Issue 52

Frattura ed Integrità Strutturale, 52 (2020); International Journal of the Italian Group of Fracture

Table of Contents

Y. Xu, Y. Cai, D. Li, T. Zhang https://youtu.be/BwLAZEacPfw Building crack monitoring based on digital image processing ....................................................... 1-8 H. Ghahramanzadeh Asl, S. Çam, O. Orhan, A. Özel https://youtu.be/QeZHNavQ_ek Experimental and numerical analysis of epoxy based adhesive failure on mono- and bi-material single lap joints under different displacement rates ………………………………………. 9-24 W. Xiangming, G. Erfu https://youtu.be/wqcaqQYhqJQ Numerical analysis and verification of residual stress in T joint of S355 steel ……..…………. 25-32 O. Kryvyi, Y. Morozov https://youtu.be/fXVU1yjMyD4 Thermally active interphase inclusion in a smooth contact conditions with transversely isotropic half-spaces ….......................................................................................................................... 33-50 B. E. Sobrinho, G. Gomes, W. V. da Silva, R. S. Y. R. C. Silva, L. M. Bezerra, E. U. L. Palechor https://youtu.be/D_Q4WN0pCFU Differential evolution algorithm for identification of structural damage in steel beams …………. 51-66 A. Ahmadi, G.H. Farrahi, K. Reza Kashyzadeh, Sh. Azadi, K. Jahani https://youtu.be/6emxxgSoslk A comparative study on the fatigue life of the vehicle body spot welds using different numerical techniques: Inertia relief and Modal dynamic analyses …………….……………………... 67-81 M. F. Bouali, A. Hima https://youtu.be/y01QADxMwDw Alternative estimation of effective Young’s Modulus for Lightweight Aggregate Concrete LWAC 82-97 M. Saadatmand, R. Talemi https://youtu.be/zr2jqq8ipi0 Study on the thermal cycle of Wire Arc Additive Manufactured (WAAM) carbon steel wall using numerical simulation ………………………………………...……………........ 98-104

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Fracture and Structural Integrity, 52 (2020); ISSN 1971-9883

B. Paermentier, D. Debruyne, R. Talemi https://youtu.be/XInEvX3wPT4 Numerical modelling of dynamic ductile fracture propagation in different lab-scale experiments using GTN damage model ………………........................................................................... 105-112 A. Laureys, M. Pinson, L. Claeys, T. De Seranno, T. Depover, K. Verbeken https://youtu.be/kKaDSKOgCfU Initiation of hydrogen induced cracks at secondary phase particles …………………..……… 113-127 R. Hadj Boulenouar, B. Boutabout, N. Djebbar https://youtu.be/Ke1DutfJuvg Three-dimensional numerical analysis of a joint bonded reinforced with silica nanoparticles (SiO 2 ) 128-136 S. Budhe, M.D. Banea, S. de Barros https://youtu.be/VmkkDMaNLtU Prediction of the burst pressure for defective pipelines using different semi-empirical models …….. 137-147 A. Ayadi, K. Meftah, S. Sedira https://youtu.be/bn-cFIy7cqQ Elastoplastic analysis of plane structures using improved membrane finite element with rotational DOFs …………………………………………………………………….……... 148-162 J. Kasivitamnuay, P. Singhatanadgid https://youtu.be/flqlcpJ7SGc Object-Oriented Software for Fitness-For-Service Assessment of Cracked Cylinder Based on API RP 579 ……………………………………………………………………... 163-180 A. Drai, B. Aour, N. Belayachi, A. Talha, N. Benseddiq https://youtu.be/30UA-qBjqwY Finite element modeling of the behavior of polymethyl-methacrylate (PMMA) during high pressure torsion process ………………………………………........................................ 181-196 H. EL-Emam, A. El-Sisi, R. Reda, M. Seleem, M. Bneni https://youtu.be/_366H6woTG0 Effect of concrete cover thickness and main reinforcement ratio on flexural behavior of RC beams strengthened by NSM-GFRP bars …………………………………………………... 197-210 H. Latifi, N. Amini https://youtu.be/BklnLkI0sRo Effect of aggregate type on moisture susceptibility of modified cold recycled mix asphalt: evaluation by mechanical tests and Surface Free Energy method ………………………....………….. 211-229 N. Hebbar, I. Hebbar, D. Ouinas, M. Bourada https://youtu.be/URLpfEDgE4M Numerical modeling of bending, buckling, and vibration of functionally graded beams by using a higher-order shear deformation theory …….............................................................................. 230-246

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Frattura ed Integrità Strutturale, 52 (2020); International Journal of the Italian Group of Fracture

C. Caselle, S. Bonetto, D. Costanzo https://youtu.be/DtsyUCjESiY Crack coalescence and strain accommodation in gypsum rock ……………………………... 247-255 W. N. Bouzitouna, W. Oudad, M. Belhamiani, D. E. Belhadri, L. Zouambi https://youtu.be/4XstOifnbcs Elastoplastic analysis of cracked Aluminum plates with a hybrid repair technique using the bonded composite patch and drilling hole in opening mode I ……………………………….. 256-268 J. Akbari, M. Ahmadifarid, A. Kazemi Amiri https://youtu.be/dFGv79dNbwk Multiple crack detection using wavelet transforms and energy signal techniques ………………. 269-280 M. Fouzia, L. Abdelkader, M. Abdelkader, S. Abderahmane https://youtu.be/zNgUeMZPI4Y Optimization design based approach for the determination and minimization of the displacement under tensile load in hybrid composite joint …………………………………………….. 281-298 A.V. Tumanov, V.N. Shlyannikov, A.P. Zakharov https://youtu.be/sueQTVURYUc Crack growth rate prediction based on damage accumulation functions for creep-fatigue interaction 299-309

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Fracture and Structural Integrity, 52 (2020); ISSN 1971-9883

Editorial Team

Editor-in-Chief Francesco Iacoviello

(Università di Cassino e del Lazio Meridionale, Italy)

Co-Editor in Chief Filippo Berto

(Norwegian University of Science and Technology (NTNU), Trondheim, Norway)

Section Editors Marco Boniardi

(Politecnico di Milano, Italy)

Nicola Bonora Milos Djukic

(Università di Cassino e del Lazio Meridionale, Italy)

(University of Belgrade, Serbia)

Stavros Kourkoulis

(National Technical University of Athens, Greece) (University Politehnica Timisoara, Romania)

Liviu Marsavina Pedro Moreira

(INEGI, University of Porto, Portugal)

Guest Editor

SI: Structural Integrity and Safety: Experimental and Numerical Perspectives

José António Fonseca de Oliveira Correia

(University of Porto, Portugal.)

