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Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To quantify the seismic effectiveness of the most commonly used fishing line tie up method for securing museum collections and optimize fixed strategies for exhibitions, shaking table tests of the seismic systems used for typical museum collection replicas have been carried out. The influence of body shape and fixed measure parameters on the seismic responses of replicas and the interaction behavior between replicas and fixed measures have been explored. Based on the results, seismic effectiveness evaluation indexes of the tie up method are proposed. Reasonable suggestions for fixed strategies are given, which provide a basis for the exhibition of delicate museum collections considering the principle of minimizing seismic responses and intervention. The analysis results show that a larger ratio of height of mass center to bottom diameter led to more intense rocking responses. Increasing the initial pretension of fishing lines was conducive to reducing the seismic responses and stress variation of the lines. Through comprehensive consideration of the interaction forces and effective securement, it is recommended to apply 20% of breaking stress as the initial pretension. For specific museum collections that cannot be effectively protected by the independent tie up method, an optimized strategy of a combination of fishing lines and fasteners is recommended. [ABSTRACT FROM AUTHOR]

The optimized design of a new high-temperature superconducting rotating pole machine is presented. Its main structural feature is the use of a double stator core which separates the synchronous machine pole shoe from the pole body to rotate separately as the machine rotor, allowing the superconducting coil to operate in a stationary state. The inner stator core, the stationary dewar and the rotor core together form the excitation system of the machine. The excitation coil windings adopt a rectangular cross-section, with flux divertor strategically placed between the high-temperature superconducting coils. This configuration aims to modulate the background magnetic field, specifically reducing the perpendicular magnetic field component. This mitigation minimizes the impact of ambient magnetic fields on the superconducting coil's current carrying capacity, ensuring an optimized magnetic field environment for its operation. Through the integration of these modifications, the technical and economic parameters of the enhanced high-temperature superconducting machine have been significantly improved. The optimization of design, coupled with detailed calculations of the 3D electromagnetic field, was achieved utilizing the commercial software Ansys EM module. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In response to the challenges posed by the difficult cleaning of tunnel retro-reflective rings and the unsuitability of existing climbing robots for ascending tunnel retro-reflective rings, a tunnel retro-reflective ring cleaning robot is proposed. Firstly, based on the analysis of the operational and environmental characteristics and functional requirements inside the tunnel, the design and planning of the robot's main framework, motion system, cleaning mechanism, and intelligent detection system are conducted to evaluate its walking ability under various working conditions, such as aluminum plate overlaps and rivet protrusions. Subsequently, stability analysis is performed on the robot. The static analysis explored conditions that can make the climbing robot stable, the dynamic analysis obtained the minimum driving torque and finally, verified the stability of the robot through experiments. After that, by changing the material and thickness of the main framework for deformation simulation analysis, the optimal parameters to optimize the design of the main framework are found. Finally, the three factors affecting the cleaning effect of the robot are discussed by the response surface method, and single factor analysis and response surface regression analysis are carried out, respectively. The mathematical regression model of the three factors is established and the best combination of the three factors is found. The cleaning effect is best when the cleaning disc pressure is 5.101 N, the walking wheel motor speed is 36.93 rad/min, and the cleaning disc motor speed is 38.252 rad/min. The development of this machine can provide equipment support for the cleaning of tunnel retro-reflective rings, reducing the requirement of manpower and material resources. [ABSTRACT FROM AUTHOR]

A multifunctional leveling platform for orchard in hilly and mountainous areas is developed. The platform design optimizes the double circuit hydraulic system and the horizontal and vertical bidirectional leveling structure to realize synchronous adjustment. Based on the attitude sensor, an intelligent detection and control system is developed to realize the automatic leveling and platform stabilization. The test results show that the platform can reach the maximum climbing capacity of 30° and the limit leveling angle of 15°, which can meet the requirements of orchard operation in large slope and complex terrain, and provide theoretical basis for the future design of orchard operation platform in hilly and mountainous areas. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper takes the frame as the research object and explores the vibration characteristics of the frame to address the vibration problem of a 1-MSD straw-crushing and residual film recycling machine in the field operation process, and an accurate identification of the modal parameters of the frame is carried out to solve the resonance problem of the machine, which can achieve cost reduction and increase income to a certain extent. The first six natural frequencies of the frame are extracted by finite element modal identification and modal tests, respectively. The rationality of the modal test results is verified using the comprehensive modal and frequency response confidences. The maximum frequency error of modal frequency results of the two methods is only 6.61%, which provides a theoretical basis for the optimal design of the frame. In order to further analyze the resonance problem of the machine, the external excitation frequency of the machine during normal operation in the field is solved and compared with the first six natural frequencies of the frame. The results show that the first natural frequency of the frame (18.89 Hz) is close to the external excitation generated by the stripping roller (16.67 Hz). The first natural frequency and the volume of the frame are set as the optimization objectives, and the optimal optimization scheme is obtained by using the Optistruct solver, sensitivity method, and grey correlation method. The results indicate the first-order natural frequency of the optimized frame is 21.89 Hz, an increase of 15.882%, which is much higher than the excitation frequency of 16.67 Hz, and resonance can be avoided. The corresponding frame volume is 9.975 × 107 mm3, and the volume reduction is 3.46%; the optimized frame has good dynamic performance, which avoids the resonance of the machine and conforms to the lightweight design criteria of agricultural machinery structures. The research results can provide some theoretical reference for this kind of machine in solving the resonance problem and carrying out related vibration characteristics research. [ABSTRACT FROM AUTHOR]

