Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3

River Rapids Conference Proceedings of the Society for Experimental Mechanics Series Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3 Luciano Lamberti Ming-Tzer Lin Cosme Furlong Cesar Sciammarella Phillip L. Reu Michael A Sutton Proceedings of the 2018 Annual Conference on Experimental and Applied Mechanics River Publishers

Conference Proceedings of the Society for Experimental Mechanics Series Series Editor Kristin B. Zimmerman, Ph.D. Society for Experimental Mechanics, Inc., Bethel, CT, USA

River Publishers Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3 Proceedings of the 2018 Annual Conference on Experimental and Applied Mechanics Luciano Lamberti • Ming-Tzer Lin • Cosme Furlong • Cesar Sciammarella Phillip L. Reu • Michael A Sutton Editors

Published, sold and distributed by: River Publishers Broagervej 10 9260 Gistrup Denmark www.riverpublishers.com ISBN 978-87-7004-976-4 (eBook) Conference Proceedings of the Society for Experimental Mechanics An imprint of River Publishers © The Society for Experimental Mechanics, Inc. 2019 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, or reproduction in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Preface Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics represents one of the eight volumes of technical papers presented at the 2018 SEM Annual Conference & Exposition on Experimental and Applied Mechanics organized by the Society for Experimental Mechanics and held in Greenville, SC, June 4–7, 2018. The complete proceedings also include volumes on Dynamic Behavior of Materials; Challenges in Mechanics of TimeDependent Materials; Mechanics of Biological Systems & Micro-and Nanomechanics; Mechanics of Composite, Hybrid & Multifunctional Materials; Fracture, Fatigue, Failure and Damage Evolution; Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems; and Mechanics of Additive and Advanced Manufacturing. Each collection presents early findings from experimental and computational investigations on an important area within experimental mechanics, optical methods, and DIC being important areas. With the advancement in imaging instrumentation, lighting resources, computational power, and data storage, optical methods have gained wide applications across the experimental mechanics society during the past decades. These methods have been applied for measurements over a wide range of spatial domain and temporal resolution. Optical methods have utilized a full-range of wavelengths from X-ray to visible lights and infrared. They have been developed not only to make two-dimensional and three-dimensional deformation measurements on the surface but also to make volumetric measurements throughout the interior of a material body. Besides regular papers, the volume includes invited papers presented in a symposium on optical methods celebrating the 75th anniversary of the Society for Experimental Mechanics. The area of digital image correlation has been an integral track within the SEM Annual Conference spearheaded by Professor Michael Sutton from the University of South Carolina. The contributed papers within this section of the volume span technical aspects of DIC. The conference organizers thank the authors, presenters, and session chairs for their participation, support, and contribution to this very exciting area of experimental mechanics. Bari, Italy Luciano Lamberti Taichung, Taiwan Ming-Tzer Lin Worcester, MA, USA Cosme Furlong Chicago, IL, USA Cesar Sciammarella Albuquerque, NM, USA Phillip L. Reu Columbia, SC, USA Michael A Sutton v

Contents 1 Beyond the Airbrush: Applications of Digital Image Correlation in Vascular Biomechanics .................. 1 Susan M. Lessner and John F. Eberth 2 A New Method of Fringe Pattern Analysis ........................................................................... 5 C. A. Sciammarella and L. Lamberti 3 A Review: Optical Methods That Evaluate Displacement .......................................................... 23 Cesar A. Sciammarella 4 Measuring Spallation Strength of Epoxy by Laser Spallation Technique......................................... 53 Sarthak S. Singh and R. Kitey 5 Uncertainty Quantifications for Multiviewcorrelation .............................................................. 59 F. Hild and S. Roux 6 Image Analysis of Curvature Using Classical Mechanics, the Elastica............................................ 63 Charles Wilson and James Dawson 7 Fast Adaptive Global Digital Image Correlation..................................................................... 69 Jin Yang and Kaushik Bhattacharya 8 Speckle Image Rendering for DIC Performance Assessment....................................................... 75 F. Sur, B. Blaysat, and M. Grédiac 9 Speckles and DIC or Checkerboards and LSA? ..................................................................... 79 M. Grédiac, B. Blaysat, and F. Sur 10 Update on the 2D-DIC Challenge: Results and Conclusions ....................................................... 81 P. L. Reu, E. Toussaint, E. Jones, H. Bruck, M. Iadicola, R. Balcaen, D. Turner, T. Siebert, P. Lava, M. Simonsen, and M. Grewer 11 Eliminating Air Refraction Issues in DIC by Conducting Experiments in Vacuum............................. 85 P. L. Reu and E. M. C. Jones 12 Identification of Deformation Mechanisms in Biomaterials Through AFM and Digital Image Correlation....................................................................................................... 89 Horacio D. Espinosa 13 Fast, Sub-pixel Accurate Digital Image Correlation Algorithm Powered by Heterogeneous (CPU-GPU) Framework................................................................................................ 95 Mullai Thiagu, Sankara J. Subramanian, and Rupesh Nasre 14 Vibration Modal Analysis by High-Speed and Accurate Shape Measurement Using One-Pitch Phase Analysis Method......................................................................................................... 103 Yoshiharu Morimoto, Akifumi Takagi, Masaki Ueki, and Lionel Pirsig 15 DIC Image on FIB Ring-Core Analysis of Depth Sensing Residual Stress Measurement of Thin Films ...... 109 Wen Chieh Pan, Ang-Ting Tsai, Fa-Yen Cheng, Terry Yuan-Fang Chen, and Ming-Tzer Lin vii

