Combination Of Operating Parameters Research Articles

Low-carbon scheduling of electricity consumption in wastewater treatment plant by using photovoltaic system

Sewage treatment as a high energy consumption industry, its electricity consumption accounts for 3 % of the total electricity consumption of society. That means significant greenhouse gas emissions. In the context of China's goal of “reaching carbon peak by 2030 and achieving carbon neutrality by 2060”, reducing the energy consumption of wastewater treatment systems has emerged as an important issue in recent years. In this paper, the GPS-X simulation software was employed to conduct a simulation study of a modified Anoxic-Aerobic-Oxic wastewater treatment plant (WWTP) in Wuhan, and the response surface methodology (RSM) was utilized to ascertain the interactive effects of DO, IRF, ERR, and SD on the effluent quality, thereby identifying the operational parameters that minimize energy consumption while maintaining satisfactory effluent quality. Additionally, the PVsyst software was employed to design the solar power generation system of the WWTP and analyze its power generation potential. On this basis, through the coupling of photovoltaic power, electricity load, time-of-use pricing, and the water quality simulation model, and taking the WWTP data in September as a case study, the electricity usage strategies under various illumination conditions were formulated. The aim is to maximize the use of photovoltaic power to reduce the cost and carbon emissions of the WWTP. The results show that the optimal combination of operational parameters, including an external reflux ratio of 0.3, the internal recycle flow of 50,000 m3/d, and the sludge discharge of 448 m3/d, resulted in a reduction in power of 208.5 kW, and after the combination optimization of operational parameters and electricity utilization, the operation cost of the WWTP in September was reduced by 40 % ∼ 60 %, and the carbon emission attributable to electricity was reduced by 30 % ∼ 50 %.

Eddy currents operation parameters optimization

With the development of non-destructive inspection techniques, more and more challenging situations have arisen and the correct choice of operating parameters can be decisive for a good detection sensitivity. Based on that, an algorithm was developed to obtain the best combination of an eddy current sensor operation parameters. The results obtained demonstrate the improvement in the cracks detection in welded parts after optimization.

Performance Assessment and Optimization of the Ultra-High Speed Air Compressor in Hydrogen Fuel Cell Vehicles

Air compressors in hydrogen fuel cell vehicles play a crucial role in ensuring the stability of the cathode air system. However, they currently face challenges related to low efficiency and poor stability. To address these issues, the experimental setup for the pneumatic performance of air compressors is established. The effects of operational parameters on energy consumption, efficiency, and mass flow rate of the air compressor are revealed based on a Morris global sensitivity analysis. Considering a higher flow rate, larger efficiency, and lower energy consumption simultaneously, the optimal operating combination of the air compressor is determined based on grey relational multi-objective optimization. The optimal combination of operational parameters consisted of a speed of 80,000 rpm, a pressure ratio of 1.8, and an inlet temperature of 18.3 °C. Compared to the average values, the isentropic efficiency achieved a 48.23% increase, and the mass flow rate rose by 78.88% under the optimal operational combination. These findings hold significant value in guiding the efficient and stable operation of air compressors. The comprehensive methodology employed in this study is applicable further to investigate air compressors for hydrogen fuel cell vehicles.

Numerical analyses ridge-forming for whole film-mulching and double ridge-furrow, a discrete element method

The Northwest of China is a typical production mode of rain-fed agriculture, which mostly adopts the whole film-mulching and double ridge–furrow technique to address the difficulty of surface water storage. However, the quality of ridge formation directly affects the water storage on both sides of the ridges, the reliability of plastic film mulching, and the crop growth. This study focused on the process of rotary tillage ridging, took different inclination angles and depths of ridger as variable factors, explored the influence of different operation parameters on the quality of ridge forming. The soil viscoelastic model was established in the study using the discrete element method. The changes in ridger resistance, ridge structure, and soil particle disturbance were analyzed in detailed, respectively. The results indicated that as the inclination angles and depths of ridger increased, the resistance of ridger also increased. The height of the ridges significantly influenced by the inclination angles and depths of ridger, and under the same inclination angles of ridger, the height of the ridges was directly proportional to the depth of ridger. Under different combinations of operational parameters, the height of the small ridges had good agreement with the ridging agronomy. As for the large ridges, when the depth of ridger was 100 mm and the inclination angles were 15°, 30°, and 45°, the working parameters met the agronomic requirements for ridge forming. In terms of soil disturbance, the soil located within a range of 30–90 mm from the surface was most susceptible to disturbance from the rotary tillage and the ridger, and the soil disturbance was stronger in the small ridges compared to the large ridges. The results of study contributed to a deeper understanding of the rotary tillage ridging process and provided insights into the factors influencing the quality of ridge forming.