SI: 1st Benelux Network Meeting and Workshop on Damage and Fracture Mechanics

Guest Editors

Johan Hoefnagels

(Eindhoven University of Technology, Nederland)

(KU Leuven, Belgium)

Reza Talemi

Advisory Editorial Board Harm Askes

(University of Sheffield, Italy) (Tel Aviv University, Israel) (Politecnico di Torino, Italy) (Università di Parma, Italy) (Politecnico di Torino, Italy) (Politecnico di Torino, Italy)

Leslie Banks-Sills Alberto Carpinteri Andrea Carpinteri Giuseppe Ferro

Donato Firrao

Emmanuel Gdoutos

(Democritus University of Thrace, Greece) (Chinese Academy of Sciences, China)

Youshi Hong M. Neil James Gary Marquis

(University of Plymouth, UK)

(Helsinki University of Technology, Finland)

(Ecole Nationale Supérieure d'Arts et Métiers | ENSAM · Institute of Mechanics and Mechanical Engineering (I2M) – Bordeaux, France)

Thierry Palin-Luc Robert O. Ritchie Ashok Saxena Darrell F. Socie Shouwen Yu Cetin Morris Sonsino

(University of California, USA)

(Galgotias University, Greater Noida, UP, India; University of Arkansas, USA)

(University of Illinois at Urbana-Champaign, USA)

(Tsinghua University, China) (Fraunhofer LBF, Germany) (Texas A&M University, USA) (University of Dublin, Ireland)

Ramesh Talreja David Taylor John Yates Shouwen Yu

(The Engineering Integrity Society; Sheffield Fracture Mechanics, UK)

(Tsinghua University, China)

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Frattura ed Integrità Strutturale, 52 (2020); International Journal of the Italian Group of Fracture

Regional Editorial Board Nicola Bonora

(Università di Cassino e del Lazio Meridionale, Italy)

Raj Das

(RMIT University, Aerospace and Aviation department, Australia)

Dorota Koca ń da Stavros Kourkoulis Carlo Mapelli Liviu Marsavina

(Military University of Technology, Poland) (National Technical University of Athens, Greece)

(Politecnico di Milano, Italy)

(University of Timisoara, Romania) (Tecnun Universidad de Navarra, Spain)

Antonio Martin-Meizoso

Raghu Prakash

(Indian Institute of Technology/Madras in Chennai, India)

Luis Reis Elio Sacco

(Instituto Superior Técnico, Portugal) (Università di Napoli "Federico II", Italy) (University of Belgrade, Serbia) (Tel-Aviv University, Tel-Aviv, Israel)

Aleksandar Sedmak

Dov Sherman Karel Sláme č ka

(Brno University of Technology, Brno, Czech Republic) (Middle East Technical University (METU), Turkey) (Ternopil National Ivan Puluj Technical University, Ukraine)

Tuncay Yalcinkaya

Petro Yasniy

Editorial Board Jafar Albinmousa Nagamani Jaya Balila

(King Fahd University of Petroleum & Minerals, Saudi Arabia)

(Indian Institute of Technology Bombay, India) (Indian Institute of Technology Kanpur, India)

Sumit Basu

Stefano Beretta Filippo Berto K. N. Bharath

(Politecnico di Milano, Italy)

(Norwegian University of Science and Technology, Norway) (GM Institute of Technology, Dept. Of Mechanical Engg., India)

Elisabeth Bowman

(University of Sheffield)

Alfonso Fernández-Canteli

(University of Oviedo, Spain) (Università di Parma, Italy)

Luca Collini

Antonio Corbo Esposito

(Università di Cassino e del Lazio Meridionale, Italy)

Mauro Corrado

(Politecnico di Torino, Italy) (University of Porto, Portugal)

José António Correia

Dan Mihai Constantinescu

(University Politehnica of Bucharest, Romania)

Manuel de Freitas Abílio de Jesus Vittorio Di Cocco Andrei Dumitrescu Riccardo Fincato Milos Djukic

(EDAM MIT, Portugal)

(University of Porto, Portugal)

(Università di Cassino e del Lazio Meridionale, Italy)

(University of Belgrade, Serbia)

(Petroleum-Gas University of Ploiesti, Romania)

(Osaka University, Japan)

Eugenio Giner Ercan Gürses

(Universitat Politecnica de Valencia, Spain) (Middle East Technical University, Turkey)

Ali Javili

(Bilkent University, Turkey) (University of Piraeus, Greece)

Dimitris Karalekas Sergiy Kotrechko Grzegorz Lesiuk Paolo Lonetti Carmine Maletta

(G.V. Kurdyumov Institute for Metal Physics, N.A.S. of Ukraine, Ukraine)

(Wroclaw University of Science and Technology, Poland)

(Università della Calabria, Italy) (Università della Calabria, Italy)

Sonia Marfia

(Università di Cassino e del Lazio Meridionale, Italy)

Lucas Filipe Martins da Silva

(University of Porto, Portugal)

