Response Surface Analysis Research Articles

Response Surface Methodology to Explore the Influence Mechanism of Fiber Diameter in a New Multi-Needle Electrospinning Spinneret.

Multi-needle electrospinning is an efficient method for producing nanofiber membranes. However, fluctuations in the fluid flow rate during the process affect membrane quality and cause instability, an issue that remains unresolved. To address this, a multi-stage flow runner spinneret needs to be developed for large-scale nanofiber membrane production. This paper uses COMSOL finite element software to simulate polymer flow in the spinneret runner. From this, the velocity field distribution and velocity instability coefficient were obtained, providing theoretical guidance for optimal spinneret design. In addition, response surface analysis (RSM) was used to experimentally explore the process parameters, and then residual probability plots were used for reliability verification to evaluate the effect of each process parameter on fiber diameter. These process parameters can guide the controlled production of nanofibers during multi-needle electrospinning.

Achieving partial nitrification by sludge treatment using sulfide: Optimal conditions determination, long-term stability evaluation and microbial mechanism exploration

This study proposes an innovative strategy for achieving PN in synthetic domestic wastewater by side-stream sludge treatment using sulfide as the sole control factor. By conducting controllable batch experiments and response surface analysis, optimal sulfide treatment conditions were firstly determined as 90 mg/L of sulfide, 7.5 of pH, 100 rpm of rotation and 12 h of treatment time. After treatment, half of ammonia oxidizing bacteria (AOB) activity remained, but nitrite oxidizing bacteria (NOB) activity was barely detected. Nitrite accumulation rate of long-term running PN steadily reached 83.9 % with 99.1 % of ammonia removal efficiency. Sulfide treatment increased community diversity and facilitated stability of microbiota functioning with PN phenotype, which might be sustained by the positive correlation between ammonia oxidation gene (amoA) and sulfur oxidation gene (soxB). Correspondingly, the network analysis identified the keystone microbial taxa of persistent PN microbiota as Nitrosomonas, Thauera, Truepera, Defluviimonas and Sulitalea in the later stage of long-term reactor.

Integrated torque sensors for humanoid robot joints

Abstract Torque sensors are becoming increasingly important in the joints of humanoid robots, serving as an indispensable part of the joint system. This paper designs a strain-based torque sensor integrated into the output flange of a cycloidal reducer. Through mechanical analysis, the relationship between strain and torque is derived. Then, through model simulation analysis, the optimal placement for the strain gauge is determined. A combination of experimental design and response surface analysis is used to optimize the structure’s parameters. Finally, finite element simulation is conducted using ANSYS to obtain the optimized performance parameters. Subsequent steps include the static calibration of the integrated sensor. Based on the measured data points, a linear relationship between the sensor’s output signal and torque is established.

Moderation in Response Surface Analysis: Current Shortcomings, Recommendations, and Software

Moderation in Response Surface Analysis: Current Shortcomings, Recommendations, and Software

Response Surface Analysis on Multiple Parameter Effects on Borehole Gas Extraction Efficiency

Response Surface Analysis on Multiple Parameter Effects on Borehole Gas Extraction Efficiency

Manager-Team (Dis)agreement on Stress-Preventive Behaviours: Relationship with Psychosocial Work Environment and Employees' Well-Being.

The "Management Competencies to Prevent and Reduce Stress at Work" (MCPARS) approach focuses on identifying the stress-preventive managers' competencies able to optimise the employees' well-being through the management of the psychosocial work environment. Considering leadership as contextualised in complex social dynamics, the self-other agreement (SOA) investigation of the MCPARS may enhance previous findings, as it allows for exploring the manager-team perceptions' (dis)agreement and its potential implications. However, no studies have tested the MCPARS using the SOA and multisource data. Grounded in Yammarino and Atwater's SOA reference theory, we conducted an in-depth investigation on the MCPARS's theoretical framework by examining the implications of manager-team (dis)agreement, regarding managers' competencies, on employees' psychosocial environment (H1-H2) and affective well-being (H3). Data from 36 managers and 475 employees were analysed by performing several polynomial regressions, response surface, and mediation analyses. The results reveal a significant relationship between SOA on MCPARS and employees' perceptions of the psychosocial environment (H1). Employees report better perceptions when supervised by in-agreement good or under-estimator managers, while lower ratings occur under over-estimator or in-agreement poor managers (H2). Moreover, the psychosocial environment significantly mediated the relationship between SOA on MCPARS and employees' well-being (H3). The MCPARS theoretical model's soundness is supported, and its implications are discussed.

