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.
<ol>
	<li>Run the simulation software and drag the Mesh component from the &#34;Component Systems&#34; to the &#34;Project Schematic&#34; window. Name it &#34;the bottom&#34;. Right-click Geometry and click Browse to import the bottom X_T file.</li>
	<li>Right-click Geometry, click New DesignModeler Geometry to enter into the &#34;Mesh-Designmodeler&#34; window, and click Generate to display the bottom model.</li>
	<li>Right-click the upper surface and click Named Selection to rename it &#34;vented box_upper&#34;. Select Selection Filter: Bodies. Right-click the bottom model to select the Named Selection and rename it as &#34;the bottom&#34;.</li>
	<li>Select Selection Filter: Faces and switch the &#34;Select Mode&#34; to Box Select. Select all the inner surfaces, right-click to select the Named Selection, and rename it as &#34;inner surfaces_external&#34;, defined as mech interfaces later. Return to the initial window.</li>
	<li>Double-click the bottom Mesh. Enter the &#34;Meshing&#34; window. Change the &#34;Physical Preferences&#34; from Mechanical to CFD. Click Update to generate the mesh model. Return to the initial window.</li>
	<li>Drag the Meshcomponent from the &#34;Component Systems&#34; to the &#34;Project Schematic&#34; window. Name it &#34;top&#34;. Right-click Geometry and click Browse to import the top X_T file.</li>
	<li>Right-click Geometry and click New DesignModeler Geometry to enter into the &#34;Mesh-Designmodeler&#34; window. Click Generate to display the top model.</li>
	<li>Right-click the lower surface and click Named Selection to rename it as &#34;vented box_lower&#34;. Select Selection Filter: Bodies. Right-click the top model to select the Named Selection and rename it as &#34;top&#34;.</li>
	<li>Select Selection Filter: Faces. Right-click the upper surface and click Named Selection to rename it as the outlet. Return to the initial window.</li>
	<li>Double-click the top&#39;s Mesh. Enter the &#34;Meshing&#34; window. Change the &#34;Physical Preferences&#34; from Mechanical to CFD. Right-click Mesh to select the Sizing in the &#34;Insert&#34;. Select Selection Filter: Bodies. Select the top model and type 18 in &#34;Element Size&#34;. Click Update. Return to the initial window.</li>
	<li>Drag the Mesh component from the &#34;Component Systems&#34; to the &#34;Project Schematic&#34; window. Name it as the pipe. Import the pipe X_T file by clicking Geometry.</li>
	<li>Enter the &#34;Mesh-Designmodeler&#34; window. Click Generate to display the pipe model displays again.</li>
	<li>Select the two end faces of the pipe and label them as &#34;inlet1&#34; and &#34;inlet2&#34;, and the pipe by body selecting and labeling as a pipe.</li>
	<li>All inner surfaces by box selecting are labeled as &#34;inner surfaces_internal&#34;, defined as mesh interfaces later. Return to the initial window.</li>
	<li>DoubleClick the pipe&#39;s Mesh. Enter the &#34;Meshing&#34; window. Change the &#34;Physical Preferences&#34; from Mechanical to CFD. The mesh model can be generated by clicking &#34;Update&#34;. Return to the initial window. 
	NOTE: Figure 2A shows the grid of the bottom half of the vented box, Figure 2B shows the grid of the top half of the vented box, and Figure 2C shows the grid of the pipe. As shown in Figure 3, with the number of grids increasing from 4,137,724 to 5,490,081, the standard deviation changes are less than 0.0008. Considering the computation ability and accuracy, the following analysis is based on a grid model with 4,448,536 grids.</li>
</ol>
2. Simulation analysis
NOTE: The following operations are described based on the general sequence of simulation analysis from setup to solution to result.
<ol>
	<li>Drag the Simulation component to the &#34;Project Schematic&#34; window. Link three Mesh components to the simulation component and update to enter.</li>
	<li>Setup 
	NOTE: The &#34;Setup&#34; consists of five steps: General, Models, Materials, Cell Zone Conditions, and Boundary Conditions.
	<ol>
		<li>General: Verify the validity of the mesh model. Check whether the mesh has negative volume. Select Steady. For the relaxation, residual, and time scale factors, select the default values. If there is any problem with the divided grid or model settings, an error message will pop up.</li>
		<li>Models: Enter the setting interface of &#34;Viscous Model&#34; to select the K-epsilon Model.</li>
		<li>Materials: Set the &#34;air&#34; material.</li>
		<li>Cell Zone Conditions: Change the type of cell zone to Fluid.</li>
	</ol>
	</li>
	<li>Boundary Conditions
	<ol>
