Efficient bolted joint design is an essential part of designing the minimum weight aerospace structures, since structural failures usually occur at connections and interface. A comprehensive numerical study of three-d...Efficient bolted joint design is an essential part of designing the minimum weight aerospace structures, since structural failures usually occur at connections and interface. A comprehensive numerical study of three-dimensional(3D) stress variations is prohibitively expensive for a large-scale structure where hundreds of bolts can be present. In this work, the hybrid composite-to-metal bolted connections used in the upper stage of European Ariane 5ME rocket are analyzed using the global-local finite element(FE) approach which involves an approximate analysis of the whole structure followed by a detailed analysis of a significantly smaller region of interest. We calculate the Tsai-Wu failure index and the margin of safety using the stresses obtained from ABAQUS. We find that the composite part of a hybrid bolted connection is prone to failure compared to the metal part. We determine the bolt preload based on the clamp-up load calculated using a maximum preload to make the composite part safe. We conclude that the unsuitable bolt preload may cause the failure of the composite part due to the high stress concentration in the vicinity of the bolt. The global-local analysis provides an efficient computational tool for enhancing 3D stress analysis in the highly loaded region.展开更多
In most framed structures anticipated deformations in accordance with current codes fall into acceptable limit states, whereas they go through substantial residual deformations in the aftermath of severe ground motion...In most framed structures anticipated deformations in accordance with current codes fall into acceptable limit states, whereas they go through substantial residual deformations in the aftermath of severe ground motions. These structures seem unsafe to occupants since static imminent instability in the immediate post-earthquake may be occurred. Moreover, rehabilitation costs of extensive residual deformations are not usually reasonable. Apparently, there is a lack of detailed knowledge related to reducing residual drift techniques when code-based seismic design is considered. In this paper, reduced beam section connections as a positive approach are taken action to mitigate the huge amount of residual drifts which are greatly amplified by P-Δ effects. To demonstrate the efficacy of RBS, a sixteen-story moment resisting frame is analyzed based on a suite of 8 single-component near field records which have been scaled according to the code provisions. The results are then processed to assess the effects of RBS detailing on drift profile, maximum drift, and residual drift. Besides, a special emphasis is given to estimate overall trend towards drift accumulation in each story in the presence of RBS assembly. A main conclusion is that using this connection predominantly alleviates the adverse effects of P-Δ on amplifying residual drifts.展开更多
Corrosion is a primary cause of the slippage of friction⁃type high⁃strength bolted(FHSB)T⁃stub connections.This paper attempts to quantify the residual capacity of FHSB T⁃stub connections with corroded nuts.Firstly,co...Corrosion is a primary cause of the slippage of friction⁃type high⁃strength bolted(FHSB)T⁃stub connections.This paper attempts to quantify the residual capacity of FHSB T⁃stub connections with corroded nuts.Firstly,corrosion simulation tests were conducted on 48 manually cut nuts to find out the relationship between the damage degree of nut section and the residual clamping force(RCF)of bolt.Then,static load tests were carried out on 24 FHSB T⁃stub connections with nuts of different degrees of damage to obtain the failure modes.By finite⁃element(FE)models,a comparative analysis was performed on the initial friction load(IFL)and ultimate strength(US)of each connection with corroded nuts.Finally,the parameters of 96 FE models for FHSB T⁃stub connections were analyzed and used to derive the calculation formulas for the degree of damage for each nut and the IFL and US of each connection.The results show that the RCF decay of a bolt is a quadratic function of the equivalent radius loss ratio and the shear failure after nut corrosion;the IFL of each connection had a clear linear correlation with the RCF of the corresponding bolts,and the correlation depends on the applied load and static friction on connecting plate interface induced by the clamping force;the static friction had little impact on the US of the connection;the proposed IFL and US formulas can effectively derive the residual anti⁃slip capacity of FHSB T⁃stub connections from the degree of damage of the corroded nut section.The research results provide a scientific basis for the replacement and maintenance of corroded bolts of FHSB T⁃stub connections.展开更多
