7.10 Radiographic Inspection of Composite Materials

Crane, Robert L.

doi:10.1016/b978-0-12-803581-8.03928-x

Cited by 3 publications

(3 citation statements)

References 122 publications

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“…Radiografi industri adalah modalitas pengujian non-destructive yang menggunakan radiasi pengion untuk memeriksa bahan dan komponen dengan tujuan menemukan dan mengukur cacat dan degradasi sifat material yang akan menyebabkan kegagalan struktur teknik (Crane, 2018). Radiasi pengion memainkan peran penting dalam sains dan teknologi yang dibutuhkan untuk memastikan kualitas dan keandalan produk (BAPETEN, 2014).…”

Section: B Radiografi Industriunclassified

Analisis Efektifitas Metode Penerapan Sni Iso 9712:2014 Untuk Perpanjangan Masa Pemberlakuan Sertifikasi Personil Uji Tak Rusak Radiografi Level 1 Dan Level 2 Pada Lembaga Sertifikasi Person Batan

Widjanarko¹,

Khotimah²

2021

PPIS

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Lembaga Sertifikasi Person (LSP) BATAN memiliki wewenang melakukan penilaian kompetensi personal Bidang Uji Tak Rusak (UTR) berdasarkan pada pemenuhan standar SNI ISO 9712: 2014 tentang Uji Tak Rusak -Kualifikasi dan Sertifikasi Personal Radiografi. Masa berlaku sertifikat personil UTR radiografi adalah 5 tahun, dimana sertifikat dapat diperpanjang masa berlakunya oleh LSP BATAN untuk periode baru setelahnya. Selama ini, penerapan perpanjangan sertifikasi tersebut dilakukan dengan verifikasi dokumen terhadap aktifitas kerja. Kondisi demikian belum efektif karena tidak meyakinkan bahwa pemegang sertifikat telah melakukan aktivitas kerja berkelanjutan tanpa jeda waktu dan terpelihara kompetensinya, serta formatnya belum dapat merangkum semua kegiatan yang dilakukan oleh pemegang sertifikasi. Oleh karena itu, penelitian ini bertujuan untuk meningkatkan keefektifan penerapan SNI ISO 9712:2014 pada UTR radiografi BATAN dengan tambahan metode validasi aktivitas kerja berkelanjutan tanpa jeda waktu tidak bekerja melalui validasi wawancara secara kualitatif dengan teknik wawancara pada 9 informan dari industri pengguna radiografi. Hasil dari penelitian ini menunjukkan bahwa validasi melalui wawancara yang mengacu pada pedoman mutu LSP BATAN dengan 7 parameter validasi (2 parameter utama dan 4 parameter pendukung) mewajibkan nilai parameter utama dan total gabungannya di atas rata-rata 70 untuk sertifikasi perpanjangan berlaku pada informan 3,4, 7 dan 8, serta rekomendasi untuk dilakukan sertifikasi ulang jika nilainya dibawah rata-rata 70 terjadi pada informan 1,2,5,6, dan 9. Dengan demikian, metode validasi wawancara menjadi penilaian yang efektif untuk pemastian aktivitas kerja berkelanjutan tanpa jeda waktu dan kompetensinya terjaga bagi pekerja radiografi dalam memperpanjang masa pemberlakuan sertifikasi.

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Section: B Radiografi Industriunclassified

Analisis Efektifitas Metode Penerapan Sni Iso 9712:2014 Untuk Perpanjangan Masa Pemberlakuan Sertifikasi Personil Uji Tak Rusak Radiografi Level 1 Dan Level 2 Pada Lembaga Sertifikasi Person Batan

Widjanarko¹,

Khotimah²

2021

PPIS

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“…• Ultrasonic testing: this method uses ultrasonic waves mechanically induced by a transducer converting an electric signal into mechanical one; through the analysis of the wave transmission or reflection, it is able to detect, e.g., delamination or inclusions [1,11]; ultrasonic testing is described as "the most versatile of the testing techniques available to industry" [13]; • Thermography: this method is based on the observation of heat distribution over the tested sample's surface and the search for hot spots that may indicate a defect in the component/object under examination; the test object may be heated by mechanical force, by illumination with a very strong light, by a laser, or by any other method [10,[14][15][16]; • Radiographic testing: this technique is similar to well-known medical radiography; it uses X-radiation (electromagnetic radiation with energy within 10-50 kV); X-rays passing through the specimen are recorded on an X-ray-sensitive medium, and the analysis of the recorded radiographic image makes it possible "to examine composites for flaws and compliance to manufacturing standards" [17][18][19].…”

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confidence: 99%

Detection of Material Degradation of a Composite Cylinder Using Mode Shapes and Convolutional Neural Networks

Miller

Ziemiański

2021

Materials

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This paper presents a numerical study of the feasibility of using vibration mode shapes to identify material degradation in composite structures. The considered structure is a multilayer composite cylinder, while the material degradation zone is, for simplicity, considered a square section of the lateral surface of the cylinder. The material degradation zone size and location along the cylinder axis are identified using a deep learning approach (convolutional neural networks, CNNs, are applied) on the basis of previously identified vibration mode shapes. The different numbers and combinations of identified mode shapes used to assess the damaged zone size and location were analyzed in detail. The final selection of mode shapes considered in the identification procedure yielded high accuracy in the identification of the degradation zone.

