A modified method for the design of pervious concrete mix-Reference-Cited by-同舟云学术

A modified method for the design of pervious concrete mix

Published:2014-12 Issue: Volume:73 Page:271-282
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Nguyen Dang Hanh,Sebaibi Nassim,Boutouil Mohamed,Leleyter Lydia,Baraud Fabienne

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference37 articles.

1. Experimental study on properties of pervious concrete pavement materials;Yang;Cem Concr Res,2003

2. ACI 522R-10. Report on pervious concrete. Farmington Hills, Michigan: American Concrete Institute; 2010. 38p.

3. Tennis PD, Leming ML, Akers DJ. Pervious concrete pavements. Technical report, EB302.02. Portland Cement Association, Skokie, Illinois, and National Ready Mixed Concrete Association, Silver Spring, Maryland; 2004. 32p.

4. Valorization of seashell by-products in pervious concrete pavers;Nguyen;Constr Build Mater,2013

5. Schaefer VR, Wang K, Suleiman MT, Kevern J. Mix design development for pervious concrete in cold climates. Technical report, National Concrete Pavement Technology Center, Iowa State University; 2006. 85p.

Cited by 176 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Permeability Measurement of Pervious Concrete by Constant and Falling Head Methods: Influence of Aggregate Gradation and Cement-to-Aggregate Ratio;Practice Periodical on Structural Design and Construction;2024-11

2. Porous concrete modification with silica fume and ground granulated blast furnace slag: Hydraulic and mechanical properties before and after freeze-thaw exposure;Construction and Building Materials;2024-10

3. Evolution of Piled Raft Foundation at Static Loading Condition and Application of Numerical Modelling: A State-of-the-Art Review;Archives of Computational Methods in Engineering;2024-09-04

4. Optimizing pervious concrete with machine learning: Predicting permeability and compressive strength using artificial neural networks;Construction and Building Materials;2024-09

5. Optimizing Porous Concrete Using Granite Stone-Crushing Waste: Composition, Strength, and Density Analysis;Applied Sciences;2024-08-08