A novel switch diagnosis method based on self-attention and residual deep convolutional neural networks(CNNs)is proposed.Because of the imbalanced dataset,the K-means synthetic minority oversampling technique(SMOTE)is...A novel switch diagnosis method based on self-attention and residual deep convolutional neural networks(CNNs)is proposed.Because of the imbalanced dataset,the K-means synthetic minority oversampling technique(SMOTE)is applied to balancing the dataset at first.Then,the deep CNN is utilized to extract local features from long power curves,and the residual connection is performed to handle the performance degeneration.In the end,the multi-heads channel self attention focuses on those important local features.The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods.With the residual connection and multi-heads channel self attention,the proposed method has achieved an impressive accuracy of 99.83%.The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.展开更多
脱机手写中文字符识别(handwritten Chinese character recognition,HCCR)在计算机视觉领域一直是一个巨大的挑战。相比传统方法,基于深度学习的网络通过训练大量数据在识别任务中取得了差异化的效果,但识别效果依旧处于发展过程中。基...脱机手写中文字符识别(handwritten Chinese character recognition,HCCR)在计算机视觉领域一直是一个巨大的挑战。相比传统方法,基于深度学习的网络通过训练大量数据在识别任务中取得了差异化的效果,但识别效果依旧处于发展过程中。基于此,结合DW卷积和残差连接设计了一种多分支残差模块,该模块通过DW卷积以较小的内存和参数量为代价来加深网络深度,增强网络的特征提取能力;再通过残差连接抑制网络梯度问题和退化问题;另外,提出了一种多分支权重算法,来改善多分支残差模块中各分支的权重分配问题;并将六个以多分支残差模块为主的结构线性连接,组成HCCR识别网络。该模型在CASIA-HWDB1.0、CASIA-HWDB1.1、ICDAR2013数据集上的识别准确率分别达到了97.77%、97.30%、97.64%,表现出高精度的识别效果。展开更多
多数基于卷积神经网络的语义分割算法伴随庞大的参数量和计算复杂度,限制了其在实时处理场景中的应用。为解决该问题,提出了一种基于全局-局部上下文网络(GLCNet)的轻量级语义分割算法。该算法主要由全局-局部上下文(GLC)模块和多分辨...多数基于卷积神经网络的语义分割算法伴随庞大的参数量和计算复杂度,限制了其在实时处理场景中的应用。为解决该问题,提出了一种基于全局-局部上下文网络(GLCNet)的轻量级语义分割算法。该算法主要由全局-局部上下文(GLC)模块和多分辨率融合(MRF)模块构成。全局-局部上下文模块学习图像的全局信息和局部上下文信息,使用残差连接增强特征之间的依赖关系。在此基础上,提出了多分辨率融合模块聚合不同阶段的特征,对低分辨率特征进行上采样,与高分辨率特征融合增强高层特征的空间信息。在Cityscapes和Camvid数据集上进行测试,平均交并比(mIoU)分别达到69.89%和68.86%,在单块NVIDIA Titan V GPU上,速度分别达到87帧/s和122帧/s。实验结果表明:所提算法在分割精度、效率及参数量之间实现了较好的平衡,参数量仅有0.68×10^(6)。展开更多
基金Project(282522)supported by the European Union's Research and Innovation Funding Programme
文摘Efficient bolted joint design is an essential part of designing the minimum weight aerospace structures, since structural failures usually occur at connections and interface. A comprehensive numerical study of three-dimensional(3D) stress variations is prohibitively expensive for a large-scale structure where hundreds of bolts can be present. In this work, the hybrid composite-to-metal bolted connections used in the upper stage of European Ariane 5ME rocket are analyzed using the global-local finite element(FE) approach which involves an approximate analysis of the whole structure followed by a detailed analysis of a significantly smaller region of interest. We calculate the Tsai-Wu failure index and the margin of safety using the stresses obtained from ABAQUS. We find that the composite part of a hybrid bolted connection is prone to failure compared to the metal part. We determine the bolt preload based on the clamp-up load calculated using a maximum preload to make the composite part safe. We conclude that the unsuitable bolt preload may cause the failure of the composite part due to the high stress concentration in the vicinity of the bolt. The global-local analysis provides an efficient computational tool for enhancing 3D stress analysis in the highly loaded region.
文摘In most framed structures anticipated deformations in accordance with current codes fall into acceptable limit states, whereas they go through substantial residual deformations in the aftermath of severe ground motions. These structures seem unsafe to occupants since static imminent instability in the immediate post-earthquake may be occurred. Moreover, rehabilitation costs of extensive residual deformations are not usually reasonable. Apparently, there is a lack of detailed knowledge related to reducing residual drift techniques when code-based seismic design is considered. In this paper, reduced beam section connections as a positive approach are taken action to mitigate the huge amount of residual drifts which are greatly amplified by P-Δ effects. To demonstrate the efficacy of RBS, a sixteen-story moment resisting frame is analyzed based on a suite of 8 single-component near field records which have been scaled according to the code provisions. The results are then processed to assess the effects of RBS detailing on drift profile, maximum drift, and residual drift. Besides, a special emphasis is given to estimate overall trend towards drift accumulation in each story in the presence of RBS assembly. A main conclusion is that using this connection predominantly alleviates the adverse effects of P-Δ on amplifying residual drifts.
