Rotor Speed Research Articles

Optimized triangular observer based adaptive supertwisting sliding mode control for wind turbine system

This paper presents a modified adaptive supertwisting sliding mode controller (AST-SMC) that dynamically adjusts control settings without prior knowledge of uncertainty limits, thereby removing chattering and putting reliability first while maintaining the original benefits of sliding mode control (SMC). First, we model and build the wind turbine system using three different controllers: the AST-SMC, the supertwisting sliding mode controller (ST-SMC), and the first-order sliding mode controller (FOSMC). A second comparison is necessary. Only the rotor speed is available to the control law because of concealed state information, which makes use of the full system state. In order to minimize observing errors over time, an asymptotic observer triangle is used to estimate the unknown rotor acceleration. By improving AST-SMC's control law, particle swarm optimization finds the most effective controller. The stability of AST-SMC over a finite time is shown via the Lyapunov stability theorem. Based on simulation findings, it is proven to be more effective than traditional SMC in wind turbine system control. It excels in settling time, tracking accuracy, energy consumption, and control input smoothness.

Wind turbine energy forecasting using real wind farm’s measurement data and performance of gene expression programming analytical model in comparison to traditional algorithms

ABSTRACT Forecasting wind power is vital to ensure steady, sustainable, and renewable energy. The complex nonlinear nature of wind flow and its interrelated factors make power prediction challenging. This study predicted wind power curves inspired by the Biologically Inspired Evolutionary Computation (BIEC) paradigm, incorporating Gene Expression Programming (GEP), Artificial Neural Networks (ANN), Least Square Support Vector Machines (LSSVM), and Random Forest (RF) models. Key input parameters include wind speed, yaw azimuth, turbulent intensity, veer, horizontal and vertical shear, ambient temperature, blade pitch, and rotor speed. The study evaluates these models’ effectiveness using root mean square error (RMSE) and correlation coefficient R. Results indicate that the GEP model offers transparent modeling, emphasizing critical inputs like wind speed, rotor speed, blade pitch angle, and temperature for wind power prediction. The GEP model identified wind speed, rotor speed, blade pitch angle, and temperature as the most influential parameters, with variable importance index (Ii) values of 69.39%, 24.39%, 5.46%, and 0.64% for training, and 69.37%, 25.03%, 4.98%, and 0.54% for validation. The study demonstrates the GEP model’s efficacy in accurately forecasting wind power curve, achieving a high correlation with training and validation coefficients of 0.9899 and 0.994, respectively, outperforming traditional models with minor errors.

Blade tip clearance measurement method based on blade tip timing without the once per revolution sensor

Abstract The rotor blade tip clearance (BTC) of an aeroengine is a critical parameter that significantly impacts its performance and safety. Accurately determining dynamic BTC has been a focal point of research in experimental testing. Among the effective measurement methods for dynamic BTC, the laser triangulation method based on blade tip timing (BTT) stands out. However, this method typically relies on an once-per-revolution (OPR) sensor for rotor speed and blade serial number information during measurement, leading to increased installation and maintenance costs as well as additional measurement uncertainties. In response to this challenge, this paper presents two signal processing method that eliminate the need for an OPR sensor. The first method, referred to as "none OPR method 1," closely follows the measurement principles of the traditional method but employs a skewed dual light probe (SDLP) signal to extract rotational speed information, thus obviating the need for an OPR sensor. The second method, "none OPR method 2," introduces a novel data processing approach that enables BTC determination without any source of rotor speed information. Both methods utilize dynamic and static BTC matching techniques to identify blade serial numbers and achieve BTC measurement without an OPR sensor on a simulated rotor experimental bench. Comparative analysis with traditional method BTC measurements reveals that, under stable rotor speeds, all methods achieve similar levels of accuracy and repeatability errors within 0.025mm. However, when dealing with variable speed conditions, the traditional method's accuracy is significantly affected. None OPR method 1 mitigates the impact of rotor speed changes to some extent, while none OPR method 2 remains unaffected by such changes. Importantly, both none OPR methods demonstrate the capability to measure blade-by-blade tip clearances akin to the traditional method.

Methyl ester production process from palm fatty acid distillate using hydrodynamic cavitation reactors in series with solid acid catalyst.

