Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decisi...Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decision making is adopted to ascertain the action sequence of reactive power compensation devices. First, a set of evaluation indexes including control sensitivity, regulation margin, response time, response level and cost is set up, and fuzziness of the proposed qualitative indexes is introduced to make them comparable to the proposed quantitative indexes. Then a method to calculate fuzzy weight of each index is put forward for evaluating relative importance of the proposed indexes. Finally, the action sequence of reactive power compensation devices is determined through the theory of fuzzy compromise decision making. The case study shows that the proposed method is effective to obtain the action sequence of reactive power compensation device which correspond to experience.展开更多
Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is ...Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature.Whenever there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy systems.In this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power systems.Frequency control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning models.The performance analysis of the proposed method is done with different machine learning based approaches.The forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting accuracy.Simulation results show that the Mean Absolute Percentage Error(MAPE),Root Mean Square Error(RMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.展开更多
This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and ...This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and a solar field in order to optimize the production of all the technologies. The results obtained made it possible to evaluate the operating performance of the installation and to show the complementarity between the two energy sources with regard to temporary and seasonal variations in resources. During nighttime periods or periods of low sunlight, the wind turbine is a good alternative to energy storage by batteries, the output of the wind turbine can be up to 853.76 W. It was also a question of proposing solutions for optimizing the hybrid system through the automation of the hybrid charge regulator. A minimum height of 30 m above the ground has been chosen as the optimum height for the wind turbine.展开更多
Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and h...Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and high upkeep costs.Therefore,the development of a specialized front-end filter tailored for direct current water-cooled system is importance.This involves the integration of dimensionally stable anode(DSA)and nickel alloy cathode,valued for their corrosion resistance in seawater,into a novel front-end filter system for Water-cooled applications.This system has the dual capability of generating hydrogen and chlorine for self-cleaning purposes.Implementing a flushing pulse electrolysis mode,it effectively mitigates electrode failure induced by cathodic calcium and magnesium deposition,thereby significantly prolonging electrode lifespan.Laboratory tests comprising system assembly and performance evaluations were conducted,with the system programmed to operate for 5 minutes every 24 hours under continuous flushing by natural seawater to simulate real-world conditions.After more than 11 months of continuous flushing,observations reveal that the DSA mesh and nickel alloy mesh maintain intact structural integrity and normal functioning.Subsequent 1꞉1 physical prototype Sea trial further validated the soundness of the system design and electrolytic control parameters.展开更多
In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)d...In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)during disturbances.Moreover,due to the frequency decoupling between the two ends of the MMCHVDC,the sending-end wind farm(SEWF)cannot obtain the frequency variation information of the REG to provide inertia response.Therefore,this paper proposes a novel coordinated source-network-storage inertia control strategy based on wind power transmission via MMC-HVDC system.First,the grid-side MMC station(GS-MMC)maps the frequency variations of the REG to direct current(DC)voltage variations through the frequency mapping control,and uses submodule capacitor energy to provide inertial power.Then,the wind farm-side MMC station(WF-MMC)restores the DC voltage variations to frequency variations through the frequency restoration control and power loss compensation,providing real-time frequency information for the wind farm.Finally,based on real-time frequency information,thewind farmutilizes the rotor kinetic energy and energy storage to provide fast and lasting power support through the wind-storage coordinated inertia control strategy.Meanwhile,when the wind turbines withdraw from the inertia response phase,the energy storage can increase the power output to compensate for the power deficit,preventing secondary frequency drops.Furthermore,this paper uses small-signal analysis to determine the appropriate values for the key parameters of the proposed control strategy.A simulation model of the wind power transmission via MMCHVDC system is built in MATLAB/Simulink environment to validate and evaluate the proposed method.The results show that the proposed coordinated control strategy can effectively improve the system inertia level and avoid the secondary frequency drop under the load sudden increase condition.展开更多
Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that devi...Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)syste...This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.展开更多
New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates beca...New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates because of harsh weather,significantly affecting the maintenance procedures and reliability.Different types of failure rates of the wind turbine(WT)and wave energy converter(WEC),e.g.,the degradation and failure rates during regular wind speed fluctuation,the degradation and failure rates during intense wind speed fluctuation are considered.By incorporating both WT and WEC,the HWWPG system is designed to enhance the overall amount of electrical energy produced by the system over a given period under varying weather conditions.The universal generating function technique is used to calculate the HWWPG system dependability measures in a structured and efficient manner.This research highlights that intense weather conditions increase the failure rates of both WT and WEC,resulting in higher maintenance costs and more frequent downtimes,thus impacting the HWWPG system’s reliability.Although the HWWPG system can meet the energy demands in the presence of high failure rates,the reliance of the hybrid system on both WT and WEC helps maintain a relatively stable demand satisfaction during periods of high energy demand despite adverse weather conditions.To confirm the added value and applicability of the developed model,a case study of an offshore hybrid platform is conducted.The findings underscore the system’s robustness in maintaining energy production under varied weather conditions,though higher failure rates and maintenance costs arise in intense scenarios.展开更多
Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid syste...Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid systems are mostly based on single-column platforms such as spars(single coaxial-cylinder hybrid system'hereafter).Systems based on multiple-column platforms such as semi-submersible platforms('multiple coaxial-cylinder hybrid systems'hereafter)are rarely seen or studied,despite their superiority in wave-power absorption due to the use of multiple WECs as well as in dynamic stability.This paper proposes a novel WindFloat-annular-WEC hybrid system,based on our study investigating its dynamic and power features,and optimizing the geometry and power take-off of the WECs.Our results show that the dynamic and power features of a multiple coaxial-cylinder hybrid system are different from those of a single coaxial-cylinder hybrid system,so the same optimization parameters cannot be directly applied.Flatter annular WECs absorb slightly more power in a wider wave-period range,but their geometry is confined by limitations in installation and structural strength.The overall effect of an oblique incident wave is greater intensity in the motions of the hybrid system in yaw and the direction perpendicular to propagation,although the difference is small and maybe negligible.展开更多
As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowc...As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.展开更多
This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mod...This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.展开更多
The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACT...The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.展开更多
The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind powe...The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.展开更多
The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbi...The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.展开更多
Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-...Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.展开更多
Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the pe...Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the performance of composite shelterbelts that integrate C.esculentus.This study systematically evaluated five shelterbelt models—Populus euphratica(P.euphratica),P.euphratica–C.esculentus composite,P.euphratica–nylon net–C.esculentus composite,Tamarix chinensis(T.chinensis),and T.chinensis–C.esculentus composite—using wind tunnel experiments and field observations.Sediment flux was measured at a normalized downwind distance(x/h)of 5,where x refers to the distance from the front edge(upwind side)of the shelterbelt for upwind measurements,and the distance from the rear edge(downwind side)for downwind measurements,and h represents the canopy height.Wind velocity was measured at x/h of–2,–1,1,2,3,5,and 7,and sand flux was measured at x/h=5,under initial wind velocities of 8.0 and 12.0 m/s.The results indicated that the P.euphratica–nylon net–C.esculentus composite was the most effective in reducing wind velocity,followed by the P.euphratica–C.esculentus composite.In contrast,the P.euphratica and T.chinensis exhibited relatively weaker wind reduction capabilities.Regarding sand flux,under moderate wind velocity(8.0 m/s),both the P.euphratica–C.esculentus composite and P.euphratica–nylon net–C.esculentus composite demonstrated the lowest sand flux values.However,under high wind velocity(12.0 m/s),the P.euphratica–nylon net–C.esculentus composite significantly outperformed the other shelterbelt models in sand retention,highlighting its superior windbreak and sand fixation efficacy.Field observations further validated the windbreak and sand fixation effects of C.esculentus.Comparisons between the bare sand plot and C.esculentus plot within protective forests demonstrated that planting C.esculentus can provide substantial ecological benefits in windbreak and sand-fixation.These findings,reinforced by field observations,strengthen the wind tunnel experiment results and highlight the critical role of C.esculentus in enhancing the performance of composite shelterbelts for desert ecological restoration.展开更多