文摘Corrosion is a primary cause of the slippage of friction⁃type high⁃strength bolted(FHSB)T⁃stub connections.This paper attempts to quantify the residual capacity of FHSB T⁃stub connections with corroded nuts.Firstly,corrosion simulation tests were conducted on 48 manually cut nuts to find out the relationship between the damage degree of nut section and the residual clamping force(RCF)of bolt.Then,static load tests were carried out on 24 FHSB T⁃stub connections with nuts of different degrees of damage to obtain the failure modes.By finite⁃element(FE)models,a comparative analysis was performed on the initial friction load(IFL)and ultimate strength(US)of each connection with corroded nuts.Finally,the parameters of 96 FE models for FHSB T⁃stub connections were analyzed and used to derive the calculation formulas for the degree of damage for each nut and the IFL and US of each connection.The results show that the RCF decay of a bolt is a quadratic function of the equivalent radius loss ratio and the shear failure after nut corrosion;the IFL of each connection had a clear linear correlation with the RCF of the corresponding bolts,and the correlation depends on the applied load and static friction on connecting plate interface induced by the clamping force;the static friction had little impact on the US of the connection;the proposed IFL and US formulas can effectively derive the residual anti⁃slip capacity of FHSB T⁃stub connections from the degree of damage of the corroded nut section.The research results provide a scientific basis for the replacement and maintenance of corroded bolts of FHSB T⁃stub connections.
基金the National Natural Science Foundation of China(Grant No.52072412)the Changsha Science&Technology Project(Grant No.KQ1707017)the innovation-driven project of the Central South University(Grant No.2019CX005).
文摘A novel switch diagnosis method based on self-attention and residual deep convolutional neural networks(CNNs)is proposed.Because of the imbalanced dataset,the K-means synthetic minority oversampling technique(SMOTE)is applied to balancing the dataset at first.Then,the deep CNN is utilized to extract local features from long power curves,and the residual connection is performed to handle the performance degeneration.In the end,the multi-heads channel self attention focuses on those important local features.The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods.With the residual connection and multi-heads channel self attention,the proposed method has achieved an impressive accuracy of 99.83%.The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.
文摘脱机手写中文字符识别(handwritten Chinese character recognition,HCCR)在计算机视觉领域一直是一个巨大的挑战。相比传统方法,基于深度学习的网络通过训练大量数据在识别任务中取得了差异化的效果,但识别效果依旧处于发展过程中。基于此,结合DW卷积和残差连接设计了一种多分支残差模块,该模块通过DW卷积以较小的内存和参数量为代价来加深网络深度,增强网络的特征提取能力;再通过残差连接抑制网络梯度问题和退化问题;另外,提出了一种多分支权重算法,来改善多分支残差模块中各分支的权重分配问题;并将六个以多分支残差模块为主的结构线性连接,组成HCCR识别网络。该模型在CASIA-HWDB1.0、CASIA-HWDB1.1、ICDAR2013数据集上的识别准确率分别达到了97.77%、97.30%、97.64%,表现出高精度的识别效果。
文摘多数基于卷积神经网络的语义分割算法伴随庞大的参数量和计算复杂度,限制了其在实时处理场景中的应用。为解决该问题,提出了一种基于全局-局部上下文网络(GLCNet)的轻量级语义分割算法。该算法主要由全局-局部上下文(GLC)模块和多分辨率融合(MRF)模块构成。全局-局部上下文模块学习图像的全局信息和局部上下文信息,使用残差连接增强特征之间的依赖关系。在此基础上,提出了多分辨率融合模块聚合不同阶段的特征,对低分辨率特征进行上采样,与高分辨率特征融合增强高层特征的空间信息。在Cityscapes和Camvid数据集上进行测试,平均交并比(mIoU)分别达到69.89%和68.86%,在单块NVIDIA Titan V GPU上,速度分别达到87帧/s和122帧/s。实验结果表明:所提算法在分割精度、效率及参数量之间实现了较好的平衡,参数量仅有0.68×10^(6)。
