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http://dx.doi.org/10.7855/IJHE.2014.16.3.035

Evaluation of the Dynamic Modulus by using the Impact Resonance Testing Method  

Kim, Dowan (Department of Civil Engineering, Seoul National University of Science and Technology)
Jang, ByungKwan (Department of Civil Engineering, Seoul National University of Science and Technology)
Mun, Sungho (Department of Civil Engineering, Seoul National University of Science and Technology)
Publication Information
International Journal of Highway Engineering / v.16, no.3, 2014 , pp. 35-41 More about this Journal
Abstract
PURPOSES : The dynamic modulus for a specimen can be determined by using either the non-destructed or destructed testing method. The Impact Resonance Testing (IRT) is the one of the non-destructed testing methods. The MTS has proved the source credibility and has the disadvantages which indicate the expensive equipment to operate and need a lot of manpower to manufacture the specimens because of the low repeatability with an experiment. To overcome these shortcomings from MTS, the objective of this paper is to compare the dynamic modulus obtained from IRT with MTS result and prove the source credibility. METHODS : The dynamic modulus obtained from IRT could be determined by using the Resonance Frequency (RF) from the Frequency Response Function (FRF) that derived from the Fourier Transform based on the Frequency Analysis of the Digital Signal Processing (DSP)(S. O. Oyadigi; 1985). The RF values are verified from the Coherence Function (CF). To estimate the error, the Root Mean Squared Error (RMSE) method could be used. RESULTS : The dynamic modulus data obtained from IRT have the maximum error of 8%, and RMSE of 2,000MPa compared to the dynamic modulus measured by the Dynamic Modulus Testing (DMT) of MTS testing machine. CONCLUSIONS : The IRT testing method needs the prediction model of the dynamic modulus for a Linear Visco-Elastic (LVE) specimen to improve the suitability.
Keywords
response frequency; frequency response function; impact resonance testing; coherence function; digital signal processing; stone mastic asphalt; root mean squared error;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
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