This study aims to optimize the reduction of free fatty acids (FFAs) in palm fatty acid distillate (PFAD) using hydrodynamic cavitation reactors (HCRs) in series and a solid acid catalyst for biodiesel production. Hydrodynamic cavitation is used to accelerate the esterification of FFAs using a heterogeneous acid catalyst. There are three HCRs units, and each HCR composed of a 3D-printed rotor and stator, is separated by flanges and equipped with a basket for holding Amberlyst-15 catalyst. Through response surface methodology (RSM), the esterification process is optimized by adjusting its optimal parameters, namely, methanol (2-12 wt%), circulation time (30-170min), and rotor speed (1000-3000rpm). The optimal conditions for achieving a maximum methyl ester purity of 89.76 wt% in converting FFA in first-step esterified oil are 9 wt% methanol (molar ratio of methanol to oil of 4:1), 133min of circulation time, and 2000rpm of rotor speed. An 82.48 wt% biodiesel yield is achieved from the HCRs in series under the optimal conditions. Scanning electron microscope images reveal that after the esterification process, there are minor cracks and defects on the catalyst's resin surface, indicating the presence of residual reactants. Further examination of the catalyst after the esterification process, reveals an average absorption pore diameter of 341.41 Å and BET surface area of approximately 41.68 m2/g. Although there were slight physical changes in the catalyst, HCRs technology offers a viable FFA reduction process that could enhance biodiesel production efficiency. Moreover, the optimized conditions achieved in this study contribute to the advancement of biodiesel production processes and provide insights into the performance of the catalyst used.

Intelligent Control of an Experimental Small-Scale Wind Turbine

Nowadays, wind turbines are one of the most popular devices for producing clean and renewable electric energy. The rotor blades catch the wind’s kinetic energy to produce rotational energy from the turbine and electric energy from the generator. In small-scale wind turbines, there are several methods to operate the blades to obtain the desired speed of rotation and power outputs. These methods include passive stall, active stall, and pitch control. Pitch control sets the angular position of the blades to face the wind to achieve a predefined relationship between turbine speed or power and wind velocity. Typically, conventional Proportional Integral (PI) controllers are used to set the angular position of the rotor blades or pitch angle. Nevertheless, the quality of speed or power regulation may vary substantially. This study introduces a rotor speed controller for a pitch-controlled small-scale wind turbine prototype based on fuzzy logic concepts. The basics of fuzzy systems required to implement this kind of controller are presented in detail to counteract the lack of such material in the technical literature. The knowledge base of the fuzzy speed controller is composed of Takagi–Sugeno–Kang (TSK) fuzzy inference rules that implement a dedicated PI controller for any desired interval of wind velocities. Each wind velocity interval is defined with a fuzzy set. Simulation experiments show that the TSK fuzzy PI speed controller can outperform the conventional PI controller in the speed and accuracy of response, stability, and robustness over the whole range of operation of the wind turbine prototype.

Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles

Ensuring robust and reliable control of distributed vehicles powered by in-wheel motor systems poses a significant challenge due to the harsh operating environments and high costs of such motor systems. Poor motor control, parameter variations, and sensor malfunction under these conditions can compromise the vehicle yaw stability. Integrating permanent magnet synchronous motor (PMSM) sensorless systems with vehicle yaw moment control offers a cost-effective solution for this issue without wheel angular speed sensors while enhancing yaw stability. In this paper, a composite nonlinear feedback sliding mode controller that can enhance the PMSM speed response is proposed. The proposed scheme exhibits a rotor speed overshoot and transient time of only 0.64% and 0.07s, respectively, which are smaller and shorter compared with other methods under motor parameter changes. Subsequently, the key states and tire-road friction coefficients required for vehicle control were estimated using sensorless rotor speeds and unscented Kalman filters, enabling the integration of the PMSM sensorless system with the vehicle yaw moment control. Additionally, a fuzzy adaptive hybrid sliding mode method is presented for yaw moment control enhancement. This method maintained the smallest sideslip angle root mean square error during double lane changes (0.4192 deg) compared with other methods. Analysis results show that different motor controllers and parameter changes significantly affect the vehicle dynamics performance. The proposed integrated scheme is feasible and effectively enhances the yaw moment control via high-performance sensorless PMSM systems.