Tomasz Machniewicz

(AGH University of Science and Technology)

Hisao Matsunaga Milos Milosevic Pedro Moreira

(Kyushu University, Japan)

(Innovation centre of Faculty of Mechanical Engineering in Belgrade, Serbia)

(University of Porto, Portugal)

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Fracture and Structural Integrity, 52 (2020); ISSN 1971-9883

Mahmoud Mostafavi Vasile Nastasescu

(University of Bristol, UK)

(Military Technical Academy, Bucharest; Technical Science Academy of Romania)

Stefano Natali Andrzej Neimitz

(Università di Roma “La Sapienza”, Italy) (Kielce University of Technology, Poland)

(Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine, Ukraine)

Hryhoriy Nykyforchyn

Pavlos Nomikos

(National Technical University of Athens) (IMT Institute for Advanced Studies Lucca, Italy)

Marco Paggi Hiralal Patil Oleg Plekhov

(GIDC Degree Engineering College, Abrama-Navsari, Gujarat, India) (Russian Academy of Sciences, Ural Section, Moscow Russian Federation)

Alessandro Pirondi Maria Cristina Porcu Dimitris Karalekas Luciana Restuccia Giacomo Risitano

(Università di Parma, Italy) (Università di Cagliari, Italy) (University of Piraeus, Greece) (Politecnico di Torino, Italy) (Università di Messina, Italy) (Università di Padova, Italy) (Università di Brescia, Italy) (Università di Napoli "Federico II")

Mauro Ricotta Roberto Roberti

Elio Sacco

Hossam El-Din M. Sallam

(Jazan University, Kingdom of Saudi Arabia) (Università di Roma "Tor Vergata", Italy)

Pietro Salvini Mauro Sassu

(University of Cagliari, Italy) (Università di Parma, Italy)

Andrea Spagnoli Ilias Stavrakas

(University of West Attica, Greece) (Lublin University of Technology)

Marta S ł owik Cihan Teko ğ lu Dimos Triantis Sabrina Vantadori Natalya D. Vaysfel'd Charles V. White

(TOBB University of Economics and Technology, Ankara, Turkey

(University of West Attica, Greece)

(Università di Parma, Italy)

(Odessa National Mechnikov University, Ukraine)

(Kettering University, Michigan,USA)

Shun-Peng Zhu

(University of Electronic Science and Technology of China, China)

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Frattura ed Integrità Strutturale, 52 (2020); International Journal of the Italian Group of Fracture

Frattura ed Integrità Strutturale is an Open Access journal affiliated with ESIS

Sister Associations help the journal managing Australia: Australian Fracture Group – AFG

Czech Rep.: Asociace Strojních Inženýr ů (Association of Mechanical Engineers) Greece: Greek Society of Experimental Mechanics of Materials - GSEMM India: Indian Structural Integrity Society - InSIS Israel: Israel Structural Integrity Group - ISIG Italy: Associazione Italiana di Metallurgia - AIM Italy: Associazione Italiana di Meccanica Teorica ed Applicata - AIMETA Italy: Società Scientifica Italiana di Progettazione Meccanica e Costruzione di Macchine - AIAS Poland: Group of Fatigue and Fracture Mechanics of Materials and Structures Portugal: Portuguese Structural Integrity Society - APFIE Romania: Asociatia Romana de Mecanica Ruperii - ARMR Serbia: Structural Integrity and Life Society "Prof. Stojan Sedmak" - DIVK Spain: Grupo Espanol de Fractura - Sociedad Espanola de Integridad Estructural – GEF Turkey: Turkish Solid Mechanics Group Ukraine: Ukrainian Society on Fracture Mechanics of Materials (USFMM)

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Fracture and Structural Integrity, 52 (2020); ISSN 1971-9883

Journal description and aims Frattura ed Integrità Strutturale (Fracture and Structural Integrity) is the official Journal of the Italian Group of Fracture. It is an open-access Journal published on-line every three months (January, April, July, October). Frattura ed Integrità Strutturale encompasses the broad topic of structural integrity, which is based on the mechanics of fatigue and fracture and is concerned with the reliability and effectiveness of structural components. The aim of the Journal is to promote works and researches on fracture phenomena, as well as the development of new materials and new standards for structural integrity assessment. The Journal is interdisciplinary and accepts contributions from engineers, metallurgists, materials scientists, physicists, chemists, and mathematicians. Contributions Frattura ed Integrità Strutturale is a medium for rapid dissemination of original analytical, numerical and experimental contributions on fracture mechanics and structural integrity. Research works which provide improved understanding of the fracture behaviour of conventional and innovative engineering material systems are welcome. Technical notes, letters and review papers may also be accepted depending on their quality. Special issues containing full-length papers presented during selected conferences or symposia are also solicited by the Editorial Board. Manuscript submission Manuscripts have to be written using a standard word file without any specific format and submitted via e-mail to gruppofrattura@gmail.com. Papers should be written in English. A confirmation of reception will be sent within 48 hours. The review and the on-line publication process will be concluded within three months from the date of submission. Peer review process Frattura ed Integrità Strutturale adopts a single blind reviewing procedure. The Editor in Chief receives the manuscript and, considering the paper’s main topics, the paper is remitted to a panel of referees involved in those research areas. They can be either external or members of the Editorial Board. Each paper is reviewed by two referees. After evaluation, the referees produce reports about the paper, by which the paper can be: a) accepted without modifications; the Editor in Chief forwards to the corresponding author the result of the reviewing process and the paper is directly submitted to the publishing procedure; b) accepted with minor modifications or corrections (a second review process of the modified paper is not mandatory); the Editor in Chief returns the manuscript to the corresponding author, together with the referees’ reports and all the suggestions, recommendations and comments therein. c) accepted with major modifications or corrections (a second review process of the modified paper is mandatory); the Editor in Chief returns the manuscript to the corresponding author, together with the referees’ reports and all the suggestions, recommendations and comments therein. d) rejected. The final decision concerning the papers publication belongs to the Editor in Chief and to the Associate Editors. The reviewing process is usually completed within three months. The paper is published in the first issue that is available after the end of the reviewing process.

