Orthogonal Experimental Design Research Articles

The Optimization of the Rear Guide Vane of a Bulb Tubular Pump Based on Orthogonal Tests

Bulb tubular pumps have been widely used in hydraulic engineering because of their compact structure, easy maintenance, high adaptability, and other characteristics. In this paper, the performance optimization of the bulb tubular pump in the South-to-North water diversion project is studied, as well as the influence of the design of the rear guide vane structure on the hydraulic efficiency of the pump. This study takes a certain type of bulb tubular pump as its research object, optimizing the rear guide vane. Firstly, the accuracy of the numerical simulation method is verified using grid convergence analysis and model experimentation. The orthogonal experimental design method is used to optimize the design, and the range analysis results show that the blade wrap angle has the most significant influence on the hydraulic efficiency and head. Finally, the optimization results under a 0° impeller setting angle were verified by numerical analysis, and the hydraulic efficiency of the optimized pump was increased by 0.7%, 0.88%, and 1.1% under low flow, design flow, and high flow, respectively. By introducing entropy generation theory for inflow analysis, the reduction in energy loss in the pump is proven, thus verifying the effectiveness of the optimization. Through the optimization, the separation fluid phenomenon on the guide vane surface is improved, the vortex scale is reduced, and the flow field in the pump is improved to a certain extent.

Research on Optimal Crop Planting Strategy Based on Improved Quantum Genetic Algorithm

In order to effectively cope with the complex agricultural environment and market uncertainty, this study proposed a crop planting optimization strategy based on the improved quantum genetic algorithm (QGA). Single-objective and multi-objective optimization models were proposed, focusing on profit maximization and risk balance under market fluctuations. The single-objective model used QGA to evaluate the optimal planting scheme under surplus and discount sales scenarios, and analyzed the crop area distribution and total income. For multi-objective optimization, the enhanced MO-QGA model combined with orthogonal experimental design generated a scheme that maximized expected income while minimizing the worst outcome. In addition, this study combined Pearson correlation and hierarchical clustering to quantify the substitutability and complementarity of crops, and optimized the planting strategy through crop combination analysis. The experimental results show that the enhanced QGA effectively balances profits and risks, and the effect is significantly better than traditional methods, which is conducive to improving agricultural decision-making efficiency

Co-application of polyethylene oxide (PEO), biochar, and seaweed fertilizer improves desert soil properties

Improving water retention, erosion resistance and nutrients in desert areas is essential for ecological sustainability. This study evaluated the effects of biochar, polyethylene oxide (PEO), and seaweed fertilizer on the properties of desert sandy soil, focusing on water retention, erosion resistance, and soil nutrients. The sandy soil used in the study was taken from the Tengger Desert in Gansu, China, and an orthogonal experimental design was used to select three different proportions of biochar, PEO, and seaweed fertilizer. Compared with the control, applying of these three substances decreased bulk density by 5.8–9.6%, increased porosity by 8.3–14%, and increased water-holding capacity by 2.2–6.7%. The erosion rate decreased by more than 99%, and water-stable aggregates increased by 9.7–37.4%. Soil nutrients showed varying degrees of increase, and seed germination increased by 26.7%. The results of the principal component analysis showed that B6P0.6S2 had the best overall improvement effect. Therefore, a ratio of 6% biochar, 0.6% PEO, and 2% seaweed fertilizer is recommended to improve the properties of sandy desert soils. Overall, biochar, PEO, and seaweed fertilizer can improve the physical properties of desert sandy soil, enhance soil nutrients, and create a stable and suitable environment for plant growth.

