Video cameras are common at volcano observatories,but their utility is often limited during periods of crisis due to the large data volume from continuous acquisition and time requirements for manual analysis.For came...Video cameras are common at volcano observatories,but their utility is often limited during periods of crisis due to the large data volume from continuous acquisition and time requirements for manual analysis.For cameras to serve as effective monitoring tools,video frames must be synthesized into relevant time series signals and further analyzed to classify and characterize observable activity.In this study,we use computer vision and machine learning algorithms to identify periods of volcanic activity and quantify plume rise velocities from video observations.Data were collected at Villarrica Volcano,Chile from two visible band cameras located^17 km from the vent that recorded at 0.1 and 30 frames per second between February and April 2015.Over these two months,Villarrica exhibited a diverse range of eruptive activity,including a paroxysmal eruption on 3 March.Prior to and after the eruption,activity included nighttime incandescence,dark and light emissions,inactivity,and periods of cloud cover.We quantify the color and spatial extent of plume emissions using a blob detection algorithm,whose outputs are fed into a trained artificial neural network that categorizes the observable activity into five classes.Activity shifts from primarily nighttime incandescence to ash emissions following the 3 March paroxysm,which likely relates to the reemergence of the buried lava lake.Time periods exhibiting plume emissions are further analyzed using a row and column projection algorithm that identifies plume onsets and calculates apparent plume horizontal and vertical rise velocities.Plume onsets are episodic,occurring with an average period of^50 s and suggests a puffing style of degassing,which is commonly observed at Villarrica.However,the lack of clear acoustic transients in the accompanying infrasound record suggests puffing may be controlled by atmospheric effects rather than a degassing regime at the vent.Methods presented here offer a generalized toolset for volcano monitors to classify and track emission statistics at a variety of volcanoes to better monitor periods of unrest and ultimately forecast major eruptions.展开更多
Detailed two-dimensional unsteady numerical simulation is carried out to investigate a high-power synthetic jet actuator flow field and its design characteristic. Simultaneously, mixing control mechanism of coaxial je...Detailed two-dimensional unsteady numerical simulation is carried out to investigate a high-power synthetic jet actuator flow field and its design characteristic. Simultaneously, mixing control mechanism of coaxial jets with actuators is also studied. Firstly, excitation frequency （rotating speed）, piston displacement and its exit slot width have effect on the controlling ability and controlling efficiency of actuator. With the invariable model and con- cerned parameters, the actuator becomes more desirable as the rotating speed increases. Average velocity and maximal velocity at the actuator exit section increase as the piston displacement enlarges or the exit slot width decreases. But the actuator does not always exhibit good performance with the narrower exit. Secondly, the synthetic jets also have the ＂push＂ effect on the coaxial jets, which results in the fluctuation of vorticity and temperature distribution of mixing flowfield. Finally, the employment of synthetic jet actuator can achieve mixing enhancement significantly.展开更多
基金partially supported by National Science Foundation grant EAR-0838562 and EAR1830976。
文摘Video cameras are common at volcano observatories,but their utility is often limited during periods of crisis due to the large data volume from continuous acquisition and time requirements for manual analysis.For cameras to serve as effective monitoring tools,video frames must be synthesized into relevant time series signals and further analyzed to classify and characterize observable activity.In this study,we use computer vision and machine learning algorithms to identify periods of volcanic activity and quantify plume rise velocities from video observations.Data were collected at Villarrica Volcano,Chile from two visible band cameras located^17 km from the vent that recorded at 0.1 and 30 frames per second between February and April 2015.Over these two months,Villarrica exhibited a diverse range of eruptive activity,including a paroxysmal eruption on 3 March.Prior to and after the eruption,activity included nighttime incandescence,dark and light emissions,inactivity,and periods of cloud cover.We quantify the color and spatial extent of plume emissions using a blob detection algorithm,whose outputs are fed into a trained artificial neural network that categorizes the observable activity into five classes.Activity shifts from primarily nighttime incandescence to ash emissions following the 3 March paroxysm,which likely relates to the reemergence of the buried lava lake.Time periods exhibiting plume emissions are further analyzed using a row and column projection algorithm that identifies plume onsets and calculates apparent plume horizontal and vertical rise velocities.Plume onsets are episodic,occurring with an average period of^50 s and suggests a puffing style of degassing,which is commonly observed at Villarrica.However,the lack of clear acoustic transients in the accompanying infrasound record suggests puffing may be controlled by atmospheric effects rather than a degassing regime at the vent.Methods presented here offer a generalized toolset for volcano monitors to classify and track emission statistics at a variety of volcanoes to better monitor periods of unrest and ultimately forecast major eruptions.
基金Postdoctoral Science Foundation of China,Grant No.20070420300
文摘Detailed two-dimensional unsteady numerical simulation is carried out to investigate a high-power synthetic jet actuator flow field and its design characteristic. Simultaneously, mixing control mechanism of coaxial jets with actuators is also studied. Firstly, excitation frequency （rotating speed）, piston displacement and its exit slot width have effect on the controlling ability and controlling efficiency of actuator. With the invariable model and con- cerned parameters, the actuator becomes more desirable as the rotating speed increases. Average velocity and maximal velocity at the actuator exit section increase as the piston displacement enlarges or the exit slot width decreases. But the actuator does not always exhibit good performance with the narrower exit. Secondly, the synthetic jets also have the ＂push＂ effect on the coaxial jets, which results in the fluctuation of vorticity and temperature distribution of mixing flowfield. Finally, the employment of synthetic jet actuator can achieve mixing enhancement significantly.
