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In order to achieve an increase in the profitability of tissue paper production, this research aimed to identify factors that affect the degree of pulp refinement and the tension index of the tissue paper when using short fiber, long fiber and Quimizine B enzyme. The methodology considered laboratory experiments, obtaining refining curves, multilevel factorial design and response surface diagrams. The results indicated that the most significant common factor in the pulp refining degree and tension index is the specific energy consumption for both types of fiber, and that optimal operating parameters can be known by analyzing the refining degree and tension index independently and simultaneously. It was concluded that the multilevel factorial design allowed to identify significant factors that influence the properties of the refining degree and the resistance of tissue paper when looking for an individual and simultaneous optimum and, that the influence of the enzyme increased the properties of the refining degree and the tensile strength of the paper when using raw material of short and long fiber from Eucalyptus globulus and Pinus radiata, respectively. [ABSTRACT FROM AUTHOR]

[Objectives] This paper aimed to study the interaction mechanism of straw-soil-strip vertical rotary tillage system in rice stubble field, explore the influence of key operation parameters under the interaction of the three on the clearing and leveling effect of seedbed, and play a guiding role in the integrated straw field management and the optimal design of tillage machinery in the water-drought rotation system. [Methods] A 3D vertical rotation simulation model was constructed based on discrete element method. The process of vertical strip rotation under rice straw mulching was simulated, and the parameter range was optimized and verified by laboratory soil tank test. In the process of strip vertical rotation, the forward speed, the rotational speed of tool shaft and the stubble length were taken as the influencing factors. The response surface method was used to build a mathematical model to analyze the influence of each factor on the quality of the seedbed and carry out the performance optimization test. [Results]When the tillage depth was set to 15 cm, the main and secondary factors affecting the cleaning rate of stubble and the flatness of seedbed were the forward speed, the tool shaft rotational speed and stubble length. The results of multi-objective optimization showed that the quality of seedbed was the best when the tool forward speed was 1.09 m·s-1, the tool shaft rotational speed was 281.5 r·min-1 and the stubble length was 6.89 cm. The straw cleaning rate of seedbed was 81.95% and the seedbed flatness was 8.67 mm. [Conclusions] The interaction model established in this paper was proved to be reliable and could effectively reflect the effect of vertical rotation operation parameters on the clearing of straw in seed bed. [ABSTRACT FROM AUTHOR]

Abstract: The use of paper-mill residuals in concrete formulations provides an alternative to landfill disposal. A response surface statistical methodology was carried out to model the influence on the slump and compressive strength of concrete containing paper-mill residuals with and without Class F fly ash replacement. The variables considered in this study included the water/cement ratio (w/c), paper-mill residual content and fly ash content to total cementitious material (FA/CM). The performance of the derived models to achieve good balance between the workability and compressive strength were further discussed by using the contour diagrams. The results showed that the compressive strength of concrete containing paper-mill residuals could be predicted from the referred slump value. [Copyright &y& Elsevier]

Two types of waste paper materials, newspaper and office paper, were evaluated for their potential to be used as renewable feedstock for the production of fermentable sugars via the enzymatic hydrolysis of their cellulose fractions. The effects of four factors (hydrolysis time, enzyme loading, surfactant addition and phosphoric acid pretreatment) on the extent of sugar yield were assessed and quantified by using a methodical approach based on response surface methodology. The statistical experimental design used in this study requires fewer experimental runs compared to some commonly used experimental designs. In the newspaper hydrolysis case, response surface plots revealed that the degree of sugar release increased with an increase in hydrolysis time but it was hardly affected by the enzyme loading and acid pretreatment factors. The surfactant addition factor exhibited a positive effect when the enzyme loading level was relatively low. With office paper as the substrate, three of the four factors (hydrolysis time, enzyme loading and acid pretreatment) exhibited positive effects on the extent of sugar release. At local optimum conditions, the maximum sugar yield from office paper was found to be 0.82 g of reducing sugars per gram of paper, which was about 4.8 times higher than the maximum sugar release from the newspaper substrate. [ABSTRACT FROM AUTHOR]

Soil being a naturally formed material, the prediction and analysis of anchor uplift capacity incorporating the inherent variabilities in the soil properties is essential. This paper presents a probabilistic analysis of horizontal strip anchors in spatially varying soil using the multivariate adaptive regression splines (MARS) as a prediction model. The use of MARS in spatially varying soils is proposed, and its advantage over the conventional expensive Monte Carlo simulations is reported in this paper. The soil cohesion and friction angle have been modeled as lognormal random fields, and the influence of the spatially distributed soil properties on the anchor uplift capacity is assessed in the current study. Furthermore, a comparison between the deterministic and reliability-based design methodologies is presented, and their implications on the design of foundation are discussed. The results indicate that the code-specified factor of safety (FOS) value of 1.5 does not fulfill the target probability of failure ( P f ) values recommended in probabilistic design. A minimum FOS = 2 is required to satisfy the P f ≤ 0.001 criteria, which is usually recommended for the design of foundations. [ABSTRACT FROM AUTHOR]

This paper presents a finite element model of a railway crossing panel for use in multibody simulations (MBS). It is a two-layer track model with rails and sleepers represented by beam elements that use linear bushings for rail fastenings and non-linear bushings for ballast. The model is calibrated and validated to measurement data from a comprehensively instrumented switch and crossing demonstrator installed in the Austrian railway network as a part of the European research programme Shift2Rail. The validation concerns the capability of the model to capture the structural response of the crossing panel under traffic loading after calibration of physical track parameters to realistic values. The structural response is measured in the form of displacements, strains, and sleeper-ballast contact forces. It is shown that the developed model can represent the measured track responses well and that it was necessary to account for a varying sleeper-ballast gap distribution along the crossing transition sleeper to obtain good agreement. The calibration uses Latin hypercube samples to explore the parameter space in a sensitivity analysis before a parameter optimisation is performed using a gradient-based method on a response surface built from a polyharmonic spline. [ABSTRACT FROM AUTHOR]

This paper proposes a novel structural damage identification approach coupling the Mayfly algorithm (MA) with static displacement-based response surface (RS). Firstly, a hybrid optimal objective function is established that simultaneously considers the sensitivity-based residual errors of static damage identification equation and the static displacement residual. In the objective function, the static damage identification equation is addressed by the Tikhonov regularization technique. The MA is subsequently employed to conduct an optimal search and pinpoint the location and intensity of damages at the structural element level. To handle the inconformity of the static loading points and the measurement points of displacements, the model reduction and displacement extension techniques are implemented to reconstruct the static damage identification equation. Meanwhile, the static displacement-based RS is constructed to calculate the displacement residual in the hybrid objective function, thereby circumventing the time-consuming finite element calculations and improving computational efficiency. The identification results of the numerical box girder bridge demonstrate that the proposed method outperforms the particle swarm optimization, differential evolution, Jaya and whale optimization algorithms about both convergence rate in optimal searching and identification accuracy. The proposed method enables more accurate damage identification compared to methods solely based on the indicator of the residual of static damage identification equations or displacement residual. The results of identifying damage in the 21 element-truss structure and the static experiments on identifying damage in an aluminum alloy cantilever beam confirm the high efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper introduces a novel axisymmetric Helmholtz phononic crystal (AHPC) and conducts an in-depth investigation. A numerical model was developed to derive the complete bandgap of the AHPC structure, revealing the mechanism behind the formation of the bandgap, describing the characteristics of the sound pressure distribution at the edges of the bandgap, and confirming the low-frequency bandgap through experimentation, thereby validating the accuracy of the numerical model. The effects of neck length, neck width and cavity length on the low-frequency bandgap width and bandgap edge frequency were quantitatively investigated, identifying that these three parameters are the main factors affecting the bandgap distribution. Both the neck length and cavity length are positively correlated with the bandgap width and negatively correlated with the edge frequency of the bandgap, while the neck width shows a positive correlation with both bandgap width and edge frequency. Response surface analysis based on the Box-Behnken model was performed, and the functional relationships between the three factors and the bandgap width or the lower limit of the bandgap were obtained. Using these functional expressions, the structural parameters were optimized via the interior point method. The optimization results were verified by numerical simulation, and the optimal AHPC structure with a low-frequency bandgap ranging from 298. 49 Hz to 519. 27 Hz was obtained. [ABSTRACT FROM AUTHOR]

