Load Conditions Research Articles

Effect of bionic shield texture on friction behavior of silicon carbide under water lubrication condition

Abstract Reasonable texture parameters can effectively generate local dynamic pressure effects and promote the formation of lubrication film. The synergistic friction reduction mechanism of the shield-shaped texture on the Silicon Carbide (SiC) surface under water-based lubrication conditions between the flow pressure effect and the ‘rolling ball’ effect is investigated by combining simulation analysis and friction experiments. The effects of shield textured surface on the friction and wear characteristics of SiC surface and the characteristics of interfacial polarization electric field under different rotational speeds and different load conditions were analyzed. The results display that synergistic texture lubrication has a beneficial effect on improving tribological properties. The surface with 6% texture area occupancy showed the best tribological characteristics. The surface with a textured area occupancy of 6% displays the optimal tribological properties. Moreover, the friction reduction mechanisms under different working conditions are discussed, with the textured uniformly arranged surfaces being more suitable for high-speed and heavy load (140 N, 2000 rpm) conditions and the textured non-uniformly arranged surfaces being more suitable for low-speed and light load (40 N, 400 rpm) conditions.

Numerical Simulation Study on the Stable Combustion of a 660 MW Supercritical Unit Boiler at Ultra-Low Load

To investigate the safe, stable, and economically viable operation of a boiler under ultra-low-load conditions during the deep peaking process of coal-fired units, a numerical simulation study was conducted on a 660 MW front- and rear-wall hedge cyclone burner boiler. The current research on low load conditions is limited to achieving stable combustion by adjusting the operating parameters, and few effective boiler operating parameter predictions are given for very low-load conditions, i.e., below 20%. Various burner operation modes under ultra-low load conditions were analyzed using computational fluid dynamics (CFDs) methods; this operation was successfully tested with six types of pulverized coal combustion in this paper, and fitting models for outlet flue gas temperature and NOx emissions were derived based on the combustion characteristics of different types of pulverized coal. The results indicate that under 20% ultra-low-load conditions, the use of lower burners leads to a uniform temperature distribution within the furnace, achieving a minimum NOx emission of 112 ppm and a flue gas temperature of 743 K. Coal type 3, with the highest carbon content and a calorific value of 22,440 kJ/kg, has the highest average section temperature of 1435.76 K. In contrast, coal type 1 has a higher nitrogen content, with a maximum cross-sectional average NOx concentration of 865.90 ppm and an exit NOx emission concentration of 800 ppm. The overall lower NOx emissions of coal type 3 are primarily attributed to its reduced nitrogen content and increased oxygen content, which enhance pulverized coal combustion and suppress NOx formation. The fitting models accurately capture the influence of pulverized coal composition on outlet flue gas temperature and NOx emissions. This control strategy can be extended to the stable combustion of many kinds of coal. For validation, the fitting error bar for the predicted outlet flue gas temperature based on the elemental composition of coal type 6 was 8.09%, whereas the fitting error bar for the outlet NOx emissions was only 1.45%.

Application of an Improved State Feedback Control in the Selective Catalytic Reduction Denitrification Systems of Coal Power Units Under Variable Load Conditions

Selective catalytic reduction (SCR) flue gas denitrification systems are inherently complex, typically embodying characteristics of non-linearity, significant time delays, and susceptibility to multiple disturbances. In the context of coal power units engaging in deep load cycling and rapid frequency adjustment, conventional proportional-integral-derivative (PID) control struggles to meet the demands of effective control. This study introduces a control strategy that incorporates a “state observer + Linear Quadratic Regulator (LQR) state feedback + Improved Quantum Genetic Algorithm (IQGA) optimized PID”. Initially, local linear mathematical models of an SCR denitrification system at 340 MW, 450 MW, and 540 MW loads were used to design state observer and LQR state feedback control parameters for each operational condition. At a single load point, the IQGA was employed to optimize the outer loop PID parameters, followed by simulation experiments of load increases and decreases between 340 MW and 540 MW. The results demonstrated that, compared to two other strategies, the proposed approach reduced the overshoot by a minimum of 1.5% and shortened the adjustment time by 31.7% under conditions of step disturbances and internal perturbations. Throughout variable operational conditions, the strategy consistently exhibited minimal output fluctuations, rapid adjustment capabilities, strong disturbance rejection, and robust stability. This algorithm proves to be an effective method for controlling NOx concentrations, offering insights for precise ammonia injection control in future applications.