High-Precision Rotor Position Fitting Method of Permanent Magnet Synchronous Machine Based on Hall-Effect Sensors

The high-performance vector control technology of permanent magnet synchronous machines (PMSMs) relies on high-precision rotor position. The Hall-effect sensor has the advantages of low cost, simple installation, and strong anti-interference ability. However, it can only provide six discrete rotor angles in an electrical cycle, which makes high-precision vector control of PMSMs difficult. Hence, to obtain the necessary rotor position of PMSMs, a rotor position fitting method combining the Hall signal and machine flux information is proposed. Firstly, the rotor position signal output by the Hall-effect sensors is used to calibrate and update the stator flux obtained under pure integration. Then, based on the corrected stator flux and its relationship with current and angle, the rotor position and speed are obtained. Experimental verification shows that the rotor position observer combining Hall signal and flux information can reduce the initial value bias and integral drift caused by traditional average speed method hysteresis and pure integration method calculation of flux and can quickly and accurately track and estimate the rotor position, achieving high-performance vector control of PMSMs.

Enhancing Oxygen-Dissolving Capacity of Rotary Drum Food Waste Composting: Tumbling Process Optimization and Experimental Validation with Discrete and Finite Element Methods

An optimized tumbling process can significantly improve the oxygen dissolving capacity of composting and fertilizer quality: by increasing the fluffiness of the lower layer of the pile, localized anaerobic fermentation can be avoided, thereby enhancing compost quality. This paper presents a method for improving the oxygen dissolving capacity of rotary drum food waste composting through a combination of simulation optimization and experimental validation. First, the discrete element method was used to optimize the key parameters of the tumbling process. The response surface method was then employed to analyze the composting test results and determine the optimal conditions. To ensure the reliability of the equipment under this method, failure risk analysis was conducted using the finite element method. The simulation optimization results showed that with a rotary drum reactor speed of 3.5 r/min, a horizontal angle of inclination of 2.5°, a mixing blade angle of inclination of 43°, and a blade pitch of 580 mm, the fluffiness of the lower layer of the pile increased by 8.515%, achieving the best tumbling and indirectly enhancing oxygen dissolving capacity. The maximum deformation of the load-bearing components was only 0.0548 mm, and the minimum safety factor was 4.408 (≥1 is considered safe). A 14-day composting experiment was conducted to validate the optimized parameters. The results showed that the maximum temperature of the compost pile reached 68.34 °C (lasting 7 days), with the pH, moisture content, C/N ratio, humus substances, humic acid, and fulvic acid contents of the fertilizer all meeting or exceeding the levels recommended by Chinese national standards. These findings indicate that the optimized tumbling device effectively improved the stability and dissolved oxygen efficiency of food waste composting, providing valuable practical insights and a research foundation for enhancing oxygen efficiency in the composting of other organic wastes.

Movement Characteristics of Droplet Deposition in Flat Spray Nozzle for Agricultural UAVs

At present, research on aerial spraying operations with UAVs mainly focuses on the deposition outcomes of droplets, with insufficient depth in the exploration of the movement process of droplet deposition. The movement characteristics of droplet deposition as the most fundamental factors affecting the effectiveness of pesticide application by UAVs are of great significance for improving droplet deposition. This study takes flat spray nozzles as the research object, uses the Particle Image Velocimetry (PIV) technique to obtain movement data of water droplet deposition under the influence of rotor flow fields, and investigates the variation characteristics of droplet deposition speed under different influencing factors. The results show that the deposition speed and the distribution area of high-speed (>12 m/s) particles increase with the increase of rotor speed, spraying pressure, and nozzle size. When the rotor speed increases from 0 r/min to 1800 r/min, the average increase in maximum droplet deposition speed for nozzle models LU120-02, LU120-03 and LU120-04 is 33.26%, 19.02%, and 7.62%, respectively. The rotor flow field significantly increases the number of high-speed droplets, making the dispersed droplet velocity distribution more concentrated. When the rotor speed is 0, 1000, 1500, and 1800 r/min, the average decay rates of droplet deposition speed are 36.72%, 20.00%, 15.47%, and 13.21%, respectively, indicating that the rotor flow field helps to reduce the decrease in droplet deposition speed, enabling droplets to deposit on the target area at a higher speed, reducing drift risk and evaporation loss. This study’s results are beneficial for revealing the mechanism of droplet deposition movement in aerial spraying by plant protection UAVs, improving the understanding of droplet movement, and providing data support and guidance for precise spraying operations.

