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As the gymnasiums in subtropical region with hot and humid climate are naturally ventilated during non-competition periods, occupants exercising indoors often feel uncomfortable, especially in summer. In order to provide thermally comfortable and healthy environment for the occupants, the design on architectural form is found to be an effective solution on improving indoor thermal comfort of naturally ventilated gymnasiums. Therefore, a new perspective regarding optimization of naturally ventilated gymnasiums is proposed in the aspect of the architectural form. This paper presents the optimization of architectural form in naturally ventilated gymnasiums in which simulation and orthogonal experiment methods are combined. Through numerical simulation with FlowDesigner software, the significance of architectural form affecting indoor thermal comfort has been given, and the optimal architectural forms of naturally ventilated gymnasium are determined. The results show that the roof insulation type is the most significant factor influencing indoor thermal comfort; thus, it should be considered primarily in optimization. Moreover, the range analysis and variance analysis reveal the rankings of the factors for the gymnasium thermal comfort. In addition, it is demonstrated that the optimal gymnasium model, when compared with the initial gymnasium model, has a satisfactory effect on improving the indoor thermal comfort, as the average value of Predicted Thermal Sensation (PTS) in August decreased from 1.11 (Slightly hot) to 0.86 (Comfortable). This study provides a new insight for the designers in optimizing the architectural form of gymnasiums for achieving the indoor thermal comfort at hot and humid climate.

Whether the stems and leaves of leaf-vegetable sweet potatoes can be listed ahead of schedule is related to the improvement in economic benefits for farmers, and the key to all of this is to implement the safe overwintering of potato seedlings under the premise of saving production costs. Only in this way can we truly seize the “market opportunity” and achieve the goals of cost saving and increasing economic benefit. In this study, the main leaf-vegetable sweet potato variety Fucai 18 was used as the material, and the L9(34) orthogonal experiment was carried out in a simple solar greenhouse environment for two consecutive years from 2021 to 2022 and from 2022 to 2023, respectively. The effects of nine different combinations of factors on the above-ground and underground agronomic traits of overwintering sweet potato seedlings were studied under the conditions of four factors and three levels: planting density (a); different cutting seedlings (b); rooting agent concentration (c); and transplanting time (d). The methods of principal component analysis, membership function method, cluster analysis, grey correlation degree and stepwise regression analysis were used to evaluate the growth of overwintering seedlings, and try to screen out the key indicators that can be used to identify and evaluate the growth of overwintering sweet potato seedlings. Through range analysis, identify the optimal combination of four factors and three levels, and explore the main factors that have a significant impact on the key indicators for evaluating the growth of overwintering potato seedlings. The results indicate the following: (1) The use of simple sunlight greenhouse in Changsha area can achieve the safe overwintering of vegetable sweet potato seedlings. (2) Stem thickness, root length, and root diameter can be used as three key indicators for identifying and evaluating the growth potential of vegetable sweet potato overwintering seedlings. (3) Under four factors and three levels, the best combination was A3B3C1D1 (planting density of 250,000 plants/ha, stem tip core-plucking seedlings, rooting agent concentration of 50 mg/L, the first batch of transplanting time). (4) The transplanting time (D) is the main factor for the two key evaluation indicators of stem diameter and root diameter, while there is no significant difference in the three other factors. (5) Different cutting seedlings (B) are the main influencing factors for the key evaluation index of root length, while the other three factors have the following impact on root length: transplanting time (D) > rooting agent concentration (C) > planting density (A). The results of this study not only contribute to the construction of a safe overwintering cultivation technology system for vegetable sweet potato seedlings, but also provide a certain theoretical basis for the breeding of new cold-leaf-vegetable sweet potato varieties in the future.

