Research on Rapid Detection Technology and Application of Mortar Compressive Strength Based on Neural Network

Abstract

Since the rapid development of the construction industry, the production of construction waste has also multiplied, and the construction waste has caused tremendous pressure on the environment. Therefore, the main research of this subject is that the waste concrete is formed into a recycled material after a certain treatment--concrete powder. And the cement in the dry-mixed mortar is replaced by 0-30% concrete powder. The compressive strength of recycled concrete powder under different dosages was tested by experimental method. The compressive strength is then applied to the artificial neural network to establish a predictive model. Taking time as a variable, the feasibility and the best dosage of the 28-day compressive strength method for the 3d compressive strength during the test are discussed. In order to reduce the test cycle, improve work efficiency, and ultimately achieve the purpose of improving construction waste utilization.

A Review on Sustainable Fabrication of Futuristic Cementitious Binders Based on Application of Waste Concrete Powder, Steel Slags, and Coal Bottom Ash

“…In addition to the optimization of WCP proportion in mortar and concrete applications, the outcome of WCP has been researched using predictive artificial models. Lin et al (2020) used an artificial predictive model for WCP utilization in mortar. The OPC was replaced by WCP in the proportion of up to 30%.…”