The time difference of arrival (TDOA) method has traditionally proven effective for locating acoustic emission (AE) sources and detecting structural defects. Nevertheless, its applicability is constrained when applied to anisotropic materials, particularly in the context of fiber-reinforced composite structures. In response, this paper introduces a novel COmposite LOcalization using Response Surface (COLORS) algorithm based on a two-step approach for precise AE source localization suitable for laminated composite structures. Leveraging a response surface developed from critical parameters, including AE velocity profiles, attenuation rates, distances, and orientations, the proposed method offers precise AE source predictions. The incorporation of updated velocity data into the algorithm yields superior localization accuracy compared to the conventional TDOA approach relying on the theoretical AE propagation velocity. The mean absolute error (MAE) for COLORS and TDOA were found to be 6.97 mm and 8.69 mm, respectively. Similarly, the root mean square error (RMSE) for COLORS and TODA methods were found to be 9.24 mm and 12.06 mm, respectively, indicating better performance of the COLORS algorithm in the context of source location accuracy. The finding underscores the significance of AE signal attenuation in minimizing AE wave velocity discrepancies and enhancing AE localization precision. The outcome of this investigation represents a substantial advancement in AE localization within laminated composite structures, holding potential implications for improved damage detection and structural health monitoring of composite structures. [ABSTRACT FROM AUTHOR]

[Objectives]The paper aimed to improve the vacuum freeze-drying rate and product quality of blueberries. [Methods]The ultrasound treatment was used as a pretreatment method to study the effects of ultrasound temperature(45, 55, 65, 75 ℃), frequency(45, 80, 100 kHz), power(600, 700, 800, 900, 1 000 W), and time(25, 30, 35, 40 min)on the drying characteristics, texture, color, nutrient retention rate, and antioxidant activity of blueberries. Then a four factors and three levels response surface optimization experiment was conducted using drying rate, anthocyanin content, color, and brittleness as indicators to select the optimal ultrasonic pretreatment process and parameters. [Results]Ultrasound temperature had a significant impact on the anthocyanin content of blueberries(P<0.001). The effect of ultrasound frequency on the drying rate, anthocyanin content, and brittleness of blueberries was significant(P<0.05). The effect of ultrasound power on blueberry brittleness was significant(P<0.05). The effect of ultrasound conditions on the ΔE value of blueberries was not significant(P>0.05). The optimize process conditions for ultrasonic pretreatment of blueberries were obtained as follows:ultrasonic temperature 55 ℃, frequency 80 kHz, power 700 W, and time 30 minutes. Under these conditions, the drying rate of blueberries was 1.69 g·g-1·h-1, anthocyanin content 0.55 mg·g-1, brittleness 2 770.00 g, and ΔE value 6.16. [Conclusions]Ultrasonic pretreatment could improve the quality of blueberry vacuum freeze-drying. The results provide the basis for the research and product development of blueberry vacuum freeze-drying. [ABSTRACT FROM AUTHOR]

This paper analysed the acoustic emission signals acquired during the tensile test of DP780 weld-bonding joints, and the Gaussian equation was used to fit the cumulative hits and the load to establish relevant damage models. The process parameters were designed based on the Box-Behnken Design method, and the wavelet packet was used to decompose the collected AE signals. The results showed that, in the elastic stage, no AE signal emitted, and the AE signal was mainly concentrated in the plastic stage, the hardening stage and the failure moment of the weld nugget or the adhesive layer. At the failure instant of the adhesive layer or the weld nugget, the signal amplitude was the largest, and the failure frequency was mainly concentrated in the middle and low-frequency bands. The failure of the adhesive layer and the weld nugget could be distinguished from the energy distribution diagrams, and the established damage model could reflect the damage state of the specimen. The results proved that the acoustic emission technique can provide support for the non-destructive testing of the weld-bonding joint. [ABSTRACT FROM AUTHOR]

Cotton stalk is one of the most high-quality biomass resources with a wide range of applications, such as building boards, chemical product raw materials, fuel, and papermaking. China is one of the major cotton-producing countries in the world. The planting area (3×106 hm²) has been ranked third in 2022, leading to the very abundant cotton stalk resources. The cotton stalks can be fully utilized to accelerate the green and low-carbon development of agriculture. Mechanical harvesting can be expected to efficiently remove the cotton stalks from the field. However, the current uprooting machine also needs to be improved and optimized for the cotton stalk. In this research, a clamping-type uprooting device with variable stiffness was designed for a high uprooting rate and low clamping breakage rate. The variable rigidity clamping was adjusted as follows. The flexible rubber clamping was used to prevent the cotton stalk from breaking; A rigid support structure was designed on the outside of the rubber block to obtain a greater clamping force. The better performance was achieved by clamping tightly without breaking the cotton stalk. The uprooting was also improved for the two scenarios of breakage and slippage. The device often consisted of a dividing disk, variable stiffness clamping and pulling mechanism, and tensioning guide mechanism. The dividing disk was used for the orderly feeding of cotton stalks; The variable stiffness clamping and pulling mechanism was used to realize the clamping and pulling of cotton stalks; The tensioning guide mechanism was to effectively control the clamping force and gap of cotton stalks. Two sets of chains were utilized to drive multiple clamping blocks, indicating a simple and reliable structure. Moreover, the frictional heating of traditional flexible belt mechanisms was avoided in this structure. A mechanical analysis was carried out on the cotton stalk pulling motion and the interaction between the variable stiffness clamp and the cotton stalk. The critical structural dimensions and operating parameter ranges were determined for the variable stiffness clamping device. A systematic investigation was made to clarify the influencing factors on the quality of clamping and pulling. The response surface method (RSM) was used to analyze the effects of the forward speed, the rotational speed of the active sprocket, and the clamping force on the stalk uprooting performance of the variable stiffness clamping and pulling device. The field test validated the simulation. The results showed that there was very consistency between the experimental and theoretical predictions, when the forward speed was 0.68 m/s, and the sprocket speed was 95 r/min. The tension force was 1 792 N, and the cotton stalk uprooting rate was 94.70%. The relative error between the measured and predicted uprooting rate value was 1.67%, which was less than 5%. The leakage rate and breakage rate of variable stiffness clamping and uprooting devices were 3.99% and 1.32%, respectively, compared with the existing devices of 5.19% and 3.68%, respectively. Therefore, the leakage rate and breakage rate of the device were reduced by 23.1% and 64.13%, respectively, compared with the former. The variable stiffness gripper effectively reduced the cotton stalk breakage to realize the whole stalk uprooting. The finding can provide new ideas to design the variable stiffness clamps, in order to optimize and improve the cotton stalk pullers. [ABSTRACT FROM AUTHOR]