Abstract In the current research study, a new method is presented to diagnose Anterior Cruciate Ligament (ACL) tears by introducing an optimized version of the InceptionV4 model. Our proposed methodology utilizes a custom-made variant of the Snow Leopard Optimization Algorithm, known as the Fractional-order Snow Leopard Optimization Algorithm (FO-LOA), to extract essential features from knee magnetic resonance imaging (MRI) images. This results in a substantial improvement in the accuracy of ACL tear detection. By effectively extracting critical features from knee MRI images, our proposed methodology significantly enhances diagnostic accuracy, potentially reducing false negatives and false positives. The enhanced model based on FO-LOA underwent thorough testing using the MRNet dataset, demonstrating exceptional performance metrics including an accuracy rate of 98.00%, sensitivity of 98.00%, precision of 97.00%, specificity of 98.00%, F1-score of 98.00%, and Matthews Correlation Coefficient (MCC) of 88.00%. These findings surpass current methodologies like Convolutional Neural Network (CNN), Inception-v3, Deep Belief Networks and Improved Honey Badger Algorithm (DBN/IHBA), integration of the CNN with an Amended Cooking Training-based Optimizer version (CNN/ACTO), Self-Supervised Representation Learning (SSRL), signifying a significant breakthrough in ACL injury diagnosis. Using FO-SLO to optimize the InceptionV4 framework shows promise in improving the accuracy of ACL tear identification, enabling prompt and efficient treatment interventions.

To improve the drill pipe fracture failure phenomenon in deflecting drills with ultra-short radius flexible drill pipes, this study establishes a mechanical model of a deflecting drill with an ultra-short radius flexible drill pipe, numerically simulates the mechanical characteristics of the flexible drill pipe under the conventional drilling process using the finite element analysis method, performs mechanical performance tests on the flexible drill pipe, and optimizes and improves its structure. The results show that, with the gradual increase in the bending angle of the flexible drill pipe unit section, the upper drilling pressure of the flexible drill pipe unit section decreases rapidly and its friction increases approximately linearly. The tensile strength of the optimized ultra-short radius flexible drill pipe is increased by 24.7%, and the minimum threshold of its torsional strength is doubled. This effectively improves the overall strength of the ultra-short radius flexible drill pipe and provides a theoretical basis for downhole drilling stability studies of flexible drill pipes.

In the current research study, a new method is presented to diagnose Anterior Cruciate Ligament (ACL) tears by introducing an optimized version of the InceptionV4 model. Our proposed methodology utilizes a custom-made variant of the Snow Leopard Optimization Algorithm, known as the Fractional-order Snow Leopard Optimization Algorithm (FO-LOA), to extract essential features from knee magnetic resonance imaging (MRI) images. This results in a substantial improvement in the accuracy of ACL tear detection. By effectively extracting critical features from knee MRI images, our proposed methodology significantly enhances diagnostic accuracy, potentially reducing false negatives and false positives. The enhanced model based on FO-LOA underwent thorough testing using the MRNet dataset, demonstrating exceptional performance metrics including an accuracy rate of 98.00%, sensitivity of 98.00%, precision of 97.00%, specificity of 98.00%, F1-score of 98.00%, and Matthews Correlation Coefficient (MCC) of 88.00%. These findings surpass current methodologies like Convolutional Neural Network (CNN), Inception-v3, Deep Belief Networks and Improved Honey Badger Algorithm (DBN/IHBA), integration of the CNN with an Amended Cooking Training-based Optimizer version (CNN/ACTO), Self-Supervised Representation Learning (SSRL), signifying a significant breakthrough in ACL injury diagnosis. Using FO-SLO to optimize the InceptionV4 framework shows promise in improving the accuracy of ACL tear identification, enabling prompt and efficient treatment interventions. [ABSTRACT FROM AUTHOR]