Designing a Brushed DC Motor Driver with a Novel Adaptive Learning Algorithm for the Automotive Industry

In this study, a stepper driver, which is suitable for use in the automotive industry, designed for general use, capable of adaptive learning in the systems in which it is used, and with CAN and universal asynchronous receiver–transmitter (UART) communication options, was designed. This design was made with a PIC18F25K22 microcontroller unit (MCU). Rotor speed, armature current, and terminal voltage can be measured on the proposed brushed DC motor drive system. It gives the desired response by evaluating obstacles and other situations in which high currents are drawn from the source. The speed measurement of the vehicle and the open and closed status of an automatic door can be monitored. The main contribution of the designed PCB is an adaptive learning algorithm (ALA) that uses the pulses of the encoder, estimates the position of the step, and manages the operation process to prevent mechanical damage at the final point of the motor. Furthermore, unexpected hitting and pinching which are defined as obstacles to the driver can be controlled by monitoring the current value drawn from the driver. The benefit of this method is that the life of the mechanical step is increased due to the management of the forward and backward step operation, preventing potential accidents.

Variable droop gain frequency supporting control with maximum rotor kinetic energy utilization for wind-storage system

To address the emerging frequency stability issue brought by the large replacement of synchronous generators with renewable generations, wind turbine generators are required to possess frequency-supporting capability. However, existing frequency-supporting control strategies lack the assessment of the frequency support capability of wind turbine generators, leading to degraded control performance under various situations. Aiming to solve this problem, this paper proposes a variable-droop-gain control for wind turbine generators with maximum rotor kinetic energy utilization. Firstly, an analytical relationship was established between droop gain, disturbance scale, and rotor speed. Subsequently, the released energy of the wind turbine generator is evaluated, which equals the difference in the rotor kinetic energy under the initial and the post-disturbance steady-state rotor speed. It was proved that the released kinetic energy cannot exceed a certain proportion of total rotor kinetic energy. Accordingly, a variable initial gain scheme is proposed, which determines the initial droop gain as per the disturbance scale for maximizing the kinetic energy release of wind turbines. Moreover, an additional real-time droop gain adjustment rule is added to prevent the over-deceleration of wind turbines. The simulation results show that the proposed scheme may provide the maximum KE release and effectively improve the system frequency nadir while ensuring the safe operation of wind turbine generators.

Enhanced Transdermal Delivery of Cilnidpine Via Ultradeformable Vesicle Loaded Patch: Statistical Optimization, Characterization and Pharmacokinetic Assessment.

The study aimed to address the limitations of oral delivery and enhance the bioavailability of Cilnidipine (often prescribed as antihypertensive drug) (CND) through the development of transdermal patches containing ultra-deformable transferosomes. CND, known for its low oral bioavailability and adverse effects, was encapsulated in transferosomes using a thin film hydration method. Seventeen formulations were made (using Box Behnken Design), varying Soya lecithin, Tween-80, and rotary evaporator's speed, and evaluated for vesicle size, polydispersity index (PDI), and entrapment efficiency (EE %). The better formulation was selected based on these parameters and incorporated into transdermal patches. Physicochemical properties, in-vitro and ex-vivo permeation, and skin irritancy studies were conducted on the patches. Pharmacokinetic studies were conducted using male Wistar albino rats. The study found that the developed transferosomal formulations had vesicle sizes between 185 nm and 401 nm, entrapment efficiency (EE%) between 63% and 92%, and zeta potential ranging from -52 mV to -20 mV. Both in-vitro and ex-vivo permeation studies showed that transferosomal formulations provided significantly better drug permeation than plain Cilnidipine patches, with increased permeation linked to higher PEG-400 concentrations. The transferosomal patches did not cause skin irritation. The optimized formulation exhibited a higher % drug release (85.7±1.5%). In pharmacokinetic studies using male Wistar albino rats, the transferosomal patch CTP-17 demonstrated a higher maximum concentration (Cmax) of 1565.068 mcg/ml and a greater area under the curve (AUC) of 13225.352 μg h/ml compared to oral administration. The study concludes that the transferosomal patches of CND offer a promising approach for effective transdermal delivery, potentially improving hypertension management for prolonged periods in a controlled manner.

