The Experts below are selected from a list of 3663 Experts worldwide ranked by ideXlab platform
Mark J. Lewis - One of the best experts on this subject based on the ideXlab platform.
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aerothermodynamic optimization of reentry heat shield shapes for a crew exploration vehicle
Journal of Spacecraft and Rockets, 2007Co-Authors: Joshua E. Johnson, Ryan P. Starkey, Mark J. LewisAbstract:Gradient -based optimization of the aerodynamic perfor mance, static stability, and stagnation -point heat transfer has been performed to obtain optimal heat shield geometries for blunt -body planetary entry vehicles. Cross -sections considered include oblate and prolate ellipses, rounded -edge polygons, and round ed -edge concave polygons. Axial profiles consist of the Spherical -Segment, Spherically -blunted cone, and power law. Aerodynamic models are based on modified Newtonian impact theory with semi -empirical shock -standoff distance and heat transfer correlations. Methods have been verified against wind tunnel and flight data of the Apollo Command Module and the Fire II experiment; they are within 12% for aerodynamic coefficients and stagnation -point heat fluxes. The selected design point corresponds to the setting in which the Apollo 4 Command Module generated its maximum heat flux, at an altitude of 61 km and a velocity of 10.3 km/s. Results indicate that oblate parallelogram configurations provide optimal sets of aerothermodynamic characteristics.
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aerodynamic stability of reentry heat shield shapes for a crew exploration vehicle
Journal of Spacecraft and Rockets, 2006Co-Authors: Joshua E. Johnson, Ryan P. Starkey, Mark J. LewisAbstract:A parametric study of the static stability of blunt-body reentry heat shield geometries applicable to a crew exploration vehicle has been performed. Performance trends are identified by varying geometric parameters that define a range of cross sections and axial shapes. Cross sections considered include oblate and prolate ellipses, rounded-edge polygons, and rounded-edge concave polygons. Axial shapes consist of the Spherical Segment, Spherically blunted cone, and power law. Aerodynamic performance results that are based on a Newtonian surface pressure distribution have been verified against wind tunnel and flight data for the Apollo Command Module. Results are within 10% for aerodynamic coefficients, and trim angles of attack are computed within 1.2-deg. Stability and aerodynamic characteristics are observed to be more sensitive to changes in axial shape than changes in cross section. When uniform density is assumed, increased stability and performance are demonstrated at negative angles of attack for geometries with extremely blunt axial shapes and noneccentric cross sections. An unstable, oblate Spherical Segment at 20-deg angle of attack can produce a 56.1% increase in lift-to-drag ratio compared to a noneccentric stable Spherical Segment Shifting the center of gravity forward by 23.5% of its length can longitudinally stabilize this shield. The elliptical cross section, followed by the rounded-edge hexagon, and then by the rounded-edge concave hexagon rendered the most stable shapes.
Andreas Maier - One of the best experts on this subject based on the ideXlab platform.
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x ray transform invariant anatomical landmark detection for pelvic trauma surgery
Medical Image Computing and Computer-Assisted Intervention, 2018Co-Authors: Bastian Bier, Mathias Unberath, Jannico Zaech, Javad Fotouhi, Mehran Armand, Greg Osgood, Nassir Navab, Andreas MaierAbstract:X-ray image guidance enables percutaneous alternatives to complex procedures. Unfortunately, the indirect view onto the anatomy in addition to projective simplification substantially increase the task-load for the surgeon. Additional 3D information such as knowledge of anatomical landmarks can benefit surgical decision making in complicated scenarios. Automatic detection of these landmarks in transmission imaging is challenging since image-domain features characteristic to a certain landmark change substantially depending on the viewing direction. Consequently and to the best of our knowledge, the above problem has not yet been addressed. In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction. To this end, a sequential prediction framework based on convolutional layers is trained on synthetically generated data of the pelvic anatomy to predict 23 landmarks in single X-ray images. View independence is contingent on training conditions and, here, is achieved on a Spherical Segment covering 120\({^\circ }\times \)90\({^\circ }\) in LAO/RAO and CRAN/CAUD, respectively, centered around AP. On synthetic data, the proposed approach achieves a mean prediction error of \(5.6\pm 4.5\) mm. We demonstrate that the proposed network is immediately applicable to clinically acquired data of the pelvis. In particular, we show that our intra-operative landmark detection together with pre-operative CT enables X-ray pose estimation which, ultimately, benefits initialization of image-based 2D/3D registration.
