<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Ultra-high-performance concrete is a cement-based material with ultra-high strength, outstanding toughness, and excellent durability, which enables structures to achieve larger spans and lighter dimensions. In this paper, an improved GA-BP neural network model is constructed based on BP neural network, which is optimized and improved by the GA algorithm. Then, the experimental data were input into the improved GA-BP neural network model by designing experiments with different types and volume doping of blended fiber UHPC, and the ductility of blended fiber UHPC was analyzed in terms of compressive strength and tensile strength. In terms of compressive strength, the compressive strengths of each group of PE fibers with 0.5%, 1.0%, and 1.5% volume doping were from PD/S&lt;PD/H&lt;PA/S&lt;PA/H. In terms of tensile strength, the 1.0% volume doping of short straight type S and 1.5% volume doping of end hook type H had the best effect, and the tensile strength reached 12.44 MPa. GA-BP neural network can effectively analyze the factors influencing the ductility of blended fiber ultra-high performance concrete.</p>
</abstract>

Ultra-high-performance concrete is a cement-based material with ultra-high strength, outstanding toughness, and excellent durability, which enables structures to achieve larger spans and lighter dimensions. In this paper, an improved GA-BP neural network model is constructed based on BP neural network, which is optimized and improved by the GA algorithm. Then, the experimental data were input into the improved GA-BP neural network model by designing experiments with different types and volume doping of blended fiber UHPC, and the ductility of blended fiber UHPC was analyzed in terms of compressive strength and tensile strength. In terms of compressive strength, the compressive strengths of each group of PE fibers with 0.5%, 1.0%, and 1.5% volume doping were from PD/S<PD/H<PA/S<PA/H. In terms of tensile strength, the 1.0% volume doping of short straight type S and 1.5% volume doping of end hook type H had the best effect, and the tensile strength reached 12.44 MPa. GA-BP neural network can effectively analyze the factors influencing the ductility of blended fiber ultra-high performance concrete.

Analysis of ductility of hybrid fiber ultra-high performance concrete based on improved GA-BP neural network

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Ultra-high-performance concrete is a cement-based material with ultra-high strength, outstanding toughness, and excellent durability, which enables structures...

Analysis of ductility of hybrid fiber ultra-high performance concrete based on improved GA-BP neural network

Data publikacji: 26 lip 2023

Zakres stron: -

Otrzymano: 15 sie 2022

Przyjęty: 01 lut 2023

DOI: https://doi.org/10.2478/amns.2023.2.00089

Słowa kluczowe
Hybrid fiber, UHPC, BP neural network, GA algorithm, Ductility

© 2023 Qin Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of ductility of hybrid fiber ultra-high performance concrete based on improved GA-BP neural network

Data publikacji: 26 lip 2023

Zakres stron: -

Otrzymano: 15 sie 2022

Przyjęty: 01 lut 2023

DOI: https://doi.org/10.2478/amns.2023.2.00089

Słowa kluczoweHybrid fiber, UHPC, BP neural network, GA algorithm, Ductility

© 2023 Qin Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Hybrid fiber, UHPC, BP neural network, GA algorithm, Ductility