[1] Aarts, P. A., Broek, S. A. van den, Prins, G. W., Kuiken, G. D., Sixma, J. J., Heethaar, R. M.:
Blood platelets are concentrated near the wall and red blood cells, in the center in flowing blood. Arteriosclerosis 8 (1988), 819-824.
DOI 10.1161/01.atv.8.6.819
[2] Affeld, K., Reininger, A. J., Gadischke, J., Grunert, K., Schmidt, S., Thiele, F.:
Fluid mechanics of the stagnation point flow chamber and its platelet deposition. Artif. Organs. 19 (1995), 597-602.
DOI 10.1111/j.1525-1594.1995.tb02387.x
[3] G. Alzetta, D. Arndt, W. Bangerth, V. Boddu, B. Brands, D. Davydov, R. Gassmöller, T. Heister, L. Heltai, K. Kormann, M. Kronbichler, M. Maier, J.-P. Pelteret, B. Turcksin, D. Wells:
The deal.II library, version 9.0. J. Numer. Math. 26 (2018), 173-183.
DOI 10.1515/jnma-2018-0054 |
MR 3893339 |
Zbl 1410.65363
[5] D. Arndt, W. Bangerth, T. C. Clevenger, D. Davydov, M. Fehling, D. Garcia-Sanchez, G. Harper, T. Heister, L. Heltai, M. Kronbichler, R. M. Kynch, M. Maier, J.-P. Pelteret, B. Turcksin, D. Wells:
The deal.II library, version 9.1. J. Numer. Math. 27 (2019), 203-213.
DOI 10.1515/jnma-2019-0064 |
MR 4078181 |
Zbl 07181764
[6] Balay, S, Gropp, W. D., McInnes, L. C., Smith, B. F.:
PETSc: Portable, Extensible Toolkit for Scientific Computation---Toolkit for Advanced Computation. Available at
http://www.mcs.anl.gov/petsc (2018).
[8] Barlas, G.: Multicore and GPU Programming: An Integrated Approach. Morgan Kaufmann Publishers, San Francisco (2015).
[9] Bodnár, T., Fasano, A., Sequeira, A.:
Mathematical models for blood coagulation. Fluid-Structure Interaction and Biomedical Applications T. Bodnár et al. Advances in Mathematical Fluid Mechanics. Birkhäuser/Springer, Basel (2014), 483-569.
DOI 10.1007/978-3-0348-0822-4_7 |
MR 3329023 |
Zbl 1351.76320
[10] Burstedde, C., Wilcox, L. C., Ghattas, O.:
p4est: scalable algorithms for parallel adaptive mesh refinement on forests of octrees. SIAM J. Sci. Comput. 33 (2011), 1103-1133.
DOI 10.1137/100791634 |
MR 2800566 |
Zbl 1230.65106
[11] Casa, L. D. C., Deaton, D. H., Ku, D. N.:
Role of high shear rate in thrombosis. J. Vasc. Surg. 61 (2015), 1068-1080 (2015).
DOI 10.1016/j.jvs.2014.12.050
[13] Colman, R. W., Marder, V. J., Clowes, A. W., George, J. N., Goldhaber, S. Z.: Hemostasis and Thrombosis: Basic Principles and Clinical Practice. Lippincott Williams & Wilkins, Philadelphia (2005).
[17] M. A. Heroux, R. A. Bartlett, V. E. Howle, R. J. Hoekstra, J. J. Hu, T. G. Kolda, R. B. Lehoucq, K. R. Long, R. P. Pawlowski, E. T. Phipps, A. G. Salinger, H. Thornquist, R. S. Tuminaro, J. M. Willenbring, A. Williams, K. S. Stanley:
An overview of the Trilinos project. ACM Trans. Math. Softw. 31 (2005), 397-423.
DOI 10.1145/1089014.1089021 |
MR 2266800 |
Zbl 1136.65354
[19] Karypis, G., Kumar, V.:
MeTis: Unstructured Graph Partitioning and Sparse Matrix Ordering System, Version 4.0. Available at
http://www.cs.umn.edu/ {metis}, 2009.
[20] Key, N. S., Makris, M., Lillicrap, D., eds.:
Practical Hemostasis and Thrombosis. John Wiley, Chichester (2017).
DOI 10.1002/9781118344729
[23] Mohan, A.: Modeling the Growth and Dissolution of Clots in Flowing Blood. PhD Thesis, Texas A&M University, College Station (2005).
[25] Reinders, J.: Intel Threading Building Blocks: Outfitting C++ for Multi-Core Processor Parallelism. O'Reilly, Sebastopol (2007).
[26] Sakariassen, K. S., Orning, L., Turitto, V. T.:
The impact of blood shear rate on arterial thrombus formation. Future Sci. OA 1 (2015), Article ID FSO30.
DOI 10.4155/fso.15.28
[27] Sethian, J. A.:
Level Set Methods and Fast Marching Methods. Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge Monographs on Applied and Computational Mathematics 3. Cambridge University Press, Cambridge (1999).
MR 1700751 |
Zbl 0973.76003
[28] Tokarev, A. A., Butylin, A. A., Ataullakhanov, F. I.:
Platelet adhesion from shear blood flow is controlled by near-wall rebounding collisions with erythrocytes. Biophys. J. 100 (2011), 799-808.
DOI 10.1016/j.bpj.2010.12.3740
[29] Tokarev, A., Sirakov, I., Panasenko, G., Volpert, V., Shnol, E., Butylin, A., Ataullakhanov, F.:
Continuous mathematical model of platelet thrombus formation in blood flow. Russ. J. Numer. Anal. Math. Model. 27 (2012), 191-212.
DOI 10.1515/rnam-2012-0011 |
MR 2910582 |
Zbl 06032989
[31] Weller, F.:
Modeling, Analysis, and Simulation of Thrombosis and Hemostasis: PhD Thesis. Ruprecht-Karls-Universität, Heidelberg (2008).
DOI 10.11588/heidok.00008558
[34] Xu, Z., Chen, N., Shadden, S. C., Marsden, J. E., Kamocka, M. M., Rosen, E. D., Alber, M.:
Study of blood flow impact on growth of thrombi using a multiscale model. Soft Matter 5 (2009), 769-779.
DOI 10.1039/B812429A
[35] Zlobina, K. E., Guria, G. Th.:
Platelet activation risk index as a prognostic thrombosis indicator. Scientific Reports 6 (2016), Article ID 30508.
DOI 10.1038/srep30508