Response Surface Analysis Research Articles

Personality trait similarity in recently cohabiting couples: Partner choice, convergence, or selective breakup?

Romantic partners tend to be more similar in self-reported personality traits than would be expected by chance. This similarity can be due to the choice of a similar partner, partners becoming more similar to each other over time, or dissimilar couples breaking up. To examine whether these processes (choice, convergence, or breakup) explain personality trait similarities in couples, we followed a sample of 1,180 German couples (N = 2,360 individuals; age range = 17-82 years old) from right after moving in together (ranging from 0 to 4 years after) up to 16 years thereafter. Using bivariate latent growth curve models, we found that couples were already similar in openness, conscientiousness, extraversion, and agreeableness in the first years of moving in together. Although couples showed correlated change in conscientiousness, this did not increase similarity. Response surface analyses showed that separation risk was generally unrelated to dissimilarity. Furthermore, romantic partners did not become more dissimilar in the years before separation. Taken together, these results suggest that personality similarity in cohabiting couples is fully driven by choosing a similar partner. We discuss the implications of these findings for theory and research on personality similarity in romantic relationships. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Precision and uncertainty in natural gas calorific value estimation: advanced combinatorial predictive models for complex pipeline systems

Abstract In recent years, natural gas pipelines have been characterized by multiple intake points, the mixing of different gas sources, and significant variations in gas quality. The existing volumetric measurement system is no longer suitable for the development and operation of natural gas pipelines in China. To ensure accurate and equitable implementation of natural gas measurement, there is a gradual shift towards energy measurement. However, due to numerous measurement interfaces, installing chromatographs at all measurement stations would lead to substantial investment costs. Therefore, predicting the calorific value of natural gas is a key technology for energy measurement. In view of the issues existing in the current methods of obtaining natural gas calorific value, different prediction models of natural gas calorific value are constructed. According to the influencing factors of natural gas calorific value, the uncertainty evaluation is carried out, and the accuracy of different calorific value prediction models is analyzed by case data. The maximum error of regression equation (RE), response surface analysis (RSA), BP neural network and genetic algorithm (GA) prediction model is 2.29%, 0.43%, 0.59% and 0.45% respectively. However, the combined calorific value (CCV)prediction model is 0.41%. The results indicate that the predicted value calculated by the CCV prediction model is closer to the actual value and has higher prediction performance, which provides a new method for the calorific value prediction and measurement management of natural gas.

Optimization of Operating Parameters for Straw Returning Machine Based on Vibration Characteristic Analysis

For the mechanized technical mode of total wheat straw returning to field, there are problems such as large vibration during the operation of the straw returning machine that, in turn, affect the effect of stubble breaking. This study took the Tongtian 1-JHY-220 straw returning machine as the research object to conduct field experiments, with wheat stubble height, forward velocity, and PTO speed as experimental parameters. And the vibration characteristics at different positions of the machine and the final stubble breaking rate were used as evaluation indicators. Combined with the orthogonal experiment and response surface analysis method, this article analyzes and discusses the influence of various parameters on vibration characteristics and operational effectiveness. The results show that PTO speed and wheat stubble height were the main factors affecting the vibration and operation quality of the straw returning machine. Low PTO speed and high stubble height can improve the stubble breaking rate of the straw returning machine and reduce its operation vibration. Furthermore, the multi-objective optimization results show that when the forward velocity in the range of 8.5–9 km/h, the PTO speed is 540 r/min, and the stubble height is in the range of 200–250 mm, the stubble breaking rate of the straw returning machine is greater than 86%. At this time, the total vibration of the straw returning machine and tractor rear axle is relatively small. This study can lay a foundation for further studying the impact of the vibration of the straw returning machine on the stubble breaking effect and provide a reference for the preparation of high-quality seedbed under conservation tillage.

Effect of healthy dietary intention-behavior (in)consistency on depression and anxiety in the process of behavior change.

Although an increasing number of people are now committed to pursuing a healthy diet, it remains unclear how mental health changes during this process. The present study aimed to examine the combined effect of healthy dietary intention and behavior on depression and anxiety across two sub-studies. This study consisted of two parts: a cross-sectional survey (Study 1) involving 1,433 college students and an 11-day daily diary study (Study 2) with 117 college students. Polynomial regression and response surface analysis indicated that in cases of congruence, individuals' intention and behavior align at a high level and were associated with lower levels of depression and anxiety in the motivational phase but were not found similar association in the volitional phase. In cases of incongruence, individuals with high intention-low behavior tend to experience lower levels of depression and anxiety in the motivational phase. However, individuals with high intention-low behavior tend to experience higherlevels of depression and anxiety in the volitional phase. These findings not only enrich the current understanding of diet and health but also contribute to the development of holistic strategies for promoting a healthy diet.