Wind disturbance has emerged as a potential eco-friendly method for seedling cultivation.In this study,an electromechanical device was designed and built to investigate the effects of airflow on the micro-environment ...Wind disturbance has emerged as a potential eco-friendly method for seedling cultivation.In this study,an electromechanical device was designed and built to investigate the effects of airflow on the micro-environment and physiological activities of tomato seedlings in seedbeds by controlled experiments.The results indicated that airflow could enhance CO_(2) concentration near the seedling canopy,accelerate water evaporation from the seedling substrate,and reduce fluctuations in the temperature and humidity in microclimate.The photosynthetic rates of leaves at the 4th,7th,and 10th positions in seedlings subjected to airflow increased by 25.04%,8.23%,and 8.47%,respectively,whereas the transpiration rates increased by 15.59%,22.28%,and 13.26%,respectively when compared to the control group.Additionally,the strong seedling index of seedlings treated with airflow and exogenous iron element increased by 26.02%and 31.5%,respectively.Compared to seedlings treated with exogenous iron element,the geometric mean diameter of the pith tissue cells in the stems of seedlings subjected to airflow disturbance was reduced by approximately 18.66%,while the elastic modulus and bending strength of the stems increased by 10.01%and 5.89%,respectively.Similarly,the volume of root tissue cells decreased by 19.22%,but the elastic modulus of the roots increased by 6.46%.This study confirms that airflow significantly enhances seedling resilience to abiotic stress,yielding similar or better outcomes than exogenous iron application.It provides both theoretical and practical support for using airflow disturbance as a green technology for cultivating robust seedlings.展开更多
Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On ...Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On the other hand,the entry of ice crystal particles into the combustion chamber can cause a decrease in temperature or even flameout,leading to engine surge or shutdown.Therefore,it is necessary to conduct multiphase flow tests on ice crystals for aircraft components such as aircraft engines.Conducting ice crystal multiphase flow tests on aircraft is an effective research method,but it requires the construction of an ice crystal multiphase flow test platform that meets relevant technical requirements.The paper focuses on the relevant experimental requirements and combines wind tunnel test structures to conduct multiphase flow numerical simulations on various forms of jet pipelines,obtaining particle motion distribution results.After comparison,the optimal form of jet structure is obtained,providing the best selection scheme for the design of relevant wind tunnel structures.展开更多
In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A fi...In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A finite element model of the plastic-lined composite hydrogen storage cylinder,designed to withstand a working pressure of 70.0 MPa,was established by using the wound composite modeler(WCM)in the Abaqus software to analyze the forces acting on the winding layer.The Hashin failure criterion was utilized as the standard for assessing composite failure,and a progressive failure analysis of the cylinder was conducted to predict both the bursting pressure and the failure location of the composite hydrogen storage cylinder.The results indicate that the reaming process can effectively reduce the maximum filament winding thickness in the head section and promote a more uniform transition.At the bursting pressure,the stress within the head liner decreases,thereby enhancing the ultimate bearing capacity of the cylinder.A control system for a four-axis winding machine was designed by utilizing an industrial computer and a programmable multi-axis controller(PMAC).The winding line pattern is designed and the G-code trajectory is generated by the industrial computer.The numerical control system,composed of the PMAC and servo motor,executes the four-axis interpolation motion.展开更多
文摘Frequent occurrence of large-scale cascading trip-off of wind turbine raises the concern about the decision process of ordered control of reactive power compensation devices. The theory of fuzzy multi-attribute decision making is adopted to ascertain the action sequence of reactive power compensation devices. First, a set of evaluation indexes including control sensitivity, regulation margin, response time, response level and cost is set up, and fuzziness of the proposed qualitative indexes is introduced to make them comparable to the proposed quantitative indexes. Then a method to calculate fuzzy weight of each index is put forward for evaluating relative importance of the proposed indexes. Finally, the action sequence of reactive power compensation devices is determined through the theory of fuzzy compromise decision making. The case study shows that the proposed method is effective to obtain the action sequence of reactive power compensation device which correspond to experience.
