Name: design and optimization strategies of a high-performance vented box
Uploaded: 2023-06-09T14:00:00
Description: Watch this Scientific Journal Video about Design and Optimization Strategies of a High-Performance Vented Box at JoVE.com

This research is supported by Wenzhou Science and Technology Bureau of China (Wenzhou major scientific and technological innovation project under Grant No. ZG2020029). The research is funded by the Wenzhou Association for Science and Technology with Grant No. KJFW09. This research was supported by the Wenzhou Municipal Key Science and Research Program (ZN2022001).

1. Pre-simulation processing
NOTE: Considering the arrays of pipes, the three-dimensional bottom half and the top half of the vented box models are established by using three-dimensional software and saving them as X_T files, the overall dimensions are shown in Figure 1. Configurations are shown in the table of materials.
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	<li>Run the simulation software and drag the Mesh component from the &#34;Component Systems&#34; to th...

<ol>
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Due to its high performance and complex structure, in this study, we built a ventilated box based on modeling software. We analyzed the internal flow by simulation software. Simulation software is known for its advanced physics modeling capabilities, which include turbulence modeling, single- and multiphase flows, combustion, battery modeling, fluid-structure interaction, and much more. The sample selection method used in this paper is the orthogonal experimental design method, which is suitable for mechanical production...