Ultrasonic-Assisted Marine Antifouling Strategy on Gel-like Epoxy Primer

Ultrasonic technology has drawn extensive interests for its great potential in marine antifouling applications. However, its effects on the adhesion behavior of marine fouling organisms on marine structures remain underexplored. This work investigated how ultrasonic treatment impacted the adhesion of Pseudoalteromonas on a gel-like marine epoxy primer. And the process parameters for ultrasonic treatment were optimized using response surface analysis with Design-Expert software 11. The results revealed that ultrasonic treatment disrupted the cellular structure of Pseudoalteromonas, causing the deformation and fragmentation of the cell membrane, leading to bacterial death. Additionally, ultrasonic treatment reduced the particle size and Zeta potential value of Pseudoalteromonas, which disrupted the stability of bacterial suspensions. It also increased the relative surface hydrophobicity of Pseudoalteromonas cells, resulting in a reduction in adhesion to the gel-like marine epoxy primer. This study demonstrated that ultrasonic treatment significantly disturbed the adhesion behavior of microorganisms like Pseudoalteromonas on the gel-like marine epoxy primer, which provided an effective approach for controlling marine biofouling.

How Channel Integration Benefits Manufactures’ Online Market Entry Agility? The Mediating Role of dealers’ Dependency Behavior

ABSTRACT Purpose The effectiveness of channel integration performed by manufacturers in facilitating their online market entry is still an under-researched topic. This study fills the research gap by investigating and comparing the effects of channel integration strategies and their components implemented by manufacturers. Methodology/approach A questionnaire was designed and distributed to purchasing managers in downstream dealers. The survey yielded 2051 valid responses, and data analysis employed hierarchical and polynomial regressions, along with structural equation modeling and response surface analyses. Findings First, dealers’ dependence plays a crucial role in triggering manufacturers’ online market entry. Second, manufacturers’ channel consistency and transparency are more relevant to dealers’ active dependence, while information and interaction integration lead to dealers’ passive dependence. Third, channel ambidexterity is superior to integration ambidexterity in ensuring dealers’ dependence. Originality/value Significant contributions to omnichannel integration research are made by introducing four distinct types of channel integration strategies. Enhancements to the interfirm dependence literature are achieved through a comparative analysis of the effectiveness of channel integration strategies in shaping dealers’ dependency behavior. Implications Manufacturers should carefully evaluate the effectiveness of these strategies, avoiding a blind pursuit of all forms of channel integration ambidexterity. Strategic leverage of channel feature ambidexterity is recommended as a cornerstone for fostering dealers’ dependence and achieving success in online market entry.

How Blockchain-Enabled Drivers Stimulate Consumers’ Organic Food Purchase Intention: An Integrated Framework of Information Systems Success Model Within Stimulus-Organism-Response Theory in the Context of Vietnam

Integrating the Information System Success (ISS) model with the Stimulus-Organism-Response (SOR) paradigm, this study aims to explore how blockchain-enabled stimuli (blockchain-enabled traceability and blockchain-enabled transparency) affect ISS-related organisms (perceived information quality and perceived system quality), which individually, congruently, and incongruently trigger consumers’ behavioral responses (organic food purchase intentions). Using a purposive sampling of 5326 Vietnamese consumers, multiple linear regression and polynomial regression with response surface analysis are employed to examine the hypothesized model. The research indicates that both blockchain-enabled traceability and blockchain-enabled transparency significantly and positively affect perceived information quality and perceived system quality, which both significantly mediate the impacts of blockchain-enabled traceability and blockchain-enabled transparency on organic food purchase intention. The research also finds that higher congruence between perceived information quality and perceived system quality leads to increased organic food purchase intention, while greater disparity between perceived information quality and perceived system quality results in lower organic food purchase intention. This study contributes to the extant literature by integrating the ISS model with the SOR model to provide a comprehensive framework for understanding how blockchain technology affects consumer behavior in the organic food market. It also highlights the crucial role of both information and system quality in leveraging blockchain technology to enhance consumer trust and purchase intentions.