文摘Frequency deviation has to be controlled in power generation units when there arefluctuations in system frequency.With several renewable energy sources,wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature.Whenever there is a mismatch between generation and demand,the frequency deviation may arise from the actual frequency 50 Hz(in India).To mitigate the frequency deviation issue,it is necessary to develop an effective technique for better frequency control in wind energy systems.In this work,heuristic Fuzzy Logic Based Controller(FLC)is developed for providing an effective frequency control support by modeling the complex behavior of the system to enhance the load forecasting in wind based hybrid power systems.Frequency control is applied to reduce the frequency deviation due tofluctuations and load prediction information using ANN(Artificial Neural Network)and SVM(Support Vector Machine)learning models.The performance analysis of the proposed method is done with different machine learning based approaches.The forecasting assessment is done over various climates with the aim to decrease the prediction errors and to demote the forecasting accuracy.Simulation results show that the Mean Absolute Percentage Error(MAPE),Root Mean Square Error(RMSE)and Normalized Mean Absolute Error(NMAE)values are scaled down by 41.1%,9.9%and 23.1%respectively in the proposed method while comparing with existing wavelet and BPN based approach.
文摘This work is a contribution to the study of hybrid systems for converting solar and wind energy into electricity in Burkina Faso. The approach consists of evaluating and analyzing the production of a wind turbine and a solar field in order to optimize the production of all the technologies. The results obtained made it possible to evaluate the operating performance of the installation and to show the complementarity between the two energy sources with regard to temporary and seasonal variations in resources. During nighttime periods or periods of low sunlight, the wind turbine is a good alternative to energy storage by batteries, the output of the wind turbine can be up to 853.76 W. It was also a question of proposing solutions for optimizing the hybrid system through the automation of the hybrid charge regulator. A minimum height of 30 m above the ground has been chosen as the optimum height for the wind turbine.
基金Supported by the Project of Design of Anti-corrosion and Anti-fouling Solutions for Offshore Wind Power Water-Cooled Systems(No.E428161)the National Natural Science Foundation of China(No.42176047)。
文摘Water-cooled system have significantly enhanced the power generation efficiency of offshore wind turbines.However,these innovative systems are susceptible to substantial biological fouling,maintenance challenges,and high upkeep costs.Therefore,the development of a specialized front-end filter tailored for direct current water-cooled system is importance.This involves the integration of dimensionally stable anode(DSA)and nickel alloy cathode,valued for their corrosion resistance in seawater,into a novel front-end filter system for Water-cooled applications.This system has the dual capability of generating hydrogen and chlorine for self-cleaning purposes.Implementing a flushing pulse electrolysis mode,it effectively mitigates electrode failure induced by cathodic calcium and magnesium deposition,thereby significantly prolonging electrode lifespan.Laboratory tests comprising system assembly and performance evaluations were conducted,with the system programmed to operate for 5 minutes every 24 hours under continuous flushing by natural seawater to simulate real-world conditions.After more than 11 months of continuous flushing,observations reveal that the DSA mesh and nickel alloy mesh maintain intact structural integrity and normal functioning.Subsequent 1꞉1 physical prototype Sea trial further validated the soundness of the system design and electrolytic control parameters.
基金funded by State Grid Corporation of China Central Branch Technology Project(52140024000C).