		<li>Convert the type of vented box_upper, vented box_lower, inner surfaces_external, and inner surfaces_internal from the default &#34;Wall&#34; to &#34;Interface&#34;. 
		NOTE: Simulation software immediately generates the &#34;Mesh Interfaces&#34; after ending the above step.</li>
		<li>Open Mesh Interfaces and enter the &#34;Create/Edit Mesh Interfaces&#34; window. Match inner surfaces_external to inner surfaces_internal. Match vented box_upper to vented box_lower. Finally, the two mesh interfaces are created in the vented box and named interface1 and interface2, respectively.</li>
		<li>Set the airflow velocities of all inlets as 8.9525 m/s in the &#34;Velocity Inlet&#34; window and the gauge pressure of the outlet as zero in the &#34;Pressure Outlet&#34; window.</li>
	</ol>
	</li>
	<li>Solution
	<ol>
		<li>Set the style of solution initialization as Standard Initialization before initializing.</li>
		<li>Set the Number of Iterations as 2,000.</li>
		<li>Click Calculate to start the simulation and return to the initial window until the simulation ends.</li>
	</ol>
	</li>
	<li>Results
	<ol>
		<li>Click Results. Enter the &#34;CFD Post&#34; window and click the streamline icon of in the toolbox.</li>
		<li>Select outlet in &#34;Start From&#34; and Backward in &#34;Direction&#34;. Click Apply to generate the internal flow diagram of the vented box.</li>
		<li>Click Plane in &#34;Location&#34;, select ZX Plane in &#34;Method&#34;, and select the input value as 0.6. Click Apply to generate the plane 0.6 m from the bottom surface.</li>
		<li>Click the Contour icon in the toolbox, select Plane 1 in &#34;Locations&#34;, select Velocity in &#34;Variable&#34;, and select Local in &#34;Range&#34;. Click Apply to generate the velocity contour.</li>
		<li>Export the flow rate data for the plane generated above. Acquire the standard deviation of the flow rate in spreadsheet software (e.g., Excel). 
		&#8203;NOTE: Sensitivity analysis of three structural variables of the vented box was carried out. The number of pipes has four levels: eight, 10, 12, and 14. The number of holes in the middle pipes has four levels: eight, 10, 12, and 14. The number of each increment from the inside to the outside pipe has four levels: zero, two, four, and six. Modify the base model according to changes in these structural parameters. Repeat steps 1.1 through 2.5 10 times to obtain the data in Table 1. It can be seen from the table that the three structural parameters have certain effects on the standard deviation of the flow rate.</li>
	</ol>
	</li>
</ol>
3. Orthogonal experiment design and range analysis
<ol>
	<li>Run the statistical analysis software. Click Data and Generate in &#34;Orthogonal Design&#34;.</li>
	<li>Enter pipe_number into &#34;Factor Name&#34; and A in &#34;Factor Label&#34;. Click Add and Define Values to set four levels for the number of pipes. Click Continue and return to the &#34;Generate Orthogonal Design&#34; window.</li>
	<li>Enter whole_number into &#34;Factor Name&#34; and B in &#34;Factor Label&#34;. Click Add and Define Values to set four levels for the number of holes. Click Continue and return to the &#34;Generate Orthogonal Design&#34; window.</li>
	<li>Enter cumulative_number into &#34;Factor Name&#34; and C in &#34;Factor Label&#34;. Click Add and Define Values to set four levels for the number of increments. Click Continue and return to the &#34;Generate Orthogonal Design&#34; window.</li>
	<li>Click Create new data file to generate 16 array samples. Click Variable View to select Nominal in &#34;Measure&#34; and Input in &#34;Role&#34;. Rename it as &#34;standard_deviation&#215;100000&#34;.</li>
	<li>Repeat steps 1.1 to 2.5 with the sample points above; the resulting 16 standard deviations multiplied by 100,000 are filled into the sample list for later optimization.</li>
	<li>Click Analyze and Univariate in &#34;General Linear Model&#34;. Fill standard_deviation&#215;100000 into &#34;Dependent Variable&#34; and pipe_number, hole_number, cumulative_number into &#34;Fixed Factor(s)&#34;. Click Model and Build terms. Change Interaction to Main effects. Fill A, B, C into &#34;Model&#34;. Click Continue and return to the &#34;Univariate&#34; window.</li>
	<li>Click EM Means and fill A, B, C into &#34;Display Means For&#34;. Click Continue and go back to the &#34;Univariate&#34; window.</li>
	<li>Click OK and get the optimization result; the minimum value of the &#34;mean&#34; column in the table corresponds to the optimal variable. Double-click on the table, enter into the &#34;Pivot Table&#34; window, click Edit, and click Bar in &#34;Create graph&#34; to generate the histogram.</li>
</ol>

