Investigating and modeling of fine fly ash high performance concrete

Abstract

The concrete which is highly consumed by infrastructure newlinedevelopment is a common pollutant. The cement which is the binder in concrete newlineis the major provider of pollution hence there is lot of studies on alternative newlinepozzolanic material which can reduce the CO2 emission. The important pozzolan newlinematerial used till date is fly ash and the usages are limited to 15% to 20% by newlinemass of cement. The additional formation of CSH and CAH in the matrix due to newlinethe replacement of fly ash increases the micro structural behavior and increases newlinethe durability properties. But there is few negative effects on the usage of fly newlineash, which is the delayed setting and strength attainment but these can be newlineconnected to reduced drying shrinkage and lesser heat of hydration. To newlineovercome these faults finer silica fumes were used in fly ash admixed newlinecementitious system as the finer materials has the tendency to dissolve and react newlinewith the element to form pozzolanic reaction. The benefits of using finer particle newlinefly ash is, it increases the amorphous SiO2 which results in reduction of heat newlineemission and reduces the possibility of formation of harmful ions. newlineAn experimental investigation is carried on fresh, hardened and newlinedurability properties of fine grinded fly ash replaced concrete and based on the newlineexperimental values optimization of the mix ids is also arrived using newlinecomputational analysis and statistical tools. The experiments were based on the newlinefactor of evaluation of binding property, fresh concrete, mechanical behaviour, newlinedurability, morphology and chemical analysis of fine grinded fly ash concrete. newlineThis investigation in this research work was to set the adaptability and feasibility newlineof fine grinded fly ash as a pozzolanic material to make it more viable for its newlineusage in structural applications which were studied also and optimized through newlineArtificial Intelligence technique was also applied to predict compressive strength newlinesame concrete. Experiments to match the research objective were categorized newlineand carried through seven categories and follows newline newline