Design, modeling, and experiment of a multi-degree-of-freedom pneumatic soft bionic actuator

Drawing on the driving mechanism of biological muscles and combining the nonlinear hyperelastic characteristics of silicone rubber, a multi-degree-of-freedom pneumatic soft bionic actuator is designed, which can be used as the executing mechanism for soft robots and robotic arms. Using response surface analysis and numerical simulation algorithms, the optimal combination of structural dimensions parameters is determined with the maximum bending and torsion angles output by the actuator as the optimization objectives. Based on the idea of flexible mechanism Piecewise Constant Curvature (PCC) modeling, the kinematics equation of the actuator is derived. Analyze the equivalent motion structure of the actuator and establish a dynamic model of the actuator based on the Lagrange method. The physical model of the actuator is manufactured using rapid prototyping technology. Finally, experimental testing and analysis are conducted on the physical model to obtain the motion and dynamic characteristics curves and empirical formulas of the actuator, which are compared with theoretical and simulation results to verify that the pneumatic soft bionic actuator is feasible and effective. The above research methods, processes, and results can provide reference and inspiration for the research and implementation of pneumatic and hydraulic soft robots and gripping actuators for soft robotic arms.

Research on the Performance and Computational Fluid Dynamics Numerical Simulation of Plate Air Gap Membrane Distillation Module.

Membrane distillation (MD) is widely used in the field of seawater desalination. Among its various sub-categories, air gap membrane distillation (AGMD) stands out due to its high thermal efficiency and compatibility with low-grade heat sources. This study delves into the impact of varying operating conditions on AGMD performance, employing numerical simulations which are grounded in experimental validation. The objective was to enhance the performance of AGMD, mitigate polarization phenomena, and provide a reference for optimizing membrane component design. The results show that the agreements between the simulated and the experimental values were high. When increasing the feed temperature and decreasing the coolant temperature, the impact of polarization phenomena on the performance of AGMD was reduced. The mass flux, Total Permeate Concentration (TPC), and heat flux increased by 81.69%, 36.89%, and 118.01%, respectively, when the feed temperature was increased from 50 °C to 75 °C. When the coolant temperature decreased from 22 °C to 7 °C, the mass flux increased by 37.06%. The response surface analysis revealed that the feed temperature has significant influence on AGMD performance, and there is a noticeable interaction between the feed temperature and coolant temperature. These findings will play key roles in practical applications.

Innovative plasma treatment of orange juice to improve bioactive concentration: The effects of various parameters using response surface analysis.

Orange juice is a highly nutritious beverage. Traditional pasteurization methods cause nutrient loss and taste changes. Plasma treatment (PT) is an emerging method with a high sterilization rate. This study investigated the effects of corona discharge plasma on the sterilization of orange juice by changes in color difference, total phenol content, and pH value. Single-factor experiments revealed that higher voltage (40kV) and longer sterilization time (25min) had better sterilization effects. Response surface analysis indicated that frequency had the greatest impact on sterilization rates, and the optimal sterilization conditions were a voltage of 44.75kV, a frequency of 9.46kHz, and a sterilization time of 25min. Under these conditions, the sterilization rate reached 97.9%, meeting the national standard of 104 colony-forming units/mL (GB7101-2022). Compared to untreated juices, the color difference value was 16.32, the pH value decreased by 0.12, and the total phenol content increased by 0.669mg/mL. However, the evaporation of water plays an important role in increasing the total phenol co. Moreover, the comparative analysis showed that PT was comparable to pasteurization in terms of sterilization effects, flavor preservation, and the concentration of bioactive components. This study provides a theoretical basis for industrial applications of PT.