Study on the characteristics of cavitation and COD removal of an addendum rotational hydrodynamic cavitation reactors

AbstractThis paper presented an addendum rotational hydrodynamic cavitation reactors (ARHCR) that enabled circumferential shear cavitation, axial cavitation, and the Venturi effect, thus increasing cavitation efficiency. The experiments on hydroxyl (·OH) release and chemical oxygen demand (COD) removal demonstrate the feasibility of cavitation performance characterization and COD removal rate. The findings indicate that the COD removal rate can reach a maximum value of 28% or 30% with an increase in flow rate or rotating speed, respectively. Specifically, the maximum values were achieved at a rotation speed of 2,500 rpm or a flow rate of 1.0 m3·h−1. Based on the mechanism of the addendum cavitation, the wedge angles, and the crucial structural parameters, were examined for optimizing cavitation performance. The results revealed that the cavitation number and cavitation bubble were significantly influenced by wedge angles, as well as the efficiency of cavitation energy. The mechanical shear of fluid was enhanced by wedge angles, resulting in constant compression and release of fluid with increased kinetic energy. This led to stronger effects on bulge blocks, and the formation of vortexes that rebounded constantly, resulting in lower pressure areas and expanded regions of cavitation. Among the wedge angles tested, the wedge angle of 15° exhibited the highest cavitation bubbles with a maximum value of 46%. This was 31% higher than the grooves‐type cavitator reported. Furthermore, the cavitation performance was extremely improved with a wedge angle of 15°, as corresponding with the maximum efficiency of cavitation energy. These explorations provide references for the removal of COD in industrial and agricultural wastewater, as well as the development of novel reactors for wastewater treatment.

Numerical assessment of ice formation processes and its impact on a variable-pitch unmanned aerial vehicles propeller in forward flight

Unmanned aerial vehicles (UAVs) encounter significant challenges in freezing climates, as atmospheric ice accretion adversely impacts both flight safety and aerodynamic performance. This study provides an in-depth numerical investigation into the ice accretion process and its implications on the aerodynamic performance of UAV propeller. The analysis explores at various propeller blade pitching angles and rotational speeds. Detailed flow field analysis around propeller blade surfaces is conducted to address the performance degradations associated with ice accretion. The investigation reveals a noteworthy shift in ice shapes and extents with varying pitching angles and rotational speeds. The iced propeller demonstrates increased aerodynamic losses, marked by large size separation bubbles aft the ice shapes at outer radial locations. Remarkably, at higher pitching angles, the iced propeller outperforms the baseline propeller, followed by a propeller with increased rotating speed. For both baseline and higher pitching angles, the most significant losses in thrust coefficient 57.60% and 25.39%, respectively, occur at −2 °C, accompanied by maximum spikes in power coefficient of 140.08% and 93.92% at −4 °C. Meanwhile, an increase in rotating speed results in a decrease in thrust coefficient by 48.60% and an increase in power coefficient by 150.66% at an icing temperature of −4 °C.

DEM simulation of an impact crusher using the fast-cutting breakage model

The impact crusher that exploits impact rather than pressure to break down materials has been widely used in the mineral industry. To further improve its performance in material crushing, numerical simulation capable of providing a deeper insight into the complicated dynamics of feed materials than experimental study has emerged as a promising tool. However, the field of the accurate prediction of product quality and explicit simulation of breakage events inside an industrial-scale crusher remains underexplored on account of the absence of a robust breakage model and heavy computational cost. In this study, a numerical investigation of an industrial-scale crusher using the fast-cutting breakage model is conducted within the DEM (Discrete Element Method) framework. The accuracy of the breakage simulation is quantitatively validated by comparing the predicted results with the measurements from actual production. Furthermore, the influence of operating conditions including the rotation speed of the rotor and the feeding rate on the interested parameters, i.e., the power consumption of the equipment, the size distribution of the products, and the impact-induced wear is investigated comprehensively. The results illustrate that (i) the size of the product increases with the rotor speed until a critical value, after which a further increase in rotor speed will exert no significant influence on the size distribution; (ii) The feeding rate is not a critical operating condition that largely determines the fineness of the product and the efficiency of the equipment almost remain stable under a certain range of feeding rates; (iii) The wear of the devices concentrates on the rotor and the impact plates, and the distribution of the wear exhibits different characteristics in different parts, caused by the complex collision between the particles and the devices.

