Suksangpanya, Nobphadon

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Preferred name
Suksangpanya, Nobphadon
Alternative Name
Suksangpanya, N.
Main Affiliation
Email
nobphadon.su@kmitl.ac.th

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    Item type:Publication,
    Automatic classification of pararubber trees in Thailand from LANDSAT-8 images using neural networks method
    (2019-07-01)
    Supunyachotsakul, Chisaphat
    ;
    Anan, Thanwarat
    ;
    Suksangpanya, Nobphadon
    ;
    Nakya, Suvalak
    Classifying features from satellite images has been a time-consuming manual process which requires lots of manpower. This work exploits deep convolutional decoder encoder neural network, to develop an algorithm that can automatically classify the extents of the Pararubber tree growing areas from the LANDSAT-8 images. The classification resulted from this approach was verified. In conclusion, the classification accuracy achieved is at 86.90% with Cohen's kappa at 73.80% which is considered satisfactory.
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    Item type:Publication,
    Crack twisting and toughening strategies in Bouligand architectures
    (2018-10-01)
    Suksangpanya, Nobphadon
    ;
    Yaraghi, Nicholas A.
    ;
    Pipes, R. Byron
    ;
    Kisailus, David
    ;
    Zavattieri, Pablo
    The Bouligand structure in some arthropods is a hierarchical composite comprised of a helicoidal arrangement of strong fibers in a weak matrix. In this study, we focus on the Bouligand structure present in the dactyl club of the smashing mantis shrimp due to its exceptional capability to withstand repetitive high-energy impact without catastrophic failure. We carry out a combined computational and experimental approach to investigate the high damage resistance of the Bouligand structure through a biomimetic composite material. This is studied by performing specific fracture experiments on the helicoidal composites specimens, where it was found that crack twisting, driven by the fiber architecture, is the main fracture mechanisms. This crack twisting mechanism competes with other alternative mechanisms such as crack branching and delamination, delaying catastrophic failure. The main mechanism of crack twisting is studied through specifically designed specimens in which the crack propagation path is controlled. Further quantification of the toughening mechanisms and crack growth rate is analyzed with analytical and finite element models. The biomimetic helicoidal composites are shown to have improved fracture resistance as the crack twists mainly driven by the increase in crack surface area and fracture mode mixity. Our analysis allowed us to study the effect of crack front shape, stress distribution and energy dissipation mechanisms.