Double-layer heat tubes have been designed to effectively reduce the occurrence of heat pipe rupture accidents. However, inter-tube thermal contact resistance can decrease heat transfer efficiency, thus hampering the heat dissipation in the primary loop system of lead-bismuth reactors. Therefore, optimizing the design of double-layer heat tubes is necessary. This work focuses on the double-layer heat exchanger of a lead-bismuth reactor and utilizes gallium-based graphene nanofluids as a thermal interface material to fill the gap between the heat tubes. Furthermore, the impact of the length, wall thickness, outer diameter, and spacing of heat tubes on the heat transfer performance of the double-layer heat exchanger with and without the nanofluids has been analyzed. The study aims to optimize the JF factor and cost-effectiveness ratio (CER). Genetic algorithms are employed to optimize and evaluate the heat transfer performance of the main heat exchanger based on the four aforementioned parameters. Consequently, a new design scheme is obtained for the double-layer heat exchanger, which increases the optimized overall heat transfer coefficient of the main heat exchanger by 5.79%, pressure drop in the primary loop by 2.32%, JF factor by 5%, and CER by 24.62%. These results demonstrate that the gallium-based graphene nanofluids can effectively enhance the heat transfer performance of the double-layer heat exchanger while reducing the likelihood of steam generator tube rupture accidents. [ABSTRACT FROM AUTHOR]

In order to improve the performance and service life of the Leningrader seal of the Stirling engine piston rod, interference, preload and friction coefficient were taken as influencing factors, and the curved surface response method was adopted to reduce the contact stress of sealing surface and von Mises stress of the sealing sleeve as the response index, with the optimization goal of reducing wear and extending life. The above three key parameters are analyzed and optimized, the influence of each parameter on the sealing performance and service life is obtained, and the best combination scheme of the three is determined. The results show that the interaction between pretightening force and interference fit has the greatest impact on contact stress. The interaction between interference fit and friction coefficient has the most significant effect on von Mises stress. The optimized parameters can reduce the maximum contact stress and maximum von Mises stress of the sealing sleeve by 26.3% and 20.6%, respectively, under a media pressure of 5-9 MPa. Test bench verification shows that the leakage of the optimized sealing device in 12 h is reduced by 0.44 cc·min-1 (1 cc=1 cm³). The wear rate of the sealing sleeve is 1.08% before optimization and 0.45% after optimization, indicating that the optimized parameters in this paper are effective. [ABSTRACT FROM AUTHOR]

To address the problems of long optimization times of bionic wear-resistant structures in discrete element simulation. We established two-dimensional homoscale discrete element simulation models for four biomimetic structures, along with their respective abrasive wear computational models. We then deliberated upon their wear behavior in relation to the structural morphology, contact constraints, contact force, and wear volume during the wear process. The study found that the shedding of brittle wear body surface abrasives had little effect on the substrate of the bionic structure. Based on the above findings, a multi-scale/cross-level study of the interaction between biological wear surface structure and abrasive was conducted. The findings evince that utilization of a multi-scale computational model ensures the precise examination of the mechanical response of a material to external forces, while also economizing computational time. Finally, the design of the conical bionic structure is optimized based on the multi-scale/cross-level computational model. The results show that the conical bionic structure has good wear resistance when the abrasive grain size is small and when the monomer spacing is not larger than the monomer width. The bionic structure/abrasive interaction multi-scale numerical simulation system established in this paper reduces the complexity of dynamic numerical simulation of wear behavior on the surface of wear- resistant organisms, improves the calculation efficiency, and provides an important research means and method for optimizing the design of bionic wear-resistant parts. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Low-carbon design that reduces the life cycle carbon emissions of products at source is increasingly becoming an important direction in product design to mitigate global warming further. An important design principle should be minimizing the product's weight and movement efficiency while minimizing its life cycle carbon emissions. This paper proposed a product kinematic analysis based on carbon footprint. After that, it developed a flexible picking actuator for tomato fruit based on the Bricard mechanism. Through kinematic analysis of the picking actuator, the optimized design of the mechanism is followed by simulation tests to reduce the carbon footprint over its life cycle. A systematic carbon footprint calculation model for the Bricard mechanism-based picking actuator is also developed and applied in the product design process to verify the design mechanism's feasibility, method and technology. [ABSTRACT FROM AUTHOR]

