Quadratic Response Surface Research Articles

Optimising nanoparticles: harnessing quality by design through 3-level factorial design and box-behnken methodology

Nanoparticles (NPs) have become essential elements in a number of scientific and industrial domains, such as materials research, drug delivery, and diagnostics, because of their special qualities and potential for focused uses. An ideal formulation procedure is essential to maximising the effectiveness and efficiency of nanoparticles. In order to optimise the formulation and production processes for nanoparticles, this research investigates the application of Quality by Design (QbD) principles in conjunction with sophisticated statistical approaches, namely the 3-level factorial design and the Box-Behnken methodology. The Quality by Design methodology is a methodical approach that prioritises predetermined goals, in-depth process comprehension, and careful control grounded in reliable science and quality risk management. When QbD is incorporated into nanoparticle optimisation, reliable and repeatable formulations that adhere to specifications with little variation are guaranteed. To look into how different factors interact and affect the properties of nanoparticles, the 3-level factorial design is used. With this design approach, a thorough understanding of the process variables can be obtained by exploring a broad variety of component values. Critical quality attributes (CQAs) include important parameters such drug encapsulation efficiency, zeta potential, polydispersity index (PDI), and particle size. These parameters are methodically examined to determine the ideal amounts of each. To further refine the 3-level factorial design, the Box-Behnken methodology is applied. Without the requirement for extensive combination testing, this response surface methodology (RSM) is especially useful for building second-order polynomial models and investigating quadratic response surfaces. By enabling a more accurate comprehension of the interactions between inputs and responses, the Box-Behnken design improves the optimisation process and makes it easier to identify the ideal circumstances for nanoparticle synthesis. By utilising both approaches in tandem, this work methodically determines ideal formulation parameters that minimise nanoparticle size and polydispersity while optimising stability and drug loading efficiency. The outcomes highlight how important a QbD framework is for directing the creation of reliable nanoparticle systems that function consistently and predictably.

The Application of Converter Sludge and Slag to Produce Ecological Cement Mortars.

The paper presents an analysis of the effective use of a mixture of steel sludge (S1) and slag (S2) from the converter process of steel production for the production of cement mortars. Metallurgical waste used in the research, which is currently deposited in waste landfills and heaps near plants, posing a threat to groundwater (possibility of leaching metal ions present in the waste), was used as a substitute for natural sand in the range of 0-20% by weight of cement (each). The obtained test results and their numerical analysis made it possible to determine the conditions for replacing part of the sand in cement mortars with a mixture of sludge and slag from a basic oxygen furnace (BOF) and to determine the effects of such modification. For the numerical analysis, a full quadratic Response Surface Model (RSM) was utilized for two controlled factors. This model was subsequently optimized through backward stepwise regression, ensuring the inclusion of only statistically significant components and verifying the consistency of residual distribution with the normal distribution (tested via Ryan-Joiner's test, p > 0.1). The designated material models are helpful in designing ecological cement mortars using difficult-to-recycle waste (i.e., sludge and converter slag), which is important for a circular economy. Mortars modified with a mixture of metallurgical waste (up to 20% each) are characterized by a slightly lower consistency, compressive and flexural strength, and water absorption. However, they show a lower decrease in mechanical strength after the freezing-thawing process (frost resistance) compared to control mortars. Mortars modified with metallurgical waste do not have a negative impact on the environment in terms of leaching heavy metal ions. The use of a mixture of sludge and steel slag in the amount of 40% (slag/sludge in a 20/20 ratio) allows you to save 200 kg of sand when producing 1 m3 of cement mortar (cost reduction by approx. EUR 5.1/Mg) and will also reduce the costs of the environmental fee for depositing waste.