The effect of leader-team (in-)congruence in future orientation on leader’s participative leadership: the moderating role of leader workload

Purpose Prior studies have consistently treated participative leadership as a given leadership style. Conversely, this study aims to prove that participative leadership can be predicted by leaders and teams collectively, depending on leaders' work characteristics (i.e. workload). Design/methodology/approach A two-source survey was designed to collect data from a sample of 89 leader-team dyads in a trading company in a southeastern Chinese city. Polynomial regression and response surface analysis were used to test the hypotheses. Findings The leader showed more participative leadership when leader-team future orientation was congruent rather than incongruent; in the congruent situation, there was an inverted U-shaped relationship between leader-team future orientation congruence and participative leadership; in the incongruent situation, when the team's future orientation gradually exceeded the leader's, participative leadership first increased and then decreased; and leader workload positively moderated the relationship between leader-team future orientation congruence and participative leadership. Originality/value These findings theoretically respond to the call for investigating the influence of leader-team future orientation congruence on leaders’ behaviors, and in practice enlighten managers on how to encourage supervisors to involve employees in decision-making processes.

Tribo-informatics analysis of in-situ TiC reinforced ZA27 alloy: Microstructural insights and wear performance modeling by machine learning

The study examines the performance of ZA27 alloy reinforced with in-situ TiC under high-stress abrasive wear conditions. The ZA27 + 10 wt% TiC composite demonstrates superior wear resistance among all the materials tested. Response surface analysis revealed that increasing the applied load reduces the wear resistance of the specimens. Analysis of worn-out surfaces revealed mild grooves at low loads and deeper grooves at higher loads. The removal of material is mainly caused by ploughing and cutting actions from abrasive surfaces. Machine Learning models were employed to forecast wear rate, coefficient of friction, and temperature. The MLP model excelled, achieving an R² value of 0.88 during testing. Furthermore, feature importance analysis revealed that reinforcement wt% has the maximum influence in predicting the wear rate.

The Roles of Proactive Personality and Career Satisfaction in the Impact of Employer Brand Attributes Congruence on Creativity.

Although the relationship between employer brand and employee creativity has become a popular theme, this nexus is indirect and ambiguous. Additionally, most studies ignore the consistency of instrumental and symbolic attributes when discussing the consequences of employer brand. This study explored the mechanism of employer brand attributes congruence on employee creativity through career satisfaction, and further revealed the moderating role of proactive personality. Based on the cue consistency theory and the social information processing theory, a polynomial regression model was created and a response surface analysis was conducted using 488 paired questionnaires. The results showed that employer brand attributes congruence impacted employee creativity via career satisfaction. A consistent employer brand strategy is more effective for the creativity of less proactive individuals, while a high-level proactive personality can compensate for the deficiencies of employer brand attributes incongruence. The results complemented employer brand research from the perspective of the instrumental-symbolic attribute configuration and provided supportive empirical evidence of employer brand practices aiming at improving employee creativity. This study has certain practical implications for HR practitioners.

Optimizing the extraction process of total saponins from Panax vietnamensis based on response surface analysis and backpropagation neural network-genetic algorithm

Panax vietnamensis (PV), a member of the Araliaceae family, is noted for its saponin-rich roots and rhizomes. Recent pharmacological studies have shown its anti-inflammatory, anti-cancer, anti-myocardial ischemia, and hypoglycemic effects, establishing PV as a highly valuable variety of ginseng worldwide. Herein, we used an ultrasound-assisted method to optimize the extraction of total saponins from PV, and developed a genetic algorithm (GA) to optimize the backpropagation (BP) neural network model and predict the best process conditions. The best process with an ethanol concentration of 65.8 %, extraction times of 4.0, ultrasonic temperature of 40.7°C, and an extraction rate of 4.4103 % was achieved through response surface optimization. Conversely, the best process optimized by the GA-BP neural network model had an ethanol concentration of 70.0 %, extraction times of 4.0, ultrasonic temperature of 41.0°C, and an extraction rate of 4.5492 %. Moreover, 254 terpenoids, consisting of 182 triterpenes, 33 monoterpenes, 19 sesquiterpenes, and 20 diterpenes, along with various types of saponins, were identified through ultra-high performance liquid chromatography-MS/MS (UPLC-MS/MS). Specifically, 87 dammarane-type saponins were detected, including 46 protopanaxadiol types, 41 protopanaxatriol types, 5 octilonol types, and 18 oleanolic acid types. The total saponin extraction rate achieved through the GA-BP neural network model surpassed that of the response surface optimization process, indicating the superiority and stability of the GA-BP neural network optimized process and thus revealing the optimal method for PV total saponin extraction. The comprehensive analysis of PV saponins using UPLC-MS/MS enhanced our understanding of total saponins in PV, laying the foundations for the strategic development and utilization of PV plant resources.