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x ray transform invariant anatomical landmark detection for pelvic trauma surgery
arXiv: Computer Vision and Pattern Recognition, 2018Co-Authors: Bastian Bier, Mathias Unberath, Jannico Zaech, Javad Fotouhi, Mehran Armand, Greg Osgood, Nassir Navab, Andreas MaierAbstract:X-ray image guidance enables percutaneous alternatives to complex procedures. Unfortunately, the indirect view onto the anatomy in addition to projective simplification substantially increase the task-load for the surgeon. Additional 3D information such as knowledge of anatomical landmarks can benefit surgical decision making in complicated scenarios. Automatic detection of these landmarks in transmission imaging is challenging since image-domain features characteristic to a certain landmark change substantially depending on the viewing direction. Consequently and to the best of our knowledge, the above problem has not yet been addressed. In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction. To this end, a sequential prediction framework based on convolutional layers is trained on synthetically generated data of the pelvic anatomy to predict 23 landmarks in single X-ray images. View independence is contingent on training conditions and, here, is achieved on a Spherical Segment covering (120 x 90) degrees in LAO/RAO and CRAN/CAUD, respectively, centered around AP. On synthetic data, the proposed approach achieves a mean prediction error of 5.6 +- 4.5 mm. We demonstrate that the proposed network is immediately applicable to clinically acquired data of the pelvis. In particular, we show that our intra-operative landmark detection together with pre-operative CT enables X-ray pose estimation which, ultimately, benefits initialization of image-based 2D/3D registration.
Joshua E. Johnson - One of the best experts on this subject based on the ideXlab platform.
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aerothermodynamic optimization of reentry heat shield shapes for a crew exploration vehicle
Journal of Spacecraft and Rockets, 2007Co-Authors: Joshua E. Johnson, Ryan P. Starkey, Mark J. LewisAbstract:Gradient -based optimization of the aerodynamic perfor mance, static stability, and stagnation -point heat transfer has been performed to obtain optimal heat shield geometries for blunt -body planetary entry vehicles. Cross -sections considered include oblate and prolate ellipses, rounded -edge polygons, and round ed -edge concave polygons. Axial profiles consist of the Spherical -Segment, Spherically -blunted cone, and power law. Aerodynamic models are based on modified Newtonian impact theory with semi -empirical shock -standoff distance and heat transfer correlations. Methods have been verified against wind tunnel and flight data of the Apollo Command Module and the Fire II experiment; they are within 12% for aerodynamic coefficients and stagnation -point heat fluxes. The selected design point corresponds to the setting in which the Apollo 4 Command Module generated its maximum heat flux, at an altitude of 61 km and a velocity of 10.3 km/s. Results indicate that oblate parallelogram configurations provide optimal sets of aerothermodynamic characteristics.
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aerodynamic stability of reentry heat shield shapes for a crew exploration vehicle
Journal of Spacecraft and Rockets, 2006Co-Authors: Joshua E. Johnson, Ryan P. Starkey, Mark J. LewisAbstract:A parametric study of the static stability of blunt-body reentry heat shield geometries applicable to a crew exploration vehicle has been performed. Performance trends are identified by varying geometric parameters that define a range of cross sections and axial shapes. Cross sections considered include oblate and prolate ellipses, rounded-edge polygons, and rounded-edge concave polygons. Axial shapes consist of the Spherical Segment, Spherically blunted cone, and power law. Aerodynamic performance results that are based on a Newtonian surface pressure distribution have been verified against wind tunnel and flight data for the Apollo Command Module. Results are within 10% for aerodynamic coefficients, and trim angles of attack are computed within 1.2-deg. Stability and aerodynamic characteristics are observed to be more sensitive to changes in axial shape than changes in cross section. When uniform density is assumed, increased stability and performance are demonstrated at negative angles of attack for geometries with extremely blunt axial shapes and noneccentric cross sections. An unstable, oblate Spherical Segment at 20-deg angle of attack can produce a 56.1% increase in lift-to-drag ratio compared to a noneccentric stable Spherical Segment Shifting the center of gravity forward by 23.5% of its length can longitudinally stabilize this shield. The elliptical cross section, followed by the rounded-edge hexagon, and then by the rounded-edge concave hexagon rendered the most stable shapes.
Bastian Bier - One of the best experts on this subject based on the ideXlab platform.
