聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程...聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程化评价保障学习效果。研究表明,该范式能有效提升学生阅读兴趣与综合语言能力,为小学英语阅读启蒙教学提供可复制、可推广的创新路径。展开更多
The unstarted flow field in a hypersonic inlet model at a design point of Ma 6 is studied experimentally.The time-resolved spatial flow characteristics of the separation shock oscillation,which is induced by the unsta...The unstarted flow field in a hypersonic inlet model at a design point of Ma 6 is studied experimentally.The time-resolved spatial flow characteristics of the separation shock oscillation,which is induced by the unstarted flow,are analyzed based on a high-speed Schlieren system and an image processing method.The motion of the separation shock detected by the shock-detection algorithm is compared to the results of fast-response wall-pressure measurements,and good agreement is demonstrated by comparing the frequency components in the power spectral density contours between shock oscillation and pressure fluctuation.The hysteresis of the pressure and separation shock during oscillation cycles is observed from the time history of the shock motion,which means that the unsteady flow pattern of the unstarted hypersonic flow can be accurately clarified by time-resolved Schlieren image processing.These results convincingly demonstrate that the shock-detection technique is successfully applied to an unstarted hypersonic flow case.展开更多
In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight tech...In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.展开更多
In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicle...In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicles(UAVs)has garnered significant attention.The PEMFC,serving as the primary energy supply,markedly extends the UAV’s operational endurance.However,due to payload limitations and spatial constraints in the airframe layout of UAVs,the stack requires customized adaptation.Moreover,the implementation of auxiliary systems to facilitate cold starts of the PEMFC under low-temperature conditions is not feasible.Relying solely on thermal insulation measures also proves inadequate to address the challenges posed by complex low-temperature startup scenarios.To overcomethis,our study leverages the UAV’s lithium battery to heat the cathode inlet airflow,aiding the cathode-open PEMFC cold start process.To validate the feasibility of the proposed air-assisted heating strategy during the conceptual design phase,this study develops a transient,non-isothermal 3Dcathode-open PEMF Cunitmodel incorporating cathode air-assisted heating and gas-ice phase change.The model’s accuracy was verified against experimental cold-start data from a stack composed of identical single cells.This computational framework enables quantitative analysis of temperature fields and ice fraction distributions across domains under varying air-assisted heating powers during cold starts.Building upon this model,the study further investigates the improvement in cold start performance by heating the cathode intake air with varying power levels.The results demonstrate that the fuel cell achieves self-startup at temperatures as low as−13℃ under a constant current density of 100mA/cm^(2) without air-assisted heating.At an ambient temperature of−20℃,a successful start-up can be achieved with a heating power of 0.45 W/cm^(2).The temperature variation overtime during the cold start process can be represented by a sum of two exponential functions.The air-assisted heating scheme proposed in this study has significantly improved the cold start performance of fuel cells in low-temperature environments.Additionally,it provides critical reference data and validation support for component selection and feasibility assessment of hybrid power systems.展开更多
引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工...引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工智能的引入,极大地增强了课堂的互动性和趣味性,使学生更深入地理解食物链的逻辑,激发了学习英语的兴趣。人工智能不仅能够为孩子们提供个性化学习体验,还能够极大地提高教学效率和质量。展开更多
This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also pr...This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also predicts the transient characteristics of the pump under non-rated operating conditions to assess the accuracy of various machine learning methods in forecasting its instantaneous performance.Results indicate that the pump’s transient behavior in power-frequency mode markedly differs from that in frequency-conversion mode.Specifically,the power-frequency mode achieves steady-state values faster and exhibits smaller fluctuations before stabilization compared to the other mode.During the start-up phase,as the steady-state flow rate increases,inlet and outlet pressures and head also rise,while torque and shaft power decrease,with rotational speed remaining largely unchanged.Conversely,during the shutdown phase,no significant changes were observed in torque,shaft power,or rotational speed.Six machine learning models,including Gaussian Process Regression(GPR),Decision Tree Regression(DTR),and Deep Learning Networks(DLN),demonstrated high accuracy in predicting the hydraulic performance of the centrifugal pump during the start-up and shutdown phases in both power-frequency and frequency-conversion conditions.The findings provide a theoretical foundation for improved prediction of pump hydraulic performance.For instance,when predicting head and flow rate during power-frequency start-up,GPR achieved absolute and relative errors of 0.54 m(7.84%)and 0.21 m3/h(13.57%),respectively,while the Feedforward Neural Network(FNN)reported errors of 0.98 m(8.24%)and 0.10 m3/h(16.71%).By contrast,the Support Vector Machine Regression(SVMR)and Generalized Additive Model(GAM)generally yielded less satisfactory prediction accuracy compared to the other methods.展开更多
The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key ...The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.展开更多
文摘聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程化评价保障学习效果。研究表明,该范式能有效提升学生阅读兴趣与综合语言能力,为小学英语阅读启蒙教学提供可复制、可推广的创新路径。
基金supported by National Natural Science Foundation of China (Nos. 51776096 and 51476076)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘The unstarted flow field in a hypersonic inlet model at a design point of Ma 6 is studied experimentally.The time-resolved spatial flow characteristics of the separation shock oscillation,which is induced by the unstarted flow,are analyzed based on a high-speed Schlieren system and an image processing method.The motion of the separation shock detected by the shock-detection algorithm is compared to the results of fast-response wall-pressure measurements,and good agreement is demonstrated by comparing the frequency components in the power spectral density contours between shock oscillation and pressure fluctuation.The hysteresis of the pressure and separation shock during oscillation cycles is observed from the time history of the shock motion,which means that the unsteady flow pattern of the unstarted hypersonic flow can be accurately clarified by time-resolved Schlieren image processing.These results convincingly demonstrate that the shock-detection technique is successfully applied to an unstarted hypersonic flow case.