Optimization design of hydro turbine support structure based on GA-FA-BP method

The rational design of the turbine support structure ensures the safe operation of the system, achieves significant economic benefits and improves the efficiency of the turbine. This paper presents a novel turbine support structure capable of vertical movement along the guide column. In addition, the GA-FA-BP method has been developed for the optimization design of the support structure, which combines genetic algorithm (GA), firefly algorithm (FA) and back-propagation neural network (BP). The use of quadratic response surface (RS) method along with NSGA-II for the result validation of the GA-FA-BP model ensures the robustness and reliability of the optimization results. A finite element model is set up to analyse the mechanical behaviour of the support structure under 10 different combined load conditions. The most critical load conditions in the static mechanical models are used to generate training data, and the mass, deformation and equivalent stress of the optimized and unoptimized support structures are analyzed and compared. The results show that the optimized support structure can maintain deformation and equivalent stress within a weight reduction of 21.83% compared to the original design. Compared to a single optimization model, the proposed GA-FA-BP model shows higher accuracy with a correlation coefficient up to 0.9989.

On the construction of saturated split-plot designs for quadratic response surface models

Split-plot designs are commonly employed in experiments where the levels of some factors are difficult or costly to adjust. One of the primary objectives of many such experiments is to accurately predict responses using fitted response surfaces. While many split-plot designs have been proposed in the literature for this purpose, most of them require large run sizes and an excessive number of whole plots, resulting in expensive and time-consuming experiments. To address this issue, we conduct a study to determine the minimum requirements for a split-plot design that can be used to fit a response surface. Based on these requirements, we construct saturated or nearly saturated response surface split-plot (RSSP) designs that are cost-effective, featuring the fewest possible run sizes and the smallest number of whole plots. We use a motivating example and conduct simulations. Our study shows that the proposed RSSP designs not only provide cost savings, but also maintain good predictive efficiency.

Optimal configuration of passive flow control devices to reduce the aerodynamics drag of a tractor-trailer model

Aerodynamic drag plays an important role in heavy vehicles, especially when traveling at high speeds. In this context, the application of passive flow control devices emerges as a potential approach to reduce the aerodynamic drag of vehicles, leading to improvements in fuel efficiency and environmental pollution. Consequently, this study focuses on using cab side extenders and rear flaps to reduce the aerodynamic drag of a 1:8 small-scale simplified tractor-trailer model. The main parameters of this device configuration, including the length LR and deflection angle θG of the cab side extenders, the length LR and deflection angle θR of the rear flaps, are optimized to minimize the model aerodynamic drag coefficient. Numerical studies are performed using the Computational Fluid Dynamics method, with the steady k-ω SST and the unsteady DES turbulence model. The optimal solution is implemented based on a 30-level Latin Hypercube design of the experiment and a full quadratic regression response surface method. The obtained results show that a maximum reduction in the aerodynamic drag coefficient of the simplified tractor-trailer model by 20.8 % is achieved with an optimized configuration of control devices. The mechanism of aerodynamic drag reduction is also evaluated based on the analysis of flow fields around the vehicle model.

Response surface optimization of hydrogen-rich syngas production by methane dry reforming over bimetallic Mn-Ni/La2O3 catalyst in a fixed bed reactor

The present work utilizes a response surface optimization technique to optimize hydrogen-rich syngas production through the process of methane dry reforming (DRM). This optimization is achieved by employing a bimetallic Mn–Ni/La2O3 catalyst. The study aimed to evaluate the impact of three key parameters, namely reaction temperature, time on stream (TOS), and gas hourly space velocity (GHSV), on the hydrogen to carbon monoxide (H2/CO) ratio in syngas during the DRM. The Mn–Ni/La2O3 catalyst, synthesized using the sequential wet impregnation technique, exhibited suitable physicochemical properties necessary for DRM reaction, as evidenced by the obtained characterization data. Among the five models examined, it was found that the quadratic versus 2FI model substantially fit the experimental data, as evidenced by a p-value <0.05. The analysis of variance (ANOVA) conducted on the quadratic response surface model compared to the 2FI model demonstrated that both the reaction temperature and the TOS had a significant impact on the H2/CO ratio in the syngas. The only significant interaction factor was the relationship between the reaction temperature and the TOS. Under the specified optimal circumstances of 15 000 ml/g.h, 850 °C, and 258.15 min, an H2/CO ratio of 0.98 was achieved. The resulting H2/CO ratio of 0.98 is almost 1, indicating its suitability as a feedstock for methanol production in the Fischer-Tropsch synthesis (FTS).