Health monitoring of automotive clutch system through feature fusion and application of tree-based classifiers

Clutch systems are crucial components of automotive systems, essential for transferring engine power to the wheels through gear shifts. A failed clutch can halt gear shifts and power transmission, rendering a vehicle immobile. Effective fault diagnosis is vital for ensuring reliability, preventing breakdowns, and addressing root causes promptly. Consequently, condition monitoring of the clutch is essential for maintaining system reliability and minimizing unwanted breakdowns. This paper presents an innovative condition-monitoring technique derived from vibration analysis to detect faults in the clutch system. The study involves extracting statistical, histogram, and autoregressive moving average features from acquired vibration signals. The J48 decision tree algorithm is utilized to select the most significant features, which are then classified using tree-based classifiers across three load conditions (no load, 5 kg, and 10 kg) and six clutch conditions. The experimental results demonstrate that the feature fusion strategy significantly enhances classification accuracy. The obtained results state that the classification accuracies for no load, 5 kg load, and 10 kg load were 98.33%, 100.00%, and 99.16%, respectively, while applying feature fusion strategies. This study highlights the effectiveness of feature fusion in improving fault diagnosis accuracy for clutch systems, presenting a robust method for real-time condition monitoring in automotive applications.

Dual-Sliding-Surface Robust Control for the PEMFC Air-Feeding System Based on Terminal Sliding Mode Algorithm

The proton exchange membrane fuel cell (PEMFC) is the most widely used fuel cell, but it also has some limitations. One of the research pain points is controlling the oxygen content in PEMFCs. A moderate excess of oxygen boosts electrochemical reaction efficiency, while an appropriate oxygen content ensures system stability. In this paper, a fourth-order nonlinear mathematical model of a PEMFC stack air supply system is established to solve the problem of optimal oxygen excess ratio (OER) control under dynamic load conditions. Based on the model, a nonsingular terminal sliding mode controller (NTSMC) based on a sliding mode observer (SMO) is proposed. The NTSM exhibits superior robustness and performance compared to other sliding mode structures. Meanwhile, the SMO accurately predicts system states, facilitating precise control actions. Additionally, the dual sliding mode surfaces enhance system stability against parameter uncertainties and external disturbances. Our results demonstrate that the proposed controller outperforms traditional ones in terms of robustness and performance, which significantly enhances PEMFC system efficiency and stability.

Spatiotemporal Gait Asymmetries Remain Unaffected by Increased Load Carriage in Professional Intervention Police Officers

Background: Although evidence indicates that load carriage may have an influence on walking patterns, the specific impacts of progressively increased loads on spatial and temporal gait asymmetries remain underexplored. Therefore, the primary aim of this study was to examine whether an increased load carriage had an effect on spatiotemporal gait asymmetries among intervention police officers. Methods: For the purpose of this study, 96 male intervention police officers were recruited and assessed under four load conditions: (i) “No load”, (ii) “a 5 kg load”, (iii) “a 25 kg load”, and (iv) “a 45 kg load”. Spatial and temporal gait parameters were measured using a pedobarographic platform (Zebris FDM). The spatial and temporal gait parameters, along with the ground reaction forces beneath different foot regions, were examined. The gait asymmetry for each parameter was calculated using the formula (xright − xleft)/0.5 × (xright + xleft)*100%, where “x” represents the numerical value of each parameter for the left and right sides of the body. Results: The findings indicated no statistically significant differences in the spatiotemporal parameters, nor ground reaction force gait asymmetries between the left and right foot, during walking under a progressively increased load carriage. Additionally, the parameter values for both the left and right sides of the body remained consistent, with a high intercorrelation observed across all of the loading conditions. The gait speed and ground reaction forces, which served as covariates, did not significantly change the spatiotemporal gait asymmetries. Conclusions: In summary, this study demonstrates that an increased load carriage did not lead to a progressive rise in spatiotemporal gait asymmetries in professional intervention police officers. However, further examination using an advanced 3-D gait analysis and an assessment of physiological patterns and adaptations is recommended to identify and confirm the key factors influencing gait asymmetry.