Optimizing Electric Racing Car Performance through Telemetry-Integrated Battery Charging: A Response Surface Analysis Approach

Optimizing Electric Racing Car Performance through Telemetry-Integrated Battery Charging: A Response Surface Analysis Approach

How Parental Mediation and Parental Phubbing Affect Preschool Children's Screen Media Use: A Response Surface Analysis.

Parental mediation (PM) and parental phubbing (PP) are two pivotal factors that influence children's screen media use. This study used response surface analysis to examine the combined effect of PM and PP on screen time among preschool children. A total of 3,445 parents with preschool-aged children participated in this study, providing self-reported data on PM, PP, and their children's screen time (CST). The results revealed that CST decreased when parents enhanced their mediation behaviors and reduced phubbing behaviors in the cases of congruence between PM and PP. In instances of incongruence, reduced screen time was observed when parents exhibited lower frequency in mediating their CST and displayed fewer phubbing behaviors compared with situations where parents mediated their children more frequently but engaged in higher levels of phubbing behaviors. The findings suggest that PM play a significant role in mitigating preschool-aged children's excessive screen time. Moreover, it is critical to establish positive role modeling by reducing PP behaviors.

Design and Experimental Study of Banana Bunch Transportation Device with Lifting Mechanism and Automatic Bottom-Fixing Fruit Shaft

In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device’s maximum travel speed and minimizing the banana bunch’s oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption.

Development and Optimization of a Nanocomposite Gel Foam for Inhibiting Coal Spontaneous Combustion

ABSTRACT A nanocomposite gel foam inhibitor was made by grafting tea polyphenol onto sodium polyacrylate through the graft polymerization reaction, which was then combined with graphene oxide and a foaming agent. Response surface analysis was used to optimize the ratio to improve the water absorption of the inhibitor. The microstructure of the inhibitor was studied using X-ray diffraction and Fourier-transform infrared spectroscopy. The anti-spontaneous combustion performance of the nano-composite gel foam was tested through a leakage wind plugging experiment and a thermogravimetric experiment. The results show that the optimal additions of graphene, tea polyphenol, and potassium persulfate were 0.76%, 2.806%, and 0.727% of acrylic acid, respectively. The ultimate pressures of the gel foam before and after fully forming the gel were 0. 26 kPa and 0. 736 kPa, respectively, which satisfies the demand for leakage wind plugging in a coal mine. The critical temperature and dry cracking temperature of the gel foam were 112.4°C and 201.0°C, respectively, and the quality of the oxygen-absorbing and weight-gaining stage were almost unincreased. The gel foam showed good water retention, oxygen barrier, and antioxidant properties and can play a significant role in inhibiting the coal spontaneous combustion.

Integrated Eye-Tracking Response Surface Analysis to Optimize the Design of Garden Landscapes

Gardens not only provide people with a place for leisure and relaxation, they also contribute to improving urban ecological environments and promoting social interactions and cohesion. Additionally, from a psychological perspective, gardens play a role in alleviating stress, enhancing happiness, and improving the quality of life. Current research on gardens has primarily employed methods such as questionnaire surveys, environmental psychology analyses, and eye-tracking analyses; however, comprehensive studies on the relationships between multiple factors and levels in garden designs are lacking. Here, we propose a response surface analysis approach based on eye-tracking technology for the design and optimization of gardens. Firstly, the impacts of different garden elements on visitors’ psychology and fixation counts were analyzed using environmental psychology and eye-tracking analyses. Subsequently, the optimal range of each garden feature was determined through single-factor experiments, followed by response surface analysis to obtain the optimal value for each element. The results revealed that changes in garden elements such as the greenery ratio, number of buildings, and water saturation significantly affected visitors’ psychology. The greenery ratio had a greater impact than the number of buildings, which in turn had a greater impact than water saturation. This study is the first to analyze the relationships between multiple garden elements. A strong relationship was found between the greenery ratio and the number of buildings, as well as between the number of buildings and water saturation, while the relationship between the greenery ratio and water saturation was weaker. This approach can not only optimize garden designs but can also be widely applied in fields such as urban planning and public space transformation to enhance visitors’ comfort and satisfaction with the environment and promote sustainable urban development.

