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RC beams 1

ferrocement 1

high-performance ferrocement laminate (HPFL) 1

inorganic material 1

moment capacity 1

reinforcement 1

self-evolving neural network 1

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Estimating moment capacity of ferrocement members using self-evolving network

Abdussamad ISMAIL

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4, Pages 926-936 doi: 10.1007/s11709-019-0527-5

Abstract: empirical model based on self-evolving neural network is proposed for predicting the flexural behavior of ferrocementThe model is meant to serve as a simple but reliable tool for estimating the moment capacity of ferrocementThe data consists of information regarding flexural tests on ferrocement specimens which include momentexperimental data indicated that the models are capable of accurately estimating the moment capacity of ferrocement

Keywords： ferrocement moment capacity self-evolving neural network

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diagonal section and cross-section bending capacity for strengthening RC structure using high-performance ferrocement

Shouping SHANG , Fangyuan ZHOU , Wei LIU ,

Frontiers of Structural and Civil Engineering 2009, Volume 3, Issue 3, Pages 330-338 doi: 10.1007/s11709-009-0046-x

Abstract: High-performance ferrocement laminate (HPFL) is an effective method of strengthening concrete structureHigh-performance ferrocement laminate is a new type of inorganic material with the advantages such as

Keywords： RC beams high-performance ferrocement laminate (HPFL) inorganic material reinforcement