On E–Optimality Design for Quadratic Response Surface Model

On E–Optimality Design for Quadratic Response Surface Model

Orthogonal experimental study of ultrasound-assisted fused deposition molding

To improve the quality of fused deposition molding (FDM), we introduced ultrasonic vibration into the molding process to enhance the strength of the tensile samples. We used the response surface method to optimize the FDM molding process. We carried out orthogonal experiments to investigate the effects of ultrasonic power and process parameters (extrusion temperature, hotbed temperature, and delamination thickness) on the mechanical properties of fused deposition acrylonitrile butadiene styrene products. We obtained the quadratic regression equations and response surfaces of the data through analysis of variance and significance analysis by software. Last, we received the optimum combination of process parameters for tensile strength as extrusion temperature 233.85 °C, hotbed temperature 93.38 °C, delamination thickness 0.1 mm, and ultrasonic power 43.09 W.

Optimizations of structure stiffnesses and sensitivities of Y-type six-axis force/torque sensor

PurposeThe six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.Design/methodology/approachThe performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.FindingsThe sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.Originality/valueHence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

Statistical optimization of two-phase hollow fiber liquid-phase microextraction for preconcentration of strychnine in the clinical and postmortem biological fluids prior to gas chromatography-mass spectroscopy detection

Strychnine is a herbal alkaloid whose role in military and doping applications as well as the nervous system stimulation and cancer therapy has been confirmed. Because of its lethal nature, even at low dosages, developing a rapid, sensitive, and accurate method for determination of this alkaloid in the clinical and postmortem samples is of great importance. In this study, a green analytical method based on the two-phase hollow fiber liquid-phase microextraction (HF-LPME) combined with gas chromatography-mass spectrometry (GC–MS) was presented for preconcentration and determination of strychnine in biological fluids. A Box-Behnken design (BBD) with three variables, including extraction time (30–90 min), solution pH (9.0–11.0), and ionic strength (1.0–3.0 mol/L) was employed to maximize the extraction efficiency of strychnine by 1-octanol. The results were satisfactorily fitted to a quadratic response surface model (R2 = 0.979, F = 34.4) which predicted the optimum conditions of operation (extraction time of 89 min, pH = 11.0, and ionic strength of 3.0 mol/L). Based on the results, the studied variables and the interaction between pH and extraction time showed highly significant effects on the process efficiency. The calibration curve was linear in the concentration range of 2.7–1000.0 µg/L (R2 = 0.9978) and the limits of detection and quantitation were found to be 0.8 and 2.7 µg/L, respectively. Moreover, the method was successfully applied to different real samples, including urine (clinical sample), bile and stomach contents, blood, and vitreous humor (postmortem samples), and relative recoveries were obtained in the range of 93.8 % to 99.8 %. The findings of this study suggest that the environmentally friendly HF-LPME method which uses a small amount of a chlorine-free solvent, is a sensitive, cost-effective, simple, and efficient preconcentration method for trace determination of strychnine in biological fluids.