Experimental investigation of the relation between operating conditions and offshore wind turbine drivetrain dynamics

Abstract This study investigates the impact of operating and environmental conditions on the vibration induced on an offshore wind turbine drivetrain. Furthermore, it explores the role of the dynamic response of the global wind turbine structure to vibration on the drivetrain. A prolonged experimental campaign dedicated to condition monitoring the drivetrain provides experimental vibration signals. These vibration signals are acquired under varying operating conditions across multiple locations of an offshore wind turbine drivetrain of a Belgian Offshore Wind farm and serve as the basis for analysis. The signals’ statistics facilitate establishing connections between dynamic behaviour and operational variables, such as active power, rotor speed, blade pitch angle, and turbulence intensity, sampled at every second and provided by Fast-SCADA. The initial phase of the analysis involves a comprehensive examination of various statistical properties of the vibration signals to link the drivetrain’s dynamic response to operational conditions. This exploration includes both active and standstill periods of the wind turbine. A comprehensive summary that relates the global vibration characteristics with the operating conditions is formed by scrutinizing the overall vibration signals. In the study’s second phase, a detailed investigation is conducted on the vibration signals recorded during standstill conditions. Investigation of standstill data ensures that the structural modes’ spectral content does not interfere with the machines’ kinematic content. The analysis of standstill data proceeds from determining the most energetic resonance frequencies through the average power spectral density of the vibration signals. These identified frequency bands enable a thorough exploration, revealing the interlink between the offshore wind turbine drivetrain’s dynamic response and the operating/environmental conditions.

Coordinated intelligent control strategy and power management for marine gas turbine under pulsed load using optimized neural network

Faced with the challenges of potentially irreversible damage due to instantaneous large pulsed power loads onboard, considering all-electric ship's small power grid capacity and complex gas turbine system, this study proposes a coordinated intelligent control strategy. It utilizes multi-objective optimization neural network to control a validated 20MW ship three-shaft gas turbine, ensuring global optimization tailored to pulsed load variations. Research findings reveal that the gas turbine efficiency at the design point is 32.3%, with a steady-state error within 2.8% and a maximum steady time error of 3.4 seconds, demonstrating acceptable accuracy. Under slope-type pulsed load of 20MW change in 5s, the proposed control strategy effectively manages speed while utilizing the energy storage system to smooth load inputs. It is worth noting that, increasing the fuel flow rate to 1.28 kg/s and inlet guide vane to 5.8 degrees reduces overshoot by 0.7% and rotor steady time by 15.4 seconds. Under transient-type pulsed load of 10MW back and forth change in 5s, the coordinated inlet guide vane control strategy mitigates surge margin and exhaust temperature issues. Adjusting the fuel flow to 1.17 kg/s and inlet guide vane to 9.96 degrees enables the gas turbine to operate within safety boundaries, reducing rotor speed overshoot by 0.4% and steady time by 6.1 seconds. Importantly, the optimized control strategy without energy storage system provides faster and safer dynamic regulation and power transmission for ship acceleration processes under radar load. However, considering only the coordinated strategy of the fuel sub-control loop, it is advisable to avoid compressor surge and over-temperature protection for electromagnetic ejection load scenarios. The research results will lay a valuable technical foundation for the intelligent control and smooth power transfer of the all-electric ship gas turbine power system with pulse loads in the extreme missions of ships in the future.