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“…As a result, the defects of this type cannot be easily quantified and the adequacy of the produced CFRP parts is mostly based on empirical and qualitative inspections. On the other hand, the implementation of X-Rays for defect detection provided even more details about the damage as seen in [49][50]. Provided that the X-Rays are very penetrative, their implementation on composite materials gave a lot of advantages to the NDT inspection.…”

Section: Quality Assessment Of Porous Composite Laminates By Ndtmentioning

confidence: 99%

A numerical methodology for predicting the mechanical properties of unidirectional composite laminates with pores

Stamopoulos¹

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In the present thesis, a numerical methodology was developed to predict the mechanical properties of unidirectional carbon fiber reinforce polymers (CFRPs) using data from NDT tests. To achieve the goal of the thesis, X-Ray CT scan data analysis was conducted, optical microscopy was utilized, multi-scale FE models were created, mechanical tests were conducted and Artificial Neural Networks were trained by utilizing the developed FE models.Originally, UD CFRP plates with different pore content were manufactured by implementing a variety of autoclave pressures. The pressure values were the optimum, most often implemented and lowest respectively. To this end, four different types of plates of the same material were manufactured. The pores developed in the samples cut from these plates was characterized by means of X-Ray computed tomography. Prior to the final porosity quantification, a parametrical study was conducted for defining the most efficient parameters set on the software’s defect detection module. In parallel, optical microscopy was utilized for defining the large void’s dimensions in the sample with the highest pore content. By comparing the measurements obtained by the optical microscope and the XCT, the defect detection parameters were properly calibrated and validated. Small pores and micro-pores were also attributed to the analysis. At the end of this framework, porosity developed in all four samples was characterized.Subsequently, a numerical methodology was developed which employs the pore’s characteristics. Due to the pore’s dimension high ratio between the smallest and bigger observed, the methodology was designed in three distinct levels, namely the epoxy resin with small pores, porous epoxy resin with large voids and CFRP specimens. The output of each level was the input of the consecutive. The methodology was implemented in four porosity levels’ pores characteristics resulting the mechanical properties of the CFRP laminate, namely the transverse strength and stiffness, short beam strength, flexural strength and modulus. The results in terms of mechanical behavior were validated against mechanical tests. All the matrix dominated properties appeared to be highly affected by the pores and voids leading to a degradation up to 14% of the interlaminar shear strength and roughly 20% of the in-plane shear properties.After having validated the numerical methodology, an Artificial Neural Network was developed to link the pore’s characteristics defined by means of XCT and the mechanical properties of the porous UD CFRP laminate. To this end, a number of 30 different autoclave pressure scenarios were created excluding the 2 out of 4 actual cases, thus 30 pores dataset. After simulating the corresponding mechanical tests with the use of the numerical methodology developed previously, the ANN was trained utilizing the 30 input and output data. The two excluded cases which correspond to the most often implemented autoclave pressures, validated the accuracy of the developed ANN.The main conclusion of the thesis is that the developed numerical methodology can accurately predict the mechanical properties of porous CFRP laminates. Additionally, the ANN based on this methodology is equally accurate and capable of predicting the degraded mechanical properties of the CFRP material using a pore’s characteristics dataset in a direct, effective and fast manner. Consequently, both two methods –after minor modifications- may be used as tools for the scopes of designing and optimizing materials saving cost and increasing the design’s effectiveness.

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7.10 Radiographic Inspection of Composite Materials

Cited by 3 publications

References 122 publications

Analisis Efektifitas Metode Penerapan Sni Iso 9712:2014 Untuk Perpanjangan Masa Pemberlakuan Sertifikasi Personil Uji Tak Rusak Radiografi Level 1 Dan Level 2 Pada Lembaga Sertifikasi Person Batan

Analisis Efektifitas Metode Penerapan Sni Iso 9712:2014 Untuk Perpanjangan Masa Pemberlakuan Sertifikasi Personil Uji Tak Rusak Radiografi Level 1 Dan Level 2 Pada Lembaga Sertifikasi Person Batan

Detection of Material Degradation of a Composite Cylinder Using Mode Shapes and Convolutional Neural Networks

A numerical methodology for predicting the mechanical properties of unidirectional composite laminates with pores

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