Molecular dynamics simulation has become a powerful tool to deepen the understanding of the radiation damage mechanism of nuclear materials. Extracting point defects, analyzing their diffusion, and visualizing the defect dynamics in atomic simulation data are important, but challenging tasks to understand irradiation behavior. In the past, irradiation defects have been detected using the so-called Wigner–Seitz cell method and analyzed by the statistics of Frenkel pairs. However, traditional analysis modes blur the fine details of defect dynamics. In this paper, we present a visual analysis pipeline for domain scientists to comfortably explore radiation damage simulation data. We couple defect identification, defect clustering, molecule visualization, and tracking graph to form an integrated visual exploration approach. We describe the application of our approach in practice to study defect clustering in Ni–Fe alloy. With our proposed pipeline, defects can be extracted in a robust way, clusters can be visualized with a favorable representation, in-depth data analysis can be setup, and defect dynamics can be demonstrated in greater detail than previously possible.
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Alam A, Khan SN, Wilson BG, Johnson DD (2011) Efficient isoparametric integration over arbitrary space-filling voronoi polyhedra for electronic structure calculations. Phys Rev B 84(4):045105
Bhardwaj U, Sand AE, Warrier M (2020) Classification of clusters in collision cascades. Comput Mater Sci 172:109364
Bonny G, Castin N, Terentyev D (2013) Interatomic potential for studying aging under irradiation in stainless steels: the fe ni cr model alloy. Modell Simul Maters Sci Eng 21(8):5897–5909
Bremer P, Bringa E, Duchaineau M et al (2007) Topological feature extraction and tracking. J Phys Conf Series 78:012007
Bremer P, Weber G, Pascucci V, Day M, Bell J (2010) Analyzing and tracking buring structures in lean premixed hydrogen flames. IEEE Trans Visual Comput Graph 16:248–260
Bremer PT, Weber GH, Tierny J, Pascucci V, Day MS, BBell J (2011) Interactive exploration and analysis of large scale simulations using topology-based data segmentations. IEEE Trans Visual Comput Graph 17(9):1307–1324
Davis M, Efstathiou G, CSF, White SDM (1985) The evolution of large-scale structure in a universe dominated by code dark matter. Astrophys J 292:371–394
Duclos G, Adkins R, Banerjee D, Peterson MS, Varghese M et al (2020) Topological structure and dynamics of three dimensional active nematics. Science 367:1120–1124
Ester M, Kriegel H, Sander J, Xu X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the 2nd international conference on knowledge discovery and data mining, pp 226–231
Gasparotto P, Bochicchio D, Ceriotti M, Pavan GM (2020) Identifying and tracking defects in dynamic supramolecular polymers. J Phys Chem B 124:589–599. https://doi.org/10.1021/acs.jpcb.9b11015
Gonen RR, Gelbard R (2017) Cluster evolution analysis: identification and detection of similar clusters and migration patterns. Exp Syst Appl 83:363–373. https://doi.org/10.1016/j.eswa.2017.04.007
Grottel S, Reina G, Vrabec J, Ertl T (2007) Visual verification and analysis of cluster detection for molecular dynamics. IEEE Trans Visual Comput Graph 13(6):1624–1631. https://doi.org/10.1109/TVCG.2007.70614
Grottel S, Dietrich CA, Comba JLD, Ertl T (2009) Topological extraction and tracking of defects in crystal structures. In: Proceedings of the 3rd workshop on topological methods in data analysis and visualization, Snowbird, UT, pp 167–178, https://doi.org/10.1007/978-3-642-15014-2_14
Guo HQ, Phillips CL, Peterka T, Karpeyev D, Glatz A (2016) Extracting, tracking, and visualizing magnetic flux vortices in 3d complex-valued superconductor simulation data. IEEE Trans Visual Comput Graph 22:827–836. https://doi.org/10.1109/TVCG.2015.2466838
Keys AS, Iacovella CR, Glotzer SC (2011) Characterizing complex particle morphologies through shape matching: descriptors, applications, and algorithms. J Comput Phys 230:6438–6463. https://doi.org/10.1016/j.jcp.2011.04.017