viii Contents 16 Measurement of Local Strain Distribution and Its Variation Near Eyes During Blink Using Digital Image Correlation....................................................................................................... 113 Kasumi Sakai, Yuelin Zhang, Satoru Yoneyama, Yukihiro Miyazaki, Yuko Nagai, and Takanori Igarashi 17 Contribution to Fatigue Striation Phenomenon Analysis by Using Image Processing........................... 119 Benoit Ruellan, Eric Robin, Jean-Benoit Le Cam, Isabelle Jeanneau, Frédéric Canévet, Gérard Mauvoisin, and Didier Loison 18 Ultra-High Speed Imaging for DIC Measurements in Kolsky Bar Experiments................................. 127 Paul Moy and Timothy Walter 19 Application of Digital Image Correlation to Structures in Fire .................................................... 129 Christopher M. Smith and Matthew S. Hoehler 20 Full-Field Determination of the Taylor-Quinney Coefficient in Tension Tests of Ti-6Al-4V at Strain Rates up to 7000 s−1 ..................................................................................................... 133 Jarrod L. Smith, Jeremy D. Seidt, and Amos Gilat 21 Laser and White-Light Speckle Techniques: A Tutorial Review................................................... 141 Gary L. Cloud 22 Accurate Reconstruction of High-Gradient Strain Field in Digital Image Correlation: A Local Hermite Scheme ......................................................................................................... 173 Xin Li, Jiaqing Zhao, Jianguang Shuai, Zhengming Zhang, and Xinxin Wu 23 Development of a New Normalization Technique for Twelve Fringe Photoelasticity (TFP) .................... 177 Ashutosh Pandey and K. Ramesh 24 On Performing Spatiotemporal Stereocorrelation at Very High Temperatures.................................. 181 M. Berny, T. Archer, F. Hild, A. Mavel, P. Beauchêne, V. Herb, and B. Lacombe 25 Compression Tests on CFRP Analysed by Digital Image Correlation............................................. 185 C. Barile, C. Casavola, and G. Pappalettera 26 Evaluation of Residual Stress with Optical Methods ................................................................ 193 C. Pappalettere 27 Elevated Temperature Optical Microscopy DIC..................................................................... 203 Kevin B. Connolly and W. Carter Ralph 28 A Digital Laser Speckle Technique for Generating Slope Contours of Bent Plate ............................... 213 Austin Giordano and Fu-Pen Chiang 29 Deflectometry on Curved Surfaces .................................................................................... 217 Y. Surrel and F. Pierron 30 Measurement on a Sample of Fuel Cell at High Temperature...................................................... 223 Ning Li, NanSheng Xu, Michael A. Sutton, and Kevin Huang 31 Simulation of 3D Reconstruction of Conical Calibration Targets.................................................. 229 Wei-Chung Wang, Chi-Hung Hwang, and Yung-Hsiang Chen 32 Recent Advancements and Perspective About Digital Holography: A Super-Tool in Biomedical and Bioengineering Fields .............................................................................................. 235 F. Merola, B. Mandracchia, L. Miccio, P. Memmolo, V. Bianco, M. Mugnano, P. L. Maffettone, M. Villone, E. Di Maio, V. Ferraro, Z. Wang, V. Pagliarulo, S. Grilli, and P. Ferraro 33 High-Speed Shape and Transient Response Measurements of Tympanic Membrane........................... 243 Payam Razavi, Haimi Tang, Nima Maftoon, John J. Rosowski, Cosme Furlong, and Jeffrey Tao Cheng 34 High-Speed Digital Image Correlation for Endoscopy: A Feasibility Study...................................... 251 H. Tang, K. Pooladvand, P. Razavi, J. J. Rosowski, J. T. Cheng, and C. Furlong 35 Holographic Interferometry: Then and Now......................................................................... 257 Karl A. Stetson

Contributors T. Archer LMT (ENS Cachan/CNRS/University Paris-Saclay), Cachan, France SAFRAN, Safran Ceramics, Le Haillan, France ONERA, The French Aerospace Lab, Palaiseau, France R. Balcaen KU Leuven, Ghent, Belgium C. Barile Dipartimento di Meccanica, Matematica e Management (DMMM), Politecnico di Bari, Bari, Italy P. Beauchêne ONERA, The French Aerospace Lab, Palaiseau, France M. Berny LMT (ENS Cachan/CNRS/University Paris-Saclay), Cachan, France SAFRAN, Safran Ceramics, Le Haillan, France Kaushik Bhattacharya Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA V. Bianco NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale—DICMaPI, University of Naples Federico II, Naples, Italy B. Blaysat Université Clermont Auvergne, SIGMA, Institut Pascal, UMR CNRS 6602, Clermont-Ferrand, France H. Bruck University of Maryland, College Park, MD, USA Frédéric Canévet LC-DRIME, Joint Research Laboratory, Cooper Standard—Institut de Physique UMR 6251, Rennes Cedex, France Cooper Standard France, Rennes, France C. Casavola Dipartimento di Meccanica, Matematica e Management (DMMM), Politecnico di Bari, Bari, Italy Terry Yuan-Fang Chen Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan Yung-Hsiang Chen ITRC, NARL, Hsinchu, Taiwan, Republic of China Fa-Yen Cheng Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan Jeffrey Tao Cheng Eaton-Peabody Laboratory, Massachusetts Eye and Ear (MEE), Boston, MA, USA Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA Fu-Pen Chiang Department of Mechanical Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA Gary L. Cloud Michigan State University, Composite Vehicle Research Center, Lansing, MI, USA Kevin B. Connolly Southern Research Institute, Birmingham, AL, USA James Dawson Medtronic, Inc., Minneapolis, MN, USA ix