Impact of nano cerium oxide addition with pyrolysis waste plastic oil on combustion, performance and emission characteristics of CRDI diesel engine

Abstract This investigation examined the effect of incorporating cerium oxide (CeO2) nanoparticle into diesel and waste plastic oil (WPO) blends on the combustion, performance and emission characteristics of the diesel engine. The WPO was extracted from low density polyethylene using plastic pyrolysis. The blending of diesel and WPO with combination of D70:WPO30 and D50:WPO50 was prepared to evaluate the engine operation. Additionally, the spherical sized CeO2 with 50 mg/L and 100 mg/L was added with this blend. The various blends named as Diesel, D-WPO30, D-WPO30+Ce50, D-WPO30+Ce100, D-WPO50, D-WPO50+Ce50 and D-WPO50+Ce100 were used in this investigation to operate the engine under various load conditions. The experiment was performed using water cooled common rail direct injection (CRDI) diesel engine with prepared D-WPO blend. Different characteristics such as In-cylinder pressure (CP), heat release rate (HRR), ignition delay time (IDT), brake thermal efficiency (BTE), brake specific fuel consumption (BSFC) and exhaust gas temperature (EGT), carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOx) and smoke opacity emission are studied with respect to the effect of different blends and applied load used. It was observed that increasing of CeO2 nanoparticles in blend improved the overall performance and emission of the engine. Form the results, D-WPO30+Ce100 blend showed enhanced brake thermal efficiency (BTE), brake specific fuel consumption (BSFC) and exhaust has temperature (EGT) are 28.2%, 3% and 465oC respectively. Similarly, reduced emission of CO, NOx, HC and smoke opacity was observed in the CeO2 added blends particularly at 100 mg/L. It was concluded that among all blends prepared, the D70:WPO30 with 100 mg/L of CeO2 showed improved combustion, performance and emission characteristics in proposed diesel engine.

INFORMATION MODEL FOR SELECTING THE OPTIMAL SPATIAL FORM OF PARTS

A complex of interrelated methods and means of analysis, clustering, segmentation and classification of objects on images obtained by sensors of different physical nature (with the help of modern methods of radiography, computer and magnetic resonance imaging) is proposed, which will allow modeling the optimal form of a bone substitute with functional properties by CAD/CAM/CAE design methods, depending on the anatomical data, the nature and localization of the cavity bone defect, its size, load conditions and patterns of bone tissue neoplasm. Methods for making multi-criteria decisions have been developed, which will allow for their implementation for a wide range of optimization tasks of researching the correlation of the shape and size of porosity with indicators of the stress-deformed state of bone substitutes in order to maintain the structural integrity of the biomaterial in the process of regeneration of hard tissue.

Effects of the Interaction Between Time-on-Task and Task Load on Response Lapses

To investigate the interaction effects of prolonged working periods and different task loads on response lapses, focusing on the mechanisms of delayed responses and error lapses. Professionals such as pilots, truck drivers, and nurses often face extended work hours and fluctuating task loads. While these factors individually affect performance, their interaction and its impact on response lapses remain unclear. Twenty participants completed the Uchida–Kraepelin (U–K) Psychological Test and a dual-task version with functional near-infrared spectroscopy. Independent variables were time-on-task and task load. Dependent variables included measures of fatigue, arousal, workload, task performance (delayed and error rates), and brain functional connectivity. Both time-on-task and task load significantly affected cerebral connectivity, response lapses, workload (frustration level), fatigue, and arousal. Arousal levels significantly decreased and reaction times increased after 60 min of work. Cognitive resource regulation became challenging after 90 min under high task load levels. A decline in the connection between the prefrontal and occipital cortex during high-load tasks was observed. The findings provide insight into the mechanisms of response lapses under different task load levels and can inform strategies to mitigate these lapses during extended work periods. This study’s findings can be applied to improve work schedules and fatigue management in industries like aviation, transportation, and healthcare, helping reduce response lapses and errors during extended work periods under high task load conditions.

