Hyperspectral Scanning Data collection and live-display surfaces.

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Hyperspectral Scanning Data collection and live-display surfaces. Progressive failure analysis of hyperspectrally detected waviness in plain weave carbon/epoxy composite laminate Seyedmohammad Shams, PhD candidate & Dr. Rani Elhajjar, Associate Professor- Civil Engineering and Mechanics Department Introduction Composite structures in practice can be subjected to wrinkling defect originating to manufacturing process. The visibly superficially resin rich area can produce waviness typically impacting all or some of the plies in a laminate stack. The damage behavior of laminated composites based on initiation and growth of damage under random through the thickness waviness is investigated to evaluate the performance of the defected laminate under flexural loading. Fiber waviness profile in a composite wind turbine blade Hyperspectral Scanning The out of plane waviness have been detected by the non-destructively spot checking hyperspecteral imaging system. Near Infrared (NIR) imaging can accurately measure surface resin on composite materials from 2 to 75 mils thick, detecting virtually all resin pockets, resin filled surface wrinkles and other surface resin features. Data collection and live-display surfaces. This image shows a series of surface resin pockets in the NIR image and a visible resin feature on the surface in the video image Diagram of the hyperspectral camera scanning over the exterior of a wing part

Specimen models using computer aided design process Progressive failure analysis of hyperspectrally detected waviness in plain weave carbon/epoxy composite laminate Seyedmohammad Shams, PhD candidate & Dr. Rani Elhajjar, Associate Professor- Civil Engineering and Mechanics Department Experiments Plain Weave aerospace grade Fabric prepreg system has been targeted to investigate the effect of ply waviness on the structural strength. A number of 11 plies of 0/90 fabric is cured with hot press based on manufacturer suggested process. The wrinkles are produced by using additional pressure emerged from the mold. The 3- point flexural test has been performed according to ASTM D760. Failure progression of specimens with different fiber waviness amplitude 3point flexural test setup Modeling Process The STL file format is used to create a surface of the random waviness from hyperspectral imaging using MATCAD software. The STL is a file format native to the stereolithography CAD software created by 3D systems. Three specimens have been cut from the highest fiber waviness zone of the main panel where the waviness pattern on each specimen is unique. Specimen models using computer aided design process Resin Pocket Area of fiber waviness

Progressive Failure Analysis Progressive failure analysis of hyperspectrally detected waviness in plain weave carbon/epoxy composite laminate Seyedmohammad Shams, PhD candidate & Dr. Rani Elhajjar, Associate Professor- Civil Engineering and Mechanics Department Progressive Failure Analysis The progressive failure methodology is used to characterize damage mechanisms of through thickness fiber waviness on the flexural strength of the continuous in-plain weave fabric carbon laminate. A finite element modeling framework is proposed for the in-plain weave composite laminates comprising adjusted Hashin-puck’s continuum damage criteria and cohesive layers model. Load-displacement of wavy samples Fiber fracture and delamination at final failure Results Experimental and numerical results have shown the waviness can significantly impact the flexural strength of the laminates derived by spreading the interlaminar failure on defected areas. The failure mechanisms consist of interlaminar failure at the area of fiber waviness/resin pocket and fiber/matrix failure at final load capacity. Interlaminar failure predicted by CZM Acknowledgments 1- Gabor J. Kemeny, Gard A. Groth, Gina Stuessy, Chris Zueger, Middleton Research 8505 University Green, Middleton WI 53562 2- Ahmad Pahlavan Tafti, Computer Science Department, University of Wisconsin Milwaukee