Improving the quality of the manufacturing process is an important goal of professional technicians. This study systematically explored the key success factors in the product-forming ability and visual optimization of 3D forming in the clay-shaping process through actual manufacturing and implementation. The purpose of this study was to identify the forming technology and technical indicators that can successfully achieve a high degree of completeness and maturity in the manufacturing process, increasing the shaping performance of the end products and enabling the evaluation of optimization. In this study, we evaluated soil shaping, material use, the manufacturing process, and product forming. The key success factors were studied and analyzed via expert interviews. The research and analysis were summarized into 4 dimensions with 48 sub-dimensions. These included: (1) soil material, with 12 sub-dimensions; (2) the design concept, with 12 sub-dimensions; (3) the prototype process, comprising 12 sub-dimensions; and (4) kiln firing, comprising 12 sub-facets. A research team composed of 13 scholars and experts conducted three surveys on the evaluation dimensions of the Delphi technique. They analyzed the mean (M), mode (Mo), and standard deviation (SD) of various dimension options. They used the Kolmogorov–Smirnov one-sample test research and analysis to analyze the appropriateness and consistency of the survey results. The results of this study showed that 15 sub-dimensions met the appropriateness and consistency conditions, based on which 15 key factors were established. The results of this study provide reference indicators for the manufacturing process, forming process, and forming technology optimization quality for follow-up research. [ABSTRACT FROM AUTHOR]

The forward-curved multi-blade centrifugal fan, also termed as Sirocco fan, is characterized by its complex characteristics of internal flow within the impeller and volute. Currently most of the fans are designed with modifications or optimizations for certain geometric parameters which could not ensure the well compatibility of flow in the impeller and volute, thus it is difficult to improve the aerodynamic performances of the fans. In this paper, we performed a multi-parameter design of a Sirocco fan with optimizations on the geometric parameters of the impeller and volute. The geometric parameters of the volute were designed based on analysis of the internal flow patterns, and the influence from the impeller is also considered. Optimization on the geometric parameters was carried out using the steepest descent method to improve the static pressure rise and efficiency under the designed flow rate by taking into account the relevance of flow in the impeller and volute. The effect of the parametric optimization is evaluated and analyzed by large-eddy simulation (LES). It was found that the static pressure rise and efficiency of the optimized model increase by 1.8% and 5.0% compared with the baseline model, respectively. The static pressure rise fluctuates in a regularly periodic manner. The optimized model reduces the area of low-pressure recirculating flow at the center of the fan and the separated flow on the suction surface of the blades. The near-wall flow on the volute surface is more stable, and the pressure fluctuation around the volute tongue is reduced. The outflow of the volute exhibits better uniformity than the baseline model. [ABSTRACT FROM AUTHOR]

Tractor is the main tool of agricultural production and transportation, the performance of its various advantages and disadvantages directly affect the quality of agricultural operations. Agricultural wheeled tractor steering ladder mechanism, is the main component of the steering system. Steering trapezoidal mechanism design is good or bad, directly determines the performance of the tractor in the steering driving. To reduce tire wear during tractor steering, in this research, the steering ladder of a 75 HP tractor is optimized. The length and the initial bottom angle are determined through kinematic and geometric analysis of the steering trapezoid. The initial bottom angle is the design variable, with the actual variable angle and theoretical expectations. The relative error is the objective function. A mathematical model for the optimization design of the tractor steering trapezium is established, and a MATLAB program is developed using a hybrid genetic algorithm (HGA) to solve the problem. The results show that the steering arm length is 240 mm before optimization, the initial bottom angle is 64°, the steering arm length is 210 mm after optimization, the initial bottom angle is 61° and the objective function decreases from 19.5% to 17.8%. The verification test was carried out in the agricultural machinery test base of Anhui Agricultural University (China). The experimental results show that the RE between the measured average and the optimized the initial bottom angle is 1.49%, less than 5%. This shows that the results obtained by HGA optimization are feasible and provide a reference for improving the performance of tractor steering system.

CNC machine tools play an important role in manufacturing and are characterized by high total energy consumption and low energy efficiency. The energy consumption characteristics of the machine tool itself determine the total energy consumption and pollutant emission during its service life. Therefore, it is particularly important to design machine tools with energy consumption as the optimization target to analyze the composition of energy consumption and related characteristics, build a corresponding model based on reliability verification, guide the structural design and optimization according to the model, and ultimately use the evaluation system to evaluate and judge the overall energy consumption. In this paper, from four perspectives—the composition of the energy consumption of machine tools, modeling methods, design and optimization methods, and evaluation methods—with energy consumption optimization as the entry point, we analyze the research on CNC machine tools based on energy consumption around the world. The research results indicate that we should look forward to the role of energy consumption in the design of machine tools. [ABSTRACT FROM AUTHOR]

