Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II: beams with stirrups

2004 ◽  
Vol 26 (7) ◽  
pp. 927-936 ◽  
Author(s):  
A. Cladera ◽  
A.R. Marí
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
High Strength Concrete ◽  
Concrete Beams ◽  
Design Procedure ◽  
High Strength ◽  
Strength Concrete ◽  
Shear Design ◽  
Artificial Neural

scholarly journals Shear Design of High Strength Concrete Beams in MRFs

2019 ◽  
Vol 5 ◽  
Author(s):  
Giuseppe Campione ◽  
Calogero Cucchiara ◽  
Alessia Monaco
Keyword(s):  
High Strength Concrete ◽  
Concrete Beams ◽  
High Strength ◽  
Strength Concrete ◽  
Shear Design

Artificial Neural Networks for the Spalling Classification & Failure Prediction Times of High Strength Concrete Columns

2014 ◽  
Vol 5 (3) ◽  
pp. 203-214 ◽  
Author(s):  
John McKinney ◽  
Faris Ali
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Test Data ◽  
Experimental Test ◽  
High Strength Concrete ◽  
Failure Prediction ◽  
High Strength ◽  
Concrete Columns ◽  
Strength Concrete ◽  
High Strength Concrete Columns

This paper presents the results from two supervised Artificial Neural Networks (ANN) developed for the spalling classification and failure prediction of high strength concrete columns (HSCC) subjected to fire. The experimental test data used for the ANN are based on the HSCC tests undertaken at the Fire Research Laboratories at the University of Ulster. 80% of the chosen experimental test data was used to train the network with the remaining 20% used for testing. In the spalling classification example the key ANN input parameters were; furnace temperature, restraint, loading level, force, spalling degree, failure time and spalling type. This was also the case for the failure prediction example except for spalling type. The networks were trained using the resilient propagation algorithm. A 6-10-3 and 5-10-1 ANN architecture gave the best results for the classification and failure prediction times respectively. The results demonstrate that HSCC can be assessed using ANN.

Shear design off high strength concrete beams — Canadian code perspective

1996 ◽  
Vol 23 (4) ◽  
pp. 809-819 ◽  
Author(s):  
Maria Anna Polak ◽  
Jaroslaw J. Dubas
Keyword(s):  
Compressive Strength ◽  
Shear Strength ◽  
High Strength Concrete ◽  
Concrete Beams ◽  
High Strength ◽  
Shear Behaviour ◽  
Shear Reinforcement ◽  
Concrete Compressive Strength ◽  
Strength Concrete ◽  
Shear Design

The paper presents the results of an investigation of the influence of concrete compressive strength on the shear strength of reinforced concrete beams, both nonprestressed and prestressed. A total of 132 existing tests on high strength concrete beams, with and without shear reinforcement, were analyzed and compared with the shear design provisions of the CSA Standard CAN3-A23.3-M94 and the previous version of the code, CAN3-A23.3-M84. The main parameter in the investigation was the concrete compressive strength. Owing to the complex nature of shear behaviour and the interdependence of the factors affecting shear strength, other parameters such as the shear span to depth ratio, the longitudinal reinforcement ratio, and the amount of shear reinforcement were varied, as well as the concrete strength. Key words: shear, beams, high strength concrete, code methods, shear reinforcement index, shear ratio, predictions, strength.

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