Production and Forming of Deposition‐Welded Hybrid Multimaterial Shafts

The combination of several materials in one component can contribute to increased performance. Herein, three types of hybrid components are manufactured using two cladding processes and one joining process. The resulting workpieces are then formed and tested to determine the potential of the different material combinations. Two types of workpieces are produced to investigate multilayer claddings made of different materials, which serve to positively adjust the residual stress. The workpieces are tested using microstructural images and hardness measurements to characterize the microstructure and properties of the intermediate layers. In addition, residual stress measurements are carried out to determine the residual stress ratios. Compressive residual stresses are present in the subsurface of the welded and subsequently formed layer, which will improve the service life in case of rolling load conditions. The third type of workpiece is a combination of aluminum alloy and steel with a cladding layer that combines the performance of the cladding material in the bearing seat with the weight reduction of the aluminum alloy. Scanning Electron Microscopy (SEM) measurements are used to determine whether the application of the cladding has an influence on the intermetallic phase seam in the joining zone of aluminum alloy and steel.

Carbon dioxide capture in large-scale CCGT power plant from flue gases obtained from various fuel mixtures

In this study, the thermodynamic analysis of a combined cycle gas turbine integrated with post-combustion carbon capture and storage using the solvent method is performed. The syngas obtained from the gasification of sewage sludge is mixed with methane and nitrogen-rich natural gas fuels at different proportions, used in the gas turbine, and the properties of fuel and flue gases are analyzed. The flue gas obtained from the fuel mixture is passed through the post-combustion carbon capture and storage at various load conditions to assess the heat and electricity required for the carbon capture process. The solvent used for the carbon capture from flue gases enables CO2 capture with the high efficiency of 90%. With the calculated results, the load conditions of flue gas using fuel mixtures are identified, which reduces the heat and power demand of post-combustion carbon capture and storage and provides the possibility to achieve neutral emission. The impact of selected operating conditions of post-combustion carbon capture and storage on the CO2 emission reduction process and on the power plant performances is investigated. Considering the factors of electricity generation, energy efficiency, heat supply to the consumers, operating load of post-combustion carbon cap-ture and storage and CO2 emission, the 50% mixture of syngas with both fuels performs better. Also, the use of a mixture of 2-amino-2methyl-1-propanol and piperazine with reboiler duty 3.7 MJ/kgCO2 in post-combustion carbon capture and storage slightly enhanced the performance of the power plant compared to the use of monoethanolamine with reboiler duty 3.8 MJ/kgCO2.

Experimental investigation on the seismic performance of reinforced concrete frames with decoupled masonry infills: considering in-plane and out-of-plane load interaction effects

AbstractMasonry infills are frequently employed as both outer and inner partitions in reinforced concrete (RC) frame structures due to their outstanding characteristics in terms of energy efficiency, fire resistance and sound isolation. However, common construction practice typically involves the mortar connection between masonry infills and RC frames. For this reason, the unforeseen frame-infill interaction takes part under seismic loading, which leads to severe and uncontrollable damage to masonry infills. This interaction also causes damage or even the collapse of the RC frames and thus of the whole structures. The poor performance of infilled RC frame structures in recent earthquake events is a strong motivation for the development of innovative engineering solutions, which aim to mitigate the detrimental effects of frame-infill interaction. This article introduces an innovative decoupling system founded on the concept of decoupling the RC frame from the masonry infill. The decoupling is achieved by inserting elastomeric material between the masonry infill and RC frame. The properly designed decoupling system allows infill activation only at high in-plane drifts. Simultaneously, it provides boundary conditions for seismic loads acting perpendicular to the infill plane. Firstly, the article explains the design of the masonry infill with the decoupling system and its installation. Afterwards, the results of small specimen tests carried out to determine the load-bearing capacity of the decoupling system are presented. Furthermore, the article discusses the findings of an extensive experimental campaign conducted on nine real-size RC frames with decoupled infills subjected to separate and combined in-plane and out-of-plane loadings. In addition to different loading types, various infill configurations are considered – solid infill, infill with centric window, and infill with centric door opening. Finally, the experimental results of RC frames with decoupled infills are compared with the experimental results of traditionally infilled RC frames, which were tested within the framework of the same project. The thorough evaluation and comparison of the experimental findings demonstrate the significant improvement of seismic performance of infilled RC frames if the decoupling system is applied.

