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Title: Performance Evaluation and Microstructure Study of Pervious Concrete Prepared from Various Solid Waste Admixtures

Author(s): Yi Li, Jiong Zhang, Jie Ding, Feng‑zhen Chen, Ming‑zhu Liu, Jia Liu and Zhao Hou

Publication: IJCSM

Volume: 19

Issue:

Appears on pages(s):

Keywords: Solid waste materials, Pervious concrete, Orthogonal test method, Microstructure

DOI: 10.1186/s40069-024-00738-0

Date: 3/31/2025

Abstract:
Solid waste materials (SWM) are commonly used in the preparation of building materials due to their structural characteristics and chemical composition. Pervious concrete (PC) is a green infrastructure material that offers advantages such as reducing surface runoff and purifying water quality, making it an important component of sponge cities. This study aims to investigate the physical properties and micro-structure of PC prepared from various SWM and determine the optimal mix proportion. In this study, three common SWM, including muck, steel slag (SS) and fly ash (FA), are used as raw materials. The chemical composition and physical properties of SWM are analyzed. A fivelevel and five-factor test scheme is developed using the orthogonal test method. This scheme considers the target porosity, water–cement ratio, muck content, SS content, and FA content as variables. The mechanical properties and permeability of PC, including compressive strength, porosity and permeability coefficient are evaluated. The internal structure of PC is observed using a scanning electron microscope (SEM). The results indicate that the optimal mix proportion for preparing PC is determined through efficiency coefficient method analysis: target porosity of 25%, water–cement ratio of 0.36, muck content of 10%, SS content of 10%, and FA content of 12.5%. The corresponding performance indicators of the PC sample are measured as follows: porosity of 24.67%, compressive strength of 15.78 MPa, and permeability coefficient of 2.23 mm/s. This study provides valuable insights for the rapid and flexible batching and performance optimization research of PC based on SWM.




  


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