Publisher Gruppo Italiano Frattura (IGF) http://www.gruppofrattura.it ISSN 1971-8993 Reg. Trib. di Cassino n. 729/07, 30/07/2007

Frattura ed Integrità Strutturale (Fracture and Structural Integrity) is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0)

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Frattura ed Integrità Strutturale, 52 (2020); International Journal of the Italian Group of Fracture

NEWS from FIS

Dear friends, First of all, some information about the Publisher’s website, Gruppo Italiano Frattura (IGF). Now we have a new address (www.gruppofrattura.eu) and the website is based on Google Sites, offering many services (we will discover them all together in the next future!) and allowing to obtain a really high responsiveness of the website, being really independent on the device you use to surf the site. I hope you will appreciate this new approach. Secondly some news about the recent activities organized by IGF. Although these last months were quite hard for the events organizers, IGF opened the 2020 with two successful events: - The VCSI1 (1 st Virtual Conference on Structural Integrity; in cooperation with the Greek, the Portuguese and the Serbian Fracture groups) that was held online on January 16, 2020 and, maybe, defined a new paradigm in the organization of low cost-high quality events. All the presentations and the discussions are available in the IGF YouTube channel (https://www.youtube.com/c/IGFTube) and the papers will be published in a Procedia Structural Integrity Issue. - The MedFract1 (1 st Mediterranean Conference on Fracture and Structural Integrity, in cooperation with the Greek fracture group), that was held in Athens (Greece) in February (26-28). In this case, we were able to face the problems created by the Covid-19 organizing some virtual sessions with remote speakers. Also in this case, all the presentations are available in the IGF YouTube channel (https://www.youtube.com/c/IGFTube) and the papers will be published in a Procedia Structural Integrity Issue. Third, we are trying to “push” the YouTube channel we are using to publish the Visual Abstracts: https://www.youtube.com/channel/UC3Ob2GNW8i0phNiiKjEVv0A As you can see, as we have less than 100 subscribers, we can’t have a customized url. Please, join the channel!! In the Table of Contents now you can find the Visual Abstract url for each published paper. Please, do not hesitate to send us your suggestions to further improve our journal. Very best,

Francesco Iacoviello Frattura ed Integrità Strutturale Editor in Chief

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Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

Building crack monitoring based on digital image processing

Yanyan Xu, Yanxia Cai*, Dandan Li,Tierui Zhang Hengshui University, Hengshui, Hebei Province 053000, China xyy_xu@126.com, yxcyanx@yeah.net, zzaod5@163.com

A BSTRACT . Building crack monitoring is of great value to the judgment of building safety. In this study, the digital image processing technology was studied and applied to the monitoring of building cracks. Crack images were collected by CCD camera, and then operations such as graying, correction, denoising and segmentation were carried out to obtain clear crack images. The obtained images were processed morphologically to further improve the quality. Finally, the width and length of cracks were calculated. In the case analysis, the results of 15 cracks measured by a microscope were taken as the standards and compared with the calculated results. The results showed that the results calculated in this study and the manual measurement results differed little, and the average errors of the width and length were 0.021 mm and 0.024 mm respectively, which suggested that the method proposed had a high reliability. The findings of this study provide a new idea for the further development of the building crack monitoring field and is conducive to the accurate assessment of building safety. K EYWORDS . Digital image processing; Building crack; Monitoring; Histogram equalization.

Citation: Xu, Y.Y., Cai, Y.X., Li, D.D., Zhang, T.R., Building crack monitoring based on digital image processing, Frattura ed Integrità Strutturale, 52(2020) 1-8.

Received: 06.08.2019 Accepted: 05.12.2019 Published: 01.04.2020

Copyright: © 2020 This is an open access article under the terms of the CC-BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

I NTRODUCTION

n the process of concrete production, due to the uneven expansion and contraction, cracks will inevitably occur in the ground. In the process of component transportation and assembly, cracks may also occur due to the influence of external environment. In the process of building use, cracks will gradually occur along with the deformation of materials. Building cracks will continue to develop and expand to destroy the integrity of the building structure, resulting in a decline in the mechanical properties of the overall structure; if serious, it may lead to shorter building life and cause safety accidents. Cracks in buildings develop slowly, and changes in the width and length can reflect the safety of buildings. Therefore, effective monitoring of cracks has important practical values [1]. With the development of technology, digital image processing has shown excellent performance in crack monitoring. Riyadi et al. [2] monitored pavement cracks with digital image processing technology, developed detection technology through the Gauss pyramid method, classified cracks and non-cracks by linear discrimination, and found that the method had an accuracy of 92.8571% and the processing time of each picture was 1.5 seconds. Kim et al. [3] combined Unmanned Aerial Vehicle (UAV) technology with digital image processing technology to realize the crack assessment of concrete structures and found that the system could successfully I