Response surface optimization for deep eutectic solvents extraction of bamboo shoots proteins

To enhance the protein extraction rate of bamboo shoots, the Response Surface Methodology was utilized to optimize the protein extraction process of Chimonobambusa purpurea Hsueh f. & T.P.Yi (syn. Chimonobambusa neopurpurea T.P.Yi) bamboo shoots. Choline chloride and proline were utilized as hydrogen bond acceptors in a total of eight deep eutectic solvents, whereas glucose, sucrose, glycerol, ethylene glycol, acetylpropionic acid, malic acid, and lactic acid were used as hydrogen bond donors. This work examined the protein extraction from bamboo shoots using deep eutectic solvents. Single-factor experiments were conducted to determine the optimal composition of the deep eutectic solvents, along with the ideal gradients of material-liquid ratio gradients, water content, extraction time, and water bath temperature. The impact and interplay of various variables on the protein extraction rate of bamboo shoots were examined using the Box-Behnken Design and Response Surface Methodology. Both the water bath temperature and the extraction time significantly influenced the protein extraction rate of bamboo shoots. Notably, the interaction between extraction time and water bath temperature had the most substantial effect on the protein extraction rate of bamboo shoots. The quadratic response surface regression equation for the protein extraction rate of bamboo shoots relative to the actual values of each factor was obtained as follows: Protein extraction rate = −193.3275 + 3.8395 A - 18.7075 B + 6.3285 C + 0.2125 AB - 0.0089 AC + 0.024 BC - 0.02885 A2 + 0.685 B2 - 0.06455 C2. Finally, this work predicted optimum extraction parameters for bamboo shoots with choline chloride-sucrose (molar ratio 1:2), a material-liquid ratio of 1:50, a water content of 74 %, an extraction time of 4 h, and a water bath temperature of 44 ℃. Under the optimal conditions, the protein extraction yield was 59.39±0.45 %, which aligned with the predicted value from the response surface fitting equation. This indicated that the optimised regression equation may have practical significance. Compared with conventional extraction using a sodium hydroxide (NaOH) solution, deep eutectic solvents extraction of bamboo shoots is more environmentally friendly, non-toxic and harmless. It provides a theoretical and experimental reference for industrial extraction and offers a reference for deep eutectic solvent development in bamboo shoot resource utilization.Key message:To enhance the protein extraction rate of bamboo shoots, the Response Surface Methodology was utilized to optimize the protein extraction process of bamboo shoots.

Investigation on Traffic Carbon Emission Factor Based on Sensitivity and Uncertainty Analysis

The premise for formulating effective emission control strategies is to accurately and reasonably evaluate the actual emission level of vehicles. Firstly, the active subspace method is applied to set up a low-dimensional model of the relationship between CO2 emission and multivariate vehicle driving data, in which the vehicle specific power (VSP) is identified as the most significant factor on the CO2 emission factor, followed by speed. Additionally, acceleration and exhaust temperature had the least impact. It is inferred that the changes in data sampling transform the establishment of subspace matrices, affecting the calculation of eigenvector components and the fitting of the final quadratic response surface, so that the emission sensitivity and final fitting accuracy are impressionable by the data distribution form. For the VSP, the best fitting result can be obtained when the VSP conforms to a uniform distribution. Moreover, the Bayesian linear regression method accounts for fitting parameters between the VSP and CO2 emission factor with uncertainties derived from heteroscedastic measurement errors, and the values and distributions of the intercept and slope α and β are obtained. In general, the high-resolution inventory of the carbon emission factor of the tested vehicle is set up via systematically analyzing it, which brings a bright view of data processing in further counting the carbon footprint.

Buckling Defect Optimization of Constrained Ring Rolling of Thin-Walled Conical Rings with Inner High Ribs Combining Response Surface Method with FEM

A buckling defect will appear on the outer surface of the deformed ring during the constrained ring rolling (CRR) of an aluminum alloy thin-wall conical ring with inner high ribs (AATWCRIHR) if the geometrical dimension of the ribs does not match the wall thickness. To avoid the buckling defect, a quantitative method for characterizing the degree of the buckling defect is proposed using the area of the buckling profile. Then, an orthogonal experimental scheme was designed, taking the width of the middle rib, thickness of wall, and height of the middle rib as the design variables and defining the area of the buckling profile as the optimization objective. Subsequently, a quadratic polynomial response surface model was established by combining the optimization algorithm with the finite element method (FEM), and the geometrical dimension of the middle ribs of the deformed AATWCRIHR is optimized. Moreover, the optimal parameter combination to minimize the area of the buckling profile is obtained and verified using FE simulation. The results show that the AATWCRIHR after optimization does not generate the buckling defect during constrained ring rolling, and it is proven that the quantitative buckling defect representation method and the optimization design method based on the response surface model and the finite element simulation results are feasible for the constrained ring-rolling process of the AATWCRIHR.

