A Statistical Approach to Predicting Fresh State Properties of Sustainable Concrete

9 pages•Published: June 9, 2021

Ruoyu Jin, Qian Chen and Alfred Soboyejo

Abstract

Using environmentally friendly concrete materials can help improve the sustainability of the concrete industry. However, the effects of such materials on concrete properties must be fully understood before sustainable concrete can be widely applied. Previous research showed limited applications of statistical methods in analyzing the effects of sustainable concrete materials on fresh concrete properties. This study applies multivariate regression analysis to modeling properties of fresh concrete (i.e., slump, air content, and density) made with multiple sustainable raw materials based on variables in mixture design. Different regression models were tested to explore the best-fit model(s) that can capture and predict how these variables affect fresh concrete properties. The regression analysis showed satisfactory results in predicting air content and density, but not in predicting slump. The regression analysis, as a statistical tool, can provide deep insights into how the selected independent variables affect fresh concrete properties and the degree of the effects.

Keyphrases: fresh concrete properties, mixture design, regression analysis, statistical methods, sustainable concrete

In: Tom Leathem, Anthony Perrenoud and Wesley Collins (editors). ASC 2021. 57th Annual Associated Schools of Construction International Conference, vol 2, pages 28-36.

Links:	https://easychair.org/publications/paper/8HtR
	https://doi.org/10.29007/1h88

BibTeX entry

@inproceedings{ASC2021:Statistical_Approach_Predicting_Fresh,
  author    = {Ruoyu Jin and Qian Chen and Alfred Soboyejo},
  title     = {A Statistical Approach to Predicting Fresh State Properties of Sustainable Concrete},
  booktitle = {ASC 2021. 57th Annual Associated Schools of Construction International Conference},
  editor    = {Tom Leathem and Anthony Perrenoud and Wesley Collins},
  series    = {EPiC Series in Built Environment},
  volume    = {2},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2632-881X},
  url       = {/publications/paper/8HtR},
  doi       = {10.29007/1h88},
  pages     = {28-36},
  year      = {2021}}

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