With the help of the coordinate transformation technique, the symplectic dual solv- ing system is developed for multi-material wedges under antiplane deformation. A virtue of present method is that the compatibility c...With the help of the coordinate transformation technique, the symplectic dual solv- ing system is developed for multi-material wedges under antiplane deformation. A virtue of present method is that the compatibility conditions at interfaces of a multi-material wedge are expressed directly by the dual variables, therefore the governing equation of eigenvalue can be derived easily even with the increase of the material number. Then, stress singularity on multi-material wedges under antiplane deformation is investigated, and some solutions can be presented to show the validity of the method. Simultaneously, an interesting phenomenon is found and proved strictly that one of the singularities of a special five-material wedge is independent of the crack direction.展开更多
Exact solutions in form of elementary functions were derived for the stress and electric displacement intensity factors of a circular crack in a transversely isotropic piezoelectric space interacting with various stre...Exact solutions in form of elementary functions were derived for the stress and electric displacement intensity factors of a circular crack in a transversely isotropic piezoelectric space interacting with various stress and charge sources： force dipoles, electric dipoles, moments, force dilatation and rotation. The circular crack includes penny-shaped crack and external circular crack and the locations and orientations of these resultant sources with respect to the crack are arbitrary. Such stress and charge sources may model defects like vacancies, foreign particles, and dislocations. Numerical results are presented at last.展开更多
Purpose–The purpose of this paper is to provide an effective and simple technique to structural damage identification,particularly to identify a crack in a structure.Artificial neural networks approach is an alternat...Purpose–The purpose of this paper is to provide an effective and simple technique to structural damage identification,particularly to identify a crack in a structure.Artificial neural networks approach is an alternative to identify the extent and location of the damage over the classical methods.Radial basis function(RBF)networks are good at function mapping and generalization ability among the various neural network approaches.RBF neural networks are chosen for the present study of crack identification.Design/methodology/approach–Analyzing the vibration response of a structure is an effective way to monitor its health and even to detect the damage.A novel two-stage improved radial basis function(IRBF)neural network methodology with conventional RBF in the first stage and a reduced search space moving technique in the second stage is proposed to identify the crack in a cantilever beam structure in the frequency domain.Latin hypercube sampling(LHS)technique is used in both stages to sample the frequency modal patterns to train the proposed network.Study is also conducted with and without addition of 5%white noise to the input patterns to simulate the experimental errors.Findings–The results show a significant improvement in identifying the location and magnitude of a crack by the proposed IRBF method,in comparison with conventional RBF method and other classical methods.In case of crack location in a beam,the average identification error over 12 test cases was 0.69 per cent by IRBF network compared to 4.88 per cent by conventional RBF.Similar improvements are reported when compared to hybrid CPN BPN networks.It also requires much less computational effort as compared to other hybrid neural network approaches and classical methods.Originality/value–The proposed novel IRBF crack identification technique is unique in originality and not reported elsewhere.It can identify the crack location and crack depth with very good accuracy,less computational effort and ease of implementation.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 10772039)the National Basic Research Program of China (Program 973, No. 2010CB832704)
文摘With the help of the coordinate transformation technique, the symplectic dual solv- ing system is developed for multi-material wedges under antiplane deformation. A virtue of present method is that the compatibility conditions at interfaces of a multi-material wedge are expressed directly by the dual variables, therefore the governing equation of eigenvalue can be derived easily even with the increase of the material number. Then, stress singularity on multi-material wedges under antiplane deformation is investigated, and some solutions can be presented to show the validity of the method. Simultaneously, an interesting phenomenon is found and proved strictly that one of the singularities of a special five-material wedge is independent of the crack direction.
基金Project supported by the National Natural Science Foundation of China (No.10472102)Special Foundation of City University of HongKong (No.9610022)Outstanding Young Teacher Foundation of Hunan Province (No.521105236)the Yu-Ying Foundation of Hunan University (No.531103011110)
文摘Exact solutions in form of elementary functions were derived for the stress and electric displacement intensity factors of a circular crack in a transversely isotropic piezoelectric space interacting with various stress and charge sources： force dipoles, electric dipoles, moments, force dilatation and rotation. The circular crack includes penny-shaped crack and external circular crack and the locations and orientations of these resultant sources with respect to the crack are arbitrary. Such stress and charge sources may model defects like vacancies, foreign particles, and dislocations. Numerical results are presented at last.
文摘Purpose–The purpose of this paper is to provide an effective and simple technique to structural damage identification,particularly to identify a crack in a structure.Artificial neural networks approach is an alternative to identify the extent and location of the damage over the classical methods.Radial basis function(RBF)networks are good at function mapping and generalization ability among the various neural network approaches.RBF neural networks are chosen for the present study of crack identification.Design/methodology/approach–Analyzing the vibration response of a structure is an effective way to monitor its health and even to detect the damage.A novel two-stage improved radial basis function(IRBF)neural network methodology with conventional RBF in the first stage and a reduced search space moving technique in the second stage is proposed to identify the crack in a cantilever beam structure in the frequency domain.Latin hypercube sampling(LHS)technique is used in both stages to sample the frequency modal patterns to train the proposed network.Study is also conducted with and without addition of 5%white noise to the input patterns to simulate the experimental errors.Findings–The results show a significant improvement in identifying the location and magnitude of a crack by the proposed IRBF method,in comparison with conventional RBF method and other classical methods.In case of crack location in a beam,the average identification error over 12 test cases was 0.69 per cent by IRBF network compared to 4.88 per cent by conventional RBF.Similar improvements are reported when compared to hybrid CPN BPN networks.It also requires much less computational effort as compared to other hybrid neural network approaches and classical methods.Originality/value–The proposed novel IRBF crack identification technique is unique in originality and not reported elsewhere.It can identify the crack location and crack depth with very good accuracy,less computational effort and ease of implementation.
