Application of Machine Learning Techniques to Predict Rheology and Compressive Strength of Steel Fibre Reinforced Concrete
Author:
Affiliation:
1. Swinburne University of Technology Hawthorn,Centre for Smart Infrastructure and Digital Construction,Department of Civil & Construction Engineering,Melbourne,VIC,Australia,3122
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10520249/10520342/10520599.pdf?arnumber=10520599
Reference55 articles.
1. Mechanical and durability properties of steel fiber‐reinforced concrete containing coarse recycled concrete aggregate
2. Effects of Coarse Aggregate Maximum Size on Synthetic/Steel Fiber Reinforced Concrete Performance with Different Fiber Parameters
3. Constitutive Relation of Fiber Reinforced Concrete under Uniaxial Compression
4. Behavior of recycled steel fiber reinforced concrete under uniaxial cyclic compression and biaxial tests
5. Experimental study on compressive properties of SFRC under high strain rate with different fiber content and aspect ratio
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