x Contributors E. DiMaio NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale—DICMaPI, University of Naples Federico II, Naples, Italy John F. Eberth Department of Cell Biology and Anatomy, University of South Carolina, Columbia, SC, USA Horacio D. Espinosa Department of Mechanical Engineering, Northwestern University Technological Institute, Evanston, IL, USA P. Ferraro CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy V. Ferraro NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale—DICMaPI, University of Naples Federico II, Naples, Italy Cosme Furlong Center for Holographic Studies and Laser micro-mechaTronics (CHSLT), Worcester Polytechnic Institute, Worcester, MA, USA Mechanical Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA Eaton-Peabody Laboratory, Massachusetts Eye and Ear (MEE), Boston, MA, USA Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA AmosGilat Department of Mechanical Engineering, The Ohio State University, Scott Laboratory, Columbus, OH, USA Austin Giordano Department of Mechanical Engineering, State University of New York at Stony Brook, Stony Brook, NY, USA M.Grédiac Université Clermont Auvergne, SIGMA, Institut Pascal, UMR CNRS 6602, Clermont-Ferrand, France M.Grewer LaVision GmbH, Goettingen, Germany S.Grilli CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy V.Herb SAFRAN, Safran Ceramics, Le Haillan, France F.Hild LMT (ENS Cachan/CNRS/University Paris-Saclay), Cachan, France Matthew S. Hoehler National Institute of Standards and Technology, Gaithersburg, MD, USA Kevin Huang Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA Chi-Hung Hwang ITRC, NARL, Hsinchu, Taiwan, Republic of China M. Iadicola National Institute of Standards, Gaithersburg, MD, USA Takanori Igarashi Skincare Products Research, Kao Corporation, Tokyo, Japan Isabelle Jeanneau LC-DRIME, Joint Research Laboratory, Cooper Standard—Institut de Physique UMR 6251, Rennes Cedex, France Cooper Standard France, Rennes, France E. M. C. Jones Sandia National Laboratories, Albuquerque, NM, USA R.Kitey Department of Aerospace Engineering, Indian Institute of Technology, Kanpur, India B. Lacombe SAFRAN, Safran Ceramics, Le Haillan, France L. Lamberti Dipartimento Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy P. Lava MatchID, Ghent, Belgium Jean-Benoit Le Cam Univ Rennes, CNRS, IPR (Institute de Physique de Rennes)–UMR 6251, Rennes, France LC-DRIME, Joint Research Laboratory, Cooper Standard—Institut de Physique UMR 6251, Rennes Cedex, France

Contributors xi Susan M. Lessner Department of Cell Biology and Anatomy, University of South Carolina, Columbia, SC, USA NingLi Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA XinLi Collaborative Innovation Center of Advanced Nuclear Energy Technology, The Key Laboratory of Advanced Reactor Engineering and Safety of MOE, Institute of Nuclear and New Energy Technology of Tsinghua University, Beijing, China Ming-Tzer Lin Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung, Taiwan Didier Loison Univ Rennes, CNRS, IPR (Institute de Physique de Rennes)–UMR 6251, Rennes, France P. L. Maffettone NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale—DICMaPI, University of Naples Federico II, Naples, Italy Nima Maftoon Eaton-Peabody Laboratory, Massachusetts Eye and Ear (MEE), Boston, MA, USA Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA B. Mandracchia CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Gérard Mauvoisin Laboratoire de Génie Civil et Génie Mécanique EA 3913, IUT-Université de Rennes 1, Rennes, France A.Mavel ONERA, The French Aerospace Lab, Palaiseau, France P.Memmolo CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy F.Merola CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy L.Miccio CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Yukihiro Miyazaki Makeup Products Research, Kao Corporation, Odawara, Japan Yoshiharu Morimoto Wakayama University, Wakayama, Japan 4D Sensor Inc., Wakayama, Japan PaulMoy U.S. Army Research Laboratory, Weapons and Materials Research Directorate, Adelphi, MD, USA M.Mugnano CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy YukoNagai Makeup Products Research, Kao Corporation, Odawara, Japan Rupesh Nasre Department of Engineering Design, Indian Institute of Technology, Madras, Chennai, India V. Pagliarulo CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Wen Chieh Pan Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung, Taiwan Ashutosh Pandey Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India G. Pappalettera Dipartimento di Meccanica, Matematica e Management (DMMM), Politecnico di Bari, Bari, Italy C. Pappalettere Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy F. Pierron Engineering and the Environment, University of Southampton, Southampton, UK Lionel Pirsig 4D Sensor Inc., Wakayama, Japan