Optimal ventilation strategy for multi-bed hospital inpatient wards: CFD simulations using a genetic algorithm

Optimising ventilation strategy for an indoor environment necessitates systematically evaluating the influence of a diverse combination of physical and operational parameters in the design space. This study proposes a methodology that couples an evolutionary algorithm (genetic algorithm) with an evaluation mechanism (computational fluid dynamics) to determine the optimal ventilation strategy for an inpatient ward. The traditional approach would exhaustively simulate numerous scenarios to identify the optimal combination of parameters meeting the design objective. The proposed methodology would iteratively evaluate diverse design solutions with fewer CFD simulations than the traditional approach. The results of design space exploration suggest that design parameters, namely, location of the infected patient; air change rate; flow rate through local exhaust grille; and number, location and size of supply air diffuser and local air exhaust grille, are critical in minimising the risk of cross-infection caused through contact transmission in a ward.

Development and Optimization of Operational Parameters for Tractor-Operated Boom Sprayer for Field Crops

Spraying is a crucial practice in agriculture, especially for the application of chemical pesticides that play a vital role in protecting crops. However, there has been a worrisome rise in the annual consumption of pesticides, leading to significant concerns. The excessive use of these pesticides has resulted in substantial wastage, which is a cause for alarm. To address these issues and enhance the efficiency of pesticide application, a tractor-operated boom sprayer was developed to ensure effective spraying. The study focused on evaluating and optimizing three operational factors: spacing between nozzles (30, 40, 50 cm), spray boom height (80, 90, 100 cm), and pressure (17.5, 21.0, 24.5 kg.cm-2). A factorial Completely Randomized Design (CRD) approach was employed, 81 experiments were conducted and data were analyzed statistically by using the SPSS software package to investigate the effect of operational parameters on the performance of the sprayer. The results revealed that the operational parameters were significantly influencing the swath width and percent of overlap during spraying. The optimum combination of operational parameters was obtained using the R-software, the optimum combination for obtaining maximum swath width and minimum overlap is spacing between nozzles at 50 cm, spray boom height at 90 cm, and operating pressure at 24.5 kg.cm-2. The swath width and overlap at optimum combination were 7.77m and 43.12%, respectively. Implementing this optimal combination significantly improved the performance of the spraying activity, ensuring better coverage.

Optimization of Process Parameters for Pellet Production from Corn Stalk Rinds Using Box–Behnken Design

In the current study, corn stalk rinds were used as feedstock for the production of solid-fuel pellets. In an effort to comprehensively analyze the effects of different operational parameters on the physical properties of pellets, response surface methodology (RSM) was employed in conjunction with a Box–Behnken experimental design (BBD). By assessing multiple variables simultaneously and examining their interactions, BBD facilitates the development of a reliable response model that can predict how changes in independent variables will impact response variables. The recorded responses included relaxed density, mechanical durability, and compressive strength. Based on the results, greater R2 values of 0.9467, 0.8669, and 0.9196, could be, respectively, attained for the quadratic regression models. The analysis of variance revealed that all independent variables had significant effects on the responses. The optimal processing condition for the pellets was established by determining the ideal combination of operational parameters. The process entailed the choice of a particle dimension measuring 0.5 mm, a moisture level of 11.35%, the application of heat at 125.7 °C on the die, and the utilization of a molding pressure of 154.2 MPa. Based on these factors, the predicted response values were determined to be 1639.61 kg/m3 for relaxed density, 97.95% for mechanical durability, and 10.18 MPa for compressive strength. The values obtained experimentally under the optimized conditions were similar to the predicted values with a desirability value of 1.00.

