Porosity detection in composite aeronautical structures

Ciliberto, A.; Cavaccini, Giovanni; Salvetti, Ovidio; Chimenti, M.; Azzarelli, L; Bison, P.; Маринетти, С.; Freda, Andrea; Grinzato, E.

doi:10.1016/s1350-4495(02)00132-9

Cited by 41 publications

(15 citation statements)

References 3 publications

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“…This family of methods has been extensively applied for inspection and characterisation of conventional materials and advanced material systems (Margetan, 2012;Taheri et al, 2014). UT techniques have also shown some promise as methods for characterisation of AM materials such as porosity detection in aeronautical structures (Ciliberto et al, 2002) and in more routine application to finished parts.…”

Section: Ultrasonic Techniquesmentioning

confidence: 99%

Powder-based additive manufacturing - a review of types of defects, generation mechanisms, detection, property evaluation and metrology

Taheri

Shoaib

Koester³

et al. 2017

IJASMM

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Powder-based additive manufacturing (AM) technologies have been evaluated for use in different fields of application (aerospace, medical, etc.). Ideally, AM parts should be at least equivalent, or preferably better quality than conventionally produced parts. Manufacturing defects and their effects on the quality and performance of AM parts are a currently a major concern. It is essential to understand the defect types, their generation mechanisms, and the detection methodologies for mechanical properties evaluation and quality control. We consider the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder based AM parts in this work. Methods of in-situ non-destructive evaluation and the influence of defects on mechanical properties and design considerations are also reviewed. Together, these provide a framework to understand the relevant machine and material parameters, optimise the process and production, and select appropriate characterisation methods.Abstract: Powder-based additive manufacturing (AM) technologies have been evaluated for use in different fields of application (aerospace, medical, etc.). Ideally, AM parts should be at least equivalent, or preferably better quality than conventionally produced parts. Manufacturing defects and their effects on the quality and performance of AM parts are a currently a major concern. It is essential to understand the defect types, their generation mechanisms, and the detection methodologies for mechanical properties evaluation and quality control. We consider the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder based AM parts in this work. Methods of in-situ non-destructive evaluation and the influence of defects on mechanical properties and design considerations are also reviewed. Together, these provide a framework to understand the relevant machine and material parameters, optimise the process and production, and select appropriate characterisation methods.Reference to this paper should be made as follows: Taheri, H., Shoaib, M.R.M., Koester, L., Bigelow, T.A., Collins, P.C. and Bond, L.J. (2017) 'Powder-based additive manufacturing -a review of types of defects, generation mechanisms, detection, property evaluation and metrology', Int. Institute of Aviation Technology conducting research on UAVs and designing and printing 3D parts for UAVs. His research interest areas include engineering mechanics, additive manufacturing and non-destructive testing.Lucas W. Koester received his PhD from the University of Nebraska at Lincoln studying wave propagation and scattering in polycrystalline media. His current and past research interests include wave propagation in polycrystalline media, defect scattering, and modelling with emphasis on additive manufacturing processes and materials.Powder-based additive...

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Section: Ultrasonic Techniquesmentioning

confidence: 99%

Powder-based additive manufacturing - a review of types of defects, generation mechanisms, detection, property evaluation and metrology

Taheri

Shoaib

Koester³

et al. 2017

IJASMM

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“…The processors possess an internal memory acquired as a result of training. Neural networks are convenient for solving multiparametric problems [90].…”

Section: Neural Networkmentioning

confidence: 99%

Review of pulsed thermal NDT: Physical principles, theory and data processing

Вавилов

Burleigh²

2015

NDT & E International

281

120

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“…The sensing systems either incorporate sensors into the composite structures such as Fibre Bragg gratings (FBG) or attach or insert sensors into the compos- 15 ite structures such as acoustic methods and Fabry Perot Interferometer (FPI) [14,16,17,18]. Once those sensors have been integrated into the composite structures a new challenge will have to be overcome; establishing a relationship between changes in the physical properties of the sensors and changes in properties of the composite structures being monitored, such as temperature, 20 pressure, mass, stiffness etc.…”

Section: Introductionmentioning

confidence: 99%