Simulation and experimental study of aerodynamic characteristics of a rotor adsorption wall-climbing robot

Abstract High-rise buildings are prone to gusts of wind, especially crosswinds. In order to investigate the effect of crosswinds on the aerodynamic characteristics of rotor blades at different near-wall distances, a CFD simulation model is designed for four near-wall distances and five wind speeds, and the change curves of rotor pulling force, pressure cloud diagrams and velocity cloud diagrams are obtained by using Fluent for the various conditions. The mechanism and pattern of its influence on the aerodynamic characteristics of rotor blades are studied by observing the pulling force change curve and cloud diagram. Finally, an experimental platform is built to verify the correctness of the simulation results. The simulation and experimental results have a similar law, i.e., crosswinds do not only have a negative effect on reducing the pulling force generated by the rotor blades, but can also have a gain effect on the pulling force in some cases. This law has some application value, which can be utilized to compensate the rotor speed accordingly. When the pulling force is reduced, the speed is increased appropriately to improve the reliability of the adsorption, and when the pull force is increased, the speed is reduced appropriately, which can reduce the power consumption and increase the range.

Optimization of fermentation conditions for physcion production of Aspergillus chevalieri BYST01 by response surface methodology.

This study aimed to optimize the culture conditions of the termite-derived fungus Aspergillus chevalieri BYST01 for the production of physcion, a characteristic component of the traditional herb rhubarb, which has been commercially approved as a botanical fungicide in China. First, potato dextrose broth was screened as the suitable basal medium for further optimization, with an initial yield of 28.0 mg/L. Then, the suitable carbon source, fermentation time, temperature, pH value, and the rotary shaker speed for physcion production were determined using the one-variable-at-a-time method. Based on the results of single factors experiments, the variables with statistically significant effects on physcion production were further confirmed using the Plackett-Burman design (PBD). Among the five variables, temperature, initial pH, and rotary shaker speed were identified as significant factors (P < 0.05) for physcion productivity in the PDB and were further analyzed by response surface methodology (RSM). Finally, we found that the maximum physcion production (82.0 mg/L) was achieved under the following optimized conditions:initial pH 6.6, rotary shaker speed of 177 rpm, temperature of 28 °C, and glucose concentration of 30 g/L in PDB medium after 11 d of fermentation. The yield of physcion under the optimized culture conditions was approximately threefold higher than that obtained using the basal culture medium. Furthermore, the optimum fermentation conditions in the 5-L bioreactor achieved a maximal physcion yield of 85.2 mg/L within 8 d of fermentation. Hence, response surface methodology proved to be a powerful tool for optimizing physcion production by A. chevalieri BYST01. This study may be helpful in promoting the application of physcion produced by A. chevalieri BYST01 to manage plant diseases.

Design and Testing of a Branched Air-Chamber Type Pneumatic Seed Metering Device for Rice

To meet the diverse seeding requirements of super hybrid rice, common hybrid rice, and conventional rice—which vary from 1 to 3 seeds, 2 to 4 seeds, and 5 to 8 seeds per hole, respectively—this study developed a branched air-chamber type pneumatic seed metering device for rice. The device utilizes an air chamber control board to manage the branched air chamber casing, enabling precise adjustments to the seeding quantity. This study presents a theoretical analysis of the seed metering device’s operation and its critical components. Structural parameter optimization was conducted using Ansys-Fluent (2021 R1) software, followed by multi-objective optimization of operational parameters through bench testing. Simulation results indicated that optimal vacuum pressure in the seed metering disc pores reached a maximum of 857 Pa with a chamber depth of 22 mm, an angle of 100°, and a cavity depth of 25 mm, achieving a minimal coefficient of variation of 0.86%. Bench test results showed that for seeding targets of 1 to 3 rice seeds per hole, the optimal operational parameters were: two openings, a working vacuum of 1355 Pa, and a rotor speed of 32.78 r/min, resulting in a missed seeding rate of 4.70%, a qualification rate of 85.81%, and a re-seeding rate of 9.49%. For targets of 2 to 4 seeds per hole, the best parameters included three openings, a working vacuum of 1357 Pa, and a speed of 32.87 r/min, with a missed seeding rate of 4.60%, a qualification rate of 85.59%, and a re-seeding rate of 9.81%. For 5 to 8 seeds per hole, optimal parameters were six openings, a vacuum of 1339 Pa, and a rotor speed of 31.07 r/min, yielding a missed seeding rate of 4.09%, a qualification rate of 87.27%, and a re-seeding rate of 8.64%. These findings demonstrate that the branched air-chamber type pneumatic seed metering device effectively meets the varied direct seeding requirements of rice, enhancing the adaptability of pneumatic seed metering devices to different seeding quantities in rice and potentially informing the design of pneumatic seeders for other crops.