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Determination of Young’s moduli of clays using image processing technique and stress-strain calculation

Ekawita R.a, Widiatmoko E.a, Nawir H.b, Suprijadic, Khairurrijala

a Physics of Electronic Materials Research Division, Faculty of Mathematics and Natural Sciences, Bandung, Indonesia
b Geotechnical Engineering Research Division, Faculty of Civil and Environmental Engineering, Bandung, Indonesia
c Theoretical High Energy Physics and Instrumentation Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesa, Bandung, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2006-2015 Asian Research Publishing Network (ARPN).A system that consists of compression, imaging, and computation subsystems was successfully developed to determine Young’s moduli of clay samples. The compression subsystem utilized a Mark-10 instrument that has a compressor with a capacity of 11.3 Nm. The instrument also has a displacement sensor with a resolution of 0.01 mm and an integrated display that was used as a standard to compare deformations obtained from images. The imaging subsystem operated a Canon IVX digital camera to obtain images with sizes of 3000×4000 pixels. The computation subsystem exploited a personal computer (PC) installed with Scilab ver. 5.3.3 to process the images. Experimentally, a clay sample was initially prepared in cylindrical shape. The sample was then continuously compressed at the rate of 80 mm/min and its image was subsequently captured every second. Next, the obtained images were processed to extract deformation experienced by the sample. Finally, the sample deformation was used to calculate its Young’s modulus. It was shown that deformation data obtained from image processing are almost the same as those recorded by the Mark-10 display with the coefficient of determination R2 of 0.99. As the accurate displacement sensor is much more expensive than the Canon IVX digital camera, the image processing technique offers an affordable way to obtain deformation. It was demonstrated that Young’s modulus versus the quadratic of height has very good linearity as revealed by the R2 coefficient of 0.94. This result is in agreement with the theoretical formula.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Compression,Deformation,Image processing,Young’s modulus[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]