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The authors have nothing to disclose.

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><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&lt;br/&gt; 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...

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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 ...

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1.0K Views.  Wenzhou University. 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.

Video: Design and Optimization Strategies of a High-Performance Vented Box

Research and Development of High-performance Explosives

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance tests to verify theoretical calculations. For newly developed formulations, the process begins with small-scale mixes, thermal testing, and impact and friction sensitivity. Only then do subsequent larger scale formulations proceed to detonation testing, which will be covered in this paper. Recent advances in characterization techniques have led to unparalleled precision in the characterization of early-time evolution of detonations. The new technique of Photonic Doppler Velocimetry (PDV) for the measurement of detonation pressure will be shared and compared with traditional fiber-optic detonation velocity and plate-dent calculation of detonation pressure. In particular, the role of aluminum in explosive formulations will be discussed. Recent developments led to the development of explosive formulations that result in reaction of aluminum very early in the detonation product expansion. This enhanced reaction leads to changes in the detonation velocity and pressure due to reaction of the aluminum with oxygen in the expanding gas products.

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance tests to verify theoretical calculations. This paper will share typical development tests associated with the measurement of detonation velocity and detonation pressure.

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance ...

Assessment of Methane and Nitrous Oxide Fluxes from Paddy Field by Means of Static Closed Chambers Maintaining Plants Within Headspace

This protocol describes the measurement of greenhouse gas (GHG) emissions from paddy soils using the static closed chamber technique. This method is based on the diffusion theory. A known volume of air overlaying a defined soil area is enclosed within a parallelepiped cover (named &#34;chamber&#34;), for a defined period of time. During this enclosure period, gases (methane (CH4) and nitrous oxide (N2O)) move from soil pore air near their microbial source (i.e., methanogens, nitrifiers, denitrifiers) to the chamber headspace, following a natural concentration gradient. Fluxes are then estimated from chamber headspace concentration variations sampled at regular intervals throughout the enclosure and then analyzed with gas chromatography. Among the techniques available for GHG measurement, the static closed chamber method is suitable for plot experiments, as it does not require large homogenously treated soil areas. Furthermore, it is manageable with limited resources and can identify relationships among ecosystem properties, processes, and fluxes, especially when combined with GHG driving force measurements. Nevertheless, with respect to the micrometeorological method, it causes a minimal but still unavoidable soil disturbance, and allows a minor temporal resolution. Several phases are key to the method implementation: i) chamber design and deployment, ii) sample handling and analyses, and iii) flux estimation. Technique implementation success in paddy fields demands adjustments for field flooding during much of the cropping cycle, and for rice plant maintenance within the chamber headspace during measurements. Therefore, the additional elements to be considered with respect to the usual application of non-flooded agricultural soils consist of devices for: i) avoiding any unintended water disturbance that could overestimate fluxes, and ii) including rice plants within the chamber headspace to fully consider gases emitted through aerenchyma transportation.

