A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
To date, concrete structure modeling has involved the development of mathematical models of concrete structure behavior derived from human observation of, and reasoning with, experimental data. An alternative, discussed in this paper, is to use a computation and knowledge representation paradigm, called neural network, developed by researchers in connectionism (a subfield of artificial intelligence) to model concrete structure behavior. The main benefits in using a neural-network approach are that all behavior can be represented within a unified environment of a neural network and that the network is built directly from experimental data using self-organizing capabilities of the neural network, i.e., the network is presented with the experimental data and learns the relationships between stresses and strains. Such a modeling strategy has important implications for modeling the behavior of modern, complex concrete structures. In this paper, the behavior of prestressed concrete frames is modeled with a back-propagation neural network. The preliminary results of using networks to model concrete structure look very promising.
To date, concrete structure modeling has involved the development of mathematical models of concrete structure behavior derived from human observation of, and reasoning with, experimental data. An alternative, discussed in this paper, is to use a computation and knowledge representation paradigm, called neural network, developed by researchers in connectionism (a subfield of artificial intelligence) to model concrete structure behavior. The main benefits in using a neural-network approach are that all behavior can be represented within a unified environment of a neural network and that the network is built directly from experimental data using self-organizing capabilities of the neural network, i.e., the network is presented with the experimental data and learns the relationships between stresses and strains. Such a modeling strategy has important implications for modeling the behavior of modern, complex concrete structures. In this paper, the behavior of prestressed concrete frames is modeled with a back-propagation neural network. The preliminary results of using networks to model concrete structure look very promising.
Investigation of prestressed concrete frame behavior with neural networks
Untersuchung von Spannbetonrahmen mit Hilfe neuronaler Netze
Journal of Intelligent Material Systems and Structures ; 6 ; 566-573
1995
8 Seiten, 8 Bilder, 1 Tabelle, 19 Quellen
Article (Journal)
English
Investigation of Prestressed Concrete Frame Behavior with Neural Networks
| British Library Online Contents | 1995
Inelastic space frame -- Prestressed concrete
| Engineering Index Backfile | 1964
Precast Chemically Prestressed Concrete Frame
| NTIS | 1963
| DOAJ | 2024
Rigid-frame bridge of prestressed concrete
Engineering Index Backfile | 1951