Prediction of the moment capacity of reinforced concrete slabs in fire using artificial neural networks

2010 ◽  
Vol 41 (2) ◽  
pp. 270-276 ◽  
Author(s):  
Hakan Erdem
2018 ◽  
Vol 4 (4) ◽  
pp. 712 ◽  
Author(s):  
Abdelraouf Tawfik Kassem

Reinforced concrete slabs are elements in direct contact with superimposed loads, having high surface area and small thickness. Such a condition makes slabs highly vulnerable to fire conditions. Fire results in exaggerated deformations in reinforced concrete slabs, as a result of material deterioration and thermal induced stresses. The main objective of this paper is to deeply investigate how circular R.C. slabs, of different configurations, behave in fire condition. That objective has been achieved through finite element modelling. Thermal-structural finite element models have been prepared, using "Ansys". Finite element models used solid elements to model both thermal and structural slab behaviour. Structural loads had been applied, representing slab operational loads, then thermal loads were applied in accordance with ISO 843 fire curve. Outputs in the form of deflection profile and edge rotation have been extracted out of the models to present slab deformations. A parametric study has been conducted to figure out the significance of various parameters such as; slab depth, slenderness ratio, load ratio, and opening size; regarding slab deformations. It was found that deformational behaviour differs significantly for slabs of thickness equal or below 100 mm, than slabs of thickness equal or above 200 mm. On the other hand considerable changes in slabs behaviour take place after 30 minutes of fire exposure for slabs of thickness equals or below 100 mm, while such changes delay till 60 minutes for slabs of thickness equals or above 200 mm.


2021 ◽  
Author(s):  
Mikhail Borisov ◽  
Mikhail Krinitskiy

<p>Total cloud score is a characteristic of weather conditions. At the moment, there are algorithms that automatically calculate cloudiness based on a photograph of the sky These algorithms do not know how to find the solar disk, so their work is not absolutely accurate.</p><p>To create an algorithm that solves this data, the data used, obtained as a result of sea research voyages, is used, which is marked up for training the neural network.</p><p>As a result of the work, an algorithm was obtained based on neural networks, based on a photograph of the sky, in order to determine the size and position of the solar disk, other algorithms can be used to work with images of the visible hemisphere of the sky.</p>


2020 ◽  
Vol 221 ◽  
pp. 111058 ◽  
Author(s):  
Antonio Bilotta ◽  
Alberto Compagnone ◽  
Laura Esposito ◽  
Emidio Nigro

2018 ◽  
Vol 100 ◽  
pp. 171-185 ◽  
Author(s):  
Yong Wang ◽  
Guanglin Yuan ◽  
Zhaohui Huang ◽  
Junli Lyu ◽  
Qingtao Li ◽  
...  

2007 ◽  
Vol 353-358 ◽  
pp. 2676-2680
Author(s):  
Xiu Shan Sun ◽  
Ying Hua Liu ◽  
Zhang Zhi Cen ◽  
Dong Ping Fang

In this paper, full-scale reinforced concrete slabs are analyzed under thermal-mechanical loads in fire conditions. The rectangular one-way slabs including a simply supported slab and a three-span continuous slab are concerned in the analysis. Finite element simulation is carried out by using the ABAQUS program to evaluate the non-uniform temperature distributions in thickness of the slabs and to analyze the deformation and stress redistribution of the slabs at elevated temperatures. Sequentially coupled thermal and structural analyses are performed to simulate the responses of the slabs in fire conditions. Deformation and strength of the slabs under thermal and mechanical loads are discussed. The numerical results are compared with the experimental ones and good agreements are observed. The analysis results show that the main reinforcement ratio has significant effects on the deformation and strength of the slabs at elevated temperatures and the three-span continuous slab has better performance of fire-resistance than the simply supported slab.


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