xii Contributors K. Pooladvand Center for Holographic Studies and Laser micro-mechaTronics (CHSLT), Worcester, MA, USA Mechanical Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA W. Carter Ralph Southern Research Institute, Birmingham, AL, USA K. Ramesh Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India Payam Razavi Center for Holographic Studies and Laser micro-mechaTronics (CHSLT), Worcester Polytechnic Institute, Worcester, MA, USA Mechanical Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA P. L. Reu Sandia National Laboratories, Albuquerque, NM, USA EricRobin Univ Rennes, CNRS, IPR (Institute de Physique de Rennes)–UMR 6251, Rennes, France LC-DRIME, Joint Research Laboratory, Cooper Standard—Institut de Physique UMR 6251, Rennes Cedex, France John J. Rosowski Eaton-Peabody Laboratory, Massachusetts Eye and Ear (MEE), Boston, MA, USA Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA S. Roux LMT, ENS Paris Saclay/CNRS UMR 8535/University Paris Saclay, Cachan, France Benoit Ruellan Univ Rennes, CNRS, IPR (Institute de Physique de Rennes)–UMR 6251, Rennes, France LC-DRIME, Joint Research Laboratory, Cooper Standard—Institut de Physique UMR 6251, Rennes Cedex, France Cooper Standard France, Rennes, France Kasumi Sakai Department of Mechanical Engineering, Aoyama Gakuin University, Sagamihara, Japan Cesar A. Sciammarella Department of Mechanical, Materials and Aerospace Engineering, Illinois Institute of Technology, Chicago, IL, USA Department of Mechanical Engineering, Northern Illinois University, DeKalb, IL, USA Jeremy D. Seidt Department of Mechanical Engineering, The Ohio State University, Scott Laboratory, Columbus, OH, USA Jianguang Shuai Department of Mechanical Engineering of Tsinghua University, Beijing, China T. Siebert Dantec Dynamics GmbH, Ulm, Germany M. Simonsen Correlated Solutions Inc., Columbia, SC, USA Sarthak S. Singh Department of Aerospace Engineering, Indian Institute of Technology, Kanpur, India Christopher M. Smith Berkshire Hathaway Specialty Insurance, Boston, MA, USA Jarrod L. Smith Department of Mechanical Engineering, The Ohio State University, Scott Laboratory, Columbus, OH, USA Karl A. Stetson Karl Stetson Associates, LLC, Coventry, CT, USA Sankara J. Subramanian Department of Engineering Design, Indian Institute of Technology, Madras, Chennai, India F. Sur Université de Lorraine, CNRS, INRIA projet Magrit, Vandoeuvre-lès-Nancy Cedex, France Y. Surrel Engineering and the Environment, University of Southampton, Southampton, UK Yves Surrel Expertise and Consultancy, St-Étienne, France Michael A. Sutton Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA Akifumi Takagi 4D Sensor Inc., Wakayama, Japan Haimi Tang Center for Holographic Studies and Laser micro-mechaTronics (CHSLT), Worcester Polytechnic Institute, Worcester, MA, USA Mechanical Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA Mullai Thiagu Department of Engineering Design, Indian Institute of Technology, Madras, Chennai, India

Contributors xiii E. Toussaint Université Clermont Auvergne, Clermont-Ferrand, France Ang-Ting Tsai Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung, Taiwan D. Turner Sandia National Laboratories, Albuquerque, NM, USA Masaki Ueki 4D Sensor Inc., Wakayama, Japan M. Villone NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale—DICMaPI, University of Naples Federico II, Naples, Italy Timothy Walter U.S. Army Research Laboratory, Weapons and Materials Research Directorate, Adelphi, MD, USA Wei-Chung Wang Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan, Republic of China Z.Wang CNR-ISASI, Istituto di Scienze Applicate e Sistemi Intelligenti “E. Caianiello”, Pozzuoli NA, Italy NEAPoLIS Numerical and Experimental Advanced Program on Liquids and Interface Systems, Naples, Italy Charles Wilson Medtronic, Inc., Minneapolis, MN, USA XinxinWu Collaborative Innovation Center of Advanced Nuclear Energy Technology, The Key Laboratory of Advanced Reactor Engineering and Safety of MOE, Institute of Nuclear and New Energy Technology of Tsinghua University, Beijing, China NanSheng Xu Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA JinYang Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA Satoru Yoneyama Department of Mechanical Engineering, Aoyama Gakuin University, Sagamihara, Japan Yuelin Zhang Department of Mechanical Engineering, Aoyama Gakuin University, Sagamihara, Japan Zhengming Zhang Collaborative Innovation Center of Advanced Nuclear Energy Technology, The Key Laboratory of Advanced Reactor Engineering and Safety of MOE, Institute of Nuclear and New Energy Technology of Tsinghua University, Beijing, China Jiaqing Zhao Collaborative Innovation Center of Advanced Nuclear Energy Technology, The Key Laboratory of Advanced Reactor Engineering and Safety of MOE, Institute of Nuclear and New Energy Technology of Tsinghua University, Beijing, China

