Direct numerical simulations （DNS） have now become a well established tool to examine complex multiphase flows. Such flows typically exhibit a large range of scales and it is generally necessary to use different des...Direct numerical simulations （DNS） have now become a well established tool to examine complex multiphase flows. Such flows typically exhibit a large range of scales and it is generally necessary to use different descriptions of the flow depending on the scale that we are examining. Here we discuss multiphase flows from a multiscale perspective. Those include both how DNS are providing insight and understanding for modeling of scales much larger than the ＂dominant scale＂ （defined where surface tension, viscous forces or inertia are important）, as well as how DNS are often limited by the need to resolve processes taking place on much smaller scales. Both problems can be cast into a language introduced for general classes of multiscale problems and reveal that while the classification may be new, the issues are not.展开更多
Selection of sugar beet(Beta vulgaris L.)cultivars that are resistant to Cercospora Leaf Spot(CLS)disease is critical to increase yield.Such selection requires an automatic,fast,and objective method to assess CLS seve...Selection of sugar beet(Beta vulgaris L.)cultivars that are resistant to Cercospora Leaf Spot(CLS)disease is critical to increase yield.Such selection requires an automatic,fast,and objective method to assess CLS severity on thousands of cultivars in the field.For this purpose,we compare the use of submillimeter scale RGB imagery acquired from an Unmanned Ground Vehicle(UGV)under active illumination and centimeter scale multispectral imagery acquired from an Unmanned Aerial Vehicle(UAV)under passive illumination.Several variables are extracted from the images(spot density and spot size for UGV,green fraction for UGV and UAV)and related to visual scores assessed by an expert.Results show that spot density and green fraction are critical variables to assess low and high CLS severities,respectively,which emphasizes the importance of having submillimeter images to early detect CLS in field conditions.Genotype sensitivity to CLS can then be accurately retrieved based on time integrals of UGV-and UAV-derived scores.While UGV shows the best estimation performance,UAV can show accurate estimates of cultivar sensitivity if the data are properly acquired.Advantages and limitations of UGV,UAV,and visual scoring methods are finally discussed in the perspective of high-throughput phenotyping.展开更多
文摘Direct numerical simulations （DNS） have now become a well established tool to examine complex multiphase flows. Such flows typically exhibit a large range of scales and it is generally necessary to use different descriptions of the flow depending on the scale that we are examining. Here we discuss multiphase flows from a multiscale perspective. Those include both how DNS are providing insight and understanding for modeling of scales much larger than the ＂dominant scale＂ （defined where surface tension, viscous forces or inertia are important）, as well as how DNS are often limited by the need to resolve processes taking place on much smaller scales. Both problems can be cast into a language introduced for general classes of multiscale problems and reveal that while the classification may be new, the issues are not.
基金The authors would like to thank Catherine Zanotto and Mathieu Hemmerléfor their help in the experiments.This work was supported by the French National Research Agency in the framework of the“Investissements d’avenir”program AKER(ANR-11-BTBR-0007).
文摘Selection of sugar beet(Beta vulgaris L.)cultivars that are resistant to Cercospora Leaf Spot(CLS)disease is critical to increase yield.Such selection requires an automatic,fast,and objective method to assess CLS severity on thousands of cultivars in the field.For this purpose,we compare the use of submillimeter scale RGB imagery acquired from an Unmanned Ground Vehicle(UGV)under active illumination and centimeter scale multispectral imagery acquired from an Unmanned Aerial Vehicle(UAV)under passive illumination.Several variables are extracted from the images(spot density and spot size for UGV,green fraction for UGV and UAV)and related to visual scores assessed by an expert.Results show that spot density and green fraction are critical variables to assess low and high CLS severities,respectively,which emphasizes the importance of having submillimeter images to early detect CLS in field conditions.Genotype sensitivity to CLS can then be accurately retrieved based on time integrals of UGV-and UAV-derived scores.While UGV shows the best estimation performance,UAV can show accurate estimates of cultivar sensitivity if the data are properly acquired.Advantages and limitations of UGV,UAV,and visual scoring methods are finally discussed in the perspective of high-throughput phenotyping.