Effect of Dynamic Corrosion and Degradation on Fatigue Life of an AA2024-T3 Aircraft Profile: Experimental, Statistical, and Numerical Analyses

The effect of parameters such as angle of attack, flow velocity, and electrolyte concentration (saline solution) on the extent of material degradation, as well as the morphology and depth of corrosion pits in an airfoil made of 2024-T3 aluminum alloy, was studied in detail. An orthogonal L9 design of experiments (Taguchi method) was applied to promote high pitting corrosion through the quality characteristic “the higher the better”. Potentiodynamic curves of the three experiments with low, medium, and high saline concentration were obtained through the CorrTest CS350 equipment. The above allowed the determination of the electrochemical corrosion parameters under static test conditions. The corroded airfoils were analyzed using light optical microscopy (LOM). In addition, the roughness measurements correlated with the extent of the degraded surface. A complete pit shape and depth characterization was obtained by applying mechanical ground, surface wear level monitoring (every 0.01 mm), and LOM observations. Pitting defects (depth and morphology) and mechanical strength reduction were considered by a finite element (FE) model to simulate the airfoil fatigue behavior. Numerical results helped to determine the contribution of pitting and the extent of degradation on sudden airfoil failure.

Effects of Forest Land Mulching on the Soil CO2 Emission Rate of Phyllostachys violascens Forests

This study investigates the dynamics of soil CO2 emissions during the cover period of Phyllostachys violascens and the impact of different cover measures, aiming to provide references for reducing the environmental effects of bamboo cover. An L27 (913) orthogonal experimental design was employed, setting the following variables: (1) heating materials: chicken manure, straw cake, and wheat ash; (2) thickness of husk layer: 15 cm, 25 cm, and 35 cm; (3) soil moisture levels before covering: moisture to 10 cm, 15 cm, and 20 cm. The soil CO2 emission rate showed a unimodal curve, with a significant overall increase during the cover period. Throughout the entire cover period, the average soil CO2 emission rate (25.39 μmol·m−2·s−1) was 5.1 times higher than that of the uncovered Lei bamboo forest (5.02 μmol·m−2·s−1) during the same period. Thicker husk layers (25 cm and 35 cm) corresponded to higher soil CO2 emission rates, with significant differences noted among the thicknesses. When the soil was moist to 10 cm, the CO2 emission rate was highest (62.51 μmol·m−2·s−1); moisture to 15 cm and 20 cm resulted in significantly lower emission rates. Chicken manure produced the highest peak CO2 emissions in the third week, at 70.64 μmol·m−2·s−1, while straw cake and wheat ash reached their peaks in the fifth week, at 66.56 μmol·m−2·s−1 and 57.58 μmol·m−2·s−1, respectively. The interactions between the three factors (heating materials, husk layer thickness, and moisture levels) significantly affected the soil CO2 emission rates. By optimally configuring these factors, CO2 emissions can be regulated. This study recommends using wheat ash or straw cake as heating materials, combined with a 25 cm husk layer thickness, and moistening the soil to 15 cm before covering. This approach effectively reduces the peak and total soil CO2 emissions while ensuring suitable soil temperatures for the growth of bamboo shoots in spring. This research provides a scientific basis for the environmental management of bamboo forests, aiding in the optimization of covering measures to achieve low-carbon and sustainable bamboo management.

Investigation of the Effect of Cutting-Edge Rounding on Surface Quality in Milling of Al 7075 and Al 6082 Alloys

Al 7075 and Al 6082 alloys are alloys that are widely used in many sectors, especially aviation and automotive. During their processing along with the widespread use of those alloys, significant machinability problems such as low surface quality due to chip accumulation (Built Up Edge-BUE) on the cutting edge are observed. In this study, the effect of cutting-edge corner rounding and machining parameters on surface roughness in milling of Al 7075 and Al 6082 alloys were experimentally investigated. To determine the effect of cutting-edge rounding, two different corner rounding values (5.5-6 µm and 7-9 µm) were applied and compared with standard/coated and standard/uncoated tools in terms of machining performance. In the experimental studies, cutting parameters were determined as two different cutting speeds (300 m/min, 400 m/min) and two different feed rates (0.085 mm/tooth, 0.11 mm/tooth). With each tool, peripheral milling was performed on four sides of the prismatic test specimens under dry machining conditions. Taguchi L8 orthogonal array experimental design was used as the experimental design. Analysis of variance (ANOVA) was performed to evaluate the effects of cutting parameters on surface roughness and the reliability of all results was above 85%. The results of the analysis of variance revealed that the alloy type was more effective on the surface roughness. In the surface roughness measurements, the best surface roughness values (Ra=0.14 µm) were obtained in the experiments performed with a standard/coated cutting tool using a cutting speed of 300 m/min and a feed rate of 0.11 mm/tooth.