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Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

measure cracks with thickness greater than 0.1 mm and the estimated error of the maximum length was 7.3%. Hoang et al. [4] studied the detection and classification of cracks in asphalt pavement, processed images with digital image processing technology, classified images by machine learning algorithm, and found that the method was helpful to assist inspectors in assessing pavement conditions. Lu et al. [5] studied the cracks of cement matrix composites, designed a double threshold algorithm for image processing, and found through experiments that the proposed method could effectively calculate the crack width. Felli et al. [6] studied related cracks of the right foreleg of Colleoni equestrian statue and made long-term examination on the crack expansion through pasting Fiber Bragg Grating sensor. In this study, a series of digital image processing methods were designed for building cracks, and the example analysis verified that the proposed method had high monitoring accuracy, which provides some bases for its practical application and is conducive to the effective evaluation of building health and the improvement of safety and reliability of buildings. igital images refer to images composed of data points (pixels). Taking a 360*500 image as an example, it refers to an image which is composed of 360 rows of pixels and 500 columns of pixels. Digital image processing refers to the transformation of image signal to digital signal through computer. Digital image processing has many advantages: (1) high accuracy: by processing each pixel in the image, the image can maintain a high accuracy; (2) high processing speed: data-based digital images can perform various operations quickly in the process of processing; (3) easy storage: unlike paper images, digital images are not affected by time and are easy to store; (4) a wide range of applications: no matter what kind of equipment the image is collected, it can be processed by digital image processing; (5) high flexibility: linear and non-linear processing can be realized. In the actual acquisition, the image of building cracks may be affected by illumination, photography, occlusion and so on, which makes the boundary between cracks and background unclear and makes it difficult to accurately extract cracks. Clear crack images can be obtained through digital image processing technology to realize the monitoring of cracks. D D IGITAL IMAGE PROCESSING

I MAGE PROCESSING METHOD FOR BUILDING CRACKS

I

Image acquisition n order to obtain high-quality images, the selected image acquisition equipment should have high pixel and resolution. In this study, MV-VDM200SM/SC CCD industrial camera produced by Video Digital Image Company (Fig. 1) was used. Some of its parameters are shown in Tab. 1.

Figure 1: CCD camera.

Maximum resolution

1600* 1200

Pixel size Frame rate Output mode

4.40 μ m × 4.40 μ m

12 fps USB2.0

Power supply requirements

5V

Power

2.4W

Table 1: Parameters of CCD camera.

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Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

In the process of acquisition, the lens was located in front of the crack. The stable image was obtained by tripod and level instrument, and a ruler was set around the crack to provide a standard for crack calculation. Then the acquired image was input to the computer through USB. Image preprocessing Under the influence of illumination and noise, the collected images often have some problems, such as low clarity and inconspicuous details, which are not conducive to crack monitoring. Therefore, image preprocessing is needed to improve the quality. Image graying The image captured by camera is usually color image in RGB format. The amount of calculation involved in the processing is considerable, which can seriously affect the speed of image processing. Therefore, it is necessary to gray the RGB image. In this study, graying was achieved by the weighted average method [7]. It is assumed that there is an RGB image   , f i j . The treatment formula is:         , 0.3 , 0.59 , 0.11 , f i j R i j G i j B i j    . (1) Gray level correction In order to improve the gray resolution of the image, gray correction can be made to the image. In this study, the image was corrected by the histogram equalization method [8]. Firstly, the gray histogram   k p r of the image is calculated:   , 0,1, , 225 k k n p r k N    , where k r stands for the k -th grayscale, N stands for number of pixels, k n stands for the number of pixels with gray level of k , and   k p r stands for the proportion of k r in the whole image. The cumulative distribution function k s is calculated: , where k g stands for the new grayscale of the corrected image. All the gray levels of the image are corrected according to the above procedures, and then the corrected gray level image is obtained. Image denoising The image is denoised by Median filter [9], that is, the gray value in window W is ranked. Then the median value is used as the gray value of the central point. The calculation formula is:         , , , , g p q med f p i q j i j W     , (3) where   , f i j stands for the original gray value in W and   , g p q stands for the gray value after median filtering denoising. 0 n  k j k j n s   . (2) k s is taken as a transform function to correct the gray level of the image: 225 0.5 k k s g N   

Image segmentation Cracks and background are separated by image binarization. For the original image 

 , f x y , threshold T is set, and the

segmented image is:





 , f x y T f x y T    ,

 

1 0





, g x y

.

(4)



3

Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

max 2 T T T  

min

The method for determining the threshold is as follows. Firstly the initial threshold is calculated, where max T and min T stand for the maximum and minimum gray values in the image respectively. The image gray level is divided into two groups, group 1 with gray level larger than T and group 2 with gray level smaller or equal to T . The average gray values 1  and 2  of the two groups are calculated. Suppose 1 2 2 T     . The above procedures repeat until T is stable, and finally the binarization threshold is obtained. C RACK CALCULATION Morphological treatment or the segmented crack image, the morphological algorithm is taken for further improvement, which mainly includes two steps: corrosion and expansion. (1) Corrosion:     | A B x B x A    , where A stands for the target image and B stands for the structural element. The noise and burr in the image can be further removed after corrosion. (2) Expansion:     | A B x B x x      . After expansion, the image can be restored to the original size. , where  represents the pixel scale parameter, which is the actual size represented by the pixel. As cracks are mostly irregular, the coordinates of left pixels are kept unchanged in the calculation, and then the coordinates of right pixels are calculated in turn with the window size of 5×5, and the minimum value is denoted as the crack width. Calculation of crack length The length of crack is calculated through the Euclidean distance between the starting point of crack   , s s x y and the ending point   , e e x y :     2 2 e s e s l x x y y      , where  stands for the pixel proportion parameter. F Calculation of crack width Coordinates are set around the crack to calculate the distance between the two points:    2  2 right x x left right left w y y     

C ASE STUDY

Crack image acquisition ifteen cracks were collected by CCD camera in building A in Hengshui, Hebei, China. The data of the length and width of the fifteen cracks were collected using a WYSK-40X reading microscope (Fig. 2). The specification of the microscope was 50 × 23 × 138 mm. The focus of the microscope was adjustable, and it carried with pure white LED light source, had scale, and had 40X magnification. F

Figure 2: The reading microscope.

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Image processing The images were processed using the method described in the section of image preprocessing. Four of the images were taken as examples, and the original images of the four images are shown in Fig. 3.

Figure 3: Original crack images.

