Adhesively bonded carbon fiber reinforced plastic (CFRP) skin-stringer structures have been widely used to build lightweight aircraft structures. However, the appearance of debonding degrades the adhesive joint. Hence, we attempted to establish a technique for monitoring the structural integrity by applying a developed ultrasonic sensing system to the debonding detection in the skin-stringer structure. In the technique, dispersion characteristics and mode conversions of Lamb waves were analyzed for providing the theoretical basis of our method. In accordance with the theoretical analysis, we used the arrival time of a mode as a damage index to successfully identify the adhesive debonding.
Acoustic emission (AE) is an elastic wave generated by the release of energy when the damage occurred in a material. In this research, we proposed a new signal processing technique by applying a neural network to analyzing the AE waveform in CFRP laminates. Through verification experiments, we demonstrated that the proposed method was able to clarify the complex relation between the AE singles with different waveform features and the damage-induced AE sources with individual mechanisms in exciting AEs. Hence, the new technique is potentially used to identify the types of damages, such as transverse crack and delamination, in CFRP laminates.
This study explored the ability of synthetic aperture radar (SAR) images for landslide detection in a tile level. Applied data are pre- and post-event ALOS-2 products captured in the affected area of 2018 Hokkaido Estern Iburi Earthquake. First, intensity information of the two applied images was extracted in SNAP software. Then the classification indicator-intensity difference absolute value was calculated using the extracted intensity information, and the analysis tiles were generated in ArcGIS software. Finally, the mean of intensity difference absolute value within each tile was calculated and employed to classify landslide and non-landslide areas. Classification results showed that 83.3% of the landslide and non-landslide tiles were distinguished in the study area.
The common practice of construction in RC framed buildings with infill masonry in urban/semi-urban areas in Nepal is to open the ground floor for commercial shutter/ parking and close the upper floor with infill masonry for residential purpose resulting vulnerable soft storey buildings. In recent 2015 Gorkha Earthquake （Mw= 7.9）, the major loss in RC frame buildings was due to this problem. There are researches recommending solution to the problem of soft storey, nevertheless there is lack of practical implementation in ground level. The authors have conducted field study comprising of questionnaire survey and interactions with different stakeholders and identified that; this problem is not a technical limitation alone but is complemented by the social condition of Nepal. Different factors to be considered while proposing retrofitting solutions for soft storey problem in Nepal are recommended through this study.