A reinforcement learning based memetic algorithm for energy-efficient distributed two-stage flexible job shop scheduling problem

Given the increasingly severe environmental challenges, distributed green manufacturing has garnered significant academic and industrial interest. This paper addresses the distributed two-stage flexible job shop scheduling problem (DTFJSP) under time-of-use (TOU) electricity pricing, with the objective of minimizing both makespan and total energy consumption costs (TEC). To tackle the problem, a hybrid memetic algorithm (HMA) is proposed. Initially, a three-tier vector encoding scheme and three population initialization strategies are devised. Subsequently, global search operators are tailored to the problem’s characteristics, and seven local search algorithms based on Q-learning are introduced. Additionally, an energy-saving operator is incorporated. Finally, orthogonal experimental design is employed to set algorithm parameters and validate the efficacy of some components. The numerical experimental results demonstrate that the proposed local search operator and energy-saving strategy are effective. Furthermore, the HMA exhibits superior diversity, breadth, and distribution compared to VNS, CMA, and NSGA-II, thereby validating the efficacy of the specialized designs of the HMA in addressing the DTFJSP.

Calibration and Testing of Discrete Element Simulation Parameters for Ultrasonic Vibration-Cutter-Soil Interaction Model

This paper established an accurate discrete element for ultrasonic vibration-cutter-soil interaction model to study the interaction mechanism between the soil-engaging component and the soil. In order to reduce the interaction between calibration parameters and improve the calibration accuracy, it is proposed that the soil constitutive, contact parameters, and bonding parameters be calibrated by combining the soil repose angle experiment and the soil resistance experiment of ultrasonic vibration cutting. The study adopts the Hertz-Mindlin (no slip) contact model used in EDEM, to explore soil particle interactions. The central composite design is used to achieve systematic investigation. 3-factor 3-level orthogonal design experiment was employed using the coefficient of restitution, the coefficient of static friction, and the coefficient of rolling friction as key test factors and soil’s repose angle as the response index. Based on the Hertz-Mindlin with bonding contact model, Design-Expert 13.0 software was used to design the Plackett-Burman experiment, the steepest ascent, and the Box-Behnken experiment. With the maximum soil cutting resistance in ultrasonic vibration cutting experiment used as the response value, the adhesion parameters were optimized, and the optimal solution combination was obtained as: Normal Stiffness = 4.635 × 106 N/m, Shear Stiffness = 3.401 × 106 N/m, and Bonded Disk Radius = 2.57 mm. The optimal parameter combinations obtained from the calibration experiments were verified in two ways: ultrasonic vibration cutting and non-ultrasonic vibration cutting. The results showed that the errors between the simulation values and the actual values of the two comparative experiments were less than 5%, and the model calibrated for the three parameters can be used to study the drag reduction mechanism of ultrasonic vibration cutting in soil.