In this paper, a pelletizing method has been researched to enhance the subsequent iron-making process applying Guisha limonite, with advantages including large reserves and low price. The purpose is to provide an alternative for the sinter, thus reducing the greenhouse gas emission during the iron-making process. The response surface method is used to optimize the experimental design of the pelleting process. A multivariate regression model for estimating the compressive strength of pellets was developed using Box–Behnken experimental methodology, where the relevant factors were the roasting temperature, pellet diameter, and bentonite content. The maximum influencing factors of each experimental design response are determined using analysis of variance (ANOVA). Under optimum conditions, the compressive strength of pure limonite pellets is 2705 N, similar to the response goal value of 2570.3 N, with a relative error of 5.20%. Since the high-grade iron ore resources are depleted, the comprehensive utilization of ore resources is becoming increasingly important. The aim of this paper was to provide a valuable technical foundation for lignite pellet-roasting processes in the iron and steel industries, since steel companies is increasing its imports of Guisha limonite. [ABSTRACT FROM AUTHOR]

Titanium alloy parts are more and more widely used in the field of aerospace. In order to improve the service life of titanium alloy parts, the response surface method was used to study surface residual stress and roughness under different turning parameters. In addition, a mathematical model was established through multiple linear regression to determine the relationship between surface integrity parameters and fatigue life. The test results indicate that the turning parameters have an effect on surface residual stress in the order of feed rate > depth of cut > cutting speed and on surface roughness in the order of feed rate > cutting speed > depth of cut. The analysis results of surface integrity show that the residual compressive stress on the surface has the greatest impact on fatigue life, followed by surface roughness. The fatigue life increases with the increase in residual compressive stress and decreases linearly with the increase in surface roughness. The feed rate has a significant impact on residual stress and surface roughness. Therefore, under the experimental conditions of this paper, the appropriate feed rate can be selected to ensure that the   R a < 2 μm and a large residual compressive stress is obtained. [ABSTRACT FROM AUTHOR]

Intelligent algorithms and surrogate models are commonly used in electromagnetic design of electrical machines. But they are rarely employed for other single-physics or multi-physics designs, such as that for electromagnetic vibration suppression. On the other hand, it is uncommon in existing literatures to compare the performances of different surrogate models for optimization. In this paper, the accuracies of three surrogate models are compared for different optimization objectives, and a 15-input 7-output problem involving electromagnetic vibration is solved through particle swarm optimization. After optimization, the motor electromagnetic vibrations at all dominant frequencies are significantly reduced and the torque performance is improved. The optimization result is verified with both finite element simulation and experimental measurement. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT) sensors provide a versatile chemical platform for ambient monitoring of ozone (O3) and nitrogen dioxide (NO2), two important airborne pollutants known to cause acute respiratory and cardiovascular health problems. CNTs have shown great potential for use as sensing layers due to their unique properties, including high surface to volume ratio, numerous active sites and crystal facets with high surface reactivity, and high thermal and electrical conductivity. With operational advantages such as compactness, low-power operation, and easy integration with electronics devices, nanotechnology is expected to have a significant impact on portable low-cost environmental sensors. Enhanced sensitivity is feasible by functionalizing the CNTs with polymers, metals, and metal oxides. This paper focuses on the design and performance of a two-element array of O3 and NO2 sensors comprising single-walled CNTs functionalized by covalent modification with organic functional groups. Unlike the conventional chemiresistor in which the change in DC resistance across the sensor terminals is measured, we characterize the sensor array response by measuring both the magnitude and phase of the AC impedance. Multivariate response provides higher degrees of freedom in sensor array data processing. The complex impedance of each sensor is measured at 5 kHz in a controlled gas-flow chamber using gas mixtures with O3 in the 60–120 ppb range and NO2 between 20 and 80 ppb. The measured data reveal response change in the 26–36% range for the O3 sensor and 5–31% for the NO2 sensor. Multivariate optimization is used to fit the laboratory measurements to a response surface mathematical model, from which sensitivity and selectivity are calculated. The ozone sensor exhibits high sensitivity (e.g., 5 to 6 MΩ/ppb for the impedance magnitude) and high selectivity (0.8 to 0.9) for interferent (NO2) levels below 30 ppb. However, the NO2 sensor is not selective. [ABSTRACT FROM AUTHOR]

Olive oil production generates a large amount of wastewater called olive mill wastewater. This paper presents the study of the effect of transmembrane pressure and cross flow velocity on the decrease in permeate flux of different ultrafiltration membranes (material and pore size) when treating a two-phase olive mill wastewater (olive oil washing wastewater). Both semi-empirical models (Hermia models adapted to tangential filtration, combined model, and series resistance model), as well as statistical and machine learning methods (response surface methodology and artificial neural networks), were studied. Regarding the Hermia model, despite the good fit, the main drawback is that it does not consider the possibility that these mechanisms occur simultaneously in the same process. According to the accuracy of the fit of the models, in terms of R2 and SD, both the series resistance model and the combined model were able to represent the experimental data well. This indicates that both cake layer formation and pore blockage contributed to membrane fouling. The inorganic membranes showed a greater tendency to irreversible fouling, with higher values of the Ra/RT (adsorption/total resistance) ratio. Response surface methodology ANOVA showed that both cross flow velocity and transmembrane pressure are significant variables with respect to permeate flux for all membranes studied. Regarding artificial neural networks, the tansig function presented better results than the selu function, all presenting high R2, ranging from 0.96 to 0.99. However, the comparison of all the analyzed models showed that depending on the membrane, one model fits better than the others. Finally, through this work, it was possible to provide a better understanding of the data modelling of different ultrafiltration membranes used for the treatment of olive mill wastewater. [ABSTRACT FROM AUTHOR]

This paper is aimed at the problems of multiple factors influencing the roof stability near a heading face and unreasonable values of the unsupported distance leading to a slow excavation speed. The behavior of the direct roof subsidence in the unsupported area is analyzed, and numerical simulation and the response surface method are used to study the key factors affecting the roof deformation and their interaction relations. The results indicate that roof strength is the most critical factor affecting deformation and failure, followed by soft rock thickness, unsupported distance, and support strength. The interaction analysis in Zhaozhuang Coal Mine's 33082 lane shows that it is difficult to control the roof subsidence when the unsupported distance is more than 2 m and the soft rock thickness is more than 4 m. After the unsupported distance is set to about 2 m and the support strength is increased to 0.25 MPa, the excavation speed approximately doubles, and the overall roadway is stable and controllable. By implementing field applications, the rationality of the research approach was confirmed. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for robust design optimization of braced excavations in soft clay with response surface methodology based on the pareto-optimal trade-off between system performance and cost. As prediction of maximum ground settlement induced by excavation is generally accompanied by an implicit numerical model, the response surface methodology is employed to build the performance function with respect to both design parameters and uncertain geotechnical parameters. Then a pareto-optimal performance-based robust design framework of braced excavations in soft clay is formulated to find the optimal design that meets the design requirements while optimizing the system performance and construction cost. With the aid of a multi-objective optimization approach, trade-off relationship between performance robustness and cost efficiency are developed to help identify the most robust design based on the targeted performance levels. A design example of braced excavation in Taipei soft clay is used to illustrate the significance of the proposed methodology. [ABSTRACT FROM AUTHOR]

Under low-speed collision conditions, the thin-walled structures located at the forepart of passenger car act as a significant energy absorber, which can reduce the injury degree of passengers in collision accidents. Therefore, the design of thin-walled structures is particularly important in automobile body development. High stiffness and strength contribute to structural integrity, but the resulting large collision force will be detrimental to occupant safety. To address this issue, the paper proposed a novel negative Poisson ratio thin-walled tube (NPR-TWT). In addition, the second-order sensitivity-based response surface models (SB-RSMs) were established to improve the efficiency of design optimization. Furthermore, the NPR-TWT was optimized by using the non-dominated sorting genetic algorithm (NSGA-II) to enhance its comprehensive performance. The results showed that the optimized NPR-TWT could absorb collision energy by sufficient displacement deformation and reduce the peak impact force. It can provide theoretical and practical guidance for the application of thin-walled structures in automobile body safety. [ABSTRACT FROM AUTHOR]

