[目的]比较关节镜下缝合钩和Fast-fix缝合Ⅳ型半月板Ramp区损伤的临床疗效。[方法]回顾性分析2016年1月—2020年10月45例前交叉韧带(anterior cruciate ligament, ACL)损伤合并Ⅳ型半月板Ramp损伤患者的临床资料。所有患者均取自体腘绳...[目的]比较关节镜下缝合钩和Fast-fix缝合Ⅳ型半月板Ramp区损伤的临床疗效。[方法]回顾性分析2016年1月—2020年10月45例前交叉韧带(anterior cruciate ligament, ACL)损伤合并Ⅳ型半月板Ramp损伤患者的临床资料。所有患者均取自体腘绳肌腱行ACL重建,依据术前医患沟通结果,21例应用缝合钩缝合Ramp损伤,24例应用Fast-fix缝合。对比患者围手术期、随访及影像学结果。[结果]所有患者均顺利完成手术,术中未出现血管、神经损伤等并发症。缝合钩组手术时间[(91.2±10.6) min vs (62.5±8.4) min, P<0.001]、切口总长度[(5.9±0.5) cm vs (5.1±0.6) cm, P<0.001]均显著长于Fast-fix组,但前者住院费用显著少于后者[(3.4±0.3)万元vs (4.3±0.7)万元, P<0.001]。两组Ramp撕裂长度、缝合针数、下地行走时间、切口愈合、住院时间比较差异均无统计学意义(P>0.05)。所有患者均获36~72个月随访。两组完全负重活动时间的差异无统计学意义(P>0.05)。术后1年及末次随访时,两组膝间隙压痛、麦氏征,轴移征、膝关节屈伸ROM、IKDC评分及Lysholm评分较术前均显著改善(P<0.05)。同一时间点,两组上述指标的差异均无统计学意义(P>0.05)。影像方面,与术前相比,术后1年,两组半月板损伤分级及胫骨平台后侧骨髓水肿均显著改善(P<0.05),相应时间点,两组上述指标的差异均无统计学意义(P>0.05)。术后1年MRI显示缝合钩组愈合率为90.5%、Fast-fix组为87.5%,差异无统计学意义(P>0.05)。[结论]关节镜下缝合钩和Fast-fix缝合半月板Ramp区Ⅳ型损伤均可获得满意疗效。展开更多
The influence of ramps on the transient rolling contact characteristics and damage mechanisms of switch rails remains unclear,presenting substantial challenges to the safety of railway operations.To this end,this pape...The influence of ramps on the transient rolling contact characteristics and damage mechanisms of switch rails remains unclear,presenting substantial challenges to the safety of railway operations.To this end,this paper constructs a transient rolling contact finite element model of the wheel-rail in switch under different ramps using ANSYS/LSDYNA method,and analyzes the tribology and damage characteristics when the wheel passes through the switch at a uniform speed.Our research findings reveal that the vibration induced in the switch rail during the wheel load transfer process leads to a step-like increase in the contact force.Moreover,the interaction between the wheel and the rail primarily involves slip contact,which may significantly contribute to the formation of corrugations on the switch rail.Additionally,the presence of large ramps exacerbates switch rail wear and rolling contact fatigue,resulting in a notable 13.2%increase in switch rail damage under 40‰ramp conditions compared to flat(0‰ramp)conditions.Furthermore,the large ramps can alter the direction of crack propagation,ultimately causing surface spalling of the rail.Therefore,large ramps intensify the dynamic interactions during the wheel load transfer process,further aggravating the crack and spalling damage to the switch rails.展开更多
Photovoltaic(PV)systems are being increasingly implemented in the grid,and their intermittent output fluctuations threaten the stability of the grid,thereby requiring effective power ramp control(PRRC)strategies.In th...Photovoltaic(PV)systems are being increasingly implemented in the grid,and their intermittent output fluctuations threaten the stability of the grid,thereby requiring effective power ramp control(PRRC)strategies.In this study,we proposed a power fluctuation identification method to optimize the PRRC strategy.The K-means++cluster based on DTW used in this method,which clusters the historical PV power generation data into power curves corresponding to a specific weather type(sunny,cloudy,and rainy)in a time zone.Subsequently,wavelet decomposition is applied to discretize the power curves with extreme RR overrun to accurately identify the extreme fluctuation time zones.We conducted an analysis using minute-level data from a 100 kW PV plant in Arizona,which demonstrates that the proposed method can effectively identify high-risk periods.Weather patterns within the time zones were quantitatively identified using a weather probability model.A hardware-in-the-loop experimental platform was employed to validate two days of actual power data in Arizona,demonstrating the weather zoning accuracy of the method and the reasonableness of the control.The proposed methodology contributes significantly to PRRC strategy selection and parameter optimization(e.g.,ESS capacity storage allocation and APC power reserveΔP)in different time zones and weather conditions.展开更多
Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control syst...Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control systems.Understanding their dynamic behavior under coupled magnetic,rotational,and reactive effects is crucial for the development of efficient thermal management technologies.This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO_(2)–H_(2)Ohybrid nanofluid flowing through a squarely elevated Riga tunnel.The governing model incorporates Hall and ion-slip effects,thermal radiation,and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces.Closed-form analytical solutions are derived via the Laplace transform method to describe the transient velocity,temperature,and concentration fields.To complement and validate the analytical model,an artificial neural network(ANN)optimized using the Levenberg–Marquardt backpropagation algorithm(ANN-LMBPA)is trained on datasets generated in Mathematica.Regression and error analyses confirm the model’s predictive robustness,with mean squared errors ranging between 10^(-4) and 10^(-9).In addition,an Adaptive Neuro-Fuzzy Inference System(ANFIS)is developed to estimate the heat transfer rate(HTR),achieving aminimal RMSE of 0.011012 for the heat transfer coefficient(HTC).The findings reveal that rotational motion and Hall–ion slip effects suppress primary velocity but enhance secondary flow,while the modified Hartmann number(Lorentz force)accelerates both components.Thermal radiation increases fluid temperature,whereas higher Schmidt numbers and reaction rates diminish solute concentration.The HTR decreases with increasing radiation and nanoparticle volume fraction,while the mass transfer rate(MTR)improves under stronger chemical reactivity.Overall,the proposed hybrid analytical–AI framework demonstrates high accuracy and efficiency,offering valuable insights for the design and optimization of electromagnetic nanofluid systems in advanced thermal and process engineering applications.展开更多
文摘[目的]比较关节镜下缝合钩和Fast-fix缝合Ⅳ型半月板Ramp区损伤的临床疗效。[方法]回顾性分析2016年1月—2020年10月45例前交叉韧带(anterior cruciate ligament, ACL)损伤合并Ⅳ型半月板Ramp损伤患者的临床资料。所有患者均取自体腘绳肌腱行ACL重建,依据术前医患沟通结果,21例应用缝合钩缝合Ramp损伤,24例应用Fast-fix缝合。对比患者围手术期、随访及影像学结果。[结果]所有患者均顺利完成手术,术中未出现血管、神经损伤等并发症。缝合钩组手术时间[(91.2±10.6) min vs (62.5±8.4) min, P<0.001]、切口总长度[(5.9±0.5) cm vs (5.1±0.6) cm, P<0.001]均显著长于Fast-fix组,但前者住院费用显著少于后者[(3.4±0.3)万元vs (4.3±0.7)万元, P<0.001]。两组Ramp撕裂长度、缝合针数、下地行走时间、切口愈合、住院时间比较差异均无统计学意义(P>0.05)。所有患者均获36~72个月随访。两组完全负重活动时间的差异无统计学意义(P>0.05)。术后1年及末次随访时,两组膝间隙压痛、麦氏征,轴移征、膝关节屈伸ROM、IKDC评分及Lysholm评分较术前均显著改善(P<0.05)。同一时间点,两组上述指标的差异均无统计学意义(P>0.05)。影像方面,与术前相比,术后1年,两组半月板损伤分级及胫骨平台后侧骨髓水肿均显著改善(P<0.05),相应时间点,两组上述指标的差异均无统计学意义(P>0.05)。术后1年MRI显示缝合钩组愈合率为90.5%、Fast-fix组为87.5%,差异无统计学意义(P>0.05)。[结论]关节镜下缝合钩和Fast-fix缝合半月板Ramp区Ⅳ型损伤均可获得满意疗效。
基金Project(2023YFB2604304)supported by the National Key R&D Program of ChinaProjects(52122810,51978586,51778542,U23A20666,52472458)supported by the National Natural Science Foundation of China+1 种基金Project(K2022G034)supported by the Technology Research and Development Program of China National Railway Group Co.Ltd.Projects(2020JDJQ0033,2023NSFSC0884)supported by Sichuan Province Science and Technology Support Program,China。
文摘The influence of ramps on the transient rolling contact characteristics and damage mechanisms of switch rails remains unclear,presenting substantial challenges to the safety of railway operations.To this end,this paper constructs a transient rolling contact finite element model of the wheel-rail in switch under different ramps using ANSYS/LSDYNA method,and analyzes the tribology and damage characteristics when the wheel passes through the switch at a uniform speed.Our research findings reveal that the vibration induced in the switch rail during the wheel load transfer process leads to a step-like increase in the contact force.Moreover,the interaction between the wheel and the rail primarily involves slip contact,which may significantly contribute to the formation of corrugations on the switch rail.Additionally,the presence of large ramps exacerbates switch rail wear and rolling contact fatigue,resulting in a notable 13.2%increase in switch rail damage under 40‰ramp conditions compared to flat(0‰ramp)conditions.Furthermore,the large ramps can alter the direction of crack propagation,ultimately causing surface spalling of the rail.Therefore,large ramps intensify the dynamic interactions during the wheel load transfer process,further aggravating the crack and spalling damage to the switch rails.
