• Speech Sciences
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• v.7 no.2
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• pp.113-126
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• 2000

A comparative phonetic analysis of Yodel singing and Belcanto singing by the electroglottographic(EGG) measurement was done in three singers. One professional tenor singer(SDI) who is also well trained in Yodel singing, another yodler(KWS) who is not so trained in Belcanto singing, and the other training tenor singer(CSK) who is not well trained both yodel and Belcanto singing. Closed quotient(CQ), speed quotient(SQ) and fundamental frequency (F0) at the initial modal part(I) , middle falsetto part(M), and final modal part(F) of the same phrase were measured by EGG machine and program(Kay model 4338). In the middle part, not only CQ but also SQ of the Yodel singing were much smaller than that of Belcanto singing in all three singers. However, accuracy of parameters in Belcanto singing of the yodler(KWS) and both Yodel singing and Belcanto singing of the training singer(CSK) were inferior to that of trained tenor singer(SDI). Possible advantages of utilizing Yodel singing training under the guidance of feedback control by the EGG for hyperfunctional voice disorders such as vocal nodules were discussed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.111-119
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• 2023

Recently, a variety of new cement-based materials have been developed, and attempts to predict the properties of these new materials are increasing. In this study, we aimed to predict the rheological properties of binary blended pastes. The cementitious materials used in the study included Portland cement (PC), fly ash (FA), blast furnace slag (BS), and silica fume (SF). The three binder components, fly ash, blast furnace slag, and silica fume, were blended with cement as the foundational composition. We predicted the yield stress and plastic viscosity of the pastes using the YODEL (Yield stress mODEL) and Krieger-Dougherty's equation. The predictive model's performance was validated by comparing it with experimental results obtained using a rheometer. When the rheological properties of the binary blended paste were predicted by reconstructing the properties and parameters used to predict the individual materials, it was evident that the predictions made using the proposed method closely matched the experimental results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.69-76
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• 2024

The rheological properties of fresh concrete significantly influence its manufacturing and performance. However, the diversification of newly developed mixtures and manufacturing techniques has made it challenging to accurately predict these properties using traditional empirical methods. This study introduces a multiscale rheological property prediction model designed to quantitatively anticipate the rheological characteristics from nano-scale interparticle interactions, such as those among cement particles, to micro-scale behaviors, such as those involving fine aggregates. The Yield Stress Model (YODEL), the Chateau-Ovarlez-Trung equation, and the Krieger-Dougherty equation were utilized to predict the yield stress for cement paste and mortar, as well as the plastic viscosity. Initially, predictions were made for the paste scale, using the water-cement ratio (W/C) of the cement paste. These predictions then served as a basis for further forecasting of the rheological properties at the mortar scale, incorporating the same W/C and adding the cement-sand volume ratio (C/S). Lastly, the practicality of the predictive model was assessed by comparing the forecasted outcomes to experimental results obtained from rotational rheometer.