In order to design an involute spline made of PEEK (polyetheretherketone)-based material with better performance and improve the design rules of involute splines, initially, an involute splines design theory for PEEK (polyetheretherketone)-based materials is presented, which combines international standards (ISO 4156, 1. 2. 3, 2005), American standards (ANSI B92.2M. 1989), and traditional empirical formulas. Second, using the involute splines calibration method in international standards as a guide, we developed the involute splines calibration method for PEEK-based materials by estimating the impact of energy consumption caused by viscoelasticity on temperature field calibration. Next, the contact characteristics of the designed spline were analyzed using ABAQUS2022 software to confirm the accuracy and reliability of the design and calibration methods. Finally, finite element simulation was used to analyze the influence of different pressure angles, moduli, combined lengths, and other parameters on the contact characteristics of the spline in order to realize the optimal design of PEEK-based material involute splines, to offer a theoretical foundation and improved design methodology for cylindrical straight-tooth involute splines. [ABSTRACT FROM AUTHOR]

To investigate the flow field characteristics within the cavity of the key components in a dual-airway pneumatic fallen jujube fruit pickup device under the influence of negative pressure airflow and to optimize the device’s structural parameters, we constructed a numerical simulation model for the flow field in the dual-airway pickup mouth using computational fluid dynamics. Initially, we analyzed the impact of the central partition on the flow field within the pickup suction mouth. Subsequently, utilizing the velocity unevenness coefficient as the response index, we conducted a single-factor test on the key parameters of the cavity structure to determine the optimal value range for each factor. Through an orthogonal test, response surface analysis, and a composite optimization method, we established the optimal structural parameter combination as follows: a falloff angle of 91.37°, an opening width of 50 mm, a flanging radius of 6.45 mm, and a relative height of 20mm, resulting in a velocity unevenness coefficient of 5.89%. Finally, validation tests were performed, revealing that the velocity unevenness coefficients for dual-airway pickup suction were 6.22%, 6.60%, and 6.45%, respectively. The maximum deviation from the predicted value was 0.71%, with a maximum relative error of 12.05%. This study holds significant importance not only for the optimization of complex cavity structures in pickup equipment design but also serves as a valuable reference for the development of mechanized fallen jujube fruit pickup equipment. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent decades, the development of electronic technology has provided opportunities for the Internet of Things, biomedicine, and energy harvesting. One of the challenges of the Internet of Things in the electrification era is energy supply. Centralized energy supply has been tested over hundreds of years of history, and its advantages such as ideal output power and stable performance are obvious, but it cannot meet the specific needs of the Internet of Things, and distributed energy supply also has a large demand. Since the invention of nanogenerators, another promising solution for fluid energy harvesting has been opened up. The triboelectric nanogenerator is an emerging platform technology for electromechanical energy conversion, which can realize the collection of fluid energy such as wind energy and wave energy. In this paper, we first introduce the fundamentals of triboelectric nanogenerators and their applications in wind and wave energy harvesting devices. We then discuss the methods of device optimization in the next development of TENG and conclude by considering the future prospects and challenges for triboelectric nanogenerator harvesting devices. [ABSTRACT FROM AUTHOR]

Glass curtain walls (GCWs) have become prevalent in office buildings, owing to their lightweight and modular characteristics. However, their lower thermal resistance, compared to opaque walls, results in increased energy consumption. Incorporating phase-change materials (PCMs) provides a viable solution through which to address the susceptibility of GCWs to external conditions, thus enhancing thermal performance and mitigating energy concerns. This study delves into the influences of the glazing solar heat gain coefficient (SHGC), the glazing heat transfer coefficient (U-value), and PCM thickness on the energy performance of buildings. Using Design Builder (DB) software version 6.1.0.006, a multi-story office building was simulated in different climatic zones in China, covering the climatic characteristics of severe cold, cold, hot summer and warm winter, cold summer and winter, and mild regions. The simulation results quantitatively elucidated the effects of the glazing parameters and the number of PCMs on thermal regulation and energy consumption. A sensitivity analysis identified the glazing SHGC as the most influential factor in energy consumption. Additionally, by employing Response Surface Methodology (RSM), the researchers aimed to achieve a balance between minimal building energy consumption and economic cost, ultimately determining an optimal design solution. The results demonstrated significant energy savings, ranging from 20.16% to 81.18%, accompanied by economic savings, ranging from 15.78% to 79.54%, across distinct climate zones in China. [ABSTRACT FROM AUTHOR]

This study designed three different types of sports bras based on the physiological characteristics of female upper bodies. The dressing pressure, skin temperature, and shaping support effectiveness of one subject when wearing those sports bras were evaluated under static and dynamic states. The results indicated that all designed bras illustrated excellent pressure comfort. Regarding the thermal comfort and shaping support performance, sports bras B2 and B3 with further optimizations had improved performances compared to B1. Besides, it was found that the skin temperature would increase with the dressing pressures from sports bras. The increased but comfortable dressing pressure could also benefit the shaping and support performance of sports bras. B22 and B33 had superior support performance to B1, with excellent ability to lift and gather the breasts, and to retract the waist. In summary, optimized sports bras with a cross, hollowed-out, and split design could effectively meet body comfort needs. [ABSTRACT FROM AUTHOR]