Chapter 1 Beyond the Airbrush: Applications of Digital Image Correlation in Vascular Biomechanics Susan M. Lessner and John F. Eberth Abstract Before digital image correlation (DIC) could find widespread application for strain measurement in biological soft tissues, there were a number of technical challenges that had to be addressed. The mechanical behavior of soft tissues depends significantly on hydration state; therefore, both application of a high-contrast speckle pattern and imaging must be achieved while maintaining the specimen in a fully hydrated state. Furthermore, soft tissues such as arteries typically undergo finite deformations under a physiologically relevant loading range. While hydration can be achieved by submerging the sample in a medium having appropriate osmolarity, pH, and ionic strength, imaging submerged objects introduces its own set of challenges due to refractive index changes. The issue of sample hydration also requires consideration of alternative approaches to speckle pattern creation, beyond the classic “airbrush method,” since ideally the specimen must not be allowed to dry out during pattern application. For samples that are submerged, the speckle pattern must be firmly bonded to the specimen and water-resistant, in addition to deforming with the specimen, often outside the small-strain regime. In some specific instances, nature provides a hand through the presence of intrinsic fine-scale structure in the specimen that, with innovative staining or imaging techniques, can serve as a satisfactory “speckle pattern.” Added to these issues is the difficulty of imaging small, often irregularly shaped specimens that can degrade rapidly over time. In collaboration with Dr. Sutton’s group, my colleagues and I have developed a number of approaches to address the issues of hydrating and speckling soft tissues for measurement of local strains in blood vessels at multiple length scales, with a particular focus on the mouse aorta and carotid artery. Keywords Digital image correlation · Soft tissues · Speckle pattern · Artery · Nuclear stain 1.1 Introduction Digital image correlation (DIC) originally was developed at the University of South Carolina in the 1980s as a non-destructive technique to accurately measure small strains and deformations in engineering materials such as metals and ceramics. This technique relies on optically tracking displacements of a random, high-contrast “speckle pattern” on the specimen surface during loading. 1.2 What Is a “Speckle Pattern”? The basic requirements for a “speckle pattern” suitable for DIC are that it be random, high-contrast, and scaled appropriately to the specimen and camera system in use. ‘Randomness’ implies that the pattern within the original subset area and its corresponding image after deformation be uniquely matched in a least squares best-fit sense. Patterns that are too regular in their intensity variation (e.g., a grid of evenly spaced black dots on a white background) or that have too small an intensity range (low contrast) can give rise to non-unique solutions during the matching process. A number of authors have developed analytical criteria for characterizing the quality of speckle patterns [1–4]. The physical size of ‘speckles’ can S. M. Lessner ( ) · J. F. Eberth Department of Cell Biology and Anatomy, University of South Carolina, Columbia, SC, USA e-mail: susan.lessner@uscmed.sc.edu © The Society for Experimental Mechanics, Inc. 2019 L. Lamberti et al. (eds.), Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3, Conference Proceedings of the Society for Experimental Mechanics Series, https://doi.org/10.1007/978-3-319-97481-1_1 1

2 S. M. Lessner and J. F. Eberth vary considerably, but a rule of thumb for optimum tracking of the pattern is to create speckles that cover 3–5 pixels in each direction at the image plane of the camera. Additional considerations in optimizing speckle size based on camera parameters, focal length and desired field of view can be found in [5]. 1.3 Challenges in “Speckling” Soft Tissues In comparison to typical engineering materials, soft biological tissues present a number of challenges in creating a surface speckle pattern suitable for DIC. Perhaps most vexing of these is the issue of maintaining adequate hydration. Human soft tissues range from roughly 25% to somewhat more than 75% water by weight [6], and their mechanical behavior is highly dependent on hydration state. Some water in soft tissues is tightly bound within the extracellular matrix—for example, water molecules associated with highly negatively charged proteoglycans—and its removal leads to collapse of associated matrix architecture. Thus, soft tissue specimens cannot be allowed to dry out completely. Hydration must be maintained during both patterning and imaging, which can be challenging when high intensity lights are used to ensure good image contrast. When possible, performing both patterning and imaging in solution are preferable, but these strategies present their own sets of challenges. Another challenge in speckling soft tissues arises from the large deformations experienced by many of these materials under loading. Elastin-rich tissues such as ligaments and elastic arteries can undergo strains of 50% or more under load and return to their initial dimensions with little obvious damage (i.e., without hysteresis in the loading-unloading curve). Any type of speckle pattern created by coating the specimen, either with paint or with some other film-forming material, must not only deform with the underlying tissue but must also resist delamination, cracking, and wrinkling. 1.4 Some Potential Solutions to Speckle Patterning of Soft Biological Tissues Early applications of DIC to biological specimens focused on hard tissues such as bone and used classic approaches such as airbrush application of black paint to create a suitable speckle pattern. Some pioneering studies of soft tissues [7, 8] also tried this approach with some success, although samples had to be allowed to dry off to some extent to obtain a pattern. The need to maintain tissue hydration can cause smearing or spreading in patterns created using standard inks, dyes, or paints, whether applied by hand or by airbrush. In our first collaborative efforts with Dr. Sutton [9], we used toner powder (3–10 micron, Ricoh) suspended in phosphate-buffered saline (PBS) with the addition of a small amount of surfactant to permit wetting of the hydrophobic powder. This approach provided a high-contrast but somewhat sparse speckle pattern. Unfortunately, there was some tendency for the speckles to wash off as the specimen was rehydrated between image series with a saline drip. As the advantages of DIC for strain and deformation measurements of soft tissues became evident, several groups, including our own, tested a variety of approaches to overcome the challenges of creating robust speckle patterns on these materials. In the first DIC investigation of human aorta mechanics [10], Avril and colleagues created a speckle pattern by hand-gluing a set of 300+spherical black markers to the specimen using fast-drying cyanoacrylate glue. Glues formulated with 2-octyl cyanoacrylate rather than methyl cyanoacrylate have relatively high viscosity, limiting penetration into the tissue, and are used as surgical skin adhesives (e.g., ‘Dermabond’, Ethicon). This method is limited to relatively large specimens and is too time-consuming for analysis of large numbers of specimens. Murphy and colleagues used gold nanorods suspended in a collagen gel to measure deformations associated with fibroblast-mediated remodeling of the matrix [11]. In this study, the gold nanorods were visualized under darkfield microscopy. Gold or silver nanoparticles can also be imaged by crosspolarized incident light microscopy, with the extent of depolarization dependent on particle size and shape [12, 13]. In our own stereo-DIC studies of mouse carotid artery biomechanics, we ultimately settled on using fluorescent nuclear staining as a method to create a random, dense speckle pattern (Fig. 1.1) [14, 15]. To improve the contrast, we filled the vessel lumen with diluted black tissue marking dye. While we chose to use ethidium bromide as a nuclear stain, there are a wide variety of fluorescent DNA-binding dyes that would serve equally well; the choice can be based on available excitation light sources and emission filters. Recent improvements in dye chemistry have also improved quantum yields and reduced photobleaching relative to many ‘classic’ fluorophores. In addition, we developed methods to covalently attach fluorescent microspheres to the adventitial or endothelial surface of mouse blood vessels using carbodiimide chemistry, although ultimately we abandoned this approach in favor of simpler, less time-consuming nuclear staining.