基金supported by the Natural Science Research Project of Jiangsu Higher Education Institutions(23KJB470019)the Natural Science Foundation of Jiangsu Province under Grant BK20240594.
文摘Photovoltaic(PV)systems are being increasingly implemented in the grid,and their intermittent output fluctuations threaten the stability of the grid,thereby requiring effective power ramp control(PRRC)strategies.In this study,we proposed a power fluctuation identification method to optimize the PRRC strategy.The K-means++cluster based on DTW used in this method,which clusters the historical PV power generation data into power curves corresponding to a specific weather type(sunny,cloudy,and rainy)in a time zone.Subsequently,wavelet decomposition is applied to discretize the power curves with extreme RR overrun to accurately identify the extreme fluctuation time zones.We conducted an analysis using minute-level data from a 100 kW PV plant in Arizona,which demonstrates that the proposed method can effectively identify high-risk periods.Weather patterns within the time zones were quantitatively identified using a weather probability model.A hardware-in-the-loop experimental platform was employed to validate two days of actual power data in Arizona,demonstrating the weather zoning accuracy of the method and the reasonableness of the control.The proposed methodology contributes significantly to PRRC strategy selection and parameter optimization(e.g.,ESS capacity storage allocation and APC power reserveΔP)in different time zones and weather conditions.
文摘Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control systems.Understanding their dynamic behavior under coupled magnetic,rotational,and reactive effects is crucial for the development of efficient thermal management technologies.This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO_(2)–H_(2)Ohybrid nanofluid flowing through a squarely elevated Riga tunnel.The governing model incorporates Hall and ion-slip effects,thermal radiation,and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces.Closed-form analytical solutions are derived via the Laplace transform method to describe the transient velocity,temperature,and concentration fields.To complement and validate the analytical model,an artificial neural network(ANN)optimized using the Levenberg–Marquardt backpropagation algorithm(ANN-LMBPA)is trained on datasets generated in Mathematica.Regression and error analyses confirm the model’s predictive robustness,with mean squared errors ranging between 10^(-4) and 10^(-9).In addition,an Adaptive Neuro-Fuzzy Inference System(ANFIS)is developed to estimate the heat transfer rate(HTR),achieving aminimal RMSE of 0.011012 for the heat transfer coefficient(HTC).The findings reveal that rotational motion and Hall–ion slip effects suppress primary velocity but enhance secondary flow,while the modified Hartmann number(Lorentz force)accelerates both components.Thermal radiation increases fluid temperature,whereas higher Schmidt numbers and reaction rates diminish solute concentration.The HTR decreases with increasing radiation and nanoparticle volume fraction,while the mass transfer rate(MTR)improves under stronger chemical reactivity.Overall,the proposed hybrid analytical–AI framework demonstrates high accuracy and efficiency,offering valuable insights for the design and optimization of electromagnetic nanofluid systems in advanced thermal and process engineering applications.