Fresh vegetables and fruits occupy a high proportion of human food consumption, not only because they have good taste and an attractive form, but also because they are of great benefit for people to obtain nutrition and maintain health1. Many studies have shown that fresh fruits and vegetables play a unique role in preventing many diseases2,3. In the storage process of fresh fruits and vegetables, fungi, light, temperature, and relative humidity are the important reasons for their deterioration4,5,6,7,8. These external conditions affect the quality of stored fresh fruits and vegetables by affecting the internal metabolism or chemical reactions9.
Common treatment technologies for fruits and vegetables include nonthermal and thermal preservation. Among them, thermal pretreatment has a positive effect on the drying process, but it can also have adverse effects on product quality, such as loss of nutrients, change of flavor and odor, and change of color10,11. Therefore, in recent years, the nonthermal preservation of products has received attention from the research perspective to meet the demand of consumers for fresh products. At present, there are mainly radiation processing, pulsed electric field, ozone processing, edible coatings, dense phase carbon dioxide, and other nonthermal preservation technologies to store fruits and vegetables, but these technologies often have shortcomings, such as the requirement of large equipment, high price, and the cost of use12. Therefore, the design of a simple structure, low cost, and convenient control of the preservation equipment is very meaningful to the food industry.
In the storage environment for fruits and vegetables, a proper air circulation system helps to eliminate the heat generated by the product itself, reduce the temperature gradient, and maintain the temperature and humidity in the space where it is located. Proper air circulation also prevents weight loss due to respiration and fungal infections13,14,15. Numerous studies have been conducted on airflow within different structures. Praeger et al.16,17 measured the wind speed at different positions under different fan operating powers in a warehouse through sensors and found that there could be as big as a sevenfold difference in air velocity due to different vertical heights, and the air velocity at each position was positively correlated with the fan operating power. Moreover, a study examined the effect of cargo arrangement and the number of fans on airflow, and it was concluded that increasing the distance of some fan positions and rationally choosing the number of fans was helpful in improving the effect. Berry et al.18 studied the effect of airflow in different fruit storage environments on stomata distribution in packing boxes. Using simulation software, Dehghannya et al.19,20 studied the air flow state of forced pre-cold air in the package with different vent areas, quantities, and distribution positions on the packaging wall, and obtained the nonlinear influence of each parameter on the air flow state. Delele et al.21 applied a computational fluid dynamics model to study the influence of products randomly distributed in different forms of ventilation boxes on airflow. They found that the product size, porosity, and box hole ratio had a greater impact on airflow, whereas random filling had a smaller impact. Ilangovan et al.22 studied airflow patterns and thermal behavior between the three packaging structures and compared the results with reference structural models. The results showed that the heat distribution in the box was not uniform because of the different locations and designs of the vent. Gong et al.23 optimized the width of the gap between the edge of the tray and the wall of the container.
The techniques used in this paper include simulation and optimization methods. The principle of the former is that the governing equations were discretized and numerically solved using the finite volume method21. The optimization method used in this paper is referred to as orthogonal optimization24. The orthogonal test is a typical multifactor and multilevel analysis method. The orthogonal table built using this method contains representative points uniformly distributed in the design space, which can visually describe the entire design space and be examined. That is, fewer points represent the full factor test, greatly saving time, manpower, material, and financial resources. The orthogonal test has been widely used in the design of experiments in the fields of power systems, chemistry, civil engineering, etc25.
The objective of this study is to design and optimize a high-performance vented box. A vented box can be defined as an original box including a gas control device that disperses the gas uniformly in the box. Velocity uniformity refers to how evenly air flows through the vented box. Yun-De et al.26 have previously shown that the property of multiporous material has an important effect on the velocity uniformity of a fresh vegetable box. In some experiments, a plenum or modulated chamber was left at both the top and the bottom of the test chamber to guarantee a homogenous distribution of either forced or induced air27. The vented box designed in this paper contains arrays of pipes with zigzag holes. Controlling the airflow distribution in the vented box is the main preservation strategy. There are two air inlets of equal size set parallelly at the left and right sides of the vented box, and an outlet is set at the upper side of the box. Designing the internal structure of a vented box is the key to this study. In other words, the number of pipes and holes is an important parameter for changing the internal structure of the vented box. The reference model has 10 pipes. The two middle pipes have 10 holes each, which are staggered across the pipes. The number of holes from the middle to the outer pipe increase by two at a time.
In other words, when we keep fresh vegetables, fruits, and other products, continuous and stable airflow can reduce the respiration of products, reduce ethylene and other harmful substances for product preservation, and reduce the temperature produced by the products themselves. Due to the different parameters of the vented box, it is not easy to obtain the required airflow state, which will affect the preservation property of the vented box. Therefore, the project takes the internal airflow velocity uniformity of the vented box as the control objective. A sensitivity analysis was conducted for the structural parameters of the vented box. The samples were selected by orthogonal experimental design. We used range analysis to optimize the combination of the three structural parameters. Meanwhile, we verify the desirability of the optimization results.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Hardware</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>NVIDIA GPU</td>
			<td>NVIDIA</td>
			<td>N/A</td>
			<td>An NVIDIA GPU is needed as some of the software frameworks below will not work otherwise. https://www.nvidia.com</td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ansys-Workbench</td>
			<td>ANSYS</td>
			<td>N/A</td>
			<td>Multi-purpose finite element method computer design program software.https://www.ansys.com</td>
		</tr>
		<tr>
			<td>SOLIDWORKS</td>
			<td>Dassault Systemes</td>
			<td>N/A</td>
			<td>SolidWorks provides different design solutions, reduces errors in the design process, and improves product quality 
			www.solidworks.com</td>
		</tr>
		<tr>
			<td>SPSS</td>
			<td>IBM</td>
			<td>N/A</td>
			<td>Software products for statistical analytical operations, data mining, predictive analysis, and decision support tasks software.https://www.ibm.com</td>
		</tr>
	</tbody>
</table>

design and optimization strategies of a high-performance vented box

This study aims to solve the problems of air flow chaos and poor performance in a vented box caused by the heterogeneous distribution of airflow through the design of the internal structure of the vented box with constant energy consumption. The final goal is to evenly distribute the airflow inside the vented box. Sensitivity analysis was performed for three structural parameters: the number of pipes, the number of holes in the middle pipe, and the number of each increment from the inside to the outside pipe. A total of 16 random array sets of three structural parameters with four levels were determined using the orthogonal experimental design. Commercial software was used for the construction of a 3D model for the selected experimental points, and this data was used to obtain the airflow velocities, which were then used to obtain the standard deviation of each experimental point. According to the range analysis, the combination of the three structural parameters was optimized. In other words, an efficient and economical optimization method considering the performance of the vented box was established, and it could be widely used to extend the storage time of fresh food.

Following the protocol, the first three parts were the most important, which include modeling, meshing, and simulation, all in order to obtain the standard deviation of the flow rate. Then, we completed the structure optimization of the vented box through orthogonal experiments and range analysis. The model used in the protocol is the reference-vented box model, which is the initial model obtained from the reference. Figure 4 shows the result of the streamlined flow of the reference vented b...