Slotted liner completion is a well completion method that is widely used in sand formations at home and abroad. With the increase of service quantity and service life, the problem of screen failure becomes more and more prominent. Based on the theory of elastic-plasticity, a three-dimensional parameterized FEM model of slotted liner was established to study the influence law of slot length, slot spacing and circumferential slot number on the strength and flow capacity (production capacity) of slotted liner under the action of earth stress. The response surface analysis method with three factors and two levels was used in the experiment to obtain a quadratic polynomial mathematical model of high stress area volume and flow area. The results show that the slot length is proportional to the high stress area volume and flow area. The circumferential slot number is inversely proportional to the high stress area volume and directly proportional to the flow area. And the slot spacing is inversely proportional to the high stress area volume and flow area. Under limited conditions, when the slot length is less than 70 mm, the slot spacing is greater than 15 mm, and the circumferential slot number is greater than 60, both strong mechanical performance and good flow capacity can be obtained at the same time. The research results provide a theoretical basis for optimizing the stitching parameters of slotted liner. [ABSTRACT FROM AUTHOR]

The rapid development of infinite networks and information technology has promoted the wide deployment and rapid growth of intelligent interactive devices. However, at the same time, touch interaction technology also faces many challenges such as lack of precision. This study combines federated learning with LayerGesture technology to optimize and design a touch interaction system with higher interaction accuracy and applies it to practice. The analysis results show that with the increase in the number of iterations of the federated model, the accuracy of the human–computer recognition interaction and the amount of information contained in it increases, and the accuracy curve reaches stability at about 2800 times and is at the optimal interaction adaptation. At this point, the loss function also decreases gradually, while the loss factor tends to 0, which verifies the stability of the optimized model. According to the participants' interaction experience and experimental results, the optimized LayerGesture technique of the federated learning model has an average correctness rate of 90.4% and the lowest average selection time, while the average selection time of LayerGesture in the interaction area at the edge of the screen is 2510 ms and the average correctness rate is 93.60%, which is better than the Shift technique. In addition, the subjective survey results indicated that more participants favored the optimized LayerGesture technique. In summary, this paper's joint learning algorithm contributes to the recognition effectiveness and efficiency of intelligent interactive systems. [ABSTRACT FROM AUTHOR]

The grinding process of the angle grinder generates a large amount of dust, which present hazards to the environment and workers' health. In order to capture the grinding dust more efficiently, this paper optimizes the performance of the dust collection hood of the angle grinder by building a grinding experimental platform and using the response surface method (RSM). Using the Box-Behnken design method, the collection quantity M total of all dust particles generated by grinding and the collection quantity M PM10 of PM10 are used as the main performance indicators of the dust collector. Four independent factors such as grinding wheel diameter, suction pipe diameter, mounting angle, and grinding wheel speed of the dust collection hood were optimized to arrive at the best combination of parameters. Through response surface analysis, a quadratic polynomial regression model between each influencing factor and performance indicator is established, and significance test and variance analysis are performed to verify the validity and applicability of the model. Finally, through three-dimensional response surface plots and contour plots, the interactions between each influencing factor are analyzed, and the predicted values of performance indicators under optimal experimental conditions are determined. The experimental results show that the mounting angle has the greatest impact on M total , and the grinding wheel speed has the greatest impact on M PM10. The field engineering application shows that the optimized dust collection hood can effectively prevent dust from escaping. The reduction efficiency of total dust concentration in the grinding place is over 83.6 %, and the reduction efficiency of respirable dust concentration is over 90.0 %. The research results of this paper provide some reference value for the research and application in the field of dust control. [Display omitted] [ABSTRACT FROM AUTHOR]

Optimal automobile seat design can play a significant role in passenger safety during high-speed accidents. To tackle the challenge of optimizing automotive seats, this paper presents a detailed optimization design method. In detail, the finite element models firstly established and validated through eight typical working conditions of automotive seats based on experimental data. Then, the optimized variables are screened and determined through contribution analysis, in which, the various perspectives are taken into account, such as the total cost and mass of seat materials, safety performance, and comfort index. Subsequently, an optimization strategy is constructed, which combines optimal Latin hypercube sampling, response surface method surrogate models, non-dominated sorting genetic algorithm-II, fuzzy analytic hierarchy process, entropy weighting method, gray relational analysis, and Visekriterijumsko KOmpromisno Rangiranje method for the optimal design of the automotive seat frame. Finally, a comprehensive comparative analysis of the optimal trade-off solution is carried out in terms of both decision methods and optimization strategies. The results show that ensuring the safety performance, the total cost, and total mass of the seat frame material decreased by 17.22% and 11.52%, respectively, as a result of the optimization strategy proposed in this paper, and the comfort performance is also improved to some extent. Therefore, the multi-objective optimization strategy proposed in this paper performs well in terms of both accuracy and effectiveness and provides a reliable reference for related multi-objective optimization. [ABSTRACT FROM AUTHOR]

