated simulations can be used for further studies on the effect of modified room layout on airflow distribution.
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The velocity distribution in the vertical gaps was relatively uniform compared to the speed distribution in the bins, which showed a clear vertical gradient over stack height. An option to enhance the uniformity of speed in the bins could be to increase bin wall porosity. The fan power reduction up to 44 % showed that there is significant potential for energy saving with lower revolutions, because low fan power did not affect flow uniformity in bins and gaps and still provides for airflow close to the fruit. In order to find a tolerable limit for flow reduction near the fruit the effects of temperature and humidity have to be included.
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The knowledge gained about the air speed close to the product and its fluctuations in an actual industrial cold store can be used for targeted investigations of the mass and heat transfer at the surface of produces in bulks and resulting quality maintenance.
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Acknowledgements
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The ‘COOL’ project was supported by the Federal Ministry for Economic Affairs and Energy on the basis of a decision by the German Bundestag (grant number VP2050828CL4). The authors thank in particular the company ebm‐papst Mulfingen GmbH & Co. KG, Germany, for providing the fans, Daniel Dadej (KOB), Christian Regen und Stefan Elwert (ATB) for their support during the experiment and sheme preparation for the manuscript.
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15
A
B
A
1
B
A
1
B
1
2
Fan 3
4
Mouvable wall
Tier 8 7 6 5
4 3 2 1
1
2 3 Row
4
1
2
3
4
5 Stack
6
7
A
B
Radio Antenna Mounting Post Analog/Digital Signal Processing Sensor Chip Radio Board 65 mm
Battery
·
Gap
Position ASL Position WAM (R-Radio, U-USB)
Tier 8
R
R
7
U
R
Row 1 2
U
6
U
R
U
4
U
3
U
R R R 1
2
3
4 Stack
U
U
R
2
5
5
6
7
1
1
Bin in tier 7
A
B
C
D
2 3
4
Bin in tier 3
1 2
Position Stack 5/Tier 6 Row 1 (next to the wall)
Row 2 (in the bin stack)
Position Stack 1/Tier 1 Row 1 (next to the wall)
Row 2 (in the bin stack)
3 4 5
6
Highlights • • • • •
Airflow distribution was determined in big bins and in gaps of an apple store New sensors were used for air speed inside bins and air velocity in the gaps The air speed in the bins was 7 times higher on top than on bottom of the bin stack The air velocity in the gaps was quite uniform across the height of the stacks Reduction of fan power to 44 % still provides for airflow in the whole room
Declarations of interest: none