Publications by authors named "Teemu Ojala"

The correct workability of concrete is an essential parameter for its placement and compaction. However, an absence of automatic and transparent measurement methods to estimate the workability of concrete hinders the adaptation from laborious traditional methods such as the slump test. In this paper, we developed a machine-learning framework for estimating the slump class of concrete in the mixer using a stereovision camera.

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This paper presents the characteristics of air void systems in hardened concrete with the method of digital image analysis (DIA) coupled with Schwartz-Saltykov (SS) conversion. The results indicate that the DIA method coupled with SS conversion estimates the air content with more accuracy than it would without SS conversion; the correlation between air content obtained from the DIA method, and that from the thin section (TS) method is as good as the correlation observed between the pressure saturation (PS) method and the TS method. It was also found that the DIA method shows a better correlation with the TS method when the spacing factor without SS conversion is considered, while both methods show poor correlations when the corresponding specific surface is considered.

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