포화유무 및 온도조건에 따른 콘크리트 음향방출 신호 감쇠계수 결정
Determination of acoustic emission signal attenuation coefficient of concrete according to dry, saturation, and temperature condition
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초록
본 연구는 경주 중 ‧ 저준위 지하 처분환경에서의 사일로 콘크리트의 음향방출(AE) 신호 감쇠계수()를 결정하기 위해신호감쇠 실험을 수행하였다. 활용된 시료들은 경주 중 ‧ 저준위 처분장 사일로에 사용된 콘크리트 배합비로 제작하였으며 28일간 수중 양생 후 처분환경에 맞도록 온도 및 포화유무에 따라 추가적으로 노출시켰다. 처분조건 별 각 3개씩의 공시체에 대하여 신호전달거리에 따른 AE 신호를 측정한 결과, 초기구간에서는 포화콘크리트의 AE 진폭과 절대에너지가 건조콘크리트의 경우보다 더 높게 나타났지만, 는 포화콘크리트의 경우가 더 높게 산정되었다. 또한, 포화유무와 상관없이 온도가 증가함에 따라 는 감소하는 경향을 보였다. 는 온도조건보다는 포화유무에 따른 영향이 큰 것으로 분석되었으며, 이는 콘크리트 처분구조물의 감쇠신호 측정 시 포화여부를 고려한 판단이 중요하다는 것을 의미한다. 처분환경에서의 콘크리트 는 균열이 발생한 위치에서의 실제 AE 특성 파라미터 값을 추정함으로써 경주 중 ‧ 저준위 처분환경에서 사일로 콘크리트의 건전성을 예측하고 센서의 최적 배치를 결정하는 데 도움이 될 것으로 기대한다.
Abstract
This study carried out the laboratory tests for AE signal attenuation to determine the attenuation coefficient () of silo concrete in Gyeongju low and intermediate-leveldisposal environments. The concrete samples were prepared by satisfying the concrete mixing ratio used in the Gyeongju disposal silo, and these samples were additionallyexposed depending on the temperature conditions and saturation and, dry condition. As a result of attenuation tests according to the transmission distance on three concretespecimens for each disposal condition, the AE amplitude and absolute energy measured on the saturated concrete were higher than that of the dry concrete in the initialrange of the signal transmission distance, but the of the saturated concrete was higher than that of the dry concrete. Regardless of the saturation and dry conditions, the tended to decrease as the temperature increases. The had a more major influence on the saturation and dry condition than the temperature condition, which means that thesaturation and dry condition is the main consideration in measuring the signal attenuation of a concrete disposal structure. The of concrete in the disposal environment expect to be used to predict the integrity of silos concrete in Gyeongju low and intermediate-level disposal environments by estimating the actual AE parameter values at the location of cracks and to determine the optimum location of sensors.
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