Investigation of Impact Contact Force Testing and Damage Analysis on Potatoes

To investigate the influencing factors and intrinsic relationships between potato impact force and impact damage during potato soil separation, a testing system for potato impact force was established. The impact force test system is composed of a base, a height adjustment device, a simple separation screen, a soil storage tank, an impact force sensor, and so on. By allowing potatoes to fall freely to simulate the collision process, impact force data are collected, and a high-speed camera is used to locate the impact position and analyze the degree of damage. Through the response surface analysis method, the influencing factors and laws of the impact force and impact damage during the collision process between potatoes and rods under soil and no-soil conditions were studied. The results of the response surface analysis indicate that when the screen inclination is within the range of 14.12° to 14.77°, falling height ranges from 453.83 mm to 500 mm, screen rod spacing falls within 36.50 mm to 40 mm, and the screen rod material is rubber. Potatoes can still be at a relatively low damage level when enduring a large impact force. This study has significant implications for reducing potato impact damage during harvesting, enhancing economic benefits in the potato industry, and advancing the technical level of potato harvesting equipment. In the future, based on the results of this study, further exploration can be made to optimize the design of potato harvesting equipment so as to better reduce the damage to potatoes during harvesting and subsequent processing processes and promote the sustainable development of the potato industry.

MULTIPARAMETRIC SIMULATION OPTIMIZATION OF AN IMPROVED SMALL HOLDING SOAP STAMPING-TABLETING MACHINE

The performance of a Soap Stamping-Tableting was quantified and optimized in this study to response surface methodology. The operational parameters evaluated were conveying speed, stamping and tableting speed, and time of operation while the tableting efficiency, throughput and specific energy consumption of the machine constitutes the responses variables. Response surface analysis was employed and the initial linear models developed augmented to quadratic models when it was established using the analysis of variance (ANOVA) and residual plots to estimate the performance of the soap stamping and tableting machine. The developed quadratic models were used to optimize the performance of the soap stamping and tableting machine using the D-optimality approach to establish the optimal factor settings of the soap stamping and tableting machine rounding up to the nearest whole number values are 351rpm, 21rpm, 55 minutes and an overall D-optimality value of 96 for the conveying speed, stamping and tableting speed and time of operation respectively. This soap stamping and tableting machine plays a crucial role in poverty alleviation and enhancing food security, directly contributing to Sustainable Development Goal (SDG) number 1: Zero Hunger. By efficiently manufacturing and packaging soap, this machine enables the creation of small-scale soap businesses, providing income-generating opportunities for individuals in impoverished communities. The resulting economic empowerment helps lift people out of poverty, addressing the root causes of hunger. Additionally, improved hygiene through widespread access to affordable soap contributes to better health outcomes, further supporting the overarching goal of eradicating hunger and promoting sustainable development.

Whiteness, redness, blueness and greenness profile assessment and design of experiments approach to microwave-aided sensitive and green spectrofluorophotometric determination of baclofen.

As a gamma amino butyric acid-ergic agonist, Baclofen is often prescribed to adults and children for the treatment of severe spasticity that originates in the brain or spinal cord. Even after reviewing the literature extensively, no one has documented a method for estimating baclofen using microwave-assisted stability-indicating spectrofluorimetric techniques, despite the abundance of options for baclofen stability, assay, and bioanalysis. Organic solvents, which are typically necessary for current procedures but may be costly and toxic, have a severe effect on aquatic life and the environment. Using green solvents and 4-chloro-7-nitrobezofuran as a fluorescent probe, this work conducted a stability-indicating spectrofluorimetric estimate of baclofen. Through the use of a design-of-experiments technique, a reliable microwave-aided spectrofluorimetric method was developed, with little solvent consumption and time for sample analysis. Prior to conducting response surface analysis and optimizing important variables and responses, a fractional factorial design was used to screen method variables and responses. A central composite design was then employed for these purposes. This flexible spectrofluorimetric technique was used to assess baclofen concentrations in forced degraded samples and marketed formulations. For baclofen determination, the suggested spectrofluorimetric approach was found to be green, quick, easy to use, economical, and user-friendly.