Anodic Catalyst Support via Titanium Dioxide-Graphene Aerogel (TiO2-GA) for A Direct Methanol Fuel Cell: Response Surface Approach

The direct methanol fuel cell (DMFC) has the potential for portable applications. However, it has some drawbacks that make commercialisation difficult owing to its poor kinetic oxidation efficiency and non-economic cost. To enhance the performance of direct methanol fuel cells, various aspects should be explored, and operational parameters must be tuned. This research was carried out using an experimental setup that generated the best results to evaluate the effectiveness of these variables on electrocatalysis performance in a fuel cell system. Titanium dioxide-graphene aerogel (TiO2-GA) has not yet been applied to the electrocatalysis area for fuel cell application. As a consequence, this research is an attempt to boost the effectiveness of direct methanol fuel cell electrocatalysts by incorporating bifunctional PtRu and TiO2-GA. The response surface methodology (RSM) was used to regulate the best combination of operational parameters, which include the temperature of composite TiO2-GA, the ratio of Pt to Ru (Pt:Ru), and the PtRu catalyst composition (wt%) as factors (input) and the current density (output) as a response for the optimisation investigation. The mass activity is determined using cyclic voltammetry (CV). The best-operating conditions were determined by RSM-based performance tests at a composition temperature of 202 °C, a Pt/Ru ratio of (1.1:1), and a catalyst composition of 22%. The best response is expected to be 564.87 mA/mgPtRu. The verification test is performed, and the average current density is found to be 568.15 mA/mgPtRu. It is observed that, after optimisation, the PtRu/TiO2-GA had a 7.1 times higher current density as compared to commercial PtRu. As a result, a titanium dioxide-graphene aerogel has potential as an anode electrocatalyst in direct methanol fuel cells.

Design and Testing of a Self-Propelled Dandelion Seed Harvester

At present, there are few harvesters for dandelion (Taraxacum mongolicum) seeds, which limits the large-area planting of dandelion. Furthermore, manual harvesting is characterized by huge labor intensity, low efficiency, and high costs. Combining the material characteristics of dandelion plants and seeds with agronomic requirements for harvesting dandelion seeds, a self-propelled dandelion seed harvester was designed. The harvester is mainly composed of collection devices, separation devices, transmission devices, and a rack. It can facilitate seed collection from plants, seed transportation, and seed–pappus separation in one operation. The collection and separation processes of dandelion seeds were studied to ascertain the main factors that affect the collection rate. Then, the collection and separation devices were designed, and their parameters were analyzed. Taking the forward speed, wind velocity of blowers, and rate of rotation of the drum as test factors and the collection rate as the evaluation index, quadratic regression orthogonal rotating field tests were performed. In this way, the optimal combination of operation parameters was determined: the collection rate is optimal when the forward speed is 0.8 m·s−1, the air velocity from the blowers is 1.63 m·s−1, and the rate of rotation of the drum is 419 rpm. Field test results showed that a favorable harvesting effect was achieved after operation of the harvester, and only small amounts of dandelion seeds remained unharvested. Under the optimal parameter combination, the collection rate reached 89.1%, which could meet requirements for practical field harvesting of dandelion seeds. The test results satisfy the design requirement.

Design and Test of Stripping and Impurity Removal Device for Spring-Tooth Residual Plastic Film Collector

The residual agricultural plastic film in China is not easily recovered due to the thinness and poor mechanical properties of domestic films, and a large amount of plastic film remaining in farmland soil poses a great threat to soil quality and crop production. A spring-tooth residual plastic film collector (SRPFC) is widely used in domestic residual plastic film (RPF) recycling operations. However, there are two major problems in the current SRPFC: the low recovery rate of the residual film (RRRF) caused by the difficulty of film-stripping and the high impurity rate in the film (IRF). In this paper, a stripping and impurity removal device (SIRD) is designed to address the existing problems of SRPFC, which is mainly composed of film-stripping tooth plates (FTP), two wind-collecting hoods, and two centrifugal fans. The motion and force analysis of the RPF in the film-stripping process was carried out, and the arc FTP was determined to be used for film-stripping. The size parameters of the FTP were obtained by establishing the coordinate system to solve the differential equation. By comparing and analyzing the force of RPF in the airflow field of the test bench for suspension speed and the airflow field of the wind-collecting hood, the RPF equivalent particle was established. The discrete phase model (DPM) in Fluent software was used to simulate the movement of the RPF equivalent particle, and the calculated air volume range of the centrifugal fan was 5501.88~6829.92 m3/h. The effects of forward speed, rotating speed of film conveying chain harrow (FCCH), and rotating speed of the centrifugal fan on RRRF and IRF were studied by orthogonal rotary combination experiment. The test results showed that the best combination of machine operation parameters was when the forward speed was 5 km/h, the rotating speed of the FCCH was 235 r/min, and the rotating speed of the centrifugal fan was 1978 r/min. Under these conditions, the RRRF was 92.53%, and the IRF was 9.31%. Field experiments were carried out with the rounded parameters, and the average RRRF was 92.07%, and the average IRF was 9.56% under the parameter combination, indicating that the optimization scheme of the device was feasible.