Numerical study of cellular beams under different types of loading

The integration of cellular metal beams in high-rise buildings allows for optimized space utilization for technical equipment, while also reducing floor height and, consequently, the overall weight of the superstructure. However, while these openings provide design flexibility, they can also decrease structural stability by causing deformations in the web posts, especially under concentrated loads. This study focuses on evaluating the strength and stability of open-section beams under various load conditions, using numerical simulations and three-point bending tests. Specific reinforcement solutions were developed to counter instability phenomena and enhance mechanical performance. The results indicate that the finite element model used in simulations provides accurate and consistent predictions with experimental data, validating its utility for in-depth analysis of displacements and failure modes. Notably, the addition of stiffeners proved effective in reducing displacements and enhancing beam stability. This work, still in its exploratory phase, aims to develop a theoretical formula to estimate the contribution of supports to elastic stiffness, paving the way for advances in the use of reinforced metal beams in high-rise construction.

Exploring the Application of Large Language Models Based AI Agents in Leakage Detection of Natural Gas Valve Chambers

Leakage problems occur from time to time due to the large number of equipment and complex processes during oil and gas production and transportation. The traditional detection methods highly depend on manpower with large workload and are prone to missed and false alarms, which seriously affects the efficiency and safety of oil and gas production and transportation. With the continuous improvement of information technology and the rapid advancement of artificial intelligence (AI), the research on leakage detection technology based on AI methods has attracted more and more attention. This paper discusses the application scenarios of an AI agent based on the recently emerged large language model (LLM) technology in oil and gas production leakage detection: (1) Compared with the traditional leakage detection methods, this paper innovatively employs a combination of AI-based diagnostics and infrared temperature measurement technologies to develop a specialized small model for oil and gas leakage detection, which has been proven to significantly improve the accuracy of detecting industrial venting events in natural gas valve chambers; (2) By employing retrieval-augmented generation (RAG) technology, a knowledge vector library is constructed, utilizing a series of leakage-related documents, assisting the LLM to carry out knowledge questioning and inference. Compared with the traditional SimBERT, the accuracy can be improved by about 15% in the Q&A search ability test. The correct rate is about 70% higher than the SimBERT in the Chinese complex reasoning quiz. Also, it can still remain stable under high load conditions, with the interruption rate of retrieval closing to zero. (3) By combining the specialized small model and the knowledge Q&A tool, the natural gas valve chambers’ leakage detection AI agent based on the open-source LLM model was designed and developed, which preliminarily achieved the leakage detection based on the specialized small model, and the automatic processing of the retrieval reasoning process based on the knowledge Q&A tool and the intelligent generation of corresponding leakage disposal scheme. The effectiveness of the method has been verified by actual project data. This article conducts preliminary explorations into the in-depth applications of AI agents based on LLMs in the oil and gas energy industry, demonstrating certain positive outcomes.