Watch this Scientific Journal Video about Design and Optimization Strategies of a High-Performance Vented Box at JoVE.com

Design and Optimization Strategies of a High-Performance Vented Box

Here, we present the range analysis method to optimize the sample points generated by an orthogonal experimental design to ensure that fresh food can be stored in a vented box for a long time by regulating the airflow pattern.

This study aims to solve the problems of air flow chaos and poor performance in a vented box caused by the heterogeneous distribution of airflow through ...

This study aim to solve the problems of air flow chaos and the poor performance in the vented box caused by the unreasonable distribution of air flow through the design of the internal structure of the vented box on the premise of constant energy consumption. An efficient and economical optimization method considering the performance of the vented box was established and it can be readily used to extend the storage time of fresh food. The object of this study is to design and optimize a high performance vented box containing arrays of pipes with zigzag holes.There are two air inlets of equal size set parallelly at the left and the right sides of the vented box, and an outlet was set at the upper side of the vented box. The reference model has 10 pipes. The two middle pipes have 10 holes respectively, which are staggered across the pipes.The number of holes from the middle to the outer pipe is increased by two at a time. Considering the arrays of pipes, the three dimensional bottom half and the top half of the vented box models are established by using three dimensional software and saving them as XT files. Run the simulation software and drag the mesh component from component systems to the project schematic window.Name it as bottom. Right click geometry and click browse to import the bottom XT file. Right click geometry and click new design modeler geometry to enter into the mesh design modeler window.Click generate to display the bottom model. Right click the upper surface and click the named selection to rename it as Vented Box Upper. Select the selection filter bodies.Right click the bottom model to select the named selection and rename it has bottom. Select the selection filter faces and switch the select mode to the box select. Select all inner surfaces and the right click to select the named selection and rename it as inner surfaces external, defined as mesh interfaces later.Return to the initial window. Double click the bottom's mesh. Enter into the meshing window.Change the physical preference from mechanical to CFD. Click the update to generate the mesh model. Return to the initial window.Drag the mesh component from component systems to the project schematic window. Name it as top. Right click geometry and click browse to import the top XT file.Right click geometry and click new design modeler geometry to enter into the mesh design modeler window. Click generate to display the top model. Right click the lower surface and click the named selection to rename it as vented box lower.Select the selection filter bodies. Right click the top model to select named selection and rename it as top. Select the selection filter faces.Right click the upper surface and click the named selection to rename it as outlet. Return to the initial window. Double click top's mesh.Enter into the meshing window. Change the physical preference from mechanical to CFD. Right click the mesh to select the sizing in the insert.Select the selection filter bodies. Select the top model and the top 18 in element size. Click update.Return to the initial window. Drag the mesh component from component systems to the project schematic window. Name it as pipe.Import the pipe XT file by clicking geometry. Enter into the mesh design modeler window. The pipe model displays again by clicking generate.Select the two end faces of the pipe and label them as inlet one and inlet two. The pipe by body selecting is labeled as pipe. All inner surfaces by box selecting are labeled as inner surfaces internal, defined as mesh interfaces later.Return to the initial window. Double click pipe's mesh. Enter into the meshing window.Change the physical preference from mechanical to CFD. The mesh model can be generated by clicking update. Return to the initial window.Drag the simulation component to the project schematic window. Link three mesh components to simulation component and update to enter. Verify the quality of the mesh model.Check whether the mesh has a negative volume. Select steady, relaxation factor, residual, and timescale factor. Select default values.Enter into the setting interface of viscous model to select the K-epsilon model. Set the air material. Change the type of cell zone to fluid.Convert the type of vented box upper, vented box lower, inner surfaces external, and inner surfaces internal from default wall to interface. Open the mesh interfaces and enter into the create/edit mesh interfaces window. Match inner surfaces external to inner surfaces internal.Match vented box upper to vented box lower. Finally, the two mesh interfaces are created among the vented box and named interface one and interface two, respectively. Set the airflow velocities of all inlets as 8.9525 meters per second in the velocity inlet window.Set the gauge pressure of outlet as zero in the pressure outlet window. Set the style of the solution initialization as standard initialization before initializing. Set