Experimental Study of Material Proportioning for Similar Modeling of Brittle Rocks

Over the past 30 years, China has emerged as the country with the world’s largest engineering construction industry. However, rockbursts induced by tunnel excavation in rock engineering have resulted in a substantial number of casualties and extensive property damage. Understanding the brittle failure behavior of rock masses and identifying the mechanism of rockbursts have become critical challenges in the field. Physical model tests can provide a more intuitive simulation of the rockburst process. The selection and proportioning of materials similar to brittle rocks are crucial factors for the success of these model tests. This study selected refined iron powder, barite powder, quartz sand, gypsum powder, and a rosin–alcohol solution to prepare rockburst simulation materials characterized by a low strength and high brittleness. The rockburst tendency and brittleness indices were introduced, and an orthogonal experimental design was used to establish 25 different formulation schemes. The influence of the material component proportions on the physical and mechanical properties of the specimens, as well as their brittleness characteristics, was systematically analyzed. A multiple linear regression analysis was conducted to derive linear regression equations for the physical and mechanical parameters of the brittle rock simulation materials. In addition, simulation materials and standard specimens of Jinping marble were prepared. The brittle failure modes and acoustic emission characteristics of the specimens under uniaxial compression and Brazilian splitting conditions were analyzed. The results indicate that component proportions significantly affected the physical and mechanical properties of the specimens. The refined iron powder–barite powder ratio, as well as the concentration of the rosin–alcohol solution, played a primary role in controlling the physical and mechanical parameters of the brittle rock simulation materials.

A Multi-Objective Optimization Model for Agricultural Crop Planting Strategies Using Enhanced Genetic Algorithms and Big Data Analysis

The purpose of this paper is to construct an optimization model of crop planting strategy based on improved genetic algorithm. In order to improve the efficiency of agricultural planting and maximize the economic benefits, this paper combines the linear programming model and the multi-matrix improved genetic algorithm (MI-GA), the improved NSGA-II algorithm of orthogonal experimental design, and the multiple nonlinear regression model based on heuristic exploration algorithm to explore the complex relationship between crop sales price, planting cost and yield per mu. Through the comprehensive analysis of planting constraints, market fluctuations and risk assessment of different crops, a more scientific and practical optimal planting scheme was proposed. Experimental results show that the constructed model has good convergence and optimization effect under the condition of multi-parameter change, which provides decision support for agricultural production and helps to realize the sustainable development of rural economy.

转勺式大豆精密排种器设计与试验分析

To optimize the structure of soybean precision seeder and improve the performance of sowing, a new rotary spoon precision seeder is designed, and the key component structure is designed using numerical calculation methods. Using a combination of bench experiments and field experiments for parameter optimization experiments, a multi factor quadratic orthogonal rotation combination design experiment is adopted. The experimental data is analyzed and processed using Design Expert 8.0.6 software to seek the optimal combination of parameters. The results show that when the working speed is 24.56-33.72 r/min and the forward speed is in the range of 1.31-2.21 m/s, the seeding qualification index is greater than 90% and the coefficient of variation is less than 10%, meeting the requirements of excellent seeding standards. This study uses a rotary spoon seeder to sow soybeans, providing a new idea and reference for the development of precision soybean seeders.

A study on the macro and micro mechanisms of cotton seedling growth regulation by high-voltage electrostatic field and optimization of system parameters

Addressing the issues of inefficiency and severe environmental pollution associated with artificial and chemical methods in cotton growth regulation, this study introduces the high-voltage electrostatic field environmental control technology. It delves into the technology’s macro- and microscopic impacts on cotton seedling growth and optimizes its operational parameters. At the macro level, the study examines the influence of adjusting the output voltage of the high-voltage electrostatic generator, the distance between the upper pole plate and the cotton leaf, and the action time of the electric field on seedling features above (plant height, ground diameter, and leaf area) and below ground (fresh weight and dry weight of roots). Subsequently, utilizing an orthogonal experimental design, the optimal parameters are identified: output voltage of 15.93 kV, a distance of 10.71 cm between the pole plate and cotton leaf, and an action time of 39.23 s, resulting in the most favorable overall growth condition. At the micro level, conductivity meters and transmission electron microscopy techniques are employed to investigate leaf electrical conductivity and ultrastructure changes under a high-voltage electrostatic field. Results indicate a slight conductivity increase under moderate conditions (e.g., 18 kV-8 cm), signifying healthy cell membranes. Conversely, extreme conditions (e.g., 18 kV-2 cm or 36 kV-8 cm) cause marked conductivity spikes, pointing to cellular damage. Transmission electron microscopy observations reinforce this, with intact membranes under optimal conditions but disintegration and degradation under adverse ones. In conclusion, this study unravels the internal mechanisms of high-voltage electrostatic field regulation on cotton seedling growth from macro- to micro-scales, validating its feasibility and effectiveness. This breakthrough not only pioneers a novel approach for cash crop seedling growth control but also lays a scientific foundation for refining and advancing cotton cultivation techniques, thereby advancing agricultural modernization and sustainable development goals.

