Artificial neural network modeling of compressive strength of concrete with paper sludge as fine aggregate

• Main Authors: Sy, Bryan Kimball Y., Tiu, Charles Benson, Chua, Mark Jason Y.
• Format: text
• Language: English
• Published: Animo Repository 2006
• Subjects: Aggregates (Building materials); Waste product as road materials
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/6213
• Institution: De La Salle University

Paper sludge is one of the materials being studied now. It is being studied for an add mixture or a substitute for aggregate in a concrete mix. There were already some researches on the properties and the chemical components of paper sludge. Recent studies also tested the behavior of the structural properties of concrete with certain fractions of paper sludge being substituted for some aggregate. As expected, the strength of concrete decreases as the percentage of paper sludge substituted increases. But the behavior of the decrease is not yet known because intensive research is needed. In this research, we have tried to use the power of the computer by modeling an artificial neural network to help have a simulation or estimate of the compressive strength of different concrete mixes with different target strength and different percentage of substituted paper sludge. We have input the data we have attain from testing our concrete specimens to our ANN to determine the behavior of the concrete. This will help us develop a mix design for concrete with paper sludge substitute, so that we can maximize the use of this waste material for making concrete for future use.