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Stable and realistic crack pattern generation using a cracking node method

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Abstract

This paper presents a method for simulating surface crack patterns appearing in ceramic glaze, glass, wood and mud. It uses a physically and heuristically combined method to model this type of crack pattern. A stress field is defined heuristically over the triangle mesh of an object. Then, a first-order quasi-static cracking node method (CNM) is used to model deformation. A novel combined stress and energy combined crack criterion is employed to address crack initiation and propagation separately according to physics. Meanwhile, a highest-stress-first rule is applied in crack initiation, and a breadth-first rule is applied in crack propagation. Finally, a local stress relaxation step is employed to evolve the stress field and avoid shattering artifacts. Other related issues are also discussed, such as the elimination of quadrature sub-cells, the prevention of parallel cracks and spurious crack procession. Using this method, a variety of crack patterns observed in the real world can be reproduced by changing a set of parameters. Consequently, our method is robust because the computational mesh is independent of dynamic cracks and has no sliver elements. We evaluate the realism of our results by comparing them with photographs of real-world examples. Further, we demonstrate the controllability of our method by varying different parameters.

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Acknowledgements

The authors are sincerely grateful to the referees and anonymous reviewers for their helpful comments and suggestions. The authors also would like to thank the authors of the original studies included in this analysis. This work was partially supported by the National Natural Science Foundation of China (Grant Nos. 61572078 and 61170203) and Program for New Century Excellent Talents in University (NCET-13-0051) and Beijing Natural Science Foundation (4152027). The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. College of Computer Science and Technology, Beijing Normal University, Beijing, 100875, China

    Juan Zhang, Fuqing Duan, Mingquan Zhou, Xuesong Wang, Zhongke Wu, Youliang Huang, Guoguang Du, Shaolong Liu, Pengbo Zhou & Xiangang Shang

  2. College of Art and Communication, Beijing Normal University, Beijing, 100875, China

    Pengbo Zhou

  3. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Dongcan Jiang

Authors
  1. Juan Zhang
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  2. Fuqing Duan
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  5. Xuesong Wang
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  7. Youliang Huang
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  9. Shaolong Liu
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  10. Pengbo Zhou
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  11. Xiangang Shang
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Corresponding authors

Correspondence to Fuqing Duan or Mingquan Zhou.

Additional information

Juan Zhang received the BS and MS degrees in software engineering from Northwest University, China in 2006 and 2009, respectively. She is a PhD candidate in computer application technology at College of Information Science and Technology, Beijing Normal University, China. Her research interests are computer graphics and virtual reality.

Fuqing Duan received the BS and MS degrees in mathematics from Northwest University, China in 1995 and 1998, respectively, and the PhD degree in pattern recognition from the National Laboratory of Pattern Recognition, China in 2006. He is a professor with the College of Information Science and Technology, Beijing Normal University, China. His current research interests include 3D face reconstruction, skull identification, and machine learning and applications. He has authored more than 80 conference and journal articles on related topics.

Mingquan Zhou is a full professor and PhD student supervisor with the College of Information Science and Technology, Beijing Normal University (BNU), China. He is also the director of Engineering Research Center for Virtual Reality Applications, MOE, China and the director of Key Laboratory of Digital Protection and Virtual Reality for Cultural Heritage, BNU. His research interests are computer graphics and virtual reality.

Dongcan Jiang received the BS degree in computer science and technology fromBeijing Normal University, China in 2014. She is a master student in Department of Computer Science, Peking University, China. Her interests are computer graphics, search engine, and Web mining.

Xuesong Wang received the BS and MS degrees in computer software and theory from Northwest University, China in 1999 and 2002, respectively, and the PhD degree in educational technology from Beijing Normal University, China in 2010. His research interests include image processing, virtual reality, information retrieval, and knowledge engineering.

Zhongke Wu is a full professor and the PhD student supervisor with the College of Information Science and Technology, Beijing Normal University (BNU), China. Prior to joining BNU, he was with Nanyang Technological University, Singapore, the Institute National de Recherche en Informatique et en Automatique, France, the Institute of High Performance Computing, Singapore, and the Institute of Software, Chinese Academy of Sciences, China from 1995 to 2006. His research interests are image processing and computer graphics.

Youliang Huang received the ME degree in computer application technology from Beijing Forestry University, China in 2009. He is a PhD candidate in computer application technology at College of Information Science and Technology, Beijing Normal University, China. His research interests are virtual reality, medical image processing, and biological engineering.

Guoguang Du is a PhD candidate in Beijing Key Laboratory of Digital Protection and Virtual Reality for Cultural Heritage, College of Information Science and Technology, Beijing Normal University, China. His research interests are 3D reconstruction, digital geometry processing, virtual reality, and the application areas mainly focus on the digital protection of cultural heritage.

Shaolong Liu is a PhD candidate in computer application technology at College of Information Science and Technology, Beijing Normal University, Beijing, China. His research interests include virtual reality, human computer interaction, and digital art.

Pengbo Zhou received the MS degree in applied mathematics from University of South Brittany, France in 2010. He is a PhD candidate in computer application technology at College of Information Science and Technology, Beijing Normal University, China. His research interests include image processing and virtual reality.

Xiangang Shang received the ME degree in control engineering and control theory from Shandong University of Science and Technology, China in 2005. He is a PhD candidate in computer application technology at College of Information Science and Technology, Beijing Normal University, China. His research interests include medical image processing and virtual reality.

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Zhang, J., Duan, F., Zhou, M. et al. Stable and realistic crack pattern generation using a cracking node method. Front. Comput. Sci. 12, 777–797 (2018). https://doi.org/10.1007/s11704-016-5511-9

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