Experimental investigation and parametric optimization of FSW of mineral-reinforced AA6061 matrix composite

Abstract In this work, rutile reinforced AA 6061 matrix composites were joined using friction stir welding and the process variables were optimized using Taguchi L27 orthogonal design of experiments. The rotational speed, axia force and tool tilt angle were the parameters taken into consideration. The optimum process variables were determined with reference to tensile strength, impact strength and hardness of the joint. The predicted optimal value of output responses were confirmed by conducting the confirmation run using optimum parameters. The optimal process variables combination values that resulted in improved mechanical properties were observed at a tool rotational speed of 1400 rpm, a tool tilt angle of 2 degree, and an axial force of 3KN. Scanning electron microscopy (SEM) analysis were used to probe the microstructures.

Orthogonal simulation and experimental study on SLM process parameters for micro-sized high dynamic components

Abstract Metal Additive Manufacturing (MAM) technology has become an important means of rapid prototyping of special high dynamic complex components. This study employs selective laser melting (SLM) as a technological approach for investigating micro-sized high dynamic components. The parameters that affect SLM process are analysed, mainly including laser power, laser speed, laser diameter, and scan spacing. Based on prior studies, feasible parameter ranges are identified, and an orthogonal experimental design table is established for simulation and experimental co-verification. Range and variance analysis are conducted and the influence ability of each influencing factor is explored from both simulation and experimental aspects. The SLM process model is established using finite element software, taking into account parameters such as residual stress and maximum deformation. The conclusion is drawn that the order of influence of each factor on the preparation of micro-sized high dynamic components is: scan spacing>laser power>laser diameter> laser speed. Samples of components are fabricated and subjected to static testing. The density of the components can reach over 99.15%, and the structural strength can reach 348 MPa, which meet the required standards and confirm the simulation analysis. The results demonstrates that SLM provides a novel manufacturing method for micro-sized high dynamic components.

Investigation of the effects of contour process parameters on mechanical properties and part quality in SLM

AlSi10Mg is an aluminium alloy preferred in the automotive, medical, and aerospace industries due to its engineering properties such as lightness, high corrosion resistance, and excellent castability. In metal-based additive manufacturing, offset value, laser power, and scanning speed are important manufacturing parameters. These parameters significantly impact the formation of defects that adversely affect the microstructure, mechanical properties, surface quality, and dimensional accuracy of the final product. Therefore, it is imperative to select these parameters correctly during the manufacturing process. In this context, the study focuses on improving product quality in the additive manufacturing of AlSi10Mg alloy, and samples were produced using different contour process parameters. The production of samples was carried out according to the Taguchi L27 orthogonal experimental design. Three different offset values (0.140–0.175–0.210 mm), three different laser powers (160–200-240 W), and three different scanning speeds (280–350-420 mm/s) were utilized as contour process parameters. At the conclusion of the study, it was determined that there are ideal process parameters for achieving high mechanical properties, low surface roughness, and dimensional accuracy according to nominal values. It was observed that the product quality decreased in samples produced with non-ideal parameters. Yield strength decreased by 4.12 % with an increase in the offset value from 0.140 mm to 0.175 mm, and by 3.83 % with an increase from 0.175 to 0.210 mm. Increasing the offset value from 0.140 mm to 0.175 mm resulted in a decrease in tensile strength by 1.94 % and increasing it from 0.175 mm to 0.210 mm resulted in a decrease of 2.83 %. The decrease in mechanical properties was attributed to the occurring defects. The lowest Ra value (2.011 µm) was measured at a 0.140 mm offset value, with a laser power of 200 W, and a scanning speed of 280 mm/s. For all offset values, the deviation in thickness measurement varies between approximately −5.13 % and + 4.96 %, and the deviation in width measurement varies between −1.89 and + 1.33. Multi-response optimization was conducted for mechanical properties, surface roughness, and dimensional accuracy using the Taguchi-based gray relational analysis method. According to the experimental results, the optimal contour process parameters for additive manufacturing of AlSi10Mg alloy were obtained as 0.140 mm offset value, 200 W laser power, and 280 mm/s scanning speed.