It was found from Fig. 3 that the quality of crack images was poor under the influence of illumination and noise, which was not conducive to crack monitoring. The crack images obtained after the processing of the digital image processing method proposed in this study are shown in Fig. 4.

Figure 4: Crack images after processing.

It was found from Fig. 4 that the crack images obtained were clearer and distinct from the background after processing such as denoising, segmentation and morphological treatment, which was conducive to the subsequent crack calculation. Crack calculations The width and length of the extracted crack images were calculated using the method mentioned in the section of crack calculation. The comparison between the calculated results and manual monitoring results is shown in Fig. 5 and 6.

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Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

Figure 5: Comparison of crack width.

Figure 6: Comparison of crack length.

It was found from Fig. 5 and 6 that the width and length of cracks calculated by the method were almost the same as the measured values, which showed that the method had a high monitoring accuracy and could replace manual monitoring to achieve effective monitoring of cracks. The errors between the results obtained by the proposed method and those obtained by manual monitoring are shown in Tab. 2. Number of image Width error/mm Length error/mm 1 0.01 0.03 2 0.01 0.01 3 0.03 0.02 4 0.01 0.03 5 0.03 0.03 6 0.03 0.04 7 0.01 0.04 8 0.02 0.03 9 0.01 0.01 10 0.03 0.02 11 0.02 0.02 12 0.02 0.02 13 0.03 0.03 14 0.04 0.02 15 0.02 0.01 Average error 0.021 0.024 Table 2: Errors between the results obtained using the method proposed in this study and the manual detection results It was found from Tab. 2 that the maximum error of the method was 0.04 mm, the minimum error was 0.01 mm, and the average error was 0.021 mm in the width monitoring; in the length monitoring, the maximum error was 0.04 mm, the minimum error was 0.01 mm, and the average error was 0.024 mm. The errors were so small that could be nearly neglected, which would not affect the evaluation of cracks, suggesting that the method was reliable. All the results showed that the digital image processing method could obtain almost the same results as the manual monitoring, with a good accuracy, and could realize the effective monitoring of building cracks. D ISCUSSION igital image processing has a good application in many fields [10]. For example, in the field of medicine, it can analyze ultrasound and electrocardiogram images [11] to provide a guidance for doctors’ surgery [12]. In the field of industry, it can realize the analysis and detection of circuits, chips, micro parts, etc [13,14]. In the field of D

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Y. Xu et alii, Frattura ed Integrità Strutturale, 52 (2020) 1-8; DOI: 10.3221/IGF-ESIS.52.01

security, it can identify fingerprints and iris [15]. In the field of art, it can realize the restoration and reconstruction of cultural relic pictures [16]. Cracks in buildings are closely related to the overall safety of buildings. Monitoring cracks is an important work of building health assessment. Traditional manual monitoring methods have many limitations in practical operation, which cannot meet the current needs of building crack monitoring. The emergence of digital image processing technology has brought a new idea for building crack monitoring. This study collected the building crack images by CCD camera, then obtained the clear crack images by a series of pretreatment operations such as graying, denoising and segmentation, and finally realized the monitoring of building cracks by taking the width and length as the criteria. The processing method proposed in this study was found effective in the example analysis. It was found from Fig. 4 that the blur, noise and stain in the original images were effectively removed, the image quality was significantly improved, and the cracks were clearly separated from the background, which was conducive to the follow-up operation. Then, in the comparison of the results of crack length and width, the data measured by microscope was taken as the result of manual monitoring and compared with those calculated by the method proposed in this study. Fig. 5 and 6 show that the results obtained by the two methods were very similar, which was also verified in the calculation of errors. The width error was only 0.021 mm, and the length error was only 0.024 mm. With a high accuracy, the method can realize monitoring of the cracks in buildings. In practice, the method not only has high reliability, but also is convenient, fast and highly usable. However, the manual monitoring method based on microscope is very difficult to achieve in the monitoring of a large number of cracks as it is time-consuming and energy consuming. Therefore, the method is more suitable for the monitoring of actual building cracks. In this study, although some achievements have been made in the research of building crack monitoring, there are still many shortcomings, for example, unable to achieve on-line crack monitoring and the identification of complex cracks. In the future work, it is necessary to find more accurate monitoring methods and monitor more characteristics of cracks such as area and depth. n this study, the monitoring of building cracks was studied, clear crack images were obtained through digital image processing technology, and the length and width of the cracks were calculated and compared with the results obtained by the manual detection. It was found that: (1) the crack image which was processed by digital image processing method was clear and distinguished significantly from the background; (2) the crack results obtained by the method proposed in this study had small errors with the manual detection results, and the average errors of the length and width were 0.024 mm and 0.021 mm respectively; The experimental results verified that the method was reliable in crack monitoring, which is conductive to improving the crack monitoring efficiency and scientifically analyzing crack structure and moreover makes some contributions to the safety monitoring and restoration of buildings. A CKNOWLEDGEMENT his study is supported by research on the construction of the curriculum system of innovation and entrepreneurship in Colleges and Universities under the background of "Internet +" under grant number jg2018097. I C ONCLUSION

T

R EFERENCES

[1] Prasanna, P., Dana, K. J., Gucunski, N., et al. (2016). Parvardeh H. Automated Crack Detection on Concrete Bridges, IEEE T. Autom. Sci. Eng., 13(2), pp. 591-599. DOI: 10.109/TASE.2014.2354314. [2] Riyadi, S., Sugiarto, A., Putra, S. A. and Setiawan, 1N. A. (2015). Analysis of Digital Image Using Pyramidal Gaussian Method to Detect Pavement Crack, Adv. Sci. Lett., 21(11), pp. 3565-3568. DOI: 10.1166/asl.2015.6579. [3] Kim, H., Lee, J., Ahn, E., et al. (2017). Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing, Sensors, 17(9), pp. 2052. DOI: 10.3390/s17092052.

