Full metadata record
DC FieldValueLanguage
dc.contributor.authorYang, Judy P.en_US
dc.contributor.authorLam, Hon Fung Samuelen_US
dc.date.accessioned2020-10-05T02:01:53Z-
dc.date.available2020-10-05T02:01:53Z-
dc.date.issued2020-08-01en_US
dc.identifier.urihttp://dx.doi.org/10.3390/math8081297en_US
dc.identifier.urihttp://hdl.handle.net/11536/155311-
dc.description.abstractThe weighted reproducing kernel collocation method exhibits high accuracy and efficiency in solving inverse problems as compared with traditional mesh-based methods. Nevertheless, it is known that computing higher order reproducing kernel (RK) shape functions is generally an expensive process. Computational cost may dramatically increase, especially when dealing with strong-from equations where high-order derivative operators are required as compared to weak-form approaches for obtaining results with promising levels of accuracy. Under the framework of gradient approximation, the derivatives of reproducing kernel shape functions can be constructed synchronically, thereby alleviating the complexity in computation. In view of this, the present work first introduces the weighted high-order gradient reproducing kernel collocation method in the inverse analysis. The convergence of the method is examined through the weights imposed on the boundary conditions. Then, several configurations of multiply connected domains are provided to numerically investigate the stability and efficiency of the method. To reach the desired accuracy in detecting the outer boundary for two special cases, special treatments including allocation of points and use of ghost points are adopted as the solution strategy. From four benchmark examples, the efficacy of the method in detecting the unknown boundary is demonstrated.en_US
dc.language.isoen_USen_US
dc.subjectreproducing kernel approximationen_US
dc.subjectgradient approximationen_US
dc.subjecthigh-order gradient approximationen_US
dc.subjectstrong form collocationen_US
dc.subjectinverse problemen_US
dc.subjectmultiply connected domainen_US
dc.titleDetecting Inverse Boundaries by Weighted High-Order Gradient Collocation Methoden_US
dc.typeArticleen_US
dc.identifier.doi10.3390/math8081297en_US
dc.identifier.journalMATHEMATICSen_US
dc.citation.volume8en_US
dc.citation.issue8en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000564908900001en_US
dc.citation.woscount0en_US
Appears in Collections:Articles