首页|Data from Wuhan University Advance Knowledge in Machine Learning (Effects of Aut ogenous Shrinkage Microcracks On Uhpc: Insights From a Machine Learning Based Cr ack Quantification Approach)
Data from Wuhan University Advance Knowledge in Machine Learning (Effects of Aut ogenous Shrinkage Microcracks On Uhpc: Insights From a Machine Learning Based Cr ack Quantification Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting out of Wuhan, People's Repu blic of China, by NewsRx editors, research stated, "Owing to its high pozzolanic reactivity and contribution to packing density, silica fume is almost an indisp ensable part of UHPC, but it brings potentially serious problem of high autogeno us shrinkage. Nanocellulose (NC) is very effective in controlling shrinkage but would also result in different microstructure, whose impact is not clear." Funders for this research include National Natural Science Foundation of China ( NSFC), Hubei Province Key research and development plan. Our news journalists obtained a quote from the research from Wuhan University, " This study aims to explore the compensatory effect of NC on high shrinkage of UH PC. An image process method based on machine learning and stereological methods is proposed to quantify the autogenous shrinkage induced microcracks. Results sh ow that the addition of NC reduces the crack width and area by 57.45 similar to 70.55% and 63.2-83.8%, respectively. The MIP analysis reveals that the incorporation of NC introduces a larger proportion of pores. I n terms of mechanical properties, the higher content of pores brought by NC has a negative effect on compressive strength, however, the enhancement of flexural strength by NC can reach 66.02%. Excellent correlations between 0 a nd 50 nm porosity and compressive strength, crack density and flexural strength are observed with R-2 of 0.94 and 0.98 respectively."
WuhanPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningWuhan University
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