Title:
Using Machine Learning to Predict the Performance of Coal Ash in Concrete with the Bulk Oxide Content
Author(s):
Tyler Ley
Publication:
Web Session
Volume:
ws_F23_Integration_TylerLey.pdf
Issue:
Appears on pages(s):
Keywords:
DOI:
Date:
10/29/2023
Abstract:
Coal ash is a valuable SCM for a concrete mixture. This presentation uses the bulk oxide content to predict the performance level of coal ash in concrete. The results from two different machine learning algorithms will be used. The first uses the bulk oxide content in a web interface and the second algorithm develops a simple set of look up tables that can be used in guide or recommendation documents. These tools predict the compressive strength, resistivity, diffusion coefficient, and the amount of heat released during hydration. These promise to be simple and powerful tools to help the concrete industry better use coal ash and reclaimed coal ash in the future.