Study on the Technical Parameters for Estimating HIV-1 Incidence by Using a Recombinant Antigen-based Capture Enzyme Immunoassay - China.

A novel recombinant antigen-based capture enzyme immunoassay (RAg-CEIA) was optimized and used to determine technical parameters for estimating human immunodeficiency virus type 1 (HIV-1) incidence in China. We employed orthogonal experimental design to optimize RAg-CEIA by adjusting raw material dilution ratios. The assay was used to measure normalized optical density (ODn) values in 171 longitudinal plasma specimens from 51 HIV-1 seroconverting individuals, plotted against estimated days post-seroconversion. We determined the optimal ODn threshold value for differentiating recent from long-term infections and calculated the mean duration of recent infection (MDRI) for incidence estimation. The false recent rate (FRR) was determined using 481 HIV-1 antibody-positive specimens with infection durations exceeding twice the MDRI. Optimal RAg-CEIA parameters were established with a raw material dilution ratio of 1/12 for calibrator preparation and an enzyme conjugate titer of 1:1200. ODn values demonstrated consistent temporal increases across HIV-1 seroconverting individuals, though with notable kinetic heterogeneity in individual responses. The optimal ODn threshold value of 0.8 for distinguishing recent from long-term infections corresponded to an MDRI of 205 days and an FRR of 4.78%. The optimized RAg-CEIA effectively differentiates recent from long-term HIV-1 infections at the population level, enabling reliable HIV-1 incidence estimation in China.

Enhancing the performance and revealing the thermal behavior of the water-based coating derived from waterborne alkyd resins and totally methyl etherified amino resins

In this study, the curing parameters of the water-based coating were carefully optimized using waterborne alkyd resins as the matrix resin and totally methyl etherified amino resins as the crosslinking agent. Through an orthogonal experimental design and a controlled experiment, the optimal conditions, which were a 7:1 ratio of alkyd resins to amino resins and curing at 403.15 K for 30 min, were determined. Droplet size distribution and zeta potential measurements confirmed that the composite resin emulsion prepared with the optimal ratio was more uniformly and stably dispersed in water, which helped to optimize the coating and make it have excellent physical properties, mechanical stability and chemical durability. Thermal stability was also thoroughly evaluated by TGA analysis, paying particular attention to the third degradation stage of the optimized composite resin coating (573.15–733.15 K), pyrolysis kinetic analysis provided deeper insights into its thermal behavior. Activation energies calculated through both the KSA and Starink methods exhibited consistent values of 195.47 kJ/mol and 196.06 kJ/mol, respectively. Furthermore, a reaction mechanism function of G(α) = [−ln(1-α)]3 via C-R method implying a sigmoidal rate equation or stochastic nucleation. The activation energy calculated by this method is 211.10 kJ/mol and the pre-exponential factor is 2.22 × 1016 min−1. Notably, the thermodynamic parameters obtained from all three methods show remarkable agreement.