Caprock sealing integrity and key indicators of CO2 geological storage considering the effect of hydraulic-mechanical coupling: X field in the Bohai Bay Basin, China

Caprock sealing efficiency is an essential guarantee for the long-term safety and stability of CO2 geological storage (CCS). However, the uncertainty in the physical and mechanical properties of deep formations poses challenges to accurately predict the risks of CO2 leakage resulting in CO2 breakthrough or caprock fracture. This study aims to address the issue of imperfect key indicators for caprock sealing by focusing on the CCS project in the Bohai Bay Basin, China. A hydraulic-mechanical (HM) coupling program without considering multiphase flow and the chemical reactions is secondary developed based on the finite element software ABAQUS. Furthermore, a three-dimensional finite element numerical model is established for the analysis of HM coupling, with pore pressure increment (∆PP), Coulomb failure stress (∆CFS) and displacement (U) as evaluation criteria. The Tornado analysis and response surface analysis are employed to analyze the impact of 17 indicators on the caprock sealing, including caprock thickness, burial depth, reservoir and caprock permeability parameters, and mechanical parameters. Subsequently, key performance indicators for caprock sealing are determined. The research results indicate that the reservoir permeability, injection rate, caprock permeability, caprock Young's modulus, caprock internal friction angle, caprock Poisson's ratio, and caprock burial depth are key indicators of caprock sealing capability. The reservoir permeability has a greater impact sensitivity compared to the caprock permeability. Pore pressure and displacement increase with increasing in reservoir permeability. The caprock's resistance to deformation and fracturing increases with increasing in Young's modulus and Poisson's ratio of caprock. This study provides valuable insights for evaluating caprock sealing during CO2 storage in saline aquifers.

Numerical Simulation and Response Surface Analysis of Esterification of Monobutyl Chlorophosphate with n-Butanol in a Microchannel Reactor

Microreactors are essential for microchemical reactions owing to their high mass transfer efficiency, precise control of reaction time, easy amplification, and good safety performance. These characteristics provide several advantages, including shortened reaction times and enhanced chemical reaction conversion rates, rendering microreactors particularly significant in chemical production. In this study, a finite-rate model was developed for the esterification of monobutyl chlorophosphate (MCP) and n-butanol in a microchannel reactor. This study investigates the impact of the microchannel’s length-to-diameter ratio, the mass ratio of n-butanol to MCP at the inlet, and the inlet flow ratio on the entire reaction system through numerical simulations. The findings indicate that increasing the length-to-diameter ratio and reducing the inlet flow rate effectively prolongs the residence time of materials in the microreactor, thereby enhancing the conversion rate of the reactants. Optimal results are achieved with a moderate n-butanol/MCP mass ratio, which facilitates MCP transformation. Moreover, this study employs response surface analysis to investigate the influence of independent factors, such as the microchannel’s length-to-diameter ratio, component ratio, and inlet velocity ratio, on MCP conversion rates. A prediction formula with conversion rate as the dependent variable and microchannel length-to-diameter ratio, component ratio, and inlet velocity ratio as independent variables was established.

How Empowerment Congruence Impacts Performance in Cross-Functional Project Teams: A Polynomial Regression Analysis

This study deduces the empowerment alignment in project governance through examining the roles of (in)congruence between empowering leadership and psychological empowerment in informal leadership emergence, creativity, and performance outcomes. Using the data from 210 members from 69 cross-functional project teams, the results of polynomial regression and response surface analyses indicate that the high congruence between empowering leadership and perceived empowerment enhances informal leadership emergence, then promotes creativity to facilitate performance outcomes eventually. Informal leadership emerged under the insufficient empowerment condition with higher psychological empowerment rather than the excessive empowerment condition with higher empowering leadership. The study added to the project governance body of knowledge by confirming the promoting mechanism for project performance from the congruence perspective of leader-given and subordinate-perceived empowerment.

Self-Degradable Rubber Plug for Temporary Plugging and Its Degradation Mechanism.