In order to improve the adaptability of sweet cherry sorters to sweet cherries, a full-view-type grading cup for automated sweet cherry sorters was developed based on the physical characteristics of three species of sweet cherries: Tieton, Huang Mi, and Lapins. The structure and working principle of the full-view-type grading cup are described in this paper. The main factors affecting the operating stability of the grading cup were identified in this study by analyzing the mechanical properties of sweet cherries during the conveying and rotating process. According to the Box-Behnken test design method, we took the operating speed, the Young's modulus, and the friction coefficient of the double-roller supporter as the test factors and we took the success rate as the test index. The operating parameters of the full-view-type grading cup were tested and studied, and the regression model between the test index and the test factors was established. The influence law of each factor on the test index was analyzed, and the test factors were comprehensively optimized according to the regression model. The results showed that when the operating speed was 48 sweet cherries/min; the butadiene rubber (BR) 9000, with a Young's modulus of 0.012 GPa was selected as the material for making the double-support rollers; and the friction coefficient was designed to be 15, the success rate was 86.0%. The results of this research have provided a theoretical basis for the design and optimization of grading cups for automated sweet cherry sorters. [ABSTRACT FROM AUTHOR]

During the laser cladding process, active elements will affect the direction and speed of the molten pool flow, impacting the solidification and cladding quality of the molten pool. It is significant to quantitatively evaluate the sensitivity of the influence for the cladding process parameters on cladding quality. In this paper, a three-dimensional numerical model of the laser cladding Fe60 powder was established. The effect of sulfur element on the surface tension, fluid flow, and heat transfer were calculated and analyzed, and the instantaneous evolution laws of the temperature and flow field during the cladding process were revealed. The response surface model was established based on the Box–Behnken Design (BBD) method, and the influence of different process parameters on the cladding process were analyzed. The sensitivity was analyzed by the Monte-Carlo method. The cladding profile was observed by the scanning electron microscope (SEM) to verify the validity of the model. Calculations show that sulfur changes the direction of Marangoni convection, forming a deeper molten pool. The laser power is more sensitive to the effect of the cladding temperature, and the powder feeding rate is more sensitive to the effect of the molten pool flow rate. [ABSTRACT FROM AUTHOR]

Unlike soils contaminated with divalent toxic cations, trivalent arsenic (As)-contaminated soils are difficult to treat. In this context, the present study aims to propose a ferrous sulfate (FeSO4) combined solid waste-based gelling material (MRS) method to solidify/stabilize As-contaminated soils. The interactions between FeSO4 and gelling material components were further explored in this study using the response surface method (RSM). The results showed a decrease in the compressive strength of the solidified/stabilized soil with increasing FeSO4 proportion. The leached As concentration decreased with increasing FeSO4 proportion. The RSM-based quadratic polynomial model accurately predicted the leached As concentrations and compressive strength of the solidified soils. The X-ray diffraction analysis results demonstrated the promotion effect of FeSO4 on the generation of ettringite and Fe–As in the gelling system, resulting in enhanced further pore filling and As stabilization in the soil. The X-ray photoelectron spectroscopy analysis showed that about 52% of the As(III) content was oxidized to As(V) in the FeSO4-MRS system, enhancing the stabilization of As. The presence of As during the S/S process decreased the contents of Ca(OH)2 and Fe oxides/hydroxides by precipitation as Ca–As–O and Fe–As–O, respectively, decreasing the As leaching rate by 96.4%. The strength of solidified/stabilized soil using MRS and FeSO4 was close to that of cement-based solidified/stabilized soil. This paper provides a novel research idea and technical approach for the remediation of As-contaminated sites. Furthermore, the research results provide a scientific basis and theoretical support for the effective utilization of hazardous solid waste. [ABSTRACT FROM AUTHOR]

The paper presents an approach to parametric optimization with response surface methodology. This process was performed based on the design of a construction frame for a Cartesian industrial robot. The presented installation is dedicated to the real industrial pick-and-place application. Firstly, the case study was described with relevant information about the components involved. Then, the finite element model with constraints and loads, as well as the settings of the response surface optimization were discussed. The simulation was presented to the reader within all the stages with necessary details. Into consideration were taken six methods of creating response surfaces. Influence on the final optimization result and prediction accuracy of each one was presented. In the end, to validate the outcomes of the process, the static structural analysis of the setup was computed. The paper compares the impact of applying different methods of response surface generation on the results of parametric optimization. Moreover, it indicates the most vulnerable fragments of dynamically loaded elements made of construction profiles. Its results may be used to select appropriate settings in similar applications, mainly for frame structures. [ABSTRACT FROM AUTHOR]

A car muffler is a device to improve car noise emission. Some conventional mufflers use layers of glass fiber as a material to absorb noise. However, filling glass fiber is an environmentally unfriendly work, mainly manually filling with chop strand fiber. This research selected a composite material of glass fiber and foam concrete to replace chop strand fiber to avoid this hazard and maintain the muffler's good noise reduction performance. A response surface methodology with a two-way factorial experimental design repeated the center point twice is performed. The density of the foamed concrete and the weight of the glass fiber is being considered in order to determine the nearly optimal combination of the values in two factors. The response variable is the loudness sensation in Sone of the noise generated from the muffler. At present, the lowest loudness sensation from the two-way factorial design is 16.6494 Sones, which occurred for a muffler with a formula combination of a density of 0.2 g/cm3 and 40 g of glass fiber. The significance of this paper is the presentation of a new application of foam concrete to the green muffler design. To the best of our knowledge, this unique area has never been tackled in the material application of concrete. We have discovered that foam concrete indeed does an excellent job in terms of noise reduction as compared with that of a market muffler. [ABSTRACT FROM AUTHOR]

This paper presents optimisation of the geometry of the aircraft air–oil separator (AAOS) performed to improve the device performance. For this separator type, the most important operating parameters are the oil quality, efficiency and pressure drop. In order to understand the relationships between geometric parameters and their impact on the parameters of the separator operation, an analysis was conducted using the Response Surface Method (RSM). The analysis was made based on the results of numerical simulations and using the volume-of-fluid (VOF) method. Pareto analysis was also carried out, which determined the impact of the inlet width and height and the separator diameter on the device performance. By solving the optimisation task using a genetic algorithm, it was possible to propose a new geometry for the AAOS. The favourable geometric relations for the AAOS are indicated and they are compared with those preferred for other geometries of cyclone separators. [ABSTRACT FROM AUTHOR]

Aiming at the current problem of the high rate of impurity and loss in the cleaning device of corn seed harvesters in China, this paper took the cleaning device of 4YZL-6 self-propelled corn seed harvester as a sample and analyzed the movement law of the material on the sieve. Box-Behnken response surface experimental design theory was used for the orthogonal tests. Wind inlet angle, airflow velocity, and crank angular velocity were selected as influencing factors, and the impurity rate and loss rate as the evaluation index of operation quality. A regression mathematical model between each influencing factor and indicator was established, and the model was also integrated and optimized. The optimal parameter combination was obtained as follows: the wind inlet angle was 37.95o, the airflow velocity was 11.3 m/s, and the crank angular velocity was 4.1 r/s. The corresponding impurity rate was 0.87% and the loss rate was 0.34%. Verification tests were conducted on the optimization results, and the test results showed that under the optimal combination of parameters, the impurity rate was 0.89% and the loss rate was 0.35%. The relative errors of each evaluation index and its model prediction were 2.29% and 2.94%, respectively. [ABSTRACT FROM AUTHOR]

