FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3092020108> ?p ?o ?g. }

• W3092020108 endingPage "104225" @default.
• W3092020108 startingPage "104225" @default.
• W3092020108 abstract "In this paper, we present a deep autoencoder based energy method (DAEM) for the bending, vibration and buckling analysis of Kirchhoff plates. The DAEM exploits the higher order continuity of the DAEM and integrates a deep autoencoder and the minimum total potential principle in one framework yielding an unsupervised feature learning method. The DAEM is a specific type of feedforward deep neural network (DNN) and can also serve as function approximator. With robust feature extraction capacity, the DAEM can more efficiently identify patterns behind the whole energy system, such as the field variables, natural frequency and critical buckling load factor studied in this paper. The objective function is to minimize the total potential energy. The DAEM performs unsupervised learning based on generated collocation points inside the physical domain so that the total potential energy is minimized at all points. For the vibration and buckling analysis, the loss function is constructed based on Rayleigh’s principle and the fundamental frequency and the critical buckling load is extracted. A scaled hyperbolic tangent activation function for the underlying mechanical model is presented which meets the continuity requirement and alleviates the gradient vanishing/explosive problems under bending. The DAEM is implemented using Pytorch and the LBFGS optimizer. To further improve the computational efficiency and enhance the generality of this machine learning method, we employ transfer learning. A comprehensive study of the DAEM configuration is performed for several numerical examples with various geometries, load conditions, and boundary conditions. • Deep autoencoder based energy method (DAEM) with tailored activation function. • Stable and accurate results without gradient vanishing/exploding problems. • Unsupervised DAEM applied to Kirchhoff plates." @default.
• W3092020108 created "2020-10-15" @default.
• W3092020108 creator A5019724877 @default.
• W3092020108 creator A5052594698 @default.
• W3092020108 creator A5065190539 @default.
• W3092020108 creator A5075916440 @default.
• W3092020108 creator A5090972958 @default.
• W3092020108 date "2021-05-01" @default.
• W3092020108 modified "2023-10-16" @default.
• W3092020108 title "Deep autoencoder based energy method for the bending, vibration, and buckling analysis of Kirchhoff plates with transfer learning" @default.
• W3092020108 cites W1967649517 @default.
• W3092020108 cites W1971735090 @default.
• W3092020108 cites W1988115241 @default.
• W3092020108 cites W1994082107 @default.
• W3092020108 cites W1995341919 @default.
• W3092020108 cites W2013664015 @default.
• W3092020108 cites W2051434435 @default.
• W3092020108 cites W2068469823 @default.
• W3092020108 cites W2082706703 @default.
• W3092020108 cites W2123099218 @default.
• W3092020108 cites W2125645174 @default.
• W3092020108 cites W2136922672 @default.
• W3092020108 cites W2137983211 @default.
• W3092020108 cites W2138971860 @default.
• W3092020108 cites W2141671098 @default.
• W3092020108 cites W2148666448 @default.
• W3092020108 cites W2291542162 @default.
• W3092020108 cites W2513671774 @default.
• W3092020108 cites W2586702902 @default.
• W3092020108 cites W2594265094 @default.
• W3092020108 cites W2601590138 @default.
• W3092020108 cites W2624385633 @default.
• W3092020108 cites W2625995436 @default.
• W3092020108 cites W2749028154 @default.
• W3092020108 cites W2754833785 @default.
• W3092020108 cites W2760972773 @default.
• W3092020108 cites W2777391033 @default.
• W3092020108 cites W2788633781 @default.
• W3092020108 cites W2792716760 @default.
• W3092020108 cites W2795574921 @default.
• W3092020108 cites W2803629276 @default.
• W3092020108 cites W2809340116 @default.
• W3092020108 cites W2884367402 @default.
• W3092020108 cites W2890968382 @default.
• W3092020108 cites W2896800984 @default.
• W3092020108 cites W2899283552 @default.
• W3092020108 cites W2912581782 @default.
• W3092020108 cites W2919115771 @default.
• W3092020108 cites W2935339072 @default.
• W3092020108 cites W2942896733 @default.
• W3092020108 cites W2946298178 @default.
• W3092020108 cites W2948551291 @default.
• W3092020108 cites W2951934944 @default.
• W3092020108 cites W2969381807 @default.
• W3092020108 cites W2998366519 @default.
• W3092020108 cites W3101260193 @default.
• W3092020108 doi "https://doi.org/10.1016/j.euromechsol.2021.104225" @default.
• W3092020108 hasPublicationYear "2021" @default.
• W3092020108 type Work @default.
• W3092020108 sameAs 3092020108 @default.
• W3092020108 citedByCount "156" @default.
• W3092020108 countsByYear W30920201082021 @default.
• W3092020108 countsByYear W30920201082022 @default.
• W3092020108 countsByYear W30920201082023 @default.
• W3092020108 crossrefType "journal-article" @default.
• W3092020108 hasAuthorship W3092020108A5019724877 @default.
• W3092020108 hasAuthorship W3092020108A5052594698 @default.
• W3092020108 hasAuthorship W3092020108A5065190539 @default.
• W3092020108 hasAuthorship W3092020108A5075916440 @default.
• W3092020108 hasAuthorship W3092020108A5090972958 @default.
• W3092020108 hasBestOaLocation W30920201082 @default.
• W3092020108 hasConcept C101738243 @default.
• W3092020108 hasConcept C119599485 @default.
• W3092020108 hasConcept C121332964 @default.
• W3092020108 hasConcept C127413603 @default.
• W3092020108 hasConcept C134306372 @default.
• W3092020108 hasConcept C154945302 @default.
• W3092020108 hasConcept C182310444 @default.
• W3092020108 hasConcept C198394728 @default.
• W3092020108 hasConcept C24890656 @default.
• W3092020108 hasConcept C33923547 @default.
• W3092020108 hasConcept C41008148 @default.
• W3092020108 hasConcept C50644808 @default.
• W3092020108 hasConcept C66938386 @default.
• W3092020108 hasConcept C81299745 @default.
• W3092020108 hasConcept C85476182 @default.
• W3092020108 hasConcept C87210426 @default.
• W3092020108 hasConceptScore W3092020108C101738243 @default.
• W3092020108 hasConceptScore W3092020108C119599485 @default.
• W3092020108 hasConceptScore W3092020108C121332964 @default.
• W3092020108 hasConceptScore W3092020108C127413603 @default.
• W3092020108 hasConceptScore W3092020108C134306372 @default.
• W3092020108 hasConceptScore W3092020108C154945302 @default.
• W3092020108 hasConceptScore W3092020108C182310444 @default.
• W3092020108 hasConceptScore W3092020108C198394728 @default.
• W3092020108 hasConceptScore W3092020108C24890656 @default.
• W3092020108 hasConceptScore W3092020108C33923547 @default.
• W3092020108 hasConceptScore W3092020108C41008148 @default.

• next