Deep learning-enhanced aerodynamics design of high-load compressor cascade at low Reynolds numbers

This study addresses the challenges of designing high-efficiency compressors for long-endurance, high-altitude unmanned aerial vehicles (UAVs) under low Reynolds number (Re) and high load conditions, exploring the aerodynamic performance limits of compressor blades under extreme conditions. The research integrates advanced numerical simulations, experimental methods, and deep learning technologies to minimize profile losses and deviation angle on compressor blades. An orthogonal experimental design systematically explored the impact of key geometric factors on aerodynamic performance. A deep learning model incorporating neural networks with spatial attention mechanisms was developed to significantly enhance the accuracy of aerodynamic predictions. This model adeptly captured the complex nonlinear interactions between aerodynamic and geometric parameters. Sobol sensitivity analysis revealed that the dimensionless maximum thickness is the most critical factor, accounting for 44 % of the total variance in total pressure loss and deviation angle. The position of maximum thickness and the aspect ratio of the elliptical leading edge also significantly influenced performance. The optimized high-load compressor blade profile was validated through experimental data and detailed computational fluid dynamics analysis using large eddy simulation methods. This analysis revealed flow separation and reattachment mechanisms, shedding light on turbulence and vortex dynamics critical to performance. This research deepens the theoretical understanding of compressor cascade fluid dynamics and provides practical insights for designing more efficient compressors, especially for micro axial compressors in high-altitude UAVs.

Multi‐Objective Evolutionary Algorithm Based on Decomposition With Orthogonal Experimental Design

ABSTRACTMulti‐objective evolutionary optimisation algorithms (MOEAs) have become a widely adopted way of solving the multi‐objective optimisation problems (MOPs). The decomposition‐based MOEAs demonstrate a promising performance for solving regular MOPs. However, when handling the irregular MOPs, the decomposition‐based MOEAs cannot offer a convincing performance because no intersection between weight vector and the Pareto Front (PF) may lead to the same optimal solution assigned to the different weight vectors. To solve this problem, this paper proposes an MOEA based on decomposition with the orthogonal experimental design (MOEA/D‐OED) that involves the selection operation, Orthogonal Experimental Design (OED) operation, and adjustment operation. The selection operation is to judge the unpromising weight vectors based on the history data of relative reduction values and convergence degree. The OED method based on the relative reduction function could make an explicit guidance for removing the worthless weight vectors. The adjustment operation brings in an estimation indicator of both diversity and convergence for adding new weight vectors into the interesting regions. To verify the versatility of the proposed MOEA/D‐OED, 26 test problems with various PFs are evaluated in this paper. Empirical results have demonstrated that the proposed MOEA/D‐OED outperforms eight representative MOEAs on MOPs with various types of PFs, showing promising versatility. The proposed algorithm shows highly competitive performance on all the various MOPs.

Nozzle structure optimisation in a photovoltaic irrigation system

AbstractOn the basis of the significant impact of the sprinkler nozzle structure in photovoltaic irrigation systems, the nozzle parameters are optimised to improve sprinkler adaptability and irrigation uniformity under different light intensities. An experimental test and numerical simulation were conducted to analyse the influence of nozzles with distinct parameters on the spray irrigation effect. Taking the irrigation uniformity coefficient as the optimisation goal and the nozzle outlet shape, outlet area and straight flow channel length as the optimisation variables, an orthogonal experimental design was employed, and the optimal solution was obtained via range analysis. The experimental results indicate that the sprinkler performs best when the outlet shape is circular, the nozzle outlet area is 7 mm2 and the flow channel length is 2 mm. The optimal nozzle characteristics were tested and compared with those of the original design, and numerical simulation was used to demonstrate the optimised internal flow mechanism. The results demonstrate that the optimised flow rate and spray range are improved, and the working pressure and rotation period are significantly reduced, enabling the system to adapt to a more extensive range of light intensities. The radial water distribution structure is better, and the combined application rate and uniformity coefficient are also significantly improved. In addition, the sprinkler outlet speed is more consistent, and the area of the high‐speed zone in the spray plate increases, which is conducive to reducing energy loss and enhancing sprinkler irrigation uniformity.