Energy-exergy analyses of hydrogen enriched⸺ diesel and blended biofuel (Azolla pinnata macroalgae) on the dual fuel diesel engine

Hydrogen fuel has gained global attention as a potential alternative to conventional fuels as it reduces greenhouse gas emissions and addresses energy sustainability challenges. In addition, biofuel (Azolla pinnata) is highly productive having limited negative impacts with an exemplary productivity rate. The energy-exergy analysis in CI engine's is an effective method for determining its efficiency and effectiveness. This paper highlights the effects of diesel, H2 enriched diesel, and H2 enriched B40 (60% diesel + 40% Algal Biodiesel) on the energetic and exergetic efficiency of a dual-fuel diesel engine with a rated speed and power of 1500 rpm and 3.5 kW respectively. The analysis was done at varying engine loads: low loads (25%), medium loads (50%), and high loads (75%), respectively. The energy and exergy for 40% hydrogen-enriched B40 increased by 8.77% and 23.85%, respectively, compared to neat diesel operation at higher loads. In addition, the irreversibility of 40% hydrogen-enriched B40 decreased by 13.82% at higher load conditions as compared to base diesel operation. The sustainability index of 40% hydrogen-enriched B40 was 1.38 compared to 1.28 of diesel, showing an improvement of 7.82%. The theoretical energy-exergy analyses showed an error less than 5% compared to BTE validating the results of the energy-exergy analyses performed theoretically.

Fixed-Time Consensus Multi-Agent-Systems-Based Speed Cooperative Control for Multiple Permanent Magnet Synchronous Motors with Complementary Sliding Mode Control

To improve the tracking performance and robustness of traditional multi-motor speed cooperative control, this paper proposes a speed cooperative control method for multiple permanent magnet synchronous motors (multi-PMSMs) based on the fixed-time consensus protocol for multi-agent systems (MASs) combined with CSMC. Firstly, the speed regulation system of multi-PMSMs is regarded as a MAS. By designing a distributed consensus protocol based on an undirected communication topology, the system achieves fixed-time consensus convergence. Then, a terminal integral sliding mode observer (TISMO) is designed to estimate disturbances, and feedforward compensation is introduced into the consensus protocol to obtain the desired q-axis current. Furthermore, within the framework of the vector control speed cooperative system of PMSMs, a CSMC is designed to track the q-axis reference current. Meanwhile, the stability of the above controllers and observers is theoretically proven using the Lyapunov functions. Finally, comparative experiments are conducted on a multi-PMSM speed regulation experimental platform to verify the proposed control method against the traditional deviation coupling control (DCC) method. The results indicate that under the new control method proposed in this paper, the chattering phenomenon is reduced by about 2 r/min compared to the traditional DCC method. During sudden load and sudden relief load conditions, the speed fluctuation is reduced by approximately 4%, demonstrating good tracking performance and strong robustness.

Improving DC power supply performance: insights into Cuk and modified Cuk converters' stability and power factor

Abstract The conversion of alternating current (AC) to direct current (DC) is pivotal for modern electrical systems, significantly influencing power delivery efficiency and stability. As the reliance on DC-powered electronic devices grows, optimizing AC-DC converters becomes increasingly important. Various converter topologies, including buck, boost, buck-boost, Cuk, and SEPIC configurations, exhibit unique characteristics that affect their efficiency and impact on the power grid. This study examines the performance of Cuk and modified Cuk converters, utilizing PSIM software to simulate these converters for a 1.4 kW power supply. The simulations reveal that both the Cuk and modified Cuk converters achieve reduced ripple in voltage and current outputs, addressing a significant concern for DC power supplies. Additionally, the modified Cuk converter demonstrates a marked reduction in the total harmonic distortion (THD) of the source current. This study explored the interaction between converter topologies and varying load conditions, emphasizing their impact on power factor—a measure of electrical power consumption. A higher power factor indicates improved efficiency and reduced reactive power, benefiting both the electrical system and the grid. The research further investigates how load variations affect power factor and converter performance, providing insights into designing converters that enhance system reliability and efficiency. By validating the simulation results with experimental data, it has been established that the modified Cuk converter topology offers superior performance and stability. This advancement supports the development of converters that optimize power factor and energy consumption, which are crucial for advancing electrical infrastructure. By bridging the gap between simulation and real-world performance, this work aims to provide valuable insights that can inform future enhancements in domestic EV charging infrastructure, ultimately contributing to the broader adoption of electric vehicles.