Intuiting or rationalising self-other agreement in leadership?

PurposeCongruent self-other agreement in leadership evaluations is associated with positive outcomes such as work unit performance. In contrast, poor self-other agreement in leadership evaluations is associated with negative outcomes such as leaders making ineffective job-relevant decisions. This study examined whether the extent of leaders’ preference for intuitive and rational thinking predicted self-other agreement in leadership evaluations.Design/methodology/approachSelf-ratings and follower ratings of transformational leadership were analysed for 160 dyad pairs of leaders and followers (n = 320). Leaders self-rated their preference for rational and intuitive thinking. Response surface analysis was used to model the relationship between self-other agreement and leaders’ thinking styles.FindingsAs ratings of transformational leadership increased in both leaders and followers, we observed higher scores on preferences for both rational and intuitive thinking. Leaders’ preference for intuitive thinking showed a curvilinear relationship with self-other agreement, such that more intuitive thinking was related to higher leader–follower congruence in ratings of transformational leadership. We further uncovered that higher leader preferences for rational thinking were related to increased leader–follower disagreement in transformational leadership ratings.Originality/valueResearch has focused more on the outcomes than antecedents of self-other agreement in leadership. Thinking styles have undergone limited examination as antecedents of self-other agreement in leadership evaluations. Thinking styles are semi-malleable traits that can be used for the selection of leadership potential and developed to improve leadership performance. The current research suggests that relationships between thinking styles and self-other agreement on leadership effectiveness are more complicated than first thought.

Design and Simulation of Intra-Row Obstacle Avoidance Shovel-Type Weeding Machine in Orchard

This paper presents the design of an intra-row obstacle avoidance shovel-type weeding machine. Theoretical analysis of intra-row weeding components guided the determination of the structures and parameters for key parts, including the signal acquisition mechanism, automatic obstacle avoidance mechanism, and weeding shovel. Furthermore, a hydraulic system was designed to support these functions. The design aims to optimize intra-row weeding operations, reduce labor costs, enhance weed control effectiveness, and prevent collisions between weeding equipment and grapevines. Through the construction of a mathematical model, the analysis determined the necessary minimum return speed of the hydraulic cylinder for the intra-row weeding shovel to avoid grapevines. We also established a reasonable range for the extension speed of the hydraulic cylinder to minimize areas missed during weeding. Further analysis showed that using the minimum return speed of the hydraulic cylinder effectively reduced missed weeding areas. A virtual prototype model of the weeding machine was created in ADAMS. Using the coverage rate of weeding operation as the evaluation index, single-factor simulation tests determined that the extension speed of the piston rod in the obstacle avoidance hydraulic cylinder and the forward speed of the weeding machine are the main influencing factors. The preset threshold of the control system, which triggered the automatic obstacle avoidance mechanism when the obstacle avoidance rod reached a specific angle (the “Angle Threshold”), was identified as a secondary influencing factor. Other factors were considered irrelevant. Hydraulic cylinder extension speed, weeding machine forward speed, and angle threshold were chosen as the influencing factors. Following the principles of a Box–Behnken experimental design, a quadratic regression combination experiment was designed using a three-factor, three-level response surface analysis method. The evaluation criterion focused on the coverage rate of weeding operation. A regression model was developed to determine the coverage rate of the weeding operation, identifying the optimal parameters as follows: obstacle avoidance hydraulic cylinder extension speed of 120 mm/s, forward speed of the weeding machine at 0.6 m/s, and an angle threshold of 18°. The optimized coverage rate of the weeding operation achieved 86.1%. This study serves as a reference for further optimization of intra-row weeding machines in vineyards and for other crops.