Gangue paste material is mainly composed of coal gangue with particle size, which is mixed with cement. Fly ash and additives can be added to change its performance. In this paper, the influence of each component on the mechanical properties of gangue paste material was studied by an orthogonal experiment. The conversion relationship among various indexes of mechanical properties of gangue paste material and the response surface prediction model were discussed. The results show that the mechanical properties of gangue paste materials are positively correlated with the content of cement, the content of fly ash and the mass concentration, which increase with the increase of the three factors, and show the primary and secondary relationship of the content of cement > the content of fly ash > the mass concentration. A response surface prediction model of mechanical property parameters is established, which includes the first order term of the influencing factors of gangue paste material and the first order interaction term between any two factors. In the response surface prediction model of uniaxial compressive strength, splitting tensile strength, cohesion and elastic modulus, the goodness of fit test coefficients are 0.998, 0.957, 0.970 and 0.997, respectively, which proves that the model has good goodness of fit. The research results provide basic parameters for paste filling mining practice, and also provide the basis for numerical simulation of filling body value. [ABSTRACT FROM AUTHOR]

In this paper, malic acid sweet potato starch ester (MSE) is prepared by the microwave assisted l‐malic acid method, and its digestibility is studied. Through a response surface methodology based on a Box‐Behnken design (BBD), the optimum conditions for the preparation of MSE are obtained as follows: mass ratio (mL‐malic acid: mstarch) of 0.81, pH value of 1.21, microwave time of 6.8 min, and microwave power of 435 W, respectively. Under these conditions, the degree of substitution of MSE is 0.0712. In addition, the freeze‐thaw stability, transparency, and solubility of the MSE are better than the native starch. Microwave assisted l‐malic acid treatment significantly increases the resistant starch (RS) content in starch sample. FTIR reveals a new characteristic peak near 1735 cm–1 in MSE samples, and the relative crystallinity decreases from 33.03% to 21.18%. Differential scanning calorimetry results show that the endothermic peak of MSE decreases. These results indicate that microwave‐assisted l‐malic acid can significantly change the physicochemical properties of sweet potato starch, and it is an effective method for the preparation of RS with heat‐stable resistance. [ABSTRACT FROM AUTHOR]

Purpose: In this article, a practical design methodology is proposed for discrete sizing optimization of high-rise concrete buildings with a focus on large-scale and real-life structures. Design/methodology/approach: This framework relies on a computationally efficient approximation of the constraint and objective functions using a radial basis function model with a linear tail, also called the combined response surface methodology (RSM) in this article. Considering both the code-stipulated constraints and other construction requirements, three sub-optimization problems were constructed based on the relaxation model of the original problem, and then the structural weight could be automatically minimized under multiple constraints and loading scenarios. After modulization, the obtained results could meet the discretization requirements. By integrating the commercially available ETABS, a dedicated optimization software program with an independent interface was developed and details for practical software development were also presented in this paper. Findings: The proposed framework was used to optimize different high-rise concrete buildings, and case studies showed that material usage could be saved by up to 12.8% compared to the conventional design, and the over-limit constraints could be adjusted, which proved the feasibility and effectiveness. Originality/value: This methodology can therefore be applied by engineers to explore the optimal distribution of dimensions for high-rise buildings and to reduce material usage for a more sustainable design. [ABSTRACT FROM AUTHOR]

This paper discusses the pitfalls of using response surface methods when solving inverse problems and presents an adaptive artificial neural network-based inverse response surface method. The procedure is based on a coupling of the adaptive response surface method and artificial neural network-based inverse reliability analysis. The validity and accuracy of the method are tested on several examples. The first is a problem with a theoretical explicit nonlinear limit state function and one design parameter. Here, the accuracy of surrogate models for design parameter identification was tested for cases with the target values of the identified parameter both inside and outside of the initial range of values. The absolute percentage errors were 11.79 % and 0.19 % after the first and the last iteration of the identification process, respectively. The other two examples represent practical applications of the reliability design of structures with multiple design parameters and multiple reliability constraints. In the former, the limit state functions are defined explicitly, while in the latter, they are defined implicitly in the form of a structural analysis using the nonlinear finite element method. When assessing the reliability index values, very low absolute percentage error values were obtained in both examples. For the explicit form of the limit state function, the values were up to 0.50 % in all iterations. In the case of the implicitly defined limit state function, the absolute percentage error was equal to 6.45 % after the fist iteration and 0.79 % after the second iteration. [ABSTRACT FROM AUTHOR]

In this paper, thermogravimetric-infrared spectroscopy was used to analyze co-pyrolysis of oily sludge (OS) from oil penetration and rice husks (RH) at various ratios (1:0; 3:1; 1:1; 1:3; 0:1), obtaining pyrolysis weight-loss behaviors, the laws of mutual synergy, and gas volatilization characteristics. The Coats-redfern and response surface method were employed to analyze kinetics and optimize pyrolysis, respectively. The T i , T max , and T f increase as the heating rate increases, and the weight loss increases in the second stage. With the increase of the proportion of RH, the T i and T max of the mixture increase, while the T f and residual content decrease. The co-pyrolysis of the OS and RH has synergistic effects. The addition of RH is beneficial to reduce the E of OS pyrolysis. The mixing ratio affects the strength of small-molecular-gases volatilization. When the RH ratio is 58.9% at 10K/min, the minimum predicted E and residual amount of co-pyrolysis are 58.602 kJ/mol and 42.6%, respectively. • The co-pyrolysis characteristics and synergistic effects of OS and RH were studied. • The reaction mechanism of co-pyrolysis was analyzed by FT-IR and kinetics. • Heating rate of 10 °C/min was more favorable to co-pyrolysis of OS and RH. • Low activation energy condition was mixing ratio (58.9%) and heating rate (10 °C/min). [ABSTRACT FROM AUTHOR]

This paper investigates the efficiency of three surrogate model-based dynamic finite element model updating methods, the response surface, the support vector regression, and the radial basis function neural network, using the engineering background of the Tsing Ma Bridge tower. The influences of two different sampling methods (central composite design sampling and Box–Behnken design sampling) on the model updating results are also assessed. It was deduced that the impact of the surrogate model type on the updating results is not significant. More precisely, the models updated using the response surface method and the support vector regression method are similar in terms of reproducing the dynamic characteristics of the physical truth. However, the effects of the employed sampling method on the model updating results are significant as the model updating quality using the central composite design sampling method is higher than that using the Box–Behnken design sampling method in some considered cases. [ABSTRACT FROM AUTHOR]

