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Implementation of Highly Flowable Strain Hardening Fiber Reinforced Concrete (HF-SHFRC) to New RC Bridge Columns for Sustainability Development

Conference paper
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Part of the Sustainable Civil Infrastructures book series (SUCI)

Abstract

A remarkable development of high strength concrete and reinforcement has been achieved nowadays. The purpose of New RC project is aimed to reduce member section size by using high strength concrete (\( {\text{f}}_{\text{c}}^{\prime} > 70\;{\text{MPa}} \)) and high strength rebars (\( {\text{f}}_{\text{y}} > 685\;{\text{MPa}} \)). Material consumption can be further reduced owing to the upgrade of strength. However, the nature of brittleness of high strength concrete may also cause early cover spalling and other ductility issues. Addition of steel fibers is an alternative as transverse reinforcement in New RC infrastructure systems. Highly flowable strain hardening fiber reinforced concrete (HF-SHFRC) has excellent workability in the fresh state and exhibits the strain-hardening and multiple cracking characteristics of high performance fiber reinforced cementitious composites (HPFRCC) in their hardened state. This study aims to investigate the cyclic behavior of New RC bridge columns made of HF-SHFRC. Five large scale bridge columns are subjected cyclic lateral loading to verify their responses and deformation capacity. The test results show that by adding 1.5% of high strength hooked steel fibers, great deformation capacity is developed either stirrups spacing is even increased to two times of that of control specimen or elimination of all tires in New RC bridge columns. Implementation of HF-SHFRC to New RC infrastructure offers opportunities to significantly simplify the design and construction of members for sustainable urbanization, while ensuring adequate ductility and damage tolerance.

Keywords

RC New Fibre Reinforced Concrete (FRC) Bridge Columns High Performance Fiber Reinforced Cementitious Composites (HPFRCC) High Strength Rebars 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Civil EngineeringNational Taiwan UniversityTaipeiTaiwan

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