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Abstract

When composite structures are exposed to harsh environmental conditions or impacted by foreign objects, their surfaces may degrade or damage. Damage evaluations of composite panels often demand expensive tools and time-consuming processes. The aim of this work is to introduce a versatile inverse analysis based method that requires less measurement efforts than those of conventional techniques. In this procedure, first, strains are measured on a surface opposite to damaged surface. Then, general functions relating damage conditions to strain fields are established. These functions reduce computational efforts required during the damage identification. With the measured strains and functions, an error objective function is minimized via iterations to estimate the damage extent. To verify the effectiveness of this proposed procedure, a detailed simulation study is performed with cross-ply composite laminates possessing various damage. The results show excellent matches between the estimated damage fields and the specified conditions imposed on the models. Following this promising outcome, the proof of concept study is extended to several real cross-ply composite panels that are damaged by either sand-blasting or environmental exposure. In the latter case, the composites were exposed to combined ultraviolet radiation and moisture absorption. On composite specimens, spatial variations of strain fields are measured with strip strain-gauges. Then they are used to identify surface damage distributions with either the quadratic formulation or the B-spline method. The latter approach is suitable when the functional change of strains due to damage is not smooth. The results estimated the variation of damage extent in each specimen. This feasibility study clearly supports the possibility of using strain sensor-network or optical method to quantify surface damage.

Keywords

inverse analysis singular-value decomposition B-spline multi-variate Newton's method damage degradation composite laminate strip strain gauges.

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Estimating Surface Damage of Composite Panels with Inverse Analysis

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