Koch L, Granberg F, Brink T et al (2017) Local segregation versus irradiation effects in high-entropy alloys: steady-state conditions in a driven system. J Appl Phys 122:105106
Kozlíková B, Krone M, Lindow N, Falk M, Baaden M, Baum D, Viola I, Parulek J, Hege HC (2015) Visualization of biomolecular structure: The state of the art. In: EuroVis, https://doi.org/10.2312/eurovisstar.20151112
Laney D, Bremer PT, Mascarenhas A, Miller P, Pascucci V (2006) Understanding the structure of the turbulent mixing layer in hydrodynamic instabilities. IEEE Trans Visual Comput Graph 12:1053–1060. https://doi.org/10.1109/TVCG.2006.186
Liu YN, Ahlgren T, Bukonte L, Nordlund K, Shu X, Yu Y, Li X, Lu G (2013) Mechanism of vacancy formation induced by hydrogen in tungsten. AIP Adv 3:122111
Lorensen WE, Cline HE (1987) Marching cubes: A high resolution 3d surface construction algorithm. In: ACM SIGGRAPH Computer Graphics, New York, NY, pp 163–169, https://doi.org/10.1145/37401.37422
Lukasczyk J, Aldrich G, Steptoe M, Favelier G, Gueunet C, Tierny J, Maciejewski R, Hamann B, Leitte H (2017a) Viscous fingering: a topological visual analytic approach. Appl Mech Mater 869:9–19
Lukasczyk J, Weber G, Maciejewski R, Garth C, Leitte H (2017b) Nested tracking graphs. Comput Graph Forum 36(3):12–22. https://doi.org/10.1111/cgf.13164
Lümmen N, Kraska T (2007) Common neighbour analysis for binary atomic systems. Model Simul Mater Sci Eng 15:319–334. https://doi.org/10.1088/0965-0393/15/3/010
Palla G, Barabasi AL, Vicsek T (2007) Quantifying social group evolution. Nature 446:664. https://doi.org/10.1038/nature05670
Partner HL, Nigmatullin R, Burgermeister T, Pyka K, Keller J, Retzker A, Plenio MB, Mehlstaubler TE (2013) Dynamics of topological defects in ion coulomb crystals. New J Phys 15(10):103013
Patwary MMA, Palsetia D, Agrawal A, et al. (2012) A new scalable parallel dbscan algorithm using the disjoint-set data structure. In: Proc. SC, IEEE, Salt Lake City, UT, https://doi.org/10.1109/SC.2012.9
Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117:1–19. https://doi.org/10.1006/jcph.1995.1039
Reina G, Ertl T (2005) Hardware-accelerated glyphs for mono- and dipoles in molecular dynamics visualization. In: Eurovis, Eurographics Assoc., pp 177–182, https://doi.org/10.2312/VisSym/EuroVis05/177-182
Rycroft CH (2009) Voro++: a three-dimensional Voronoi cell library in C++. Chaos 19:041111
Sauer F, Yu HF, liu Ma K, (2014) Trajectory-based flow feature tracking in joint particle/volume datasets. IEEE Trans Visual Comput Graph 20:2565–2574. https://doi.org/10.1109/TVCG.2014.2346423
Soneda N (2014) Irradiation Embrittlement of Reactor Pressure Vessels (RPVs) in Nuclear Power Plants, first ed. edn. Woodhead Publishing Series in Energy, https://doi.org/10.1016/C2013-0-17428-4
Stukowski A (2010) Visualization and analysis of atomistic simulation data with ovito-the open visualization tool. Model Simul Mater Sci Eng 18(1):015012
Tierny J, Favelier G, Levine JA, Gueunet C, Michaux M (2018) The topology toolkit. IEEE Trans Visual Comput Graph 24(1):832–842. https://doi.org/10.1109/TVCG.2017.2743938
Wei JS, Yu HF, Grout RW, Chen JH, liu Ma K, (2011) Visual analysis of particle behaviors to understand combustion simulations. IEEE Comput Graph Appl 32:22–33. https://doi.org/10.1109/mcg.2011.108
Wigner E, Seitz F (1933) On the constitution of metallic sodium. Physl Rev 43(10):804–810. https://doi.org/10.1103/PhysRev.43.804
Zhu Y, Bridson R (2005) Animating sand as a fluid. ACM Trans Graph 24(3):965–972. https://doi.org/10.1145/1073204.1073298
This work was supported by National Key R&D Program of China [2017YFB0701502] and National Natural Science Fund of China [61403036, 11871109, and 61672003].
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Wu, G., Lin, D., Wang, H. et al. Visual analysis of defect clustering in 3D irradiation damage simulation data. J Vis (2021). https://doi.org/10.1007/s12650-021-00769-9
- Molecular dynamics visualization
- Irradiation damage
- Feature identification
- Clustering analysis