To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation in...To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation indices of deformation uniformity were provided,and the DEFORM-3D software was adopted to conduct numerical simulations of the rolling process.The metal flow and strain distribution in all stages of the rolling process were analyzed.It is shown that the strain value of the rolled piece close to the end is relatively high while the overall strain distribution is uniform in the rolling process.When the percentage reduction in area is smaller,the fluctuation range of the equivalent strain will be lower and the overall uniformity of the rolled piece will be better.A variable angle wedge was implemented to make metal flow inward and eliminate concavity.Finally,rolling experiment was performed,which indicate that the shape of the rolled piece obtained is consistent with the simulation results.Concavity value in the rolling is decreased by 92%as compared to conventional open rolling.The research results lay a theoretical basis for realizing closed-open-type cross-wedge rolling without a stub bar.展开更多
In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety system...In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety systems. We recommend an appropriate methodology for converting existing ships to run on LNG fuel, discuss all the necessary modifications to the ship’s safety systems, and also evaluate the relevant ship evacuation procedures. We outline the basic requirements with which the ship already complies for each safety system and analyze the additional restrictions that must be taken into consideration for the use of LNG fuel. Appropriate actions are recommended. Furthermore, we carry out a hazard identification study. Overall, we clearly demonstrate the technical feasibility of the investigated scenario. Minimal modifications to the ship’s safety systems are required to comply with existing safety rules for this specific type of ship.展开更多
Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model...Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.展开更多
In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a to...In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.展开更多
The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting...The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting Exoplanet Survey Satellite(TESS)offer valuable opportunities for large-scale flare studies.A variety of methods is currently employed for flare detection,with machine learning(ML)approaches demonstrating strong potential for automated classification tasks,particularly for the analysis of astronomical time series.This review provides an overview of the methods used to detect stellar flares in TESS data and evaluates their performance and effectiveness.It includes our assessment of both traditional detection techniques and more recent methods,such as ML algorithms,highlighting their strengths and limitations.By addressing current challenges and identifying promising approaches,this manuscript aims to support further studies and promote the development of stellar flare research.展开更多
Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causin...Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.展开更多
The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical lin...The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).展开更多
The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to preve...The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to prevent multiple follicles development,multiple gestation and ovary hyperstimulation.Details should be paid attention to while adopting the flare-up protocol,in order to take it’s advantages and avoid disadvantages.展开更多
Transition on a flared cone with zero angle of at- tack was studied in our newly established Mach 6 quiet wind tunnel （M6QT） via wall pressure measurement and flow visualization. High-frequency pressure transducers ...Transition on a flared cone with zero angle of at- tack was studied in our newly established Mach 6 quiet wind tunnel （M6QT） via wall pressure measurement and flow visualization. High-frequency pressure transducers were used to measure the second-mode waves＇ amplitudes and frequencies. Using pulsed schlieren diagnostic and Rayleigh scattering technique, we got a clear evolution of the second-mode disturbances. The second-mode waves exist for a long distance, which means that the second-mode waves grow linearly in a large region. Strong Mach waves are radiated from the edge of the boundary layer. With further development, the second-mode waves reach their maximum magnitude and harmonics of the second-mode instability appear. Then the disturbances grow nonlinearly. The second modes become weak and merge with each other. Finally, the nonlinear interaction of disturbance leads to a relatively quiet zone, which further breaks down, resulting in the transition of the bound- ary layer. Our results show that transition is determined by the second mode. The quiet zone before the final breakdown is observed in flow visualization for the first time. Eventual transition requires the presence of a quiet zone generated by nonlinear interactions.展开更多
火炬气的排放系统设计是一个非常复杂的过程,涉及到各泄放点的背压与管路马赫数的计算。介绍了Aspen Flare System Analyzer模拟软件的特点及应用方法,该软件遵循API的规范要求,通过计算火炬管网中各管段始末点的压力、温度、流速等参数...火炬气的排放系统设计是一个非常复杂的过程,涉及到各泄放点的背压与管路马赫数的计算。介绍了Aspen Flare System Analyzer模拟软件的特点及应用方法,该软件遵循API的规范要求,通过计算火炬管网中各管段始末点的压力、温度、流速等参数,可有效发现设计中的不合理管径并进行修改。以中东某油田地面工程项目为例,阐述了在工程实际中如何通过该软件进行火炬管网核算。高压火炬管网的核算结果显示,部分安全阀尾管背压和马赫数过大,经软件修改后的尺寸在实际运行中可满足火炬气的排放要求,保证了系统安全。表明了该软件在安全阀的选型和火炬管网的设计工作中的应用价值。展开更多