It is known that rotating cavitation (RC) characteristic of an inducer can greatly influence the safe and stable operation of a liquid rocket. In this paper, the possibility of geometrically optimizing an inducer with respect to RC generated radial forces was discussed. The characteristics of the inducer was firstly evaluated through computational fluid dynamics (CFD), which was validated against experimental results. Then by employing an orthogonal experiment combined with CFD, influences of geometric parametric combinations on RC were investigated. Primary influencing factors and the best parametric combination have been obtained through a variance analysis. Comparing with the original inducer, a significant improvement in the cavitation performance, as well as the radial force characteristic of the optimized inducer has been achieved. Pressure distribution on the blades have been analyzed to reveal the related flow mechanism. This work provides a feasible and effective route in engineering practice to optimize the characteristic of RC generated radial forces for an inducer.

This study aims to investigate the behavior of ground surface settlement in TBM double-line tunnels constructed under existing buildings and to devise a calculative representation for that behavior. Numerical simulation and field monitoring methods were used to examine the Zhongcong Tunnel in Chongqing Metro Line 9. The ground surface settlement was analyzed using an orthogonal test of 3D numerical simulation methods. The results showed that ground surface settlement was influenced by TBM tunneling parameters and the location of the existing building in the following manner. The existing building reduced the settlement trough width. Surface settlement was increased by frictional and palm surface thrust forces but reduced by grouting pressure. The settlement trough width of the first excavation iz correlated with that of the last excavation iy. To accommodate the influence of existing buildings, the tilt factor of the settlement trough TR was introduced to improve the formula for calculating the ground surface settlement of TBM double-line tunnels. The improved formula was validated by comparing the calculated results with actual measurements.

The success of the 3D-printing process depends upon the proper selection of process parameters. However, the majority of current related studies focus on the influence of process parameters on the mechanical properties of the parts. The influence of process parameters on the shape-memory effect has been little studied. This study used the orthogonal experimental design method to evaluate the influence of the layer thickness H, raster angle θ, deformation temperature Td and recovery temperature Tr on the shape-recovery ratio Rr and maximum shape-recovery rate Vm of 3D-printed polylactic acid (PLA). The order and contribution of every experimental factor on the target index were determined by range analysis and ANOVA, respectively. The experimental results indicated that the recovery temperature exerted the greatest effect with a variance ratio of 416.10, whereas the layer thickness exerted the smallest effect on the shape-recovery ratio with a variance ratio of 4.902. The recovery temperature exerted the most significant effect on the maximum shape-recovery rate with the highest variance ratio of 1049.50, whereas the raster angle exerted the minimum effect with a variance ratio of 27.163. The results showed that the shape-memory effect of 3D-printed PLA parts depended strongly on recovery temperature, and depended more weakly on the deformation temperature and 3D-printing parameters.

Minimum quantity lubrication (MQL) is an efficient, green, and eco-friendly method of applying cutting fluids in machining processes. This study presents the processing characteristics of different vegetable oil-based nanofluid MQL for grinding various workpiece materials. The performance of three lubricant types (i.e., pure palm oil, MoS 2 nanofluid, and Al 2 O 3 nanofluid) of good lubrication performance and three types of materials (i.e., Inconel 718, ductile cast iron, and AISI 1045 steel) was evaluated in terms of force ratio, specific grinding energy, and G ratio. The optimal processing combination of lubricants and workpiece materials under the same experimental conditions was obtained using orthogonal experiment. Optimization results were verified by evaluating the morphology of the workpiece surface and grinding debris. Experimental results show the different processing characteristics of materials when various workpieces are processed using dissimilar MQL lubricants. MoS 2 nanofluid MQL is suitable for machining soft medium carbon steels, such as 45 steel, while Al 2 O 3 nanofluid is suitable for machining materials of high strength and hardness, such as nickel-based alloys.