A fast uncertainty quantification methodology and sampling technique for joint probability distribution of the Arrhenius rate expression: a case study applied to H2/CO kinetic mechanism

This work proposes a fast, novel, mathematically robust, and elegant unconstrained Method of Uncertainty Quantification (MUQ) for the temperature-dependent Arrhenius rate constant using Cholesky Decomposition (CD) of the covariance matrix of the Arrhenius parameters. The Arrhenius parameters of a reaction are treated as normally distributed correlated random variables. The MUQ method lends itself to an approach for Sampling of Arrhenius Curves (SAC), which automatically ensures that the generated samples are consistent with the distribution of Arrhenius parameters. The Method of Uncertainty Quantification and Sampling of Arrhenius Curves (MUQ-SAC) is used to train a quadratic polynomial response surface (PRS). Three important classes of Arrhenius curves possible within the SAC method are identified. From the total set of targets, a small subset of targets is first used to study the combinations of different classes of Arrhenius curves and their proportions within the design matrix, which is used to train PRS. Based on this understanding, response surfaces are generated for 64 ignition delay targets (Tig), which comprises of a wide range of pressure (P: 1--32.7 atm), temperature (T: 916-DIFadd-2869 K), and equivalence ratio (ϕ: 0.5--6.11), as well as for 74 laminar flame speed targets (Fls), spanning P: 1--25 atm, T: 285--600 K, and ϕ: 0.6--5. The H 2 /CO sub-mechanism of FFCM1.0 is chosen for the case study in which 22 reactions (66 Arrhenius parameters) are considered active parameters. The quality of the generated PRS is measured using the relative Maximum Residual Error (MRE). The quality of PRS is also checked against the search iterations encountered during mechanism optimisation. Accurate PRS could be generated over the search iterations, validating that the SAC method is able to span the entire uncertainty domain while training the PRS. The implementation of the MUQ-SAC method is made available at https://github.com/KrunalPanchal1995/MUQ-SAC.git.

Macro–micro investigation on stabilization sludge as subgrade filler by the ternary blending of steel slag and fly ash and calcium carbide residue

This study investigates the efficacious utilization of sludge as a subgrade filler through in-situ shallow stabilization, employing cementitious industrial waste materials including steel slag (SS), fly ash (FA), and calcium carbide residue (CCR) as binding agents. The primary emphasis lies in the evaluation of the macro unconfined compression strength of stabilized sludge over a seven-day curing period, facilitated by a quadratic polynomial response surface model to determine the optimal composite stabilizer (WZ01) proportions. Furthermore, an array of meticulous microstructural analyses encompassing X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and energy-dispersive spectroscopy were undertaken to elucidate the development of internal cementitious products and the intrinsic mechanisms underpinning sludge stabilization in tandem with WZ01. The findings ascertain that the optimum WZ01 composition stands at SS: FA: CCR = 32:28:40. Prominent mineralogical constituents within the stabilized sludge encompass amorphous calcium silicate hydrate, calcium aluminate hydrate, and crystalline ettringite. The amelioration in stabilized sludge properties stems from intricate processes involving ion exchange, hydration reactions, and pozzolanic activities. Significantly, the WZ01 curing agent demonstrates heightened cost-effectiveness and environmental merits compared to conventional Portland cement.