1 Beyond the Airbrush: Applications of Digital Image Correlation in Vascular Biomechanics 3 Fig. 1.1 Speckle pattern created on adventitial surface of mouse carotid artery by fluorescent nuclear staining with ethidium bromide. Vessel diameter is about 300 μm In some fortuitous instances, nature provides an intrinsic pattern in or on the material that proves suitable for DIC image tracking. Pigmentation of the developingXenopus laevis (African clawed frog) embryo is one such example. Some biological materials that lack an obvious pattern under white light imaging may reveal intrinsic surface textures when viewed at specific wavelengths or under suitable imaging modalities. For example, adventitial collagen fibers on the outer surface of large blood vessels are nearly transparent under white light, but they produce a strong second harmonic signal when visualized with coherent light at near-IR wavelengths [16]. 1.5 Conclusion Continuing advances in nanoparticle synthesis, bioconjugate chemistry, optics, and image correlation software have alleviated many of the difficulties originally faced by investigators interested in applying DIC to soft biological tissues, including arteries. References 1. Lecompte, D., Smits, A., Bossuyt, S., Sol, H., Vantomme, J., Van Hemelrijck, D., Habraken, A.: Quality assessment of speckle patterns for digital image correlation. Opt. Lasers Eng. 44, 1132–1145 (2006) 2. Pan, B., Lu, Z., Xie, H.: Mean intensity gradient: an effective global parameter for quality assessment of the speckle patterns used in digital image correlation. Opt. Lasers Eng. 48, 469–477 (2010) 3. Reu, P.L., Miller, T.J., Sutton, M., Wang, Y.: Uncertainty Quantification for Digital Image Correlation. Sandia National Laboratories (SNLNM), Albuquerque, NM (2009) 4. Wang, Y.Q., Sutton, M.A., Bruck, H.A., Schreier, H.W.: Quantitative error assessment in pattern matching: effects of intensity pattern noise, interpolation, strain and image contrast on motion measurements. Strain. 45, 160–178 (2009) 5. Sutton, M.A., Orteu, J.J., Schreier, H.: Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications. Springer, New York, NY (2009) 6. Forbes, R., Cooper, A., Mitchell, H.: The composition of the adult human body as determined by chemical analysis. J. Biol. Chem. 203, 359–366 (1953) 7. Zhang, D., Arola, D.D.: Applications of digital image correlation to biological tissues. J. Biomed. Opt. 9, 691–699 (2004) 8. Zhang, D.S., Eggleton, C.D., Arola, D.D.: Evaluating the mechanical behavior of arterial tissue using digital image correlation. Exp. Mech. 42, 409–416 (2002) 9. Sutton, M.A., Ke, X., Lessner, S.M., Goldbach, M., Yost, M., Zhao, F., Schreier, H.W.: Strain field measurements on mouse carotid arteries using microscopic three-dimensional digital image correlation. J. Biomed. Mater. Res. A. 84, 178–190 (2008) 10. Avril, S., Badel, P., Duprey, A.: Anisotropic and hyperelastic identification of in vitro human arteries from full-field optical measurements. J. Biomech. 43, 2978–2985 (2010) 11. Stone, J.W., Sisco, P.N., Goldsmith, E.C., Baxter, S.C., Murphy, C.J.: Using gold nanorods to probe cell-induced collagen deformation. Nano Lett. 7, 116–119 (2007) 12. Aaron, J., de La Rosa, E., Travis, K., Harrison, N., Burt, J., José-Yacamán, M., Sokolov, K.: Polarization microscopy with stellated gold nanoparticles for robust, in-situ monitoring of biomolecules. Opt. Express. 16, 2153–2167 (2008) 13. Sokolov, K., Follen, M., Aaron, J., Pavlova, I., Malpica, A., Lotan, R., Richards-Kortum, R.: Real-time vital optical imaging of precancer using anti-epidermal growth factor receptor antibodies conjugated to gold nanoparticles. Cancer Res. 63, 1999 (2003)

4 S. M. Lessner and J. F. Eberth 14. Ning, J., Braxton, V.G., Wang, Y., Sutton, M.A., Wang, Y., Lessner, S.M.: Speckle patterning of soft tissues for strain field measurement using digital image correlation: preliminary quality assessment of patterns. Microsc. Microanal. 17, 81–90 (2011) 15. Ning, J., Xu, S., Wang, Y., Lessner, S.M., Sutton, M.A., Anderson, K., Bischoff, J.E.: Deformation measurements and material property estimation of mouse carotid artery using a microstructure-based constitutive model. J. Biomech. Eng. 132, 121010 (2010) 16. Watson, S.R., Lessner, S.M.: (Second) harmonic disharmony: nonlinear microscopy shines new light on the pathology of atherosclerosis. Microsc. Microanal. 22, 589–598 (2016)