基金supported by the Foundation of Shanghai Aerospace Science and Technology(SAST2016077)。
文摘In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.
基金funded by Zhejiang Province Spearhead and Leading Goose Research and Development Key Program,grant number 2023C01239.
文摘In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicles(UAVs)has garnered significant attention.The PEMFC,serving as the primary energy supply,markedly extends the UAV’s operational endurance.However,due to payload limitations and spatial constraints in the airframe layout of UAVs,the stack requires customized adaptation.Moreover,the implementation of auxiliary systems to facilitate cold starts of the PEMFC under low-temperature conditions is not feasible.Relying solely on thermal insulation measures also proves inadequate to address the challenges posed by complex low-temperature startup scenarios.To overcomethis,our study leverages the UAV’s lithium battery to heat the cathode inlet airflow,aiding the cathode-open PEMFC cold start process.To validate the feasibility of the proposed air-assisted heating strategy during the conceptual design phase,this study develops a transient,non-isothermal 3Dcathode-open PEMF Cunitmodel incorporating cathode air-assisted heating and gas-ice phase change.The model’s accuracy was verified against experimental cold-start data from a stack composed of identical single cells.This computational framework enables quantitative analysis of temperature fields and ice fraction distributions across domains under varying air-assisted heating powers during cold starts.Building upon this model,the study further investigates the improvement in cold start performance by heating the cathode intake air with varying power levels.The results demonstrate that the fuel cell achieves self-startup at temperatures as low as−13℃ under a constant current density of 100mA/cm^(2) without air-assisted heating.At an ambient temperature of−20℃,a successful start-up can be achieved with a heating power of 0.45 W/cm^(2).The temperature variation overtime during the cold start process can be represented by a sum of two exponential functions.The air-assisted heating scheme proposed in this study has significantly improved the cold start performance of fuel cells in low-temperature environments.Additionally,it provides critical reference data and validation support for component selection and feasibility assessment of hybrid power systems.
文摘引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工智能的引入,极大地增强了课堂的互动性和趣味性,使学生更深入地理解食物链的逻辑,激发了学习英语的兴趣。人工智能不仅能够为孩子们提供个性化学习体验,还能够极大地提高教学效率和质量。
基金financially supported by Science and Technology Project of Quzhou(Grant Nos.2023K256,2023NC08)Research Grants Program of Department of Education of Zhejiang Province(No.Y202455709)+1 种基金Zhejiang Provincial Natural Science Foundation of China(Grant No.LZY21E050001)University-Enterprise Cooperation Program for Visiting Engineers in Higher Education Institutions in Zhejiang Province(No.FG2020215).
文摘This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also predicts the transient characteristics of the pump under non-rated operating conditions to assess the accuracy of various machine learning methods in forecasting its instantaneous performance.Results indicate that the pump’s transient behavior in power-frequency mode markedly differs from that in frequency-conversion mode.Specifically,the power-frequency mode achieves steady-state values faster and exhibits smaller fluctuations before stabilization compared to the other mode.During the start-up phase,as the steady-state flow rate increases,inlet and outlet pressures and head also rise,while torque and shaft power decrease,with rotational speed remaining largely unchanged.Conversely,during the shutdown phase,no significant changes were observed in torque,shaft power,or rotational speed.Six machine learning models,including Gaussian Process Regression(GPR),Decision Tree Regression(DTR),and Deep Learning Networks(DLN),demonstrated high accuracy in predicting the hydraulic performance of the centrifugal pump during the start-up and shutdown phases in both power-frequency and frequency-conversion conditions.The findings provide a theoretical foundation for improved prediction of pump hydraulic performance.For instance,when predicting head and flow rate during power-frequency start-up,GPR achieved absolute and relative errors of 0.54 m(7.84%)and 0.21 m3/h(13.57%),respectively,while the Feedforward Neural Network(FNN)reported errors of 0.98 m(8.24%)and 0.10 m3/h(16.71%).By contrast,the Support Vector Machine Regression(SVMR)and Generalized Additive Model(GAM)generally yielded less satisfactory prediction accuracy compared to the other methods.
基金Project(2018XK2301) supported by the Change-Zhu-Tan National Independent Innavation Demonstration Zone Special Program,China。
文摘The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.
