Neural Networks Used in Design of Reinforced Layer for Existing Slabs for Airport Rigid Runway Structures

Tomme: LIX (LXIII) | Fascicle: 6 | 2013
Pages: 151-160
Abstract text:
In this paper a method of using neural networks for improving the computing method by increasing the accuracy in design of the reinforced concrete slabs from airport infrastructure is presented. The obtained results after the models developed with the method of finite element were used in order to create a neural networks simulating the function HR=f (He , css , K,adm), for dual type of landing gear, for each loading, reaction modulus considered, to design the reinforced layer for existing cement concrete slabs. The use of neural networks for the interpolations of functions to dimension the slabs proved an increase of result accuracy compared to the reading of nomograms, previously carried out, as well as the possibility of computing the variable concrete slab thickness, other than the one considered for the nomograms.
Key Words:
neural networks; airport reinforced slabs; nomograms; runway structural design.

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Author(s) Information

Gabriela Covatariu
Affiliation: „Gheorghe Asachi” Technical University of Iaşi, Faculty of Civil Engineering and Building Services

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