A self-degradable rubber plug (SDRP) was developed to address issues in existing crosslinked polymer temporary plugging technology, such as poor self-degradation properties. The synthesis formula was optimized using response surface analysis, resulting in an optimized composition of the SDRP: 13 wt% monomer, 0.02 wt% initiator, 0.7 wt% crosslinker, and 1.8 wt% degradation catalyst. Under the condition of 70-120 °C, the SDRP was transformed from a liquid to a solid gel in 30-110 min; the degradation time was 3-10 days, and the viscosity of the completely degraded solution was lower than 20 mPa·s. At an injection volume of 1 PV SDPR, a breakthrough pressure of 8.34 MPa was achieved. The hydrolysis of the unstable crosslinker was found to have caused the breakage of the SDRP. Over time, the functional groups within the unstable crosslinker underwent hydrolysis due to the combined effects of temperature and the degradation catalyst. This process led to the disruption of crosslinking points, resulting in a gradual deterioration of the network structure. As a consequence, some immobile water was converted into free water. The mobility of water molecules increased until the plug was completely degraded into a viscous liquid. This study enriches the temporary plugging gel system.

Effects of Barrel Temperature, Screw Speed and Feed Moisture Content on the Organoleptic Properties of Aerial Yam-Soybean Flour Extruded Snacks

The effects of barrel temperature, screw speed and feed moisture content, as extrusion process parameters, on the organoleptic properties of aerial yam-soybean flour extruded snacks were investigated, using Response Surface Analysis. The extruded snacks were produced using a Laboratory scale single-screw food extruder. Results of the determination of organoleptic properties of the extruded snacks showed that: texture; taste; colour; and aroma ranged from 4.38 to 6.02; 4.68 to 6.78; 4.58 to 6.97; and 4.45 to 7.00, respectively. Response surface Analysis indicated that barrel temperature and screw speed had significant effect (p < 0.05) on texture, while feed moisture had no significant effect (p > 0.05) on the texture of the snacks. All the extrusion parameters had significant effect (p < 0.05) on the taste of the snacks. Barrel temperature and feed moisture had significant effect (p < 0.05) on colour, while screw speed showed non-significant effect (p > 0.05) on the colour of the snacks. Barrel temperature had significant effect (p < 0.05) on aroma, while screw speed and feed moisture had no significant effect (p > 0.05) on the aroma of the snacks. The results obtained for the organoleptic properties of the snacks can attest to the fact that it is possible to obtain expanded or ready-to-eat (RTE) products from aerial yam-soybean flour blends by extrusion processing technology, that possess desirable organoleptic properties.

Efficiency-centered vs novelty-centered: unpacking the impact of business model design on services in manufacturing firms

PurposeHow does business model design play a role in enabling manufacturing firms’ services? This study aims to investigate the impact of two distinct types of business model design, namely, efficiency-centered business model design (EBMD) and novelty-centered business model design (NBMD), and their effects in balanced and imbalanced configurations, on two types of services: product- and customer-oriented services.Design/methodology/approachUsing matched survey data of 390 top managers and objective performance data of 195 Chinese manufacturing firms, this study uses hierarchical regression, polynomial regression and response surface analysis to test the hypotheses.FindingsThe results show that while EBMD positively affects product-oriented services, NBMD positively affects customer-oriented services. Both types of services exert a significant influence on firm performance. Furthermore, the degree of product- and customer-oriented services increases with an increasing effort level with a balance between EBMD and NBMD. Asymmetrical, imbalanced configuration effects reveal that the degree of product-oriented services is higher when the EBMD effort exceeds the NBMD effort, and the degree of customer-oriented services is higher when the NBMD effort exceeds the EBMD effort.Originality/valueThis study enriches the understanding of designing business models to facilitate service growth in manufacturing firms, ultimately benefiting firm performance. In addition, exploring balanced and imbalanced configurations of EBMD and NBMD offers new insights into business model dual design research.

The interplay between autonomy support and structure in the prediction of challenge-seeking, novelty avoidance, and procrastination

Although teachers’ autonomy support and structure are considered essential elements of the classroom environment to promote effective learning strategies, prior research has sometimes provided conflicting results. This inconsistency may stem from how autonomy support and structure relate to some outcomes but not others. Alternatively, this variability might be attributed to nonlinear relations, which have been scarcely tested thus far. In this cross-sectional study, we revisited this issue by examining both the linear and curvilinear relations of autonomy support and structure to challenge-seeking, novelty avoidance, and procrastination. Participants were 3,271 adolescents (M age = 15.91, SD = 0.34 years; 59.8% females) from 116 classrooms. Multilevel polynomial regression analyses revealed that, compared to structure, autonomy support was a more reliable predictor of challenge-seeking, both at the student and the classroom levels. In contrast, structure predicted novelty avoidance and procrastination more reliably at both levels than autonomy support. Response surface analyses indicated that the most desired pattern existed at the line of congruence. Our findings suggest that both autonomy support and structure are needed to enhance students’ learning strategies. However, the degree of necessity may vary for specific outcomes, with one potentially being more crucial than the other.