Simulation Optimization and Experimental Study of the Working Performance of a Vertical Rotary Tiller Based on the Discrete Element Method

In order to investigate the mechanism of interaction between a vertical rotary tiller and the soil to obtain the best structural and operational parameters of the tool, improve the operational quality of the rotary tiller, achieve the effect of soil breaking and leveling to meet the agronomic requirements of tillage, a series of simulation tests was conducted through the design of 3D models of rotary tillers with different structural forms and the building of discrete element models of the action between the rotary tiller and the soil. The virtual simulation of different operating parameters and structural parameters of vertical rotary tiller was carried out by EDEM, and the effects of operating parameters, tool bending angle, and cutter installation number on the operating effect were analyzed. The parameter combination with the best operating effect was obtained through orthogonal test analysis and verified by soil trough test. A soil tank test showed that, with the optimal combination of operating and structural parameters, the average soil breaking rate of the vertical rotary tiller was 81.3%, which meets the agronomic requirements of tillage operation, and the actual power consumption was 6% higher than the simulation value, which was sufficiently close to verify the validity of the simulation. This study can lay a foundation for optimization research on the vertical miniature rotary tiller.

Small Magnitude Events Highlight the Correlation Between Hydraulic Fracturing Injection Parameters, Geological Factors, and Earthquake Occurrence

AbstractHydraulic fracturing (HF) operations are widely associated with induced seismicity in the Western Canadian Sedimentary Basin. This study correlates injection parameters of 12,903 HF stages in the Kiskatinaw area in northeast British Columbia with an enhanced catalog containing 40,046 earthquakes using a supervised machine learning approach. It identifies relevant combinations of geological and operational parameters related to individual HF stages in efforts to decipher fault activation mechanisms. Our results suggest that stages targeting specific geological units (here, the Lower Montney formation) are more likely to induce an earthquake. Additional parameters positively correlated with earthquake likelihood include target formation thickness, injection volume, and completion date. Furthermore, the COVID‐19 lockdown may have reduced the potential cumulative effect of HF operations. Our results demonstrate the value of machine learning approaches for implementation as guidance tools that help facilitate safe development of unconventional energy technologies.

Multi-Objective Optimization of Organic Rankine Cycle (ORC) for Tractor Waste Heat Recovery Based on Particle Swarm Optimization

Diesel engines are widely used in agricultural tractors. During field operations, the tractors operate at low speed and high load for a long time, the fuel efficiency is only about 15% to 35%, and the exhaust waste heat accounts for 38% to 45% of the energy released from the fuel. The use of tractor exhaust waste heat can effectively reduce fuel consumption and pollutant emissions, of which the organic Rankine cycle (ORC)-based waste heat recovery conversion efficiency is the highest. First, the diesel engine map is achieved through the test rig, a plate-fin evaporator is trial-produced based on the tractor size, and the thermodynamic and economic performance model of the ORC are established. Then, taking the thermal efficiency of ORC and the specific investment cost (SIC) as the objective function, the particle swarm optimization (PSO) algorithm and the technique for order of preference by similarity to ideal solution (TOPSIS) decision method were used to obtain the optimal operating parameter set under all working conditions. Finally, the results showed that the ORC thermal efficiency could reach a maximum of 12.76% and the corresponding SIC value was 8539.66 $/kW; the ORC net output power could be up to 8.31 kW compared with the system without ORC; and the maximum brake specific fuel consumption (BSFC) could be reduced by 8.3%. The improvement in the thermodynamic performance will lead to a sacrifice in economic performance, and at high speeds, the economic benefits and thermal efficiency reach a balance and show a better thermal economic performance. Recovering exhaust heat energy through ORC can reduce tractor fuel consumption and pollution emissions, which is one of the effective technical means to achieve “carbon neutrality” in agricultural production. At the same time, through the PSO algorithm, the optimal combination of ORC operating parameters is obtained, which ensures that the exhaust heat energy can be effectively recovered during the tractor field operation, and provides a basis for the adjustment of real-time work strategies for future research.