A new anchor-siphon drainage combined method used for slope stabilization is proposed in this paper. It includes an anchoring section and a siphon drainage section. The novelty of the anchor-siphon drainage combined method is the realization of the drainage and anchoring in the one inclined borehole. The engineering cost of drilling and the resulting disturbance to the slope is reduced. To validate the feasibility of the proposed method, a numerical method that combines the pore water pressure distribution after siphon drainage and the anchoring force of the anchoring section is used to evaluate the safety of the slope with the anchor-siphon drainage method. The proposed method was illustrated and validated with the Hongpu Village landslide, in Tonglu County, Zhejiang Province, in China. Compared with the common anchor bar with the same length in the anchoring section, the factor of safety (FOS) for Hongpu Village slope with anchor-siphon drainage is increased by 0.085. The calculation method of the optimal length ratio between the drainage section and the anchoring section and its influencing factors were studied. For the different design parameters, there is always an optimal length ratio of the drainage section. Compared with the siphon drainage and full-length anchor bar with the same borehole length, the anchor-siphon drainage combined method shows better landslide prevention ability. Moreover, when the optimized parameters with a bond strength of 560 kPa, a borehole inclination of 35°, and no reduction in length are used, the calculated safety factor is 1.316, which is significantly higher than the FOS of 1.131 for the slope with siphon drainage. [ABSTRACT FROM AUTHOR]

Self-heating and electric field distribution are the primary factors affecting the accuracy of the Ultra High Voltage Direct Current (UHVDC) resistive divider. Reducing the internal temperature rise of the voltage divider caused by self-heating, reducing the maximum electric field strength of the voltage divider, and uniform electric field distribution can effectively improve the UHVDC resistive divider’s accuracy. In this paper, thermal analysis and electric field distribution optimization design of 1200 kV UHVDC resistive divider are carried out: (1) Using the proposed iterative algorithm, the heat dissipation and temperature distribution of the high voltage DC resistive divider are studied, and the influence of the ambient temperature and the power of the divider on the temperature of the insulating medium of the divider is analyzed; (2) Established the finite element models of 1200 kV and 2 × 600 kV DC resistive dividers, analyzed the influence of the size of the grading ring and the installation position on the maximum electric field strength of the voltage divider, and calculated the impact of the shielding resistor layer on the vicinity of the measuring resistor layer. The research indicates that: (1) The temperature of the insulating medium is linearly related to the horsepower of the voltage divider and the ambient temperature; (2) After the optimized design of the electric field, the maximum electric field strength of the 1200 kV DC resistive divider is reduced to 1471 V/mm, which is about 24% lower than that of the unoptimized design; (3) Installing the shielding resistor layer can significantly improve the electric field near the measuring resistor layer. This paper has an important reference function for improving the accuracy of the UHVDC resistive divider. [ABSTRACT FROM AUTHOR]

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Double-layer heat tubes have been designed to effectively reduce the occurrence of heat pipe rupture accidents. However, inter-tube thermal contact resistance can decrease heat transfer efficiency, thus hampering the heat dissipation in the primary loop system of lead-bismuth reactors. Therefore, optimizing the design of double-layer heat tubes is necessary. This work focuses on the double-layer heat exchanger of a lead-bismuth reactor and utilizes gallium-based graphene nanofluids as a thermal interface material to fill the gap between the heat tubes. Furthermore, the impact of the length, wall thickness, outer diameter, and spacing of heat tubes on the heat transfer performance of the double-layer heat exchanger with and without the nanofluids has been analyzed. The study aims to optimize the JF factor and cost-effectiveness ratio (CER). Genetic algorithms are employed to optimize and evaluate the heat transfer performance of the main heat exchanger based on the four aforementioned parameters. Consequently, a new design scheme is obtained for the double-layer heat exchanger, which increases the optimized overall heat transfer coefficient of the main heat exchanger by 5.79%, pressure drop in the primary loop by 2.32%, JF factor by 5%, and CER by 24.62%. These results demonstrate that the gallium-based graphene nanofluids can effectively enhance the heat transfer performance of the double-layer heat exchanger while reducing the likelihood of steam generator tube rupture accidents.