This study was designed to compare the impact of post and core systems on resistance to fracture of endodontically treated anterior teeth with flared root canals and to assess their fracture pattern. Sixty central inc...This study was designed to compare the impact of post and core systems on resistance to fracture of endodontically treated anterior teeth with flared root canals and to assess their fracture pattern. Sixty central incisors were cut horizontally 2 mm coronal to the cementoenamel junction(CEJ). After root canal therapy, teeth were assigned into 6 groups(n = 10 each) based on a post system and used as follows: Group C, non-flared root received size #1 glass fiber posts(Control); Group AP, flared root restored with anatomical post; Group RC, flared root restored with size #1 fiber post and cemented with thick layer of resin cement; Group CR, flared root restored with size #1 and reinforced with composite resin; Group CM, cast post-core; Group CP, CAD/CAM polymer-infiltrated ceramic post and core.Following post cementation, core build-up and crown insertion, the specimens were thermo-cycled up to 10,000 cycles(5 C/55 C; 30 seconds dwell time, 6 seconds transition time) and then statically loaded at 1 mm/minute crosshead speed using a universal testing machine. One-way ANOVA and Tukey HSD post hoc test(α= 0.05) were used for data analysis. Group C recorded significantly higher resistance to fracture values [(826.9±39.1) N] followed by group CP [(793.8±55.6) N] while group RC yielded the lowest fracture resistance values [(586.7±51.4) N]. The resistance to fracture of wide root canals can be enhanced by using one-piece CAM/CAM post and core as an alternative to the use of either glass fiber post, relined with composite resin increasing the thickness of luting cement or the use of cast post and core system. However, this was an in vitro investigation and further in vivo studies are necessary.展开更多
A method combining the support vector machine （SVM） the K-Nearest Neighbors （KNN）, labelled the SVM-KNN method, is used to construct a solar flare forecasting model. Based on a proven relationship between SVM and ...A method combining the support vector machine （SVM） the K-Nearest Neighbors （KNN）, labelled the SVM-KNN method, is used to construct a solar flare forecasting model. Based on a proven relationship between SVM and KNN, the SVM-KNN method improves the SVM algorithm of classification by taking advantage of the KNN algorithm according to the distribution of test samples in a feature space. In our flare forecast study, sunspots and 10cm radio flux data observed during Solar Cycle 23 are taken as predictors, and whether an M class flare will occur for each active region within two days will be predicted. The SVM- KNN method is compared with the SVM and Neural networks-based method. The test results indicate that the rate of correct predictions from the SVM-KNN method is higher than that from the other two methods. This method shows promise as a practicable future forecasting model.展开更多
基金The authors gratefully acknowledge the support of K.C.Wong Education Foundation.Hong Kong,the National Natural Science Foundation of China(Grant Number 51975301)the Natural Science Foundation of Zhejiang(Grant Number LZI7EO5OOO1).
文摘To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation indices of deformation uniformity were provided,and the DEFORM-3D software was adopted to conduct numerical simulations of the rolling process.The metal flow and strain distribution in all stages of the rolling process were analyzed.It is shown that the strain value of the rolled piece close to the end is relatively high while the overall strain distribution is uniform in the rolling process.When the percentage reduction in area is smaller,the fluctuation range of the equivalent strain will be lower and the overall uniformity of the rolled piece will be better.A variable angle wedge was implemented to make metal flow inward and eliminate concavity.Finally,rolling experiment was performed,which indicate that the shape of the rolled piece obtained is consistent with the simulation results.Concavity value in the rolling is decreased by 92%as compared to conventional open rolling.The research results lay a theoretical basis for realizing closed-open-type cross-wedge rolling without a stub bar.
基金conducted within the framework of the project LNG-COMSHIP,Greek General Secretariat of Research and Technology Code:12CHN400,and was funded by the European Regional Development Fund(ERDF) and National Resources
文摘In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety systems. We recommend an appropriate methodology for converting existing ships to run on LNG fuel, discuss all the necessary modifications to the ship’s safety systems, and also evaluate the relevant ship evacuation procedures. We outline the basic requirements with which the ship already complies for each safety system and analyze the additional restrictions that must be taken into consideration for the use of LNG fuel. Appropriate actions are recommended. Furthermore, we carry out a hazard identification study. Overall, we clearly demonstrate the technical feasibility of the investigated scenario. Minimal modifications to the ship’s safety systems are required to comply with existing safety rules for this specific type of ship.
基金supported by the National Key R&D Program of China (Grant No.2022YFF0503700)the National Natural Science Foundation of China (42074196, 41925018)
文摘Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.
文摘In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.
基金supported by the National Natural Science Foundation of China(12473104 and U2031144).
文摘The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting Exoplanet Survey Satellite(TESS)offer valuable opportunities for large-scale flare studies.A variety of methods is currently employed for flare detection,with machine learning(ML)approaches demonstrating strong potential for automated classification tasks,particularly for the analysis of astronomical time series.This review provides an overview of the methods used to detect stellar flares in TESS data and evaluates their performance and effectiveness.It includes our assessment of both traditional detection techniques and more recent methods,such as ML algorithms,highlighting their strengths and limitations.By addressing current challenges and identifying promising approaches,this manuscript aims to support further studies and promote the development of stellar flare research.
