Application of Artificial Neural Network in mix design of high-volume fly-ash concrete

Author(s):  
Li Xiaolei ◽  
Cao Xinxin ◽  
Wang Liying ◽  
Zai Eran ◽  
Tao Feng ◽  
...  
2021 ◽  
Author(s):  
Aniruddha Baral ◽  
◽  
Jeffrey Roesler ◽  
M. Ley ◽  
Shinhyu Kang ◽  
...  

High-volume fly ash concrete (HVFAC) has improved durability and sustainability properties at a lower cost than conventional concrete, but its early-age properties like strength gain, setting time, and air entrainment can present challenges for application to concrete pavements. This research report helps with the implementation of HVFAC for pavement applications by providing guidelines for HVFAC mix design, testing protocols, and new tools for better quality control of HVFAC properties. Calorimeter tests were performed to evaluate the effects of fly ash sources, cement–fly ash interactions, chemical admixtures, and limestone replacement on the setting times and hydration reaction of HVFAC. To better target the initial air-entraining agent dosage for HVFAC, a calibration curve between air-entraining dosage for achieving 6% air content and fly ash foam index test has been developed. Further, a digital foam index test was developed to make this test more consistent across different labs and operators. For a more rapid prediction of hardened HVFAC properties, such as compressive strength, resistivity, and diffusion coefficient, an oxide-based particle model was developed. An HVFAC field test section was also constructed to demonstrate the implementation of a noncontact ultrasonic device for determining the final set time and ideal time to initiate saw cutting. Additionally, a maturity method was successfully implemented that estimates the in-place compressive strength of HVFAC through wireless thermal sensors. An HVFAC mix design procedure using the tools developed in this project such as the calorimeter test, foam index test, and particle-based model was proposed to assist engineers in implementing HVFAC pavements.


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