number of iterations as 2000.Click calculate to start the simulation and return to the initial window until the simulation end. Click the results. Enter into the CFD post window.Click the icon of streamline in the toolbox. Select outlet in start from and backward in direction. Click apply to generate the internal flow diagram of the vented box.Click the plane in location. Select ZX plane in method, and input value 0.6. Click apply to generate the plane 0.6 meters from the bottom surface.Click the icon of contour in the toolbox. Select plane one in locations. Select velocity in variable.Select local in range. Click apply to generate the velocity contour. Export the flow rate data for the plane generated above.Acquire the standard deviation of the flow rate in Excel. Run the statistical analysis software. Click data and click generate in orthogonal design.Enter pipe number into factor name and A in factor label. Click add and define values to set four levels for the number of pipes. Click continue and back to the generate orthogonal design window.Enter hole number into factor name and B in factor label. Click add and define values to set four levels for the number of holes. Click continue and back to the generate orthogonal design window.Enter cumulative number into factor name and C in factor label. Click add and define values to set four levels for the number of increments. Click continue and create new data file to generate 16 array samples.Click variable view to select nominal in measure and input in role. Rename it as standard deviation times 100, 000. Repeat steps 1.1 to 2.5 with sample points above.The resulting 16 standard deviations multiplied by 100, 000 are filled into the sample list for later optimization. Click analyze and click univariate in general linear model. Fill standard deviation times 100, 000 into dependent variable and fill pipe number, hole number, cumulative number, into fixed factors.Click model and build terms. Change interaction to main effects. Fill A, B, C into model.Click continue and back to the univariate window. Click EM means and fill A, B, C into display means for. Click continue and back to the univariate window.Click okay and get the optimization result. The minimum value of the mean column in the table corresponds to the optimal variable. Double click on the table.Enter into the pivot table window. Click edit and click bar in create graph to generate the histogram. As shown in figure four and figure five, the streamline of the later vented box is even messier than that of the former, due to the inner structure of the vented box.As shown in figure six and figure seven, the flow rate inside the vented box, which is one of the models used for sensitivity analysis, is more uneven. In order to understand the streamline distribution inside the vented box more intuitively, the standard deviation is calculated by this formula. Table one shows the standard deviation of flow rates for the 10 groups of the vented box used for sensitivity analysis.A large standard deviation represents a large difference between most flow rates and their mean flow rate. Thus, it can be seen that changing the internal structure of the vented box can change its internal flow and makes the streamline more reasonable. When designing the orthogonal experiment, there are three design variables in this article.Each of these three variables has four levels. As shown in the table, 16 groups of experimental design points were obtained by orthogonal experimental design. The standard deviations are calculated.In the end, the range analysis method is used as the optimization method for finding out optimal structure parameter combination. Figure eight shows the optimization result for the structural parameter about the number of pipes. From this, we can see that the minimum value is obtained when the number of pipes is 14.Figure nine shows the optimization result for the structure parameter about the number of holes in the middle pipes. From this, we can see that the minimum value is obtained when the number of holes in the middle pipes is 14. Figure 10 shows the optimization result for the structural parameter about the number of each increment from the inside to the outside pipe.From this, we can see that the minimum value is obtained when the number of each increment from the inside to the outside pipe is four. The above analysis shows that the optimal combination is pipe number 14, hole number 14, cumulative number four. For confirming the accuracy, the optimal case was analyzed.Figures four and 11 show the streamline of the reference model versus the optimized model. Figures six and 12 show the flow velocity distribution inside the reference model versus the optimized model. Table three shows the comparison between the optimization model and the reference model.It can be seen that the standard deviation calculated by the optimized model is lower compared to the standard deviation of the reference model. Table four shows the increase in the number of holes from four to six, with little change in standard deviation. In this paper, the internal environment of the vented box is improved by optimizing its structure, and the quality of its internal environment is measured by standard deviation.The smaller the standard deviation, the more reasonable the airflow inside of the vented box, which indicates that the optimization method adopted in this work is effective and feasible.

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