基金partially supported by the National Key R&D Program of China (2022YFE0133700)the National Natural Science Foundation of China(12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program (YQK[2023]006)the National SKA Program of China (2020SKA0110300)the National Natural Science Foundation of China(11963003)the Guizhou Provincial Basic Research Program (Natural Science)(ZK[2022]143)the Cultivation project of Guizhou University ([2020]76).
文摘Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.
文摘The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).
文摘The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to prevent multiple follicles development,multiple gestation and ovary hyperstimulation.Details should be paid attention to while adopting the flare-up protocol,in order to take it’s advantages and avoid disadvantages.
文摘Transition on a flared cone with zero angle of at- tack was studied in our newly established Mach 6 quiet wind tunnel （M6QT） via wall pressure measurement and flow visualization. High-frequency pressure transducers were used to measure the second-mode waves＇ amplitudes and frequencies. Using pulsed schlieren diagnostic and Rayleigh scattering technique, we got a clear evolution of the second-mode disturbances. The second-mode waves exist for a long distance, which means that the second-mode waves grow linearly in a large region. Strong Mach waves are radiated from the edge of the boundary layer. With further development, the second-mode waves reach their maximum magnitude and harmonics of the second-mode instability appear. Then the disturbances grow nonlinearly. The second modes become weak and merge with each other. Finally, the nonlinear interaction of disturbance leads to a relatively quiet zone, which further breaks down, resulting in the transition of the bound- ary layer. Our results show that transition is determined by the second mode. The quiet zone before the final breakdown is observed in flow visualization for the first time. Eventual transition requires the presence of a quiet zone generated by nonlinear interactions.
文摘火炬气的排放系统设计是一个非常复杂的过程,涉及到各泄放点的背压与管路马赫数的计算。介绍了Aspen Flare System Analyzer模拟软件的特点及应用方法,该软件遵循API的规范要求,通过计算火炬管网中各管段始末点的压力、温度、流速等参数,可有效发现设计中的不合理管径并进行修改。以中东某油田地面工程项目为例,阐述了在工程实际中如何通过该软件进行火炬管网核算。高压火炬管网的核算结果显示,部分安全阀尾管背压和马赫数过大,经软件修改后的尺寸在实际运行中可满足火炬气的排放要求,保证了系统安全。表明了该软件在安全阀的选型和火炬管网的设计工作中的应用价值。
文摘This study was designed to compare the impact of post and core systems on resistance to fracture of endodontically treated anterior teeth with flared root canals and to assess their fracture pattern. Sixty central incisors were cut horizontally 2 mm coronal to the cementoenamel junction(CEJ). After root canal therapy, teeth were assigned into 6 groups(n = 10 each) based on a post system and used as follows: Group C, non-flared root received size #1 glass fiber posts(Control); Group AP, flared root restored with anatomical post; Group RC, flared root restored with size #1 fiber post and cemented with thick layer of resin cement; Group CR, flared root restored with size #1 and reinforced with composite resin; Group CM, cast post-core; Group CP, CAD/CAM polymer-infiltrated ceramic post and core.Following post cementation, core build-up and crown insertion, the specimens were thermo-cycled up to 10,000 cycles(5 C/55 C; 30 seconds dwell time, 6 seconds transition time) and then statically loaded at 1 mm/minute crosshead speed using a universal testing machine. One-way ANOVA and Tukey HSD post hoc test(α= 0.05) were used for data analysis. Group C recorded significantly higher resistance to fracture values [(826.9±39.1) N] followed by group CP [(793.8±55.6) N] while group RC yielded the lowest fracture resistance values [(586.7±51.4) N]. The resistance to fracture of wide root canals can be enhanced by using one-piece CAM/CAM post and core as an alternative to the use of either glass fiber post, relined with composite resin increasing the thickness of luting cement or the use of cast post and core system. However, this was an in vitro investigation and further in vivo studies are necessary.
基金the National Natural Science Foundation of China
文摘A method combining the support vector machine （SVM） the K-Nearest Neighbors （KNN）, labelled the SVM-KNN method, is used to construct a solar flare forecasting model. Based on a proven relationship between SVM and KNN, the SVM-KNN method improves the SVM algorithm of classification by taking advantage of the KNN algorithm according to the distribution of test samples in a feature space. In our flare forecast study, sunspots and 10cm radio flux data observed during Solar Cycle 23 are taken as predictors, and whether an M class flare will occur for each active region within two days will be predicted. The SVM- KNN method is compared with the SVM and Neural networks-based method. The test results indicate that the rate of correct predictions from the SVM-KNN method is higher than that from the other two methods. This method shows promise as a practicable future forecasting model.