文摘In wind power transmission via modular multilevel converter based high voltage direct current(MMCHVDC)systems,under traditional control strategies,MMC-HVDCcannot provide inertia support to the receiving-end grid(REG)during disturbances.Moreover,due to the frequency decoupling between the two ends of the MMCHVDC,the sending-end wind farm(SEWF)cannot obtain the frequency variation information of the REG to provide inertia response.Therefore,this paper proposes a novel coordinated source-network-storage inertia control strategy based on wind power transmission via MMC-HVDC system.First,the grid-side MMC station(GS-MMC)maps the frequency variations of the REG to direct current(DC)voltage variations through the frequency mapping control,and uses submodule capacitor energy to provide inertial power.Then,the wind farm-side MMC station(WF-MMC)restores the DC voltage variations to frequency variations through the frequency restoration control and power loss compensation,providing real-time frequency information for the wind farm.Finally,based on real-time frequency information,thewind farmutilizes the rotor kinetic energy and energy storage to provide fast and lasting power support through the wind-storage coordinated inertia control strategy.Meanwhile,when the wind turbines withdraw from the inertia response phase,the energy storage can increase the power output to compensate for the power deficit,preventing secondary frequency drops.Furthermore,this paper uses small-signal analysis to determine the appropriate values for the key parameters of the proposed control strategy.A simulation model of the wind power transmission via MMCHVDC system is built in MATLAB/Simulink environment to validate and evaluate the proposed method.The results show that the proposed coordinated control strategy can effectively improve the system inertia level and avoid the secondary frequency drop under the load sudden increase condition.
基金supported in part by the National Natural Science Foundation of China(No.52467008)Gansu Provincial Depatment of Education Youth Doctoral Suppo Project(2024QB-051).
文摘Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
文摘This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.
文摘New renewable energy exploitation technologies in offshore structures are vital for future energy production systems.Offshore hybrid wind-wave power generation(HWWPG)systems face increased component failure rates because of harsh weather,significantly affecting the maintenance procedures and reliability.Different types of failure rates of the wind turbine(WT)and wave energy converter(WEC),e.g.,the degradation and failure rates during regular wind speed fluctuation,the degradation and failure rates during intense wind speed fluctuation are considered.By incorporating both WT and WEC,the HWWPG system is designed to enhance the overall amount of electrical energy produced by the system over a given period under varying weather conditions.The universal generating function technique is used to calculate the HWWPG system dependability measures in a structured and efficient manner.This research highlights that intense weather conditions increase the failure rates of both WT and WEC,resulting in higher maintenance costs and more frequent downtimes,thus impacting the HWWPG system’s reliability.Although the HWWPG system can meet the energy demands in the presence of high failure rates,the reliance of the hybrid system on both WT and WEC helps maintain a relatively stable demand satisfaction during periods of high energy demand despite adverse weather conditions.To confirm the added value and applicability of the developed model,a case study of an offshore hybrid platform is conducted.The findings underscore the system’s robustness in maintaining energy production under varied weather conditions,though higher failure rates and maintenance costs arise in intense scenarios.
基金supported by the National Natural Science Foundation of China(Nos.52201322,52222109,and 52071096)the Guangdong Basic and Applied Basic Research Foundation(Nos.2022B1515020036 and 2023A1515012144)the Natural Science Foundation of Guangzhou City(No.202201010055),China.
文摘Installing annular wave-energy converters(WECs)on the columns of floating wind platforms in the form of a coaxial-cylinder provides a convenient means of integration.Extant coaxial-cylinder-type wind-wave hybrid systems are mostly based on single-column platforms such as spars(single coaxial-cylinder hybrid system'hereafter).Systems based on multiple-column platforms such as semi-submersible platforms('multiple coaxial-cylinder hybrid systems'hereafter)are rarely seen or studied,despite their superiority in wave-power absorption due to the use of multiple WECs as well as in dynamic stability.This paper proposes a novel WindFloat-annular-WEC hybrid system,based on our study investigating its dynamic and power features,and optimizing the geometry and power take-off of the WECs.Our results show that the dynamic and power features of a multiple coaxial-cylinder hybrid system are different from those of a single coaxial-cylinder hybrid system,so the same optimization parameters cannot be directly applied.Flatter annular WECs absorb slightly more power in a wider wave-period range,but their geometry is confined by limitations in installation and structural strength.The overall effect of an oblique incident wave is greater intensity in the motions of the hybrid system in yaw and the direction perpendicular to propagation,although the difference is small and maybe negligible.