Chapter 2 A New Method of Fringe Pattern Analysis C. A. Sciammarella and L. Lamberti Abstract Fringe patterns can be optically generated by the different developed optical methods or computer generated. This study tackles down one of the more difficult aspects of classical fringe pattern analysis, pattern unwrapping. Discontinuous patterns such as the microscopic displacement/strain fields of a particulate composite and shear bands are studied. Keywords Unwrapping of singular fringe patterns · Determination of displacements and strains · Particulate composites · Shear bands 2.1 Introduction In previous papers [1–4], the authors analyzed different aspects of processing displacement information given as scalar functions of gray levels called fringe patterns. These fringe patterns can be optically generated by the different developed optical methods or computer generated for example as it is the case in the magnetic resonance method (MRI). The approach adopted in these papers is the utilization of the Image Analysis Science basic framework supported by the general mathematical theory of transforms. The theory of transforms deals with vector spaces and the selection of a set of basis functions that lead to simplifications of the problem under study. In these papers, different basic concepts in fringe pattern analysis have been discussed within the wider frame work of the General Theory of Signal Analysis. One of the purposes of this paper is to introduce one fundamental aspect of data retrieval that was anticipated in [1] and is elaborated in a more comprehensive way in this paper. This paper tackles down one of the more difficult aspects of classical fringe pattern analysis, pattern unwrapping. This is a subject that has been thoroughly analyzed in the literature of fringe patterns and there is a classical book that deals with the different problems that arise in the interpretation of fringe patterns and different possible solutions for these problems, including algorithms and software that can be applied in different cases [5]. The main difficulty of the process of extracting information, for example from fringes that are related to displacement fields, the object of this publication, is the presence of singularities in the analyzed displacement field. If one has a continuous displacement field with continuous derivatives up to the third order (usual convention in Continuum Mechanics), the isothetic lines, lines of projected displacements (moiré fringes) are either closed lines or they end at the boundaries of the field, never intersecting each other. This is not the case in many of the applications of practical interest in Experimental Mechanics. In some fields of application, the continuity condition is valid only piecewise. For example, to analyze displacement fields in composites it is required the use of tiling of patches of continuous areas that possibly are separated by the presence of microscopic cracks and networks of dislocations. To calculate the displacement/strain values it is important to define the singularities present in a field. In [6], it is shown that in complex fringe patterns it is possible to outline Burger-type circuits with the Burger’s vector equal to the grating pitch. It should be noticed that the Burger’s vector in this case is not a vector in the physical space but in the space of the projected displacements. Consequently, the analysis of patterns to obtain displacements requires a study of all the different fringe dislocations networks present in the field and the possible separation C. A. Sciammarella ( ) Department of Mechanical, Materials and Aerospace Engineering, Illinois Institute of Technology, Chicago, IL, USA Department of Mechanical Engineering, Northern Illinois University, DeKalb, IL, USA e-mail: sciammarella@iit.edu L. Lamberti Dipartimento Meccanica, Matematica e Management, Politecnico di Bari, Bari, Italy © The Society for Experimental Mechanics, Inc. 2019 L. Lamberti et al. (eds.), Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3, Conference Proceedings of the Society for Experimental Mechanics Series, https://doi.org/10.1007/978-3-319-97481-1_2 5

6 C. A. Sciammarella and L. Lamberti of continuous patches. This is not an easy task to fulfill when the fringe patterns have multiple singular points and complex fringe dislocation structures. Complex singular areas cannot be easily handled by self-adapting software and require the intervention of the operator performing the analysis of the singular patterns. 2.2 Concept of Phase Supporting a New Unwrapping Method To understand the new unwrapping method, it is necessary to review some basic concepts on the analysis of fringe patterns. We are analyzing methods that use tagged carriers to obtain displacement information by comparing the initial configuration of a carrier with its final configuration. This comparison includes large displacements that imply the comparison of very different geometries generated in the process of deformation of a body. This becomes feasible because a system of reference is introduced in the observed body [3]. Figure 2.1 shows large deformations of a ring with a system of tagged carriers. Since the tagged carriers can be given a parameter number, it is always possible to compare the initial basic element with its deformed position. A matter of notation, we will be dealing real or complex-valued functions f(x) defined on R2. Ordinary case letters will represent scalar quantities, bold letters will represent vectorial quantities and we will write f(x) or f(x,y), the bold lower case indicating a vector quantity or we will list the low cases x and y, whichever is more convenient in context. There is another important observation, if we write the equation of the displacement in 2D with respect to a Cartesian frame of [1], dT(x) =drb (x) +dr (x) (2.1) In the above equation, dT(x) is the total displacement of a point of R2, drb(x) is the result of a rigid body motion (translation and rotation), dr(x) is the relative motion of points of R2. As shown in [1], it is possible by analyzing a given pattern to separate the absolute motion that requires a reference point of known position with respect to a reference frame and the relative displacements. In the analysis of deformations, one is interested in the relative motions that are composed of deformations plus rigid body rotations. Since the carrier method is insensitive to rigid body translations, the assignment of a Fig. 2.1 Large deformations of a tagged body as a function of a reference parameter (Moiré Analysis of Strain, A. J. Durelli, V. J. Parks)

