Propellants containing micro-aluminium particles have been shown to produce faster burn rates than conventional gun propellants.However,they are also more abrasive than conventional propellants.Nano-material propellan...Propellants containing micro-aluminium particles have been shown to produce faster burn rates than conventional gun propellants.However,they are also more abrasive than conventional propellants.Nano-material propellants have been reported to give similar benefits to micron-material propellants but without the disadvantage of increased abrasion.Tests were conducted to compare the burn rates,ignitability and wear rates of a propellant loaded with 0% aluminium,15% micro-aluminium and 15%nano-aluminium.Closed vessel tests showed a burn rate increase of 39% in the range 30-250 MPa,and 70% at low pressure(50-100MPa)for the nano-aluminium propellant compared with the baseline propellant.The micro-aluminium propellant showed only a 10%increase in the burn rate compared with the standard propellant.The ignition delay for the nano-aluminium propellant was slightly shorter than that of the baseline propellant.Substantially increased wear rates were measured for the micro-aluminium propellant.The nano-aluminium propellant showed reduced wear rates compared with the micro-aluminium propellant but these were still substantially greater than those for the baseline propellant.展开更多
Several features of retinal vessels can be used to monitor the progression of diseases. Changes in vascular structures, for example, vessel caliber, branching angle, and tortuosity, are portents of many diseases such ...Several features of retinal vessels can be used to monitor the progression of diseases. Changes in vascular structures, for example, vessel caliber, branching angle, and tortuosity, are portents of many diseases such as diabetic retinopathy and arterial hypertension. This paper proposes an automatic retinal vessel segmentation method based on morphological closing and multi-scale line detection. First, an illumination correction is performed on the green band retinal image. Next, the morphological closing and subtraction processing are applied to obtain the crude retinal vessel image. Then, the multi-scale line detection is used to fine the vessel image. Finally, the binary vasculature is extracted by the Otsu algorithm, in this paper, for improving the drawbacks of multi-scale line detection, only the line detectors at 4 scales are used. The experimental results show that the accuracy is 0.939 for DRIVE (digital retinal images for vessel extraction) retinal database, which is much better than other methods.展开更多
基金funded by the Defence Science and Technology Laboratory(Dstl)part of the UK MoD,under the Hazard Modelling and Simulation task of the UK Energetics(UK-E)programme now consumed by the Weapons Science and Technology Centre(WSTC)
文摘Propellants containing micro-aluminium particles have been shown to produce faster burn rates than conventional gun propellants.However,they are also more abrasive than conventional propellants.Nano-material propellants have been reported to give similar benefits to micron-material propellants but without the disadvantage of increased abrasion.Tests were conducted to compare the burn rates,ignitability and wear rates of a propellant loaded with 0% aluminium,15% micro-aluminium and 15%nano-aluminium.Closed vessel tests showed a burn rate increase of 39% in the range 30-250 MPa,and 70% at low pressure(50-100MPa)for the nano-aluminium propellant compared with the baseline propellant.The micro-aluminium propellant showed only a 10%increase in the burn rate compared with the standard propellant.The ignition delay for the nano-aluminium propellant was slightly shorter than that of the baseline propellant.Substantially increased wear rates were measured for the micro-aluminium propellant.The nano-aluminium propellant showed reduced wear rates compared with the micro-aluminium propellant but these were still substantially greater than those for the baseline propellant.
基金supported by the NSC under Grant NSC 102-2221-E-005-082
文摘Several features of retinal vessels can be used to monitor the progression of diseases. Changes in vascular structures, for example, vessel caliber, branching angle, and tortuosity, are portents of many diseases such as diabetic retinopathy and arterial hypertension. This paper proposes an automatic retinal vessel segmentation method based on morphological closing and multi-scale line detection. First, an illumination correction is performed on the green band retinal image. Next, the morphological closing and subtraction processing are applied to obtain the crude retinal vessel image. Then, the multi-scale line detection is used to fine the vessel image. Finally, the binary vasculature is extracted by the Otsu algorithm, in this paper, for improving the drawbacks of multi-scale line detection, only the line detectors at 4 scales are used. The experimental results show that the accuracy is 0.939 for DRIVE (digital retinal images for vessel extraction) retinal database, which is much better than other methods.