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Multiscale modeling of ultra-high performance fiber reinforced concrete

Grant number: 23/14991-0
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): March 01, 2024
Effective date (End): February 28, 2027
Field of knowledge:Engineering - Civil Engineering - Structural Engineering
Principal Investigator:Luís Antônio Guimarães Bitencourt Júnior
Grantee:Amanda Tafuri Costa
Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:22/03179-0 - Multiscale modeling of plain and steel fiber reinforced concrete and its application to predicting the behavior of structural members, AP.PNGP.PI

Abstract

Ultra-high performance fiber reinforced concrete (UHPFRC) offers a promising material for constructing slender and durable structural elements, leading to increased dematerialization of structures, cost savings, and environmental impact mitigation. To further advance the current state of research, this study aims to adapt the existing multiscale models developed by Bitencourt Jr. and colleagues for both plain and steel fiber-reinforced concrete. The objective is to extend these models to predict the mechanical behavior of UHPFRC. A key focus will be on adapting the model to accommodate typical fiber distributions at high addition levels and accurately describe the intricate fiber-matrix interaction within the high-strength material. An essential component of this research involves studying fiber distributions through inductive tests and tomography to characterize the distribution of fibers within the UHPFRC comprehensively. In-depth laboratory tests, including fiber pullout tests and flexural tests on prisms, will be conducted to establish post-cracking parameters crucial for the design of structural elements using UHPFRC.The calibrated numerical model will be a robust computational tool for predicting the behavior of structural elements constructed from UHPFRC. It is expected, at the end of this research, to obtain a numerical tool capable of predicting the mechanical behavior of concrete considering the influence of its ingredients and translate this information to predict the behavior of structural elements.

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