The overall goal of this protocol is to measure greenhouse gas emissions from paddy fields using the static closed chamber technique. The measurement system needs specific adjustments due to the presence of both a permanent water layer in the field and of the plants within the chamber headspace.

This protocol describes the measurement of greenhouse gas (GHG) emissions from paddy soils using the static closed chamber technique. This method is based ...

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Probing C84-embedded Si Substrate Using Scanning Probe Microscopy and Molecular Dynamics

This paper reports an array-designed C84-embedded Si substrate fabricated using a controlled self-assembly method in an ultra-high vacuum chamber. The characteristics of the C84-embedded Si surface, such as atomic resolution topography, local electronic density of states, band gap energy, field emission properties, nanomechanical stiffness, and surface magnetism, were examined using a variety of surface analysis techniques under ultra, high vacuum (UHV) conditions as well as in an atmospheric system. Experimental results demonstrate the high uniformity of the C84-embedded Si surface fabricated using a controlled self-assembly nanotechnology mechanism, represents an important development in the application of field emission display (FED), optoelectronic device fabrication, MEMS cutting tools, and in efforts to find a suitable replacement for carbide semiconductors. Molecular dynamics (MD) method with semi-empirical potential can be used to study the nanoindentation of C84-embedded Si substrate. A detailed description for performing MD simulation is presented here. Details for a comprehensive study on mechanical analysis of MD simulation such as indentation force, Young&#39;s modulus, surface stiffness, atomic stress, and atomic strain are included. The atomic stress and von-Mises strain distributions of the indentation model can be calculated to monitor deformation mechanism with time evaluation in atomistic level.

Probing C84-embedded Si Substrate Using Scanning Probe Microscopy and Molecular Dynamics

This paper reports the nanomaterial fabrication of a fullerene Si substrate inspected and verified by nanomeasurements and molecular dynamic simulation.

This paper reports an array-designed C84-embedded Si substrate fabricated using a controlled self-assembly method in an ultra-high vacuum chamber. The ...

A High Performance Impedance-based Platform for Evaporation Rate Detection

This paper describes the method of a novel impedance-based platform for the detection of the evaporation rate. The model compound hyaluronic acid was employed here for demonstration purposes. Multiple evaporation tests on the model compound as a humectant with various concentrations in solutions were conducted for comparison purposes. A conventional weight loss approach is known as the most straightforward, but time-consuming, measurement technique for evaporation rate detection. Yet, a clear disadvantage is that a large volume of sample is required and multiple sample tests cannot be conducted at the same time. For the first time in literature, an electrical impedance sensing chip is successfully applied to a real-time evaporation investigation in a time sharing, continuous and automatic manner. Moreover, as little as 0.5 ml of test samples is required in this impedance-based apparatus, and a large impedance variation is demonstrated among various dilute solutions. The proposed high-sensitivity and fast-response impedance sensing system is found to outperform a conventional weight loss approach in terms of evaporation rate detection.

This paper presents an impedance-based apparatus for evaporation rate detection of solutions. It offers clear advantages over a conventional weight loss approach: a fast response, high-sensitivity detection, a small sample requirement, multiple sample measurements, and easy disassembly for cleaning and reuse purposes.

This paper describes the method of a novel impedance-based platform for the detection of the evaporation rate. The model compound hyaluronic acid was ...

Scalable Solution-processed Fabrication Strategy for High-performance, Flexible, Transparent Electrodes with Embedded Metal Mesh

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a polymer film. This paper also presents a low-cost, vacuum-free fabrication method for this novel TE; the approach combines lithography, electroplating, and imprint transfer (LEIT) processing. The embedded nature of the EMTEs offers many advantages, such as high surface smoothness, which is essential for organic electronic device production; superior mechanical stability during bending; favorable resistance to chemicals and moisture; and strong adhesion with plastic film. LEIT fabrication features an electroplating process for vacuum-free metal deposition and is favorable for industrial mass production. Furthermore, LEIT allows for the fabrication of metal mesh with a high aspect ratio (i.e., thickness to linewidth), significantly enhancing its electrical conductance without adversely losing optical transmittance. We demonstrate several prototypes of flexible EMTEs, with sheet resistances lower than 1 &#937;/sq and transmittances greater than 90%, resulting in very high figures of merit (FoM) &#8211; up to 1.5 x 104 &#8211; which are amongst the best values in the published literature.