Enhancement of mixture homogeneity for DI-CI engine to achieve Homogeneous Charge Compression Ignition (HCCI) combustion characteristics: a numerical approach

ABSTRACT Homogeneous Charge Compression Ignition (HCCI) engine is a new mode of engine combustion concept used for decreasing emissions like NOx and soot and to meet stringent emission norms. A numerical and modeling analysis of the performance and emission characteristics of a DI-CI engine is presented in this paper. The numerical analysis was carried out using CONVERGE CFD software. In this paper, four different engine parameters were considered, i.e., Compression Ratio (CR) (14.5 to 19.5), Exhaust Gas Recirculation (EGR) (0 to 30%), Fuel Injection Pressure (FIP) (200 to 280 bar), and Start of Injection (SOI) (17 to 29° CA bTDC). Response Surface Methodology (RSM) was used for developing the design matrix in the given parameter ranges. Results were analyzed in terms of NOx, soot emissions, and Indicated Specific Fuel Consumption (ISFC) with an objective of lowering ISFC, soot, and NOx. The statistical analysis showed that CR of 18.9, SOI of 25.89° CA bTDC, EGR of 24.9%, and FIP of 262.45 bar predicted as an optimum combination of operation parameters set. From the ANOVA analysis, it is observed that CR and SOI are the most influencing parameters on the output response parameters. The mixture homogeneity (i.e., Target Fuel Distribution Index (TFDI)) of air-fuel was improved by 19.2% for optimum configuration as compared to baseline configuration.

Optimizing volatile fatty acid production from municipal sludge: Linking microbial activity with reactor performance

Literature on optimum levels and combinations of bioreactor operating parameters to maximize volatile fatty acids (VFAs) via anaerobic digestion (AD) is still scant and contradictory. This study investigated the interactive impact of digester sludge retention time (SRT), temperature, and pH on optimizing VFAs production and linking reactor performance to acidogenic activities. VFAs production from municipal sludge was maximized in semi-continuous flow acid fermenters (AFs). Batch fermentation tests were utilized for the specific acidogenesis activity assays (SAdA) with a simpler substrate (glucose and acetic acid) and inocula from AFs. Fermenters operated at high pH of 8, low SRT of 2 days, and varying temperatures of 55 and 45 °C had the highest chemical oxygen demand (COD) solubilization and acidification yields. Similar fermenters had the highest VFAs fold increase (1.7–2.2) over the substrate, largest acetic acid contribution to total VFAs (52–58%), and maximum SAdA extent (368–461 mL H2/g VSS inoculum). Maximum hydrogen production rate indirectly represented substrate utilization rate, growth of the acidogens, and hence the specific activities of the acidogenic bacteria in the AFs. These results suggested that batch acidogenic assays could provide quantitative information regarding the presence and activities of cultures in continuously-fed AD utilizing more complex substrates, e.g. municipal sludge. A multiple linear regression model was derived successfully predicting VFAs fold increase of AFs with an R-squared value of 0.9999. The constructed contour plots predicted higher VFAs at relatively high fermenter pH (7.5–8.0), lower SRT (2–2.2 days), and lower temperatures (45–48 °C).

What are the challenges for ohmic heating in the food industry? Insights of a bibliometric analysis

The trends related to ohmic heating technology in food processing were evaluated using bibliometric analysis based on the scientific literature published in the last decade. Publications from Turkey, Brazil, and Iran represent 32% of all publications. Most studies have targeted the definition of the best combinations of operational parameters for application in different food matrices and their possible effects on the food properties. In addition, a tendency to use ohmic heating as an alternative technology for pasteurization was observed. Future studies should develop mathematical models that evaluate process parameters and food characteristics in the inactivation of microorganisms and enzymes and maintenance of bioactive compounds, the study of the non-thermal effect of electromagnetic waves on the food quality, the evaluation of the processing conditions and food physicochemical properties in the electrode corrosion and migration of metal ions to the treated food, and improvements of homogeneity during processing. This study was the first to perform a bibliometric analysis based on scientific literature concerning ohmic heating in food processing and presented the challenges, future trends, and evolution of scientific research.

QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy.

This paper introduces Quasar Science Resources-Autonomous University of Madrid atomic force microscopy image data set (QUAM-AFM), the largest data set of simulated atomic force microscopy (AFM) images generated from a selection of 685,513 molecules that span the most relevant bonding structures and chemical species in organic chemistry. QUAM-AFM contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances with a different combination of AFM operational parameters, resulting in a total of 165 million images with a resolution of 256 × 256 pixels. The 3D stacks are especially appropriate to tackle the goal of the chemical identification within AFM experiments by using deep learning techniques. The data provided for each molecule include, besides a set of AFM images, ball-and-stick depictions, IUPAC names, chemical formulas, atomic coordinates, and map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a graphical user interface that allows the search for structures by CID number, IUPAC name, or chemical formula.

Multifunctional Equipment for Low-temperature Separation of Food Solutions Based on The Effect of “Thermal Paradox”

The analysis of studies devoted to food solutions separation was carried out. The evolution of cryoconcentration technologies is analyzed, including the research works of the authors in the field of the block freezing plants. The purpose of the work is to reduce energy costs in block freezing plants and to intensify the process of the ice block formation. A hypothesis states that energy efficiency can be improved by recycling ice, using its energy to supercool the refrigerant before throttling. To intensify heat and mass transfer during crystallization, a scientific and technical idea for the implementation of the "thermal paradox effect" is proposed. The essence of the effect is that, with a certain combination of design and operating parameters of a block freezer, the growth of an ice block leads to a decrease in the total thermal resistance in the circuit "refrigerant — block freezer's wall — ice block — solution". The most significant result of the work was that it proved the possibility to harmonize the design and operating parameters and organized the process of separation the solutions into ice and concentrate while minimizing systemic cold losses, and, and thus the ways were proposed for developing the freezing concentration technique. The scientific significance of the obtained results lies in the fact that a new principle of efficient use of the ice block energy was proved in the work, and a new effect was obtained, which it was referred to by the authors as the "thermal paradox". The practical significance of the work was that a multifunctional freezing unit with ice recycling and frequency control of the compressor drive was created.

Development of Tractor Front Mounted Harvester for Finger Millet

Finger millet crop is important minor millet, which can serve as both food and fodder. Manual harvesting of finger millet involves harvesting earhead and stalk separately which is labor intensive. Hence, the study aimed to design and develop a harvester for finger millet to remove drudgery in harvesting and to achieve a low cost of harvesting. The important crop and machine parameters influencing the harvesting of finger millets were identified for the most prominent variety of CO (Ra) 14 in finger millet. A prototype finger millet harvester was developed and the effect of a machine and operational parameters were evaluated in terms of header loss at different levels of a rotational speed of reel 30, 35 and 40 revolutions per minute (rpm), 35, 40 and 45 cm mounting height of reel and forward speed 1.6, 2.68, and 3.48 km/h. The performance of the harvest was found satisfactory. Comparing the best combinations of machine and operational parameters, the minimum header loss of 1.25 per cent was achieved at the combination of 30 rpm rotational speed of reel, 40 cm mounting height of reel and 2.68 km/h forward speed.

English

The mechanized planting of potato mini-tubers is vital for the development of the potato industry in China. A vibration-based seeding device for mini-tubers was designed and tested. The objectives of this study were to describe the design process of the main components of the seeding device by theoretical analysis, evaluate the reliability of the key components of the seeding device by finite element analysis, assess the seeding device’s working performance, and obtain a better combination of operational parameters by bench tests. According to a theoretical analysis of the seeding device design, the eccentricity of the eccentric wheel (EEW), rotational speed of the drive shaft (RSDS) and linear speed of the conveyor belt (LSCB) were selected as critical factors influencing the seeding device’s working performance. A Box-Behnken design (BBD) was applied to conduct bench tests and build regression models. Based on the optimized results, verification experiments were performed by a bench tester. The results showed that the multiple-seeding index (MUSI) was 3.10%, the miss-seeding index (MISI) was 4.01%, and the qualified-seeding index (QSI) was 92.89% when the EEW, RSDS and LSCB were 4 mm, 821 rpm, and 86 mm s-1, respectively. Verification experiments showed that the results agreed well with the theoretical optimization values