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[4] Hoang, N. D. and Nguyen, Q. L. (2018). A novel method for asphalt pavement crack classification based on image processing and machine learning, Engineering with Computers, Accepted, In Press (Part 1), pp. 1-12. DOI: 10.1007/s00366-018-0611-9. [5] Lu, C., Yu, J. and Leung, C. K. Y. (2016). An improved image processing method for assessing multiple cracking development in strain hardening cementitious composites (SHCC), Cement Concrete Comp., 74, pp. 191-200. DOI: 10.1016/j.cemconcomp.2016.10.005. [6] Felli, F., Brotzu, A., Pilone, D. and Vendittozzi, C. (2014). Use of FBG sensors for monitoring cracks of the equestrian statue of Bartolomeo Colleoni in Venice, Frat. Integr. Strut., 8(30), pp. 48-54. DOI: 10.3221/IGF-ESIS.30.07. [7] Ren, Z. X., Bi, J. H., Xie, L. and Zhang, K. F. (2014). Quantitative detection of wood surface defects by image segmentation method, Chin. J. Liq. Cryst. Displays, 29(5), pp. 785-792. DOI: 10.3788/YJYXS20142905.0785. [8] Lai, Y. R., Tsai, P. C., Yao, C. Y. and Ruan, S. J. (2017). Improved local histogram equalization with gradient-based weighting process for edge preservation, Multimed. Tools Appl. 76(1), pp. 1-29. DOI: 10.1007/s11042-015-3147-7. [9] Aranda, L. A., Reviriego, P. and Maestro, J. A. (2017). Error Detection Technique for a Median Filter, IEEE T. Nucl. Sci., pp. 1-1. DOI: 10.1109/TNS.2017.2666843. [10] Prasad, D. S. and Reddy, B. S. (2017). Digital image processing techniques for estimating power released from the corona discharges, IEEE T. Dielect. El. In., 24(1), pp. 75-82. DOI: 10.1109/TDEI.2016.005896 [11] Robertson, S., Azizpour, H., Smith, K. and Hartman, J. (2018). Digital image analysis in breast pathology-from image processing techniques to artificial intelligence, Transl. Res. J. Lab. Clin. Med., 194, pp. 19. DOI: 10.1016/j.trsl.2017.10.010. [12] Scholz, M., Konen, W., Tombrock, S., et al. (2015). Development of an endoscopic navigation system based on digital image processing, Comput. Aided Surg., 3(3), pp. 134-143. DOI: 10.1002/(SICI)1097-0150(1998)3:33.0.CO;2-T [13] Zhang, J.J. and Meng, X.Q. (2015). Defect detection of wire rope for oil well based on adaptive angle, Frat. Integr. Strut., 9(34). DOI: 10.3221/IGF-ESIS.34.65. [14] Boschetto, A., Bottini, L., Campana, F., Consorti, L. and Pilone, D. (2013). Investigation via morphological analysis of aluminium foams produced by replication casting, Frat. Integr. Strut., 7(26), pp. 01. doi: 10.3221/IGF-ESIS.26.01. [15] Ambadiyil, S., Prakash, D., Sheeja, M. K. and Pillai, V. P. M. (2017). Secure Storage and Analysis of Fingerprints for Criminal Investigation using Holographic Techniques, Mater. Today Proc., 4(2), pp. 4389–4395. DOI: 10.1016/j.matpr.2017.04.010. [16] Pizurica, A., Platisa, L., Ruzic, T., et al. (2015). Digital Image Processing of The Ghent Altarpiece: Supporting the painting's study and conservation treatment, IEEE Signal Proc. Mag., 32(4), pp. 112-122. DOI: 10.1109/MSP.2015.2411753.

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H. Ghahramanzadeh Asl et alii, Frattura ed Integrità Strutturale, 52 (2020) 9-24; DOI: 10.3221/IGF-ESIS.52.02

Experimental and numerical analysis of epoxy based adhesive failure on mono- and bi-material single lap joints under different displacement rates

Hojjat Ghahramanzadeh Asl Karadeniz Technical University, Turkey h.kahramanzade@ktu.edu.tr, http://orcid.org/ 0000-0002-9078-1933 Salim Çam, Osman Orhan, Adnan Özel Erzincan Binali Y ı ld ı r ı m University, Turkey scam@erzincan.edu.tr, http://orcid.org/0000-0003-2603-8691 osman.orhan@erzincan.edu.tr, http://orcid.org/ 0000-0002-1632-0207 adnanozel@erzincan.edu.tr, http://orcid.org/ 0000-0001-8527-3136

A BSTRACT . Development in material science imposes to use different materials in production. This causes a problem for joining different materials because traditional joining techniques such as welding could not overcome this problem in industries such as automotive. Hence, adhesive bonding overcomes this problem by its superiorities to join different materials. The joint strength of epoxy-based adhesives is affected by adhesive thickness, adherent’s surface quality, and curing conditions. In this study, two different materials (SAE 304 and AL7075) were bonded by epoxy adhesive (3M DP460NS) as single lap joint (SLJ) of Aluminum-Aluminum, Steel-Steel, and Aluminum-Steel. The effects of adhesive thickness (0.05, 0.13, 0.25 mm) and surface roughness (281, 193, 81 nm) to strength were compared. SLJs were tested for 1, 10, 25 and 50 mm/min displacement rates. Adhesive surface structures were imaged by Scanning Electron Microscopy (SEM) to investigate adhesive fractures. Surface roughnesses were examined by using Atomic Force Microscopy (AFM) to compare its influence on failure load. Finite Element Analysis (FEA) was conducted by using Cohesive Zone Model with ANSYS 18.0 software to obtain stress distribution of adhesive. Optimum values according to the present conditions of the thickness (0.13mm) and roughness (<200nm) were determined. Experimental results were demonstrated that while displacement rates rose, failure loads increased as well. FEA analysis was fit to experimental results. It has been observed that along with material type, peel stresses become an important factor for joint strength. K EYWORDS . Single lap joint, Epoxy adhesive, Displacement rate, Thickness, Surface roughness.