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x ray transform invariant anatomical landmark detection for pelvic trauma surgery
Medical Image Computing and Computer-Assisted Intervention, 2018Co-Authors: Bastian Bier, Mathias Unberath, Jannico Zaech, Javad Fotouhi, Mehran Armand, Greg Osgood, Nassir Navab, Andreas MaierAbstract:X-ray image guidance enables percutaneous alternatives to complex procedures. Unfortunately, the indirect view onto the anatomy in addition to projective simplification substantially increase the task-load for the surgeon. Additional 3D information such as knowledge of anatomical landmarks can benefit surgical decision making in complicated scenarios. Automatic detection of these landmarks in transmission imaging is challenging since image-domain features characteristic to a certain landmark change substantially depending on the viewing direction. Consequently and to the best of our knowledge, the above problem has not yet been addressed. In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction. To this end, a sequential prediction framework based on convolutional layers is trained on synthetically generated data of the pelvic anatomy to predict 23 landmarks in single X-ray images. View independence is contingent on training conditions and, here, is achieved on a Spherical Segment covering 120\({^\circ }\times \)90\({^\circ }\) in LAO/RAO and CRAN/CAUD, respectively, centered around AP. On synthetic data, the proposed approach achieves a mean prediction error of \(5.6\pm 4.5\) mm. We demonstrate that the proposed network is immediately applicable to clinically acquired data of the pelvis. In particular, we show that our intra-operative landmark detection together with pre-operative CT enables X-ray pose estimation which, ultimately, benefits initialization of image-based 2D/3D registration.
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x ray transform invariant anatomical landmark detection for pelvic trauma surgery
arXiv: Computer Vision and Pattern Recognition, 2018Co-Authors: Bastian Bier, Mathias Unberath, Jannico Zaech, Javad Fotouhi, Mehran Armand, Greg Osgood, Nassir Navab, Andreas MaierAbstract:X-ray image guidance enables percutaneous alternatives to complex procedures. Unfortunately, the indirect view onto the anatomy in addition to projective simplification substantially increase the task-load for the surgeon. Additional 3D information such as knowledge of anatomical landmarks can benefit surgical decision making in complicated scenarios. Automatic detection of these landmarks in transmission imaging is challenging since image-domain features characteristic to a certain landmark change substantially depending on the viewing direction. Consequently and to the best of our knowledge, the above problem has not yet been addressed. In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction. To this end, a sequential prediction framework based on convolutional layers is trained on synthetically generated data of the pelvic anatomy to predict 23 landmarks in single X-ray images. View independence is contingent on training conditions and, here, is achieved on a Spherical Segment covering (120 x 90) degrees in LAO/RAO and CRAN/CAUD, respectively, centered around AP. On synthetic data, the proposed approach achieves a mean prediction error of 5.6 +- 4.5 mm. We demonstrate that the proposed network is immediately applicable to clinically acquired data of the pelvis. In particular, we show that our intra-operative landmark detection together with pre-operative CT enables X-ray pose estimation which, ultimately, benefits initialization of image-based 2D/3D registration.
Sun Jian-fei - One of the best experts on this subject based on the ideXlab platform.
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Rapid Cooling and Solidification Microstructure of Argon Atomized Ti-48Al Alloy Droplets
Journal of Materials Engineering, 2018Co-Authors: Bao Ying, Luo Lin, Yu Ze-min, Yang Dong-ye, Zhang Guo-qing, Sun Jian-feiAbstract:An analytical approach was developed to investigate nucleation and growth of Ti-48Al (atom fraction/%) alloy droplets during their flight in an argon atomization process. Evolution of microstructure of the solidified powders was investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and electron back-scatter diffraction (EBSD). Newton cooling model based on the initial number of nuclei, liquid/solid interface velocity, cooling rate and size of droplets was established. The results show that statistical nucleation events increase exponentially with the increase of powders size, and the growth of nuclei is transformed from a twinned Spherical Segment into a concentric liquid/solid interface geometry. Temperature of atomized droplets decreases rapidly with the cooling rate of 105-106K·s-1.Then temperature increases sharply to near the liquidus temperature during recalescence. When the recalescence is completed, the droplet solidifies at a relatively slower rate. Afterwards the cooling rate of the fully solid phase decreases to about 105K·s-1
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Nucleation on Thermal History and Microstructural Evolution of Atomized Ti-48Al Nano and Micro-Powders
'American Scientific Publishers', 2015Co-Authors: Yang Dong-ye, Peng Hua-xin, Fu, Yong Qing, Cao Fu-yang, Ning Zhi-liang, Guo Shu, Jia Yan-dong, Na Liu, Sun Jian-feiAbstract:An analytical approach was developed to investigate nucleation, recalescence and growth of Ti-48Al (at.%) alloy droplets during their flight in a gas atomization process. Evolution of microstructure of the solidified powders was quantitatively investigated using scanning electron microscopy, transmission electron microscopy and electron back-scatter diffraction. Relationships among the initial number of nuclei, liquid/solid interface velocity and cooling rate have been established. Results showed that statistical nucleation events increased exponentially with increasing droplet size, and the powder microstructures were transformed from a twinned Spherical Segment into a concentric liquid/solid interface geometry. Variations of initial temperature, cooling rate and solid fraction of the droplets as a function of cooling durations for the droplets with various sizes were investigated