This protocol describes a solution-based fabrication strategy for high-performance, flexible, transparent electrodes with fully-embedded, thick metal mesh. Flexible transparent electrodes fabricated by this process demonstrate among the highest reported performances, including ultra-low sheet resistance, high optical transmittance, mechanical stability under bending, strong substrate adhesion, surface smoothness, and environmental stability.

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a ...

A Rapid Method for Modeling a Variable Cycle Engine

The variable cycle engines (VCE) that combine the advantages of turbofan and turbojet engines, are widely considered to be the next generation aircraft engines. However, developing VCE requires high costs. Thus, it is essential to build a mathematical model when developing an aircraft engine, which may avoid a large number of real tests and reduce the cost dramatically. Modeling is also crucial in control law development. In this article, based on a graphical simulation environment, a rapid method for modeling a double bypass variable cycle engine using object-oriented modeling technology and modular hierarchical architecture is described. Firstly, the mathematical model of each component is built based on the thermodynamic calculation. Then, a hierarchical engine model is built via the combination of each component mathematical model and the N-R solver module. Finally, the static and dynamic simulations are carried out in the model and the simulation results prove the effectiveness of the modeling method. The VCE model built through this method has the advantages of clear structure and real-time observation.

Here, we present a protocol to build a component-level mathematical model for a variable cycle engine.

The variable cycle engines (VCE) that combine the advantages of turbofan and turbojet engines, are widely considered to be the next generation aircraft ...

Fabrication and Design of Wood-Based High-Performance Composites

Delignified densified wood is a new promising and sustainable material that possesses the potential to replace synthetic materials, such as glass fiber reinforced composites, due to its excellent mechanical properties. Delignified wood, however, is rather fragile in a wet state, which makes handling and shaping challenging. Here we present two fabrication processes, closed-mold densification and vacuum densification, to produce high-performance cellulose composites based on delignified wood, including an assessment of their advantages and limitations. Further, we suggest strategies for how the composites can be re-used or decomposed at the end-of-life cycle. Closed-mold densification has the advantage that no elaborate lab equipment is needed. Simple screw clamps or a press can be used for densification. We recommend this method for small parts with simple geometries and large radii of curvature. Vacuum densification in an open-mold process is suitable for larger objects and complex geometries, including small radii of curvature. Compared to the closed-mold process, the open-mold vacuum approach only needs the manufacture of a single mold cavity.

Delignified densified wood represents a new promising lightweight, high-performance and bio-based material with great potential to partially substitute natural fiber reinforced- or glass fiber reinforced composites in the future. We here present two versatile fabrication routes and demonstrate the possibility to create complex composite parts.

Delignified densified wood is a new promising and sustainable material that possesses the potential to replace synthetic materials, such as glass fiber ...

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Electro-hydrostatic actuators (EHAs) have been considerably researched in academia, and their applications in various industrial fields are expanding. The variable-speed EHA has now taken priority over the variable-displacement EHA, but its driving motor and associated electronics encounter issues when applied in high-power applications: low-dynamics, high thermal dissipation, high price, etc. Therefore, a variable-displacement EHA equipped with an electro-variable displacement pump (EVDP) has been considered. The EVDP itself is a mechatronic system that integrates a piston pump, a ball screw, a gearbox, and a permanent magnet synchronous motor (PMSM). Consequently, the EVDP needs to be investigated to ensure its system-level performance when applied in an EHA. In addition to the previous research on the technical parameters of the EVDP, a dedicated design method is necessary for further reducing the cost of using the EVDP and exploring its performance potential. Here, a simulation based EVDP preliminary design method is selected for designing a 37 kW EVDP. Firstly, a previously proposed multidisciplinary model of the EVDP is extended by improving the parameter generation, including the EVDP life, reliability, control models, etc. Secondly, the proposed model is partially verified using a downsized prototype. Thirdly, the EVDP is simulated at a system level, supported by the proposed model. The EVDP performance is evaluated according to the specified design requirements. The temperature, bandwidth and accuracy, reliability and lifetime, etc., are all predicted for the EVDP. The simulation results demonstrate the EVDP's applicability in variable-displacement EHA. The proposed modeling and simulation method can be used to evaluate diverse EVDP performance and respond to general design requirements. The method can also support the resolution of the preliminary design challenges in terms of limited information and robustness. Therefore, the proposed method is appropriate for the realization of the simulation-based EVDP preliminary design method.