基金supported by the Science and Technology Project of China Huaneng Group Co.,Ltd.Research on Key Technologies for Monitoring and Protection of Offshore Wind Power Underwater Equipment(HNKJ21-H40).
文摘As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.
基金supported by the 2022 Sanya Science and Technology Innovation Project,China(No.2022KJCX03)the Sanya Science and Education Innovation Park,Wuhan University of Technology,China(Grant No.2022KF0028)the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.2021JJLH0036).
文摘This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.
文摘The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.
基金Supported by the National Natural Science Foundation of China(22468035,22468036,22368038,22308048)the Natural Science Foundation of Inner Mongolia(2024QN02018,2025MS02030)+2 种基金First-class Discipline Research Special Project of Inner Mongolia(YLXKZX-NGD-045)Inner Mongolia Autonomous Region Postgraduate Research Innovation Project(KC2024047B)Research Foundation for Introducing High-level Talents in Inner Mongolia Autonomous Region。
文摘The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.
文摘The world’s most powerful offshore wind turbine has begun feeding electricity into the grid off the coast of southeast China,marking a major technological leap in the country’s wind power industry.The colossal turbine,developed and installed by China Three Gorges Corp.(CTG),is located in the Phase II Liuao offshore wind farm,more than 30 km off the coast of Fujian in waters deeper than 40 metres.The 20-mw unit successfully completed commissioning and started operation on 5 February,CTG announced.
文摘Wind turbine blade defect detection faces persistent challenges in separating small,low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints.Conven-tional image-processing pipelines struggle with scalability and robustness,and recent deep learning methods remain sensitive to class imbalance and acquisition variability.This paper introduces TurbineBladeDetNet,a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types.Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability.The model achieves 97.14%accuracy,98.65%precision,and 98.68%recall,yielding a 98.66%F1-score with 0.0110 s inference time.Class-specific analysis shows uniformly high sensitivity and specificity;lightning damage reaches 99.80%for sensitivity,precision,and F1-score,and crack achieves perfect precision and specificity with a 98.94%F1-score.Comparative evaluation against recent wind-turbine inspection approaches indicates higher performance in both accuracy and F1-score.The resulting balance of sensitivity and specificity limits both missed defects and false alarms,supporting reliable deployment in routine unmanned aerial vehicle(UAV)inspection.
基金supported by the Xinjiang Key Research and Development Programme Project(2022B02040-2)the Tianshan Yingcai Program of Xinjiang Uygur Autonomous Region(2024TSYCLJ0028).
文摘Cyperus esculentus(C.esculentus),a desert-adapted plant species with both ecological and economic value,has been widely cultivated in northern China's sandy regions.However,limited studies have investigated the performance of composite shelterbelts that integrate C.esculentus.This study systematically evaluated five shelterbelt models—Populus euphratica(P.euphratica),P.euphratica–C.esculentus composite,P.euphratica–nylon net–C.esculentus composite,Tamarix chinensis(T.chinensis),and T.chinensis–C.esculentus composite—using wind tunnel experiments and field observations.Sediment flux was measured at a normalized downwind distance(x/h)of 5,where x refers to the distance from the front edge(upwind side)of the shelterbelt for upwind measurements,and the distance from the rear edge(downwind side)for downwind measurements,and h represents the canopy height.Wind velocity was measured at x/h of–2,–1,1,2,3,5,and 7,and sand flux was measured at x/h=5,under initial wind velocities of 8.0 and 12.0 m/s.The results indicated that the P.euphratica–nylon net–C.esculentus composite was the most effective in reducing wind velocity,followed by the P.euphratica–C.esculentus composite.In contrast,the P.euphratica and T.chinensis exhibited relatively weaker wind reduction capabilities.Regarding sand flux,under moderate wind velocity(8.0 m/s),both the P.euphratica–C.esculentus composite and P.euphratica–nylon net–C.esculentus composite demonstrated the lowest sand flux values.However,under high wind velocity(12.0 m/s),the P.euphratica–nylon net–C.esculentus composite significantly outperformed the other shelterbelt models in sand retention,highlighting its superior windbreak and sand fixation efficacy.Field observations further validated the windbreak and sand fixation effects of C.esculentus.Comparisons between the bare sand plot and C.esculentus plot within protective forests demonstrated that planting C.esculentus can provide substantial ecological benefits in windbreak and sand-fixation.These findings,reinforced by field observations,strengthen the wind tunnel experiment results and highlight the critical role of C.esculentus in enhancing the performance of composite shelterbelts for desert ecological restoration.