Abstract The rapid development of infinite networks and information technology has promoted the wide deployment and rapid growth of intelligent interactive devices. However, at the same time, touch interaction technology also faces many challenges such as lack of precision. This study combines federated learning with LayerGesture technology to optimize and design a touch interaction system with higher interaction accuracy and applies it to practice. The analysis results show that with the increase in the number of iterations of the federated model, the accuracy of the human–computer recognition interaction and the amount of information contained in it increases, and the accuracy curve reaches stability at about 2800 times and is at the optimal interaction adaptation. At this point, the loss function also decreases gradually, while the loss factor tends to 0, which verifies the stability of the optimized model. According to the participants’ interaction experience and experimental results, the optimized LayerGesture technique of the federated learning model has an average correctness rate of 90.4% and the lowest average selection time, while the average selection time of LayerGesture in the interaction area at the edge of the screen is 2510 ms and the average correctness rate is 93.60%, which is better than the Shift technique. In addition, the subjective survey results indicated that more participants favored the optimized LayerGesture technique. In summary, this paper’s joint learning algorithm contributes to the recognition effectiveness and efficiency of intelligent interactive systems.

In response to the challenges posed by the difficult cleaning of tunnel retro-reflective rings and the unsuitability of existing climbing robots for ascending tunnel retro-reflective rings, a tunnel retro-reflective ring cleaning robot is proposed. Firstly, based on the analysis of the operational and environmental characteristics and functional requirements inside the tunnel, the design and planning of the robot’s main framework, motion system, cleaning mechanism, and intelligent detection system are conducted to evaluate its walking ability under various working conditions, such as aluminum plate overlaps and rivet protrusions. Subsequently, stability analysis is performed on the robot. The static analysis explored conditions that can make the climbing robot stable, the dynamic analysis obtained the minimum driving torque and finally, verified the stability of the robot through experiments. After that, by changing the material and thickness of the main framework for deformation simulation analysis, the optimal parameters to optimize the design of the main framework are found. Finally, the three factors affecting the cleaning effect of the robot are discussed by the response surface method, and single factor analysis and response surface regression analysis are carried out, respectively. The mathematical regression model of the three factors is established and the best combination of the three factors is found. The cleaning effect is best when the cleaning disc pressure is 5.101 N, the walking wheel motor speed is 36.93 rad/min, and the cleaning disc motor speed is 38.252 rad/min. The development of this machine can provide equipment support for the cleaning of tunnel retro-reflective rings, reducing the requirement of manpower and material resources.

This paper takes the frame as the research object and explores the vibration characteristics of the frame to address the vibration problem of a 1-MSD straw-crushing and residual film recycling machine in the field operation process, and an accurate identification of the modal parameters of the frame is carried out to solve the resonance problem of the machine, which can achieve cost reduction and increase income to a certain extent. The first six natural frequencies of the frame are extracted by finite element modal identification and modal tests, respectively. The rationality of the modal test results is verified using the comprehensive modal and frequency response confidences. The maximum frequency error of modal frequency results of the two methods is only 6.61%, which provides a theoretical basis for the optimal design of the frame. In order to further analyze the resonance problem of the machine, the external excitation frequency of the machine during normal operation in the field is solved and compared with the first six natural frequencies of the frame. The results show that the first natural frequency of the frame (18.89 Hz) is close to the external excitation generated by the stripping roller (16.67 Hz). The first natural frequency and the volume of the frame are set as the optimization objectives, and the optimal optimization scheme is obtained by using the Optistruct solver, sensitivity method, and grey correlation method. The results indicate the first-order natural frequency of the optimized frame is 21.89 Hz, an increase of 15.882%, which is much higher than the excitation frequency of 16.67 Hz, and resonance can be avoided. The corresponding frame volume is 9.975 × 107 mm3, and the volume reduction is 3.46%; the optimized frame has good dynamic performance, which avoids the resonance of the machine and conforms to the lightweight design criteria of agricultural machinery structures. The research results can provide some theoretical reference for this kind of machine in solving the resonance problem and carrying out related vibration characteristics research.

In response to the lack of accurate and reliable parameters in the discrete element simulation analysis of the sugarcane leaf crushing and return device, in this work, the actual and simulated errors of two stacking angles α and β of sugarcane leaves were used as indicators to calibrate the discrete element parameters. The second-order regression models between the important parameters and the indicators were obtained by Plackett-Burman test, steepest climb test, and Box-Behnken optimization test, and the analysis of variance and interaction factors were performed. The response surface method and particle swarm optimization algorithm were used to find the best significance parameters, and the best combination of significance parameters was obtained: the static friction coefficient between sugarcane leaves was 0.306, the rolling friction coefficient between sugarcane leaves was 0.198, and the recovery coefficient of sugarcane leaf-plate collision was 0.102. The relative errors of the simulation results and the physical test stacking angle α and stacking angle β were 0.609% and 1.643%, respectively. The calibration parameters can provide a theoretical reference for the design and research of sugarcane leaf crushing and returning machines, as well as the calibration of discrete element model parameters for leaf crops with high water content.