Dual Control Strategy for Non-Minimum Phase Behavior Mitigation in DC-DC Boost Converters Using Finite Control Set Model Predictive Control and Proportional–Integral Controllers

Model Predictive Control (MPC) has emerged as a promising alternative for controlling power converters, offering benefits such as flexibility, simplicity, and rapid control response, particularly when short-horizon algorithms are employed. This paper introduces a system using a short-horizon Finite Control Set MPC (FCS-MPC) strategy to specifically address the challenge of non-minimum phase behavior in boost converters. The non-minimum phase issue, which complicates the control process by introducing an initial inverse response, is effectively mitigated by the proposed method. A Proportional–Integral (PI) controller is integrated to dynamically adjust the reference current based on the output voltage error, thereby enhancing overall system stability and performance. Unlike conventional PI-MPC methods, where the PI controller has an influence on the system dynamics, the PI controller in this approach is solely used for tuning the reference current needed for the FCS-MPC controller. The PI controller addresses small deviations in output voltage, primarily due to model prediction inaccuracies, ensuring steady-state accuracy, while the FCS-MPC handles fast dynamic responses to adapt the controller’s behavior based on load conditions. This dual control strategy effectively balances the need for precise voltage regulation and rapid adaptation to varying load conditions. The proposed method’s effectiveness is validated through a multi-stage simulation test, demonstrating significant improvements in response time and stability compared to traditional control methods. Hardware-in-the-loop testing further confirms the system’s robustness and potential for real-time applications in power electronics.

Tribologically enhanced self‐healing hybrid laminates for wind turbine applications

AbstractWind turbines are subjected to extreme weather and load conditions; hence, high strength and impact resistance are required. Furthermore, wind turbine blades can be subjected to impact loads such as bird strikes, resulting in the formation of microcracks. Self‐healing capsules can be used to mend turbine blades for microscale damage. The incorporation of self‐healing capsules may cause a decrease in the mechanical characteristics of the composites prior to impact resistance, which can be compensated for with efficient fillers such as silicon carbide whiskers (SiCw). Thus, a novel hybrid composite structure is examined with the advantage of using a self‐healing mechanism and SiCw reinforcement. Tensile, tribological, and Charpy impact tests were performed to characterize the mechanical and tribological properties, which were supported with microscopic observations. Multiple experimental characterizations were performed to investigate the impact, and the ultimate tensile strength (UTS) and energy absorption capacity of the structure were shown to increase by 32% and 45%, respectively, with the addition of SiCw. The presence of self‐healing agents provides a 5% rise in UTS after enough time for healing following the collision. The structure's tribological performance is improved by 10% in wear resistance and 20% in friction coefficient.Highlights Hybrid laminated composite structure with silicon carbide whisker and self‐healing capsules. Tensile and Charpy impact tests conducted with microscopic observations Increased ultimate tensile strength and energy absorption capacity by 32% and 45%. Tribological improvement by 10% in wear resistance and 20% in friction coefficient.

Study on Operation Effect of Two-Stage MSL System for Rural Decentralized Sewage Treatment

To improve the removal efficiency of rural domestic sewage, a two-stage multi-soil-layer sewage treatment system with an “aeration section + non-aeration section” was designed, and its treatment performance was observed under different influent loads and aeration intensities. The experiment ran for a total of 150 days, and the results showed that the two-stage multi-soil-layer (MSL) system could effectively reduce the effluent concentration of sewage to meet discharge standards. Under the operating conditions of an influent hydraulic load of 1000 L·m−2·d−1 and an air–water ratio of 4:1, the final effluent average concentrations of COD, NH3-N, TN, and TP were 106.5 mg·L−1, 7.4 mg·L−1, 13.9 mg·L−1, 0.12 mg·L−1, and 18.6 mg·L−1, respectively, with average removal rates of 85.3%, 82%, 72.5%, 96%, and 85%. A longer hydraulic retention time and ideal anoxic conditions were ensured by designing a certain effluent height in the system. Adding aeration to the system allowed for a synchronous nitrification–denitrification reaction under reasonable influent loads, ultimately enabling the effluent to meet discharge standards.