Citation: Kahramanzade, H., Çam, S., Orhan, O., Özel, A., Experimental and Numerical Analysis of Epoxy Based Adhesive Failure on Mono- and Bi-Material Single Lap Joints Under Different Displacement Rates, Frattura ed Integrità Strutturale, 52 (2020) 9-24.

Received: 07.11.2019 Accepted: 13.12.2019 Published: 01.04.2020

Copyright: © 2020 This is an open access article under the terms of the CC-BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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H. Ghahramanzadeh Asl et alii, Frattura ed Integrità Strutturale, 52 (2020) 9-24; DOI: 10.3221/IGF-ESIS.52.02

I NTRODUCTION

A

erospace, naval and automotive industries have been using composite materials along with steel and aluminum for structure lately. Due to the difficulties of joining of two or more different materials, adhesive joints become more suitable in the application. While joining technique should enable the ability to bond different materials, it also should be strong enough regarding strength. Although the performance of the joint under static and dynamic conditions is essential, crashworthiness of joint is also considered as crucial in case of accidents. As for crashworthiness, it highly depends on the strain rate of impact [1,2]. Single lap joint (SLJ) is widely used for adhesive joints due to its easy application, simple geometry and explicit results in order to understand joint strain rate dependency [3]. There are some inconsistent factors that affect adhesive SLJs strength. For instance, a structural adhesive DP460, manufactured by 3M, technic sheet suggests aluminum adherend’s overlap shear strength as around 30 MPa when epoxy fully cured. Some researchers report that it could be 13.6 MPa curing conditions at 140 °C for 60 min [4], 23.6 MPa at 60 °C for 120 min [5] and 13.9 MPa 23 °C for 2 days [6]. Along with this, adhesive strength enhancement studies have been proposed by others [7,8] and these pure adhesive strengths were used as a reference of base adhesive strength. These studies focused on strain rate, adhesive thickness or surface quality of adhesive joints but few of them considered all of these together in one work. However, these parameters are interconnected between and impose bond strength crucially [9,10]. Although some of the studies report different adhesive strengths with high fluctuation [5,11–13] experiments need to be performed by considering all factors into account to clarify results. From this perspective of view, separate works have been conducted by researchers by taking thickness, overlap length, adherend type, adherend thickness, strain rate, and surface quality into consideration. Bamberg et al. [6] conducted SLJ tests by changing adhesive thickness, overlap length and adherents using DP460 (3M) adhesive. They concluded that increasing overlap length from 7 to 25 improved failure load of joints. Aydin et al.[11] compared different adherend thicknesses and overlap lengths by using the same adhesive at 0.28 MPa curing pressure and 0.12 mm adhesive thickness. They reported that increasing adherend thickness also distributed stress concentrations from edges to the middle of the adhesive layer. They have not supplied the effects of different curing pressure and adhesive thickness while other factors change. By using the same adhesive, similar thickness and aluminum adherents; failure load of SLJ was reported by Bamberg et al. [6] as 8.7 kN and Gültekin et al.[8] as 14.7 kN. This difference of 68% needs to be explained by further studies. Adams and Peppiatt[14] investigated the effects of adhesive thickness on failure load by adopting five approaches then predicted an intersection point at 0.13 mm as an ideal adhesive thickness. Niranjan[15] reported three independent factors that were affected by adhesive thickness; adhesive defects, stresses, and strain rate. Adams and Peppiatt landed up the presence of voids and microcracks in the adhesive layer that affects adhesive strength which was the first consideration of Niranjan. Further study by Grant et al. [16] concluded that while adhesive thickness increased, the bending moment also amplified. This caused a decrease of joint strength which is related to Niranjan's second consideration. Although this adhesive thickness is widely accepted as optimum adhesive thickness for SLJ, it needs to be investigated more due to the reliance of stress on the single lap joint, its dependence of strain rate and adherend material. Along with previous studies, a study that considers both the effects of overlap length and strain rate under impact and quasi-static conditions conducted by Araújo et al. [17]. They concluded that 25mm overlap length provides better damping than 12.5 and 50mm overlap lengths. Blackman et al.’s study [18] showed crack propagation with regards to the test rate for adhesively bonded joints. According to their results, while the test rate increased, crack formation velocity accelerated, thus adhesive fracture energy lowered. Lißner et al. [19] investigated the rate dependency of adhesive joints. They used 3 different surface treatments, adhesive thicknesses and loading rates for this purpose. They concluded that for higher loading rates; while stress in adhesive increased, the energy that disappears during fracture decreased independently of adhesive thickness. When adhesive thickness set from 0.3 to 1.0, stress in joints tended to reduce. Trimino et al. [12] employed epoxy adhesives (include 3M DP460NS) to determine strain rate dependency. They applied quasi-static and impact tests on the adhesive samples. They found that stress at failure augmented by increasing the strain rate. Avendaño et al. [20] conducted tests on SLJ’s under two crosshead speeds. They observed that while speed rose from 1mm/min to 100mm/min, failure loads amplified by 14%. Boutar et al. [21] investigated the effect of surface roughness on adhesive joint failure. They used sandpaper from 50- to 1000-grid afterward measured surface roughnesses of adherends. They reported that surface roughness decreased by using fine-grained sandpaper consequently bond strength of joint improved. Among approaches to model adhesively bonded joints, the Cohesive Zone Model (CZM) is widely used because of its relatively easy application and simulation capability of joints [22]. Campilho et al. [23] inspected triangular, trapezoidal and exponential CZMs and concluded that although triangular CZM has been used most, all of these models predict mechanical

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