Defects in Thick Composites and Some Methods to Locate Them

Murri, W. J.; Sermon, Bradley W.; Andersen, Rikke; Martinez, L. A.; Heiden, E. J. Van der; Garner, Christian

doi:10.1007/978-1-4615-3742-7_58

Cited by 9 publications

(4 citation statements)

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“…where i,j f g 1, 2, 3 f g and k 1, 2, …,N lamina f g . In Equations (2)(3)(4), the position within the laminate, x 3,k is shown in Figure 1A. The stiffness matrix is then inverted to form the compliance matrix as…”

Section: Effective Stiffness and Failure Criteriamentioning

confidence: 99%

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A statistical approach for failure analysis involving uncertainty in determining ply orientation

Rahul,

Jack,

Smith

2024

Polymer Composites

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This article presents the uncertainty of the part performance due to the estimated ply orientations of a carbon fiber laminate inspected using ultrasound inspection. Recent developments to quantify the orientation using ultrasound inspection is accurate to within for each lamina. The research presented in the current work statistically analyzes the impact this uncertainty in measurement has on the resulting expected failure envelope using two different analytical methods: (1) Monte‐Carlo (MC) simulation approach extending classical laminate theory and (2) Closed form approach of Mean Value First Order Second Moment method based on derivatives of failure envelope as a function of lamina orientation. The results are validated against a commercial finite element‐based MC simulation approach. The Tsai‐Wu failure criteria is implemented to determine the first ply failure stresses by applying a variety of planer loads to form the failure envelope for a given layup sequence of a carbon fiber reinforced polymer laminate. In this article, using stochastic simulations, the failure envelope is no longer deterministic but is stochastic in nature and converts the reporting from a deterministic factor of safety concept to a probability of failure for a given loading state. The analysis is visualized and quantified using the cumulative‐density‐function (CDF), which demonstrates the similarity between the stochastic results and the classical deterministic approach. To demonstrate a possible end use of the presented statistical analysis, a study of a woven composite laminate is presented where the ply orientation is estimated using ultrasound and the resulting CDF of failure is presented.Highlights Statistical analysis (Monte‐Carlo, mean value, first order, second moment) on the ply orientation variability via ultrasound inspection. Statistical analysis of classical laminate theory and FE based Tsai‐Wu failure model is developed and compared. Tsai‐Wu failure envelope is quantified and visualized using cumulative density function.

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Section: Effective Stiffness and Failure Criteriamentioning

confidence: 99%

“…(see e.g., reference 1). Due to their anisotropic characteristics and complex geometry, the as manufactured properties and defect identification of a carbon fiber composites has become a significant challenge for part qualification (see e.g., reference 2). One of the fundamental properties of a composite laminate is its ply orientation.…”

Section: Introductionmentioning

confidence: 99%

A statistical approach for failure analysis involving uncertainty in determining ply orientation

Rahul,

Jack,

Smith

2024

Polymer Composites

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“…Shearography is primarily employed to detect debonding or the initiation of delamination, as stress concentrations around a particular defect intensify the failure risk of composites [54][55][56][57][58][59]. However, Shearography has significant disadvantages, such as the difficulty in characterizing fiber breakage, matrix cracking, or matrix/fiber debonding (i.e., microscopic to mesoscopic damage mechanisms).…”

Section: Shearographic Testing (St)mentioning

confidence: 99%

Review of Nondestructive Testing Methods for Aerospace Composite Materials

Shetu

2024

J. Comput. Mech. Manag

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Composite structures and materials have seen significant advancements in cost-effectiveness, product eﬀiciency, and specific properties, leading to their extensive use in the aerospace industry. Reliable nondestructive testing (NDT) of composites is crucial for reducing maintenance costs and addressing safety concerns. This review provides a comprehensive analysis of various NDT methods, including Ultrasonic Testing, Acoustic Emission, Eddy Current Testing, Shearographic Testing, Infra-Red Thermography, and X-Ray Radiography. Each method’s principles, instruments, and applications for defect detection and damage evaluation in composite materials are thoroughly examined. The paper highlights the strengths and limitations of these NDT techniques, emphasizing their roles in ensuring the structural integrity of aerospace composites. Ultrasonic Testing and Infra-Red Thermography are identified as flexible and cost-effective solutions, widely applied in both academic research and industrial sectors. Despite the challenges in providing a complete diagnostic of structural integrity, each NDT method offers unique advantages. Future research in NDT for composites will focus on integrating advanced data processing techniques, such as machine learning and deep learning, and developing smart inspection systems with high precision and rapid data processing capabilities.

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“…Akbari et al 9 studied the thermal loading parameters in a shearography test by using a numerical-experimental approach. As mentioned, even though applications for shearography NDT of thin composite materials were well discussed in the literature, an inspection of thicker composites has been conducted by relatively few researchers 10,11 . More recently, Tao et.al 12,13 have performed a numerical-experimental study on the defect detection capability in thick fiber-reinforced composite laminates.…”

Section: Introductionmentioning

confidence: 99%

Comparative performance of high and medium resolution cameras for defect detection in carbon-fiber reinforced composites by digital shearography

Abedin¹,

Tao²,

Anisimov³

et al. 2023

Optical Measurement Systems for Industrial Inspection XIII

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The performance of defect detection in composite materials using digital shearography is important for correct decisionmaking in non-destructive testing. In this work, we compared a high-resolution 24-megapixel digital still camera (DSLR) and a conventional medium-resolution 5-megapixel camera to determine the detectability of blind holes in an aerospacegraded carbon-fiber reinforced polymer (CFRP) sample. The hole diameters ranged from 0.2 to 3 mm with a material thickness of 4 mm and the test sample dimensions of 200×200 mm. The sample was heated and observed from the front (defect-free side) by three halogen lamps for 5 minutes in pulsed heating mode. Speckle interferograms were acquired during the heating and cooling phases from both cameras simultaneously using identical shearing interferometers and shearing distances. Phase maps were calculated using the 4+4 temporal phase step algorithm and then unwrapped. Further, defect-induced deformation (DID) phase maps were obtained by polynomial curve fitting. The DID phase maps obtained from the two cameras were compared. Blind holes with diameters up to 1 mm were detected, which are one of the smallest defects detected with shearography and reported in literature. In addition, the DLSR camera was able to detect holes of 0.8 mm in diameter. We observed that nearly comparable detection capabilities were obtained from both cameras, even though the spatial resolution of the second camera (DLSR) was 5 times higher. Possible reasons of this limitation include effects such as fiber-related deformation in CFRP and speckle noise.

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Defects in Thick Composites and Some Methods to Locate Them

Cited by 9 publications

References 0 publications

A statistical approach for failure analysis involving uncertainty in determining ply orientation

A statistical approach for failure analysis involving uncertainty in determining ply orientation

Review of Nondestructive Testing Methods for Aerospace Composite Materials

Comparative performance of high and medium resolution cameras for defect detection in carbon-fiber reinforced composites by digital shearography

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