Influence Of Recycled Coarse Aggregate Concrete Experimental Study Of Mechanical Performance Factors

In recent years, our country construction get vigorous development, coincided with a large garbage produced of buildings. One of the most is abandoned concrete. Not only in processing costs of waste concrete on high astonishing,but also cause a series of environmental problems. Recycled concrete technology is the use of these waste concrete, after processing produce can use again concrete thickness and coarse aggregate.Many and complicated factors affect its mechanical properties cause the current research results is uneven,it still not very complete applly in engineering. Combining domestic and foreign scholar's reaches, make use of the recycled coarse aggregate concrete proportioning design and influence factors of recycled coarse aggregate's mechanical properties。The main research work are as follows:(1)Use waste concrete, after artificially crushing, brokened by machine and cleaning, screening get recycled coarse aggregate. .Get different particle sizes of recycled coarse aggregate bibulous rate and crush index more natural gravel big and apparent density is natural gravel small.(2)Use concrete test has been widely applied to the orthogonal experiment ,consider water-cement ratio, recycled coarse aggregate replacement ratio, fly ash, establish three factors three levels orthogonal test. Range and variance analys is raise the reasonable proportion of Recycled coarse aggregate concrete. Recycled coarse aggregate concrete compressive strength of the influence from high to low in turn for water-cement ratio, recycled coarse aggregate replacement ratio, fly ash by qualitative analysis.(3)Recycled coarse aggregate concrete whole stress-strain curve experimental study. Conclusion is as recycled coarse aggregate replace rate increase, recycled coarse aggregate concrete peak strain increases, peak stress decreases, and brittleness increased.(4)Using recycled coarse aggregate concrete stress-strain curve, useing of damage model and through the least squares fitting to get model parameters.