In simulation-based realization of complex systems, we are forced to address the issue of computational complexity. One critical issue that must be addressed is the approximation of reality using surrogate models to replace expensive simulation models of engineering problems. In this paper, we critically review over 200 papers. We find that a framework for selecting appropriate surrogate modeling methods for a given function with specific requirements has been lacking. Having such a framework for surrogate model users, specifically practitioners in industry, is very important because there is very limited information about the performance of different models before applying them on the problem. Our contribution in this paper is to address this gap by creating practical guidance based on a trade-off among three main drivers, namely, size (how much information is necessary to compute the surrogate model), accuracy (how accurate the surrogate model must be) and computational time (how much time is required for the surrogate modeling process). Using the proposed guidance a huge amount of time is saved by avoiding time-consuming comparisons before selecting the appropriate surrogate model. To make this contribution, we review the state-of-the-art surrogate modeling literature to answer the following three questions: (1) What are the main classes of the design of experiment (DOE) methods, surrogate modeling methods and model-fitting methods based on the requirements of size, computational time, and accuracy? (2) Which surrogate modeling method is suitable based on the critical characteristics of the requirements of size, computational time and accuracy? (3) Which DOE is suitable based on the critical characteristics of the requirements of size, computational time and accuracy? Based on these three characteristics, we find six different qualitative categories for the surrogate models through a critical evaluation of the literature. These categories provide a framework for selecting an efficient surrogate modeling process to assist those who wish to select more appropriate surrogate modeling techniques for a given function. It is also summarized in Table 4 and Figs. 2, 3. MARS, response surface models, and kriging are more appropriate for large problems, acquiring less computation time and high accuracy, respectively. Also, Latin Hypercube, fractional factorial designs and D-Optimal designs are appropriate experimental designs. Our contribution is to propose a qualitative evaluation and a mental model which is based on quantitative results and findings of authors in the published literature. The value of such a framework is in providing practical guide for researchers and practitioners in industry to choose the most appropriate surrogate model based on incomplete information about an engineering design problem. Another contribution is to use three drivers, namely, computational time, accuracy, and problem size instead of using a single measure that authors generally use in the published literature. [ABSTRACT FROM AUTHOR]

The introduction of stainless-steel legged tanks is rather recent, and their use increased in the last decades in exponential way, especially in food industry and agricultural applications since they proved to be simple to prefabricate and transport, easy to clean and chemically inert. Despite their worldwide diffusion also in high seismicity areas, most of them were not designed with earthquake-based criteria as emerged by the catastrophic consequences and heavy losses observed, even recently, after several major earthquakes. By means of incremental dynamic analyses on the finite element models of 140 winemaking and storage legged tanks, the present paper, evaluates the main features of the dynamic response and for each vessel provides the lognormal cumulative fragility functions, for three different limit states of each vessel. Then, for each limit state, by means of nonlinear regression analyses, the median and the dispersion parameters of the best fitting lognormal function of every tank were statistically elaborated in order to define the response surfaces of the parameters. The response surfaces, provided for 3-, 4- and 5-leg unanchored tanks, are defined on the basis of few geometrical tank data. The analytical expressions provided in the paper, represent a practical and useful tool to directly calculate the fragilities of legged vessel. These, obviously, will allow the fast assessment of the seismic vulnerability of the tanks in agricultural facilities located in seismic prone areas. [ABSTRACT FROM AUTHOR]

This paper aims to develop an optimal design mixture for concrete containing lightweight expanded clay aggregates (LECA) and silica fume with a holistic view in which the mechanical properties, strength retention at elevated temperatures, costs, and environmental impacts are all considered. Following the response-surface methodology, 30 concrete mixtures were developed, which contained different water-to-cement ratios (0.25–0.5), total cementitious materials contents (300–700 kg/m3 of concrete), and different amounts of LECA (0%–100% of the total aggregate volume) and silica fume (5%–15% of weight of total cementitious material). The mixtures were used to fabricate a total of 240 concrete cylinders, half of which remained at the ambient temperature, whereas the other half were exposed to an elevated temperature of 750°C for 2 h. The results of mechanical tests on specimens were combined with the economic and environmental performance indices to find the optimal mix design. The result showed that using a mixture containing 0.33 water-to-cement ratio, 300 kg/m3 cement content, 14.97% silica fume and 84% total aggregate replacement by LECA may lead to the concrete that performs the best in terms of mechanical characteristics, strength retention during fire, and economic and environmental impacts. [ABSTRACT FROM AUTHOR]

This paper, through the theory of multi-objective parameter optimization, the finite-element analysis and central composite test of the blanking process of the locating plate of the breaker are carried out. The optimal blanking process parameters of the positioning plate of the circuit breaker are determined, and the influence laws of the independent variable blanking gap, the punch edge radius and the blanking speed on the maximum blanking force and the length of the bright belt are obtained. The experimental results show that the production efficiency of the positioning plate of the circuit breaker is increased by 25%, and the actual machining error is only 4%, which provides a certain guiding significance for optimizing the blanking process parameters. [ABSTRACT FROM AUTHOR]

Cotton stalk is an important renewable resource. China is rich in cotton stalk, if such a large amount of resources are recycled, it will produce huge economic benefits. But most of them are not recycled at present. In order to improve the mechanized recovery level of cotton stalk, study the influence of different parameters on the mechanized recovery of cotton stalk, and solve the outstanding problems such as high cotton stalk plucking rate and high cotton stalk leakage rate, this paper studied and designed a toothed disc cotton stalk harvester. The machine was consisted of suspension device, limit wheel, pull-out tooth plate, stalk discharge device, hydraulic motor, hydraulic pipeline and hydraulic control box. The key component of the machine was a toothed disc type stalk pulling device. During operation, the cotton stalk was lifted out through the toothed disc, and then the cotton stalk was discharged to the surface through the stalk discharge device. Leakage rate and plucking rate of cotton stalk were the main parameters to evaluate the performance of toothed disc cotton stalk harvester. In this paper, Box-benhnken central combination test method was used to study the working parameters of toothed disc cotton stalk harvester. Three-factor and three-level quadratic regression orthogonal test was designed. The three-dimensional model of response surface was established with the diameter of the toothed disc, the toothed disc speed ratio and the lifting height as the influencing factors. The influence of each factor on the quality of work was analyzed, and the influencing factors were optimized synthetically. The results showed that the lifting height and the toothed disc speed ratio had significant effects on the cotton stalk plucking rate (P< 0.01), while the lifting height, the diameter of the toothed disc and the toothed disc speed ratio had significant effects on the rate of cotton stalk leakage rate (P<0.01). The working parameters of the machine were deduced from the regression model optimization as follows: the lifting height was 66.2 mm, the diameter of the toothed disc was 627.59 mm, and the toothed disc speed ratio was 0.57. In November 2018, field test was carried out in the Yellow River Delta (Binzhou) National Agricultural Science and Technology Park. Test area was divided into 17 test plots, leakage rate and plucking rate of cotton stalk at each test plot were calculated. The results of the Daejeon experiment showed that when the lifting height was 70 mm, diameter of the toothed disc was 630 mm and the toothed disc speed ratio was 0.57, the cotton stalk plucking rate could reach 1.5% and the cotton stalk leakage rate was low to 3.0%. The test results showed that the theoretical results were coincident with the measuring results, and the error between them was less than 4%. The research results can provide references for the structure improvement design and operation parameters optimization of toothed disc cotton stalk harvester. [ABSTRACT FROM AUTHOR]