Design and Test of Seed–Fertilizer Replenishment Device for Wheat Seeder

In view of existing problems, such as the seed and fertilizer supply link for wheat seeders still relying on manual installation and the lack of practical application equipment, a seed–fertilizer replenishment device based on the three-degree-of-freedom mechanical arm and screw conveying principle is designed using the seed box installation and supply as the operation scenario to replace the manual installation process. Combined with the requirements of the seed box replenishment operation, the key parameters of the replenishment robot arm and the screw conveyor auger are determined. Then, the kinematic model of the replenishment robot arm is established based on the modified D-H method, forward and inverse kinematics calculations are performed, and the workspace is analyzed using the Monte Carlo method. Based on this, the robotic arm task path is designed, the fifth-degree polynomial interpolation method is used to complete the trajectory planning, and MATLAB R2016a software is used to simulate the motion trajectories of each joint, verifying the feasibility of the trajectory planning solution. Finally, a prototype is trial-produced and quadratic regression orthogonal testing and response surface analyses are conducted to obtain the optimal working parameters of the replenishment device. The verification test shows that when the angular velocity of the lumbar joint of the replenishment device is 4°/s, the speed of screw conveyor is 90 r/min, and the angle of the big arm is 12°, the conveying loss rate is 3.98%, and the conveying efficiency is 0.833 kg/s. The relative errors with the theoretical optimal values are 4.2% and 2.4%, respectively, both less than 5%. The supply trajectory is reasonable, and the robot arm runs smoothly. This study can provide reference for the design of seed–fertilizer replenishment device for wheat seeders.

A response surface model to examine the reactive red 239 sorption behaviors on Rhizoclonium hieroglyphicum: isotherms, kinetics, thermodynamics and toxicity analyses.

The present study is an attempt to investigate the potentiality of Rhizoclonium hieroglyphicum in the removal of reactive red 239 (RR239) from aqueous solution and to assess the toxicity of the treated dye solution. Optimisation of the process variables namely dye and biosorbent concentrations, pH, temperature and incubation time for RR239 removal was performed using Response Surface Methodology (RSM) assisted Box Behnken Design (BBD) model. The recycling and regeneration efficiency of the dye adsorbed alga was evaluated using different eluents under optimized conditions. Further to understand the adsorption mechanism, isotherms, kinetics and thermodynamic studies were performed. UV-vis and FT-IR spectroscopy was employed to confirm the interaction between the adsorbate and biosorbent. The nature of the treated dye solution was assessed using phyto, microbial and brine shrimp toxicity studies. On the basis of quadratic polynomial equation and response surfaces given by RSM, 90% decolorization of RR239 was recorded at room temperature under specified optimal conditions (300mg/L of dye, 500mg/L of biosorbent, pH 8 and 72h of contact time). Desorption experiments demonstrated 88% of RR239 recovery using 0.1N acetic acid as an eluent and 81% of dye removal in regeneration studies. The data closely aligned with Freundlich isotherm (R2 - 0.98) and pseudo-second-order kinetic model (R2 - 0.9671). Thermodynamic analysis revealed that the process of adsorption was endothermic, spontaneous, and favorable. UV-Vis and FT-IR analyses provided evidence for adsorbate-biosorbent interaction, substantiating the process of decolorization. In addition, the results of phyto, microbial and brine shrimp toxicity assays consistently confirmed the non-toxic nature of the treated dye. Thus, the study demonstrated that R. hieroglyphicum can act as a potent bioremediation agent in alleviating the environmental repercussions of textile dyeing processes.

