Carbon/Epoxy Laminate Compression After Impact Load Carbon/Epoxy Laminate Compression After Impact Load Prediction from Ultrasonic C-Scan Data Prediction from Ultrasonic C-Scan Data Eric v. K. Hill, Christopher D. Hess and Yi Zhao Eric v. K. Hill, Christopher D. Hess and Yi Zhao OBJECTIVES •Three sets of 3.5 x 6 inch 16-ply AS4/3501-5A carbon/epoxy coupons impacted from 0-20 ft-lb f with 5/8 inch diameter hemispherical tup to create barely visible impact damage (BVID) •Back-propagation neural network (BPNN) prediction of compression after impact (CAI) load from transformed ultrasonic (UT) C-scan image • Goal: Goal: Worst case prediction error within ±15% ±15% APPROACH/TECHNICAL CHALLENGES •AE data too noisy: Train BPNN using 50 data points representing column summation data from UT C-scan image and known CAI loads as input •Test BPNN using column summation UT C- scan image to predict CAI loads on remaining coupons ACCOMPLISHMENTS/RESULTS •UT image data alone used to predict ultimate compressive strengths with worst case errors worst case errors of -12.12%, 16.62%, -12.12%, 16.62%, and -11.83% for the three sets and -11.83% for the three sets •BPNN able to predict accurately without predict accurately without C/Ep Coupon C/Ep Coupon in Boeing in Boeing BS-7260 BS-7260 Compression Compression After After Impact Test Impact Test Fixture Fixture with Three with Three Acoustic Acoustic Emission Emission Transducers Transducers Attached Attached Instron Instron Dynatup 9250 Dynatup 9250 Calibrated Calibrated Impactor Impactor Delaminations Delaminations in Coupon Due in Coupon Due to Impact to Impact Damage Damage