基金supported by an International Cooperation Key Plan of Shaanxi Province(Grant No.2022KWZ-12)an Agricultural Science Innovation and Transformation Project of Shaanxi Province[Grant No.NYKJ-2022-YL(XN)12]a High-End Foreign Expert Recruitment Program(Grant No.G2022172006L).
文摘Wind disturbance has emerged as a potential eco-friendly method for seedling cultivation.In this study,an electromechanical device was designed and built to investigate the effects of airflow on the micro-environment and physiological activities of tomato seedlings in seedbeds by controlled experiments.The results indicated that airflow could enhance CO_(2) concentration near the seedling canopy,accelerate water evaporation from the seedling substrate,and reduce fluctuations in the temperature and humidity in microclimate.The photosynthetic rates of leaves at the 4th,7th,and 10th positions in seedlings subjected to airflow increased by 25.04%,8.23%,and 8.47%,respectively,whereas the transpiration rates increased by 15.59%,22.28%,and 13.26%,respectively when compared to the control group.Additionally,the strong seedling index of seedlings treated with airflow and exogenous iron element increased by 26.02%and 31.5%,respectively.Compared to seedlings treated with exogenous iron element,the geometric mean diameter of the pith tissue cells in the stems of seedlings subjected to airflow disturbance was reduced by approximately 18.66%,while the elastic modulus and bending strength of the stems increased by 10.01%and 5.89%,respectively.Similarly,the volume of root tissue cells decreased by 19.22%,but the elastic modulus of the roots increased by 6.46%.This study confirms that airflow significantly enhances seedling resilience to abiotic stress,yielding similar or better outcomes than exogenous iron application.It provides both theoretical and practical support for using airflow disturbance as a green technology for cultivating robust seedlings.
文摘Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On the other hand,the entry of ice crystal particles into the combustion chamber can cause a decrease in temperature or even flameout,leading to engine surge or shutdown.Therefore,it is necessary to conduct multiphase flow tests on ice crystals for aircraft components such as aircraft engines.Conducting ice crystal multiphase flow tests on aircraft is an effective research method,but it requires the construction of an ice crystal multiphase flow test platform that meets relevant technical requirements.The paper focuses on the relevant experimental requirements and combines wind tunnel test structures to conduct multiphase flow numerical simulations on various forms of jet pipelines,obtaining particle motion distribution results.After comparison,the optimal form of jet structure is obtained,providing the best selection scheme for the design of relevant wind tunnel structures.
文摘In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A finite element model of the plastic-lined composite hydrogen storage cylinder,designed to withstand a working pressure of 70.0 MPa,was established by using the wound composite modeler(WCM)in the Abaqus software to analyze the forces acting on the winding layer.The Hashin failure criterion was utilized as the standard for assessing composite failure,and a progressive failure analysis of the cylinder was conducted to predict both the bursting pressure and the failure location of the composite hydrogen storage cylinder.The results indicate that the reaming process can effectively reduce the maximum filament winding thickness in the head section and promote a more uniform transition.At the bursting pressure,the stress within the head liner decreases,thereby enhancing the ultimate bearing capacity of the cylinder.A control system for a four-axis winding machine was designed by utilizing an industrial computer and a programmable multi-axis controller(PMAC).The winding line pattern is designed and the G-code trajectory is generated by the industrial computer.The numerical control system,composed of the PMAC and servo motor,executes the four-axis interpolation motion.