2 A New Method of Fringe Pattern Analysis 7 Fig. 2.2 (a) Enlarged view of region of pattern shown inb, (b) u pattern carrier in the initial condition parallel to the y-axis zero displacement is done with a criterion that depends on the analyzed problem. This means that is not necessary to perform additional measurements to establish the zero order, as is the case in photoelastic fringes. The displacement information is encoded in a carrier as levels of gray that represent the intensity at a given pixel I(x), a scalar field. A method of decoding the displacement information is to convert the scalar field of gray levels into a vectorial field of intensities I(x) that provide projected displacement vectors. This conversion is achieved using transforms, either the Fourier transform or the Hilbert transform [1–4]. As shown in Fig. 2.1, in the case of 2D a system of orthogonal carriers is required. The reason for this requirement is the mathematical need to define a tensorial field that is built in the mechanics of the continuum. These carriers have axes originally parallel to the coordinate axes. The carriers parallel to the x-axis give the vertical displacements or v-displacements, and the carriers parallel to the y-axis, give the horizontal displacements, or u-displacements plus the first order derivatives as it is going to be documented in this paper. After deformation, the carriers change their trajectories as shown in Fig. 2.2. The symbol ≡indicating the co-axiality of the involved vectors. The carrier originally parallel to the y-axis that provides the projected displacements in x-directions (u displacement) has rotated and at a point of the field the carrier makes an angle θu with the x axis. Locally, is defined a vector u(x) with components ux(x) and uy(x). We need now to review the concept of phase, a pixel function, that in the literature is called local phase. The phase concept is associated with the notion of vector. The definition of local phase or phase at a point for a 1D signal, introduces in the corresponding complex plane one additional dimension to the dimension of the physical plane, in the complex plane one has two dimensions. This notion is a fundamental concept in the Gabor’s analytic signal theory [7], basic starting point of many developments in Signal Analysis and in Optics. There is another concept of phase, the classical one in optics. This concept is the global phase that represents the optical path followed by a recorded wave front from a selected reference point where the phase is assumed to be zero, a selected departure point up to the final value at the point of arrival. The classical definition of phase in optics is an expression that measures distances through an angular variable, dφ(x) = 2πδ (x) p (2.2) where δ(x) is the optical path; p is pitch of a sinusoidal function, unit of measure utilized to evaluate a path length and convert distances into angles. The optical path length of the light arriving at an image is given by, L(x) = S0 0 δ(x)dx (2.3) How these two concepts are connected to each other? Moving from the continuum model to the discrete representation, the global phase is the sum of the local phases [1], φg (x) = j=N j =0 φL(x) (2.4) where φg(x) is the global phase at a pixel N, and φL(x) is the local phase at a given pixel.

8 C. A. Sciammarella and L. Lamberti The classical procedure of unwrapping is based on the concept of global phase, and introduces a problem: the need to secure continuity of the fringe at the end of one full cycle and the beginning of the next cycle. As it has been shown in [1], the addition of the local phases handles all the pixels independently of their position in a cycle. Thus, local phase addition does not need to recognize pixels where one cycle ends and another cycle begins. This feature is very important in the application of tagged carriers in complex patterns including many fringe singularities. The analysis of patterns observed in particulate composites is one important application where singularities can be extremely complex. 2.3 Relationship Between the Precedent Derivations and the Classical Approach for Fringe Pattern Analysis To facilitate the understanding of the paper contents, some of the basic properties of isothetic lines are reviewed. These properties were initially introduced in [8] and are further expanded and summarized in [6]. Figure 2.3 represents an isothetic line of the family u(x), the tangent to the isothetic line whose slope tgαu gives the derivative ∂u/∂x of the displacement u, projection of the gradient vector ∇u(x)on the x-axis, and the cross-derivative ∂u/∂y is the projection of the gradient on the y-axis. It can be seen that the angles θu (see Fig. 2.3) and αu are related, αu =θu + π 2 (2.5) Hence, we get the following relationship, ∂u ∂x = tg αu =−cot g θu (2.6) From Fig. 2.3, the following relationships are valid: tg θu = ∂u ∂y ∂u ∂x (2.7) Also, tg αu =− ∂u ∂x ∂u ∂y (2.8) The negative sign considers the usual convention for the sign of slopes: for α < 90 o, the slopes are positive, for α > 90 o, the slopes are negative. Similar relationships can be derived for the field of the v-displacements. Fig. 2.3 Isothetic line of the u family, gradient vector and the partial derivatives with respect to the coordinate axes

2 A New Method of Fringe Pattern Analysis 9 Fig. 2.4 (a) dSx tangent to a u-isothetic line and vectors associated with this isothetic line; (b) dSy tangent to a v-isothetic line and vectors associated with this isothetic line Fig. 2.5 Resultant displacement vector as a sum of the two projected displacement fields x y 0 ds dsy Ѳd Ѳv Ѳu u v dTx ux uy vy vx dT dTy x It is possible to connect the above derived equations with the more recent developments. In [4], it is proven the validity of the relationships graphically represented in Fig. 2.4 between the vectors that define the light intensity fields and the displacement fields. The vectors Iu(x), the displacement vector u(x), the vector gradient of u(x), and the normal vector to the isothetic line n(x) are all co-axial. Similar properties apply to the fieldv(x), Fig. 2.4b. The connection between the displacement field vector at a pixel and the scalar signal of intensity I(x) that represents light intensity in terms of gray levels is done through the equation, ux (x) = φu (x) 2π p (2.9) The quantity φu(x) 2π is the fringe order n. Since we are speaking of local fringe orders, n is a real number that can take values between 0 and 1, and p is the carrier signal pitch. The first derivatives of the displacement fields can be obtained from Eq. (2.6) if θu is a known quantity and similar equations exist for the displacement v. Figure 2.5 shows the displacement vector at a pixel as the sum of the two component vectors u(x) andv(x) and also as the vectorial addition of the components of these two vectors. The following vectorial equation applies, dT(x) =u(x) +v(x) (2.10) From Eq. (2.10), we have the projection equation dT(x) =[ux +vx] i + uy +vy j (2.11) and tgθd = uy +vy ux +vx (2.12)

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