Design and Experimentation of Small Potato Harvester for Heavy Soil in Hilly and Mountainous Areas

At present, the potato’s mechanized harvesting rate in hilly and mountainous areas is very low. The reasons for this are that in heavy soil, the separation of potato rhizomes from soil or vines is not sufficient, harvesting machinery is seriously damaged by the potato epidermis, and the harvested potato is easily buried in soil, resulting in a missed harvest. In this paper, a two-stage cleaning potato harvester with wave-type and roller-group-type separating mechanisms was designed, and its overall structure and working principle are introduced in detail. The new cleaning mechanism can increase the effective separating length and effective contact area of the potato–soil mixture so as to achieve the purpose of removing clay and heavy soil. The main separator uses a structure that combines offset waves with opposite waves and a staggered arrangement of large–small diameter straight bars. The secondary separator adopts a device combining left-hand and right-hand separating rollers. The discrete element model of the whole machine was established, and the results of the theoretical analysis were verified by simulation. The key factors affecting the harvest quality were analyzed by variance analysis and response surface analysis, and the field experiment was carried out with the rate of clean potatoes, damaged potatoes, and peeled potatoes harvested as the indexes. The field experiments showed that the machine achieved a rate of photos on or out of the earth of 98.87%, a damaged potato rate of 0.91%, and a peeled potato rate of 1.13%. The research results provide theoretical support and a technical reference for the design and optimization of potato harvesters, as well as the improvement of the potato–soil separating efficiency and harvest quality.

Particle Size Effect on Anaerobic Digestion of Fruit and Vegetable Waste

During the anaerobic digestion (AD) of fruit and vegetable waste (FVW), excessive particle size reduction can lead to the overproduction and inhibition of methanogenic microorganisms. This paper presents an in-depth analysis through experimental assays, modeling, and response surface analysis of the effect of particle size on methane production. A simple model was proposed considering the inhibition of the growth of methanogenic microorganisms and surface-based hydrolysis kinetics. The model parameters were estimated using experimental data from batch systems fed with FVW of varying particle sizes (ranging from 1.8 to 1000 μm). Response surface methodology establishes a statistical model for estimating methane production based on particle size and concentration. Numerical and statistical analyses were conducted using Matlab R2024a and Minitab 24 software. A model with an R2 of 0.89 was obtained, which determined an optimal concentration of 8.2 kg·m−3 and a particle size of 742.3 μm, yielding a methane production of 303.3 m3·kg−1 VS, similar to the experimentally obtained range of 300.95 to 316.7 m3·kg−1 VS.

Dynamic gas emission during coal seam drilling under the thermo-hydro-mechanical coupling effect: A theoretical model and numerical simulations

The potential risk of coal and gas outbursts has increased with the depth of coal mining, posing the threat of heavy casualties, vast economic losses, and harm to the ecological environment. Considering the limitations of existing coal and gas outburst prediction methods, novel indicators or methods are needed. In this study, a fully coupled dynamic drilling gas emission THM model of gas diffusion, seepage, and flow is established, and the reliability of the model was verified by the measured data. The validated model was applied to single-factor and multi-factor impact analysis of dynamic drilling gas emission. The simulation results showed that (1) During the drilling process, the increase in permeability is mainly attributed to the coal seam damage and disturbance caused by the borehole and the coupling effects of the THM model, which increase the porosity around the borehole. Driven by the pressure gradient and temperature gradient, the gas pressure and temperature of the coal seam around the borehole show a conical distribution. (2) In the single-factor analysis, increasing the values of coal seam parameters (initial gas pressure, initial permeability, and initial coal temperature) and drilling parameters (borehole radius) will promote gas emissions in the drilling process to different degrees. The most significant promoting effect is the initial permeability, and the weakest is the initial coal temperature. (3) The response surface analysis results of the four factors show that the interaction between initial coal temperature C and borehole radius D is the least significant, and the interaction between initial gas pressure A and initial permeability B is the most significant. Meanwhile, the established multiple regression model characterizes the relationship between borehole gas emissions and initial coal seam gas pressure, and the idea of using drilling gas emission volume to predict coal and gas outbursts was proposed.