Cotton stalk is an important renewable resource. China is rich in cotton stalk, if such a large amount of resources are recycled, it will produce huge economic benefits. But most of them are not recycled at present. In order to improve the mechanized recovery level of cotton stalk, study the influence of different parameters on the mechanized recovery of cotton stalk, and solve the outstanding problems such as high cotton stalk plucking rate and high cotton stalk leakage rate, this paper studied and designed a toothed disc cotton stalk harvester. The machine was consisted of suspension device, limit wheel, pull-out tooth plate, stalk discharge device, hydraulic motor, hydraulic pipeline and hydraulic control box. The key component of the machine was a toothed disc type stalk pulling device. During operation, the cotton stalk was lifted out through the toothed disc, and then the cotton stalk was discharged to the surface through the stalk discharge device. Leakage rate and plucking rate of cotton stalk were the main parameters to evaluate the performance of toothed disc cotton stalk harvester. In this paper, Box-benhnken central combination test method was used to study the working parameters of toothed disc cotton stalk harvester. Three-factor and three-level quadratic regression orthogonal test was designed. The three-dimensional model of response surface was established with the diameter of the toothed disc, the toothed disc speed ratio and the lifting height as the influencing factors. The influence of each factor on the quality of work was analyzed, and the influencing factors were optimized synthetically. The results showed that the lifting height and the toothed disc speed ratio had significant effects on the cotton stalk plucking rate (P< 0.01), while the lifting height, the diameter of the toothed disc and the toothed disc speed ratio had significant effects on the rate of cotton stalk leakage rate (P<0.01). The working parameters of the machine were deduced from the regression model optimization as follows: the lifting height was 66.2 mm, the diameter of the toothed disc was 627.59 mm, and the toothed disc speed ratio was 0.57. In November 2018, field test was carried out in the Yellow River Delta (Binzhou) National Agricultural Science and Technology Park. Test area was divided into 17 test plots (each plots is 30 m×0.76 m), leakage rate and plucking rate of cotton stalk at each test plot were calculated. The results of the Daejeon experiment showed that when the lifting height was 70 mm, diameter of the toothed disc was 630 mm and the toothed disc speed ratio was 0.57, the cotton stalk plucking rate could reach 1.5% and the cotton stalk leakage rate was low to 3.0%. The test results showed that the theoretical results were coincident with the measuring results, and the error between them was less than 4%. The research results can provide references for the structure improvement design and operation parameters optimization of toothed disc cotton stalk harvester. [ABSTRACT FROM AUTHOR]

Fish meal is rich in protein and fat and is the main animal-derived feed material. In the process of transportation and storage, the fish meal can be easily to deteriorate, resulting in the reduction of its nutritional components. This is not only endangers the normal reproduction and health of animals, but also poses certain potential safety hazards to the safety of animal-derived food and human health. It is necessary to carry out an effective detection for quality of animal-derived feed. In recent years, bionic olfaction technology has developed rapidly, it can quickly detect the quality of products, compared with near infrared spectroscopy and traditional physical and chemical index detection methods, it is faster and more accurate, but it is rarely used in the quality detection of fish meal. Therefore, in order to solve the above problems, a portable detection device on quality of fish meal has been developed in this paper. The hardware part of the device is mainly composed of a gas acquisition and transmission module, a control processing storage module, a data acquisition module, and a sensor array module, which the gas acquisition and transmission module includes a sample supplement gas cylinder, a sample gas generation chamber, an activated carbon purification bottle, two two-position two-way electromagnetic valves, a micro air pump, a gas flowmeter, a gas sampling chamber, and a one-way valve. In the software part, the strawberry pie is the core, qt creator graphical programming software across platforms was selected, and the real-time data acquisition display and storage part was mainly designed. The key component was the 10-bit ARPI600 data acquisition module. The device could basically realize the quality detection of fish meal, and the detection result was relatively accurate. In order to obtain the detection performance of the device, the test parameters of the device needed to be optimized. First, fresh fish meal was placed in a 35 ℃ thermostatic artificial climate box to make it decay gradually at the storage time. Fish meal of different levels was collected as the test sample during the storage process, and a total of six types of fish meal samples which was at different storage times were selected for the samples of the test. In this paper, it selected the factors that included gas flow, sampling time and cleaning time that had a great influence on the detection results, taking the dispersion ratio as an index, the optimal parameters were obtained through optimization analysis by using response surface method and design - expert software, and the feasibility and detection performance of the detection device for fish meal quality under the optimal parameters were verified. The test results showed that the gas flow rate, sampling time and cleaning time were all significant factors, and the primary and secondary order of factors was as follow: Cleaning time, sampling time and gas flow, and the interaction between them was significant. With the increase of gas flow and sampling time, the dispersion ratio tended to decrease first and then increase, and when the gas flow was in the range of 2-2.5 L/min and the sampling time was in the range of 35-45 s, the dispersion ratio was small. As the gas flow increased, the cleaning time decreased, while the dispersion ratio decreased first and then increased. When the gas flow rate was 2-2.5 L/ min and the cleaning time was in the range of 75-80 s, the dispersion ratio was small. As the sampling time increased, the cleaning time decreased, the dispersion ratio decreased first and then increased, and when the sampling time was in the range of 35-40 s and the cleaning time was in the range of 75-80 s, the dispersion ratio was small. In considering of all factors, the best parameters were 2.2 L/min of gas flow, 39 s of sampling time and 77 s of cleaning time. At this time, the dispersion ratio was the smallest, which was 0.579 9. Under the optimal parameters, fish meal samples with different storage time were tested, and the accuracy of different storage time discrimination was 89.4%, which could realize the detection of quality of fish meal and provide data reference and technical support for the subsequent research on the quality detection device. [ABSTRACT FROM AUTHOR]

This article studies the structure of hydraulic spool valve and the influence of different pressure differences on steady-state flow force. An improved scheme of designing a jet guide groove on the valve core is proposed to compensate for steady-state flow force. This article uses the CFD method to study the influence of spool valve structural parameters on steady-state flow force. The response surface method is used to establish the Polynomial regression model of the steady-state flow force, and the optimal structure size of the jet guide slot is obtained. The results indicate that the flow force increases with the increase of pressure difference. Moreover, under the same operating conditions, the absolute flow force of the spool valve with jet guide groove is smaller than that of the spool valve without jet guide groove. Therefore, the jet guide groove can effectively compensate for steady-state flow force, improve the control accuracy of the valve, and improve the stability of the spool valve. • This paper describes the principle of hydrodynamic force generation and the effect of spool structure on hydrodynamic force. • A new deflector structure consisting of a combination of triangles and circular arcs is proposed. • This structure reduces the impact of the fluid on the spool and reduces the loss of the spool. • Velocity and pressure clouds for different structures are derived and optimal structural parameters are derived. [ABSTRACT FROM AUTHOR]

• A unit-level digital twin model for predictive monitoring (DTMAR) is developed. • Real-time structural reliability evaluation model of battery brackets is proposed. • A new m-layers sampling space is defined for the samples required for modeling. • One case study for the battery bracket of a new energy commercial vehicle is given. Battery bracket for new energy commercial vehicles is subjected to variable loads and battery temperature changes both during the design road test phase and in-service operation. Therefore, their structural performance must be evaluated in real-time for reliability design and health monitoring. With the rapid development of industrial digitization, the digital twin has become an indispensable technology. This paper proposes a digital twin approach for predictive monitoring of the performance of mechanical structures. Taking the structural performance for the battery bracket of new energy commercial vehicles as an example, this paper builds a unit-level digital twin model—DTMAR. It comprises the numerical model, NN-RSR model, and hybrid machine learning model. The results reveal that the DTMAR model can efficiently and accurately calculate and predict the structural performance. This can not only provide constructive guidance for optimal design of the next generation product structure, but also aid in evaluating the structural reliability of the battery bracket of new energy commercial vehicles and improve their driving safety. [ABSTRACT FROM AUTHOR]

Abstract: Robust parameter design (RPD) aims to build product quality in the early design phase of product development by optimizing operating conditions of process parameters. A vast majority of the current RPD studies are based on an uncensored random sample from a process distribution. In reality, censoring schemes are widely implemented in lifetime testing, survival analysis, and reliability studies in which the value of a measurement is only partially known. However, there has been little work on the development of RPD when censored data are under study. To fill in the research gaps given practical needs, this paper proposes response surface–based RPD models that focus on survival times and hazard rate. Primary tools used in this paper include the Kaplan‐Meier estimator, Greenwood's formula, the Cox proportional hazards regression method, and a nonlinear programming method. The experimental modeling and optimization procedures are demonstrated through a numerical example. Various response surface–based RPD optimization models are proposed, and their RPD solutions are compared. [ABSTRACT FROM AUTHOR]

