Honeycomb sandwich structures are widely used in lightweight applications.Usually,these structures are subjected to extreme loading conditions,leading to potential failures due to delamination and debonding between th...Honeycomb sandwich structures are widely used in lightweight applications.Usually,these structures are subjected to extreme loading conditions,leading to potential failures due to delamination and debonding between the face sheet and the honeycomb core.Therefore,the present study is focused on the mechanical characterisation of honeycomb sandwich structures fabricated using advanced 3D printing technology.The continuous carbon fibres and ONYX-FR matrix materials have been used as raw materials for 3D printing of the specimens needed for various mechanical characterization testing;ONYX-FR is a commercial trade name for flame retardant short carbon fibre filled nylon filaments,used as a reinforcing material in Morkforged 3D printer.Edgewise and flatwise compression tests have been conducted for different configurations of honeycomb sandwich structures,fabricated by varying the face sheet thickness and core cell size,while keeping the core cell thickness and core height constant.Based on these tests,the proposed structure with face sheet thickness of 3.2 mm and a core cell size of 12.7 mm exhibited the highest energy absorption and prevented delamination and debonding failures.Therefore,3D printing technology can also be considered as an alternative method for sandwich structure fabrication.However,detailed parametric studies still need to be conducted to meet various other structural integrity criteria related to the lightweight applications.展开更多
The strength of lightweight concrete under triaxial compressive stress is studied experimentally with the concrete triaxial apparatus designed by the authors, and is compared with that of normal concrete under the sam...The strength of lightweight concrete under triaxial compressive stress is studied experimentally with the concrete triaxial apparatus designed by the authors, and is compared with that of normal concrete under the same stress state. Ninety-five 100 mm cubes under twenty stress ratios are tested. As compared with normal concrete, it is found that not only the multiaxial compressive strength of lightweight concrete is small, but also the ratio of the multiaxial compressive strength to the uniaxial compressive strength is small. The influence of the intermediate principal stress on the multiaxial strength of lightweight concrete is discussed. The strength criteria which are expressed in the principal stresses and the octahedral stresses respectively are proposed.展开更多
A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calcula...A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.展开更多
文摘Honeycomb sandwich structures are widely used in lightweight applications.Usually,these structures are subjected to extreme loading conditions,leading to potential failures due to delamination and debonding between the face sheet and the honeycomb core.Therefore,the present study is focused on the mechanical characterisation of honeycomb sandwich structures fabricated using advanced 3D printing technology.The continuous carbon fibres and ONYX-FR matrix materials have been used as raw materials for 3D printing of the specimens needed for various mechanical characterization testing;ONYX-FR is a commercial trade name for flame retardant short carbon fibre filled nylon filaments,used as a reinforcing material in Morkforged 3D printer.Edgewise and flatwise compression tests have been conducted for different configurations of honeycomb sandwich structures,fabricated by varying the face sheet thickness and core cell size,while keeping the core cell thickness and core height constant.Based on these tests,the proposed structure with face sheet thickness of 3.2 mm and a core cell size of 12.7 mm exhibited the highest energy absorption and prevented delamination and debonding failures.Therefore,3D printing technology can also be considered as an alternative method for sandwich structure fabrication.However,detailed parametric studies still need to be conducted to meet various other structural integrity criteria related to the lightweight applications.
文摘The strength of lightweight concrete under triaxial compressive stress is studied experimentally with the concrete triaxial apparatus designed by the authors, and is compared with that of normal concrete under the same stress state. Ninety-five 100 mm cubes under twenty stress ratios are tested. As compared with normal concrete, it is found that not only the multiaxial compressive strength of lightweight concrete is small, but also the ratio of the multiaxial compressive strength to the uniaxial compressive strength is small. The influence of the intermediate principal stress on the multiaxial strength of lightweight concrete is discussed. The strength criteria which are expressed in the principal stresses and the octahedral stresses respectively are proposed.
文摘A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.