Design and experiment of a soybean shaftless spiral seed discharge and seed delivery device

When the driven stubble-breaking and anti-blocking no-till planter operates in the Southwest China, the stubble-breaking blades will impact with the ground as they cut through the soil and straw stubble, causing the planter to vibrate. This results in poor performances of the seed discharge by seed discharger and the seed guide by the seed guide tube. Based on the principle of spiral conveying, a soybean shaftless spiral seed discharge and seed delivery device was designed. The optimum seed filling size and speed range of the spiral blade were obtained by analyzing the size, force, and motion of soybean seeds of "ZhongHuang 37". The quadratic regression orthogonal rotation test and response surface method were used to analyze the operating parameters of the shaftless spiral seed discharge and seed delivery device by joint EDEM (Discrete Element Method)-RecurDyn simulation. The optimum parameters were obtained: the spacing of spiral was 11.4 mm, spiral outer radius was 5.5 mm, spiral inner radius was 2.9 mm and rotation speed was 10.4 r·s−1. Based on simulation and optimization results, the device was trialed and its field performance was tested. The results showed that at a surface slope of 16.1°, an average surface flatness of 8.9 cm, an average planter vibration frequency of 75.2 Hz, and an average amplitude of 7.2 mm, the average seeding qualification index, multiple index, missing seeding index, and damage index of the shaftless spiral seed discharge and seed delivery device were 92.6%, 5.03%, 2.4% and 0.92%, respectively, which were in line with the local agronomic requirements. The designed soybean shaftless spiral seed discharge and seed delivery device meets the requirements of the quality of no-till seeding and can provide a reference for the design and improvement of seed discharger and seed guide tube under poor ground leveling and long-distance seed delivery conditions.

Modeling stream baseflow nitrate concentration in an agricultural watershed using neural network and bootstrap method

The evaluation of water resource vulnerability to nonpoint source pollution in the presence of uncertainty remains a crucial concern. To enhance the accuracy of the assessment and pinpoint the key factors that affect watershed water quality, the integration of an artificial neural network (ANN) into the evaluation process is imperative. The research involved the collection of streams baseflow samples from thirty-eight sites between 1994 and 1999 in the Tomorrow-Waupaca River Watershed in central Wisconsin, USA, with a focus on examining the relationship between nitrate concentrations and a range of environmental and land use variables extracted from the watershed GIS database. This study utilized ANN methodology, combined with a bootstrap technique that employed a random resampling approach from a single input dataset, to simulate monthly stream baseflow nitrate concentrations. The effectiveness and predictive ability of the ANN model were assessed by comparing it to conventional multivariate regression methods. Through the use of ANN, more precise outcomes can be achieved while taking into account the uncertainty associated with the analysis. The findings demonstrated that the ANN outperformed both the multivariate linear regression and nonlinear quadratic response surface models in explaining the variance of stream nitrate and in external prediction consistency. This study also highlighted several key variables, such as the areal percentage of agricultural land and grassland, stream order, and the average slope of the groundwater flow path, that significantly impacted the stream baseflow nitrate concentrations in this watershed that was dominated by dairy farming and groundwater. Of these variables, the percentage of agricultural land emerged as the most significant factor.

Structural parameters of venturi injector for periodic air recovery based on response surface methodology

This work is devoted to the study of the structural parameters of a venturi injector for periodic air recovery. Using a push chain concrete spraying machine as a case, a numerical simulation study was conducted on the venturi injector under different structural parameter combinations. The venturi injector structure parameters diameter ratio of the throat to pipe a, convergent angle α, throat length to diameter ratio b, and diffusional angle β are designed and combined by the response surface method. The numerical simulation results and the prediction model obtained by the response surface method were verified by experiments, and the simulation results and prediction model were in good agreement with the experimental results. The results show that the residual air recovery of the push chain concrete spraying machine is best when a, α, b, and β are 0.8, 25°, 2.5, and 10°, respectively. In addition, the quadratic polynomial response surface model of the venturi injector pressure variation coefficient Cv and pressure drop Pd concerning the structural parameters was established, and the influence rules of each structural parameter on the Cv and Pd were obtained. The variation patterns of turbulent kinetic energy in the venturi at different times and stable sections at the back end are revealed. This paper can provide help for the design of venturi structures used for periodic air recovery in other chemical fields.