This study explores mix proportion design and mechanical property prediction of EPS lightweight structural concrete using orthogonal experimentation and machine learning models. The research systematically analyzed the effects of EPS content, water-to-binder ratio, and POM fiber content on compressive strength, splitting tensile strength, thermal conductivity, and frost resistance. Key findings reveal that EPS content significantly enhances thermal insulation and frost resistance but reduces mechanical strength. POM fibers were shown to improve tensile strength and frost resistance by limiting crack propagation. A novel dataset was established and utilized in performance prediction using XGBoost, optimized with Seagull Optimization Algorithm (SOA), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO). Among these, SOA-XGBoost achieved the highest prediction accuracy and stability. The optimal mix proportion, combining 35% EPS, 0.21 water-to-binder ratio, and 0.65% POM fiber content, was identified, providing an effective balance between mechanical and thermal performance. The proposed framework offers valuable insights and methodologies for optimizing lightweight concrete and serves as a reference for other composite materials in engineering applications.

This paper focuses on the study of factors influencing the performance of 4D-printed PFO occluder frames. First, polyethylene glycol (PEG, Mn = 2000) was used to blend and modify polylactic acid (PLA). At a PEG content of 15%, the glass transition temperature of the blend decreased from 74°C for pure PLA to 56°C, with a significant increase in hydrophilicity and the water contact angle decreased from 74° to 62°. Regarding mechanical properties, tensile strength decreased from 60.0 ± 1.8 MPa to 27.5 ± 1.2 MPa, while elongation at break increased substantially from 4.8 ± 0.8% to 300 ± 50.2%.When PEG content was increased to 25%, the glass transition temperature decreased to 58°C, hydrophilicity continued to enhance, and the contact angle decreased to 54°. At this point, tensile strength decreased to 15.6 ± 2.0 MPa, while elongation at break further increased to 432.5 ± 30.2%. Then, orthogonal + response surface experiments were conducted to optimize the FDM 4D printing process parameters, identifying fill rate as the key factor influencing the shape recovery rate and tensile strength of PLA parts. A regression model was established linking tensile strength to printing temperature, speed, and fill rate. Mechanical testing indicated that the 8-ligament occluder exhibited the best mechanical properties, while shape memory recovery rate tests showed that occluders made from PLA/PEG2K-25 filament had superior shape recovery rates compared to those made from PLA/PEG2K-15. The study demonstrates that through PEG modification of PLA and control of the 4D printing process, comprehensive optimization of the mechanical and shape memory properties of PFO occluder frameworks can be achieved.

The acoustic black hole (ABH) can alter the velocity of bending waves and concentrate vibration energy with the change of thickness. However, the frequency of the ABH is primarily concentrated above the cut-off frequency and the effect on frequencies below the cut-off frequency is negligible. This paper investigates the vibration characteristics of the ABH damping oscillator (ABH-DO) structure in the frequency range below the cut-off frequency and the corresponding structural parameter influence analysis is conducted. Subsequently, the vibration property of ABH-DO in multiple array configurations are analyzed and the ability of absorbing the vibration energy is experimentally verified. Finally, orthogonal experiments are performed on ABH-DO structures in multiple array configurations. The results reveal that both single and multiple ABH-DO structures demonstrate effective vibration reduction. Among the parameters of ABH-DO, the oscillator mass has the most pronounced effect on vibration peaks. The vibration characteristics of the ABH-DO structure can be optimized by adjusting the oscillator mass. Optimal parameters are determined within a given range through orthogonal experiments. The vibration characteristics of the ABH-DO structure at the optimal factor level are enhanced to varying extents.

Liquid accumulation in low-lying and uphill sections of undulating shale gas pipelines significantly threatens transportation efficiency, pressure stability, and pipeline integrity due to corrosion. Accurate prediction of liquid holdup is therefore critical for flow assurance. This study investigates the liquid distribution in a shale gas pipeline through orthogonal testing, analyzing key operational factors including water and gas flow rates. The formation mechanisms and the relative significance of these factors on liquid accumulation are systematically elucidated. Subsequently, a predictive mathematical model correlating operational parameters with liquid accumulation volume is developed. The model’s accuracy is rigorously validated against simulation results obtained from the industry-standard OLGA multiphase flow software. The findings of this study establish a theoretical foundation for optimizing pigging operations, thereby enhancing pipeline transport efficiency and reducing operational costs.