Electromagnetic devices containing permanent magnet (PM) are common and typical electromagnetic devices that have advantages of low-power consumption, small size, high sensitivity, and its optimization problem has aroused widespread concern. Calculation accuracy of electromagnetic properties and efficiency of optimization processes are two important factors that affect the optimization effect of electromagnetic devices. A fast calculation method was proposed in this paper that aimed at electromagnetic devices with PM characteristics of strong non-linearity and low solving precision. The response surface method was used to derive the basis function, and the error between actual measured values and calculated values was modified by the Kriging method. On the basis of the calculation model, the distributed collaborative strategy was adopted to fulfill the parallel execution of the fast computation. Simultaneously, the updating strategy of particles was improved, and the robustness of the multi-objective particle swarm optimization algorithm in solving the optimization problem of electromagnetic devices with PM was enhanced. Effectiveness of the method proposed in this paper was verified by the case study of a specific type of electromagnetic relay with PM. [ABSTRACT FROM AUTHOR]

In this paper, first-order response surface model incorporating neighbour effects from experimental units up to distance 2 has been discussed where experimental plots experience the neighbour effects from immediate left and right neighbouring units as well as from units at distance 2 assuming the plots are placed linearly without gaps. Conditions have been derived for the orthogonal estimation of the parameters of the model. A method of constructing designs for fitting first-order response surface model which ensures the constancy in the prediction variance after incorporating neighbor effects up to distance 2 has been developed and named as FORDDNE-2. [ABSTRACT FROM AUTHOR]

Sweet potato is an important food crop and energy crop. In order to solve the problems of larger loss rate and high damage rate of 4UZL-1 sweet potato combine harvester during the operation process, a potato connection and conveying mechanism was designed based on the analysis of the structure of 4UZL-1 sweet potato combine harvester and characteristics of domestic sweet potato planting models in this paper. The potato connection and conveying mechanism was mainly composed of a depth limiting mechanism, a digging conveying mechanism, an arc grid conveying mechanism and a scraper chain conveying mechanism. The working parameters were obtained through the kinematic and mechanical analysis of the working process of the mechanism. Aiming at the main evaluation indexes of potato damage rate and loss rate during the transfer and transportation, the Box-Benhnken test was presented on the basis of single-factor test. The angle of the digging conveyor, the conveyor angle of the scraper chain, the conveyor speed of the digging and the conveyor speed of the scraper chain were selected as testing factors. The multiple regression model of evaluation index to each factor was established, and the influence of each factor on operation quality was analyzed, and the optimal structure and operation parameters were obtained. The results showed that the order of the significance influence of factors on potato loss rate from large to small was that the conveyor angle of the scraper chain, the conveyor speed of the digging conveyor, the conveyor speed of the scraper chain and the angle of the digging conveyor. The order of the factors influencing on potato damage rate from large to small was the conveyor speed of the digging, the angle of the digging conveyor, the conveyor speed of the scraper chain and the conveyor angle of the scraper chain. When the forward speed of the machine was 1 m/s, the angle of the digging conveyor was 20°, the conveyor angle of the scraper chain was 68°, the conveyor speed of the digging was 1.2 m/s, and the conveyor speed of the scraper chain was 0.67 m/s, respectively, the potato loss rate was 1.12%, and the potato damage rate was 0.94%. Compared with the predicted values, the relative errors were 3.4% and 1.1%, respectively, the results satisfied the performance requirements of the 4UZL-1 sweet potato combine harvester. The study is benefit for the structure improvement and operation parameters optimization of the sweet potato combine harvester. [ABSTRACT FROM AUTHOR]

Phytosterol glycosides (PGs), comprising both acylated steryl glycosides (ASGs) and steryl glycosides (SGs), are active ingredients with benefits for human use. Here, we aimed to optimize the silica‐gel adsorption technique for the extraction of PGs from soybean lecithin powder, which contains 5 to 10% of these glycolipids. Both response surface methodology (RSM) and artificial neural networks (ANNs) were applied to optimize the PG extraction parameters (X1 = silica‐gel dosage, X2 = adsorption temperature, and X3 = lecithin concentration) for high‐purity phospholipid and PG production, and their prediction and optimization accuracies were compared. Although both models fitted well with the experimental data, the ANN model demonstrated better accuracy for predicting and optimizing the conditions using four interrelated dependent variables (Y1 = phospholipid yield, Y2 = ASG recovery, Y3 = SG recovery, and Y4 = PG purity) and had a higher coefficient of determination and lower root mean square error and absolute average deviation. After digitally setting the percentages of the four dependent variables for phospholipid and PG production, the ANN‐optimized phospholipid product (Y1 = 88.07%, Y2 = 98.89%, Y3 = 100%, and Y4 = 49.03%) was acquired at X1 = 3.54 g/g, X2 = 26 °C, and X3 = 43 mg/mL, whereas the PG product (Y1 = 83.83%, Y2 = 97.64%, Y3 = 100%, and Y4 = 59.21%) was obtained at X1 = 2.00 g/g, X2 = 28.38 °C, and X3 = 41 mg/mL. In conclusion, the ANN method was better than RSM for the optimization of the silica‐gel adsorption technique for PG extraction from soybean lecithin powder. Practical Application: This paper lays a theoretical foundation for the optimization of the industrial production of phytosterol glycosides and the comprehensive utilization of lecithin resources. [ABSTRACT FROM AUTHOR]

Cotton is an important cash crop in China, the cotton straw produced after cotton harvest is an important biomass energy. In view of the environmental problems existing in the traditional utilization of cotton straw, it is of great significance to transform cotton straw from agricultural waste to biochar. Based on the research of biochar processing equipment for cotton straw at home and abroad, it can be found that biomass carbonization equipment is mainly divided into microwave cracking carbonization and traditional electric heating carbonization. The traditional carbonization technology has the disadvantages of uneven carbonization and low carbonization efficiency. The traditional carbonization technology has the disadvantages of uneven carbonization and low carbonization efficiency, microwave cracking carbonization can not only improve carbonization homogeneity, but also shorten carbonization time. In order to improve the carbon yield of cotton straw and analyze the effect of different operation parameters on the carbon yield of cotton straw by microwave pyrolysis, a microwave cracking equipment was developed in this paper. The microwave cracking equipment was mainly composed of gas-liquid treatment system, cracking chamber, inert gas supplying system, constant temperature control system and so on. The key component of the equipment was the magnetron device in the cracking chamber, the magnetron device provided energy for the pyrolysis and carbonization of the cotton straw. Taking the moisture content of cotton straw, carbonization time and microwave power as the experimental factors and the carbon yield of cotton straw as the index, the response surface tests of three factors and three levels were carried out for the microwave cracking process of cotton straw. The quadratic polynomial response model of cotton yield of cotton straw to experimental factors was established. The significant order of the influence of each experimental factor on the carbon yield of cotton stalk was determined as water content of cotton straw, microwave power and carbonization time. Optimization of operation parameters was carried out by box benhnken combined test method, the result was that the moisture content of the cotton straw was 11%, carbonization time was 6 min and microwave power was 1.8 kW, at this time, the carbon yield reached 31.61%. The verification test results showed that under the optimal parameter conditions, the carbon yield of cotton straw was 30.9%, and the relative error with the theoretical value was 0.71%, the designed microwave cracking equipment basically meet the design requirements. The results can provide reference for the design and operation parameters optimization of microwave cracking equipment for cotton straw. [ABSTRACT FROM AUTHOR]