A simulation model specifically supporting the preliminary design of an electro-variable displacement pump (EVDP) is developed and partially verified by experiments. The control performance, life, reliability, etc., can all be evaluated using the proposed model, which covers the main performance requirements under the EVDP preliminary design task.

Electro-hydrostatic actuators (EHAs) have been considerably researched in academia, and their applications in various industrial fields are expanding. The ...

Optimizing Battery Heat Management in Dusty Environments

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

This study aims to solve the problem of the cell temperature rise and performance decline caused by dusty particulate matter covering the surface of the cell through the allocation of airflow velocities at the inlets of the battery cooling box under the goal of low energy consumption. We take the maximum temperature of the battery pack at a specified airflow velocity and dust-free environment as the expected temperature in a dusty environment. The maximum temperature of the battery pack in a dusty environment is solved at different inlet airflow velocities, which are the boundary conditions of the analysis model constructed in the simulation software. The arrays representing the different airflow velocity combinations of inlets are generated randomly through the optimal Latin hypercube algorithm (OLHA), where the lower and upper limits of velocities corresponding to the temperatures above the desired temperature are set in the optimization software. We establish an approximate QRSM between the velocity combination and the maximum temperature using the fitting module of the optimization software. The QRSM is optimized based on the ASAM, and the optimal result is in good agreement with the analysis result obtained by the simulation software. After optimization, the flow rate of the middle inlet is changed from 5.5 m/s to 5 m/s, and the total airflow velocity is decreased by 3%. The protocol here presents an optimization method simultaneously considering energy consumption and thermal performance of the battery management system that has been established, and it can be widely used to improve the life cycle of the battery pack with minimum operating cost.

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption 

Here, we present the adaptive simulated annealing method (ASAM) to optimize an approximate quadratic response surface model (QRSM) corresponding to a dusty particulate matter-covered battery heat management system and fulfill the temperature drops back by adjusting the airflow velocities combination of system inlets.

This study aims to solve the problem of the cell temperature rise and performance decline caused by dusty particulate matter covering the surface of the ...

A Comprehensive Approach to Investigate RMU Temperature Rise Problem

Comparative Study of Simulation of Temperature Rise in Ring Main Unit

The Ring Main Unit (RMU) is a critical device in power distribution systems used for connecting and distributing electricity. However, due to its compact internal structure and high current load, heat dissipation issues are particularly prominent. To address this problem, this study innovatively proposes a simplified RMU model, employing finite element simulation methods to accurately solve for the ohmic losses of conductors under actual operating conditions and obtain ohmic loss data for various components. This is the first in-depth investigation of the RMU's temperature rise problem using such a comprehensive approach. Subsequently, the temperature field was solved using two different temperature field analysis modules, with a detailed comparison and analysis of the simulation results to identify similarities, differences, and trends in temperature distribution. The results indicate that the temperature field solution model, which considers convective heat transfer, is more accurate and aligns with actual operating conditions. This research provides an innovative approach and practical solutions for the design and optimization of RMUs. Future research can further explore multiphysics coupling analysis methods to address structural design and mandatory validation issues for high and ultra-high voltage RMUs and other electrical equipment, thereby providing important insights for engineering design.

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

This paper addresses the temperature rise problem of the ring main unit by establishing a simplified model and conducting a comparative analysis in two temperature field-solving modules.

The Ring Main Unit (RMU) is a critical device in power distribution systems used for connecting and distributing electricity. However, due to its compact ...