Research Article An Investigation on the Aggregation and Rheodynamics of Human Red Blood Cells Using High Performance Computations Dong Xu, 1 Chunning Ji, 1 Eldad Avital, 2 Efstathios Kaliviotis, 3 Ante Munjiza, 4 and John Williams 2 1 State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Weijin Road, Tianjin 300072, China 2 School of Engineering & Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK 3 Department of Mechanical Engineering and Materials Science and Engineering, Faculty of Engineering and Technology, Cyprus University of Technology, 45 Kitiou Kyprianou, 3041 Limassol, Cyprus 4 Faculty of Civil Engineering, University of Split, Split, Croatia Correspondence should be addressed to Dong Xu; xudong@tju.edu.cn Received 6 January 2017; Accepted 28 February 2017; Published 4 April 2017 Academic Editor: Dharmendra Tripathi Copyright © 2017 Dong Xu et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Studies on the haemodynamics of human circulation are clinically and scientifcally important. In order to investigate the efect of deformation and aggregation of red blood cells (RBCs) in blood fow, a computational technique has been developed by coupling the interaction between the fuid and the deformable RBCs. Parallelization was carried out for the coupled code and a high speedup was achieved based on a spatial decomposition. In order to verify the code’s capability of simulating RBC deformation and transport, simulations were carried out for a spherical capsule in a microchannel and multiple RBC transport in a Poiseuille fow. RBC transport in a confned tube was also carried out to simulate the peristaltic efects of microvessels. Relatively large-scale simulations were carried out of the motion of 49,512 RBCs in shear fows, which yielded a hematocrit of 45%. Te large-scale feature of the simulation has enabled a macroscale verifcation and investigation of the overall characteristics of RBC aggregations to be carried out. Te results are in excellent agreement with experimental studies and, more specifcally, both the experimental and simulation results show uniform RBC distributions under high shear rates (60–100/s) whereas large aggregations were observed under a lower shear rate of 10/s. 1. Introduction Te red blood cell (RBC, also referred to as erythrocyte) is the most common type of cell occurring in human blood and occupies approximately 45% of the total blood volume for man and 40% for women. RBCs in a healthy state have a biconcave shape with a diameter of 6–8 m and a thickness of about 2 m at the edges and about 1 m at the center [1]. Te RBC aggregation, which is the mechanism that greatly infuences the non-Newtonian properties of blood [2], occurs when the shear forces are low and cells attract each other to form rouleaux (structures resembling coin piles), larger aggregates, and networks of aggregates. RBC aggregation can cause complications in health related issues; therefore, the investigation of deformability and aggregation of RBCs in blood fow can be promising for the better understanding and diagnosis of many diseases in clinical medicine. Due to the complex mechanism of fuid-structure inter- action, the theoretical analysis of RBCs or capsules is difcult and is usually limited to simple geometries and small deformations (Barthes-Biesel, 1980) and an alterna- tive approach—numerical simulation—has attracted much attention. To date, most simulations have tended to target a relatively small number of cells ([3]; Dupin et al., 2006), due to their complex nature. Te intrinsic complexity of biological systems requires a closer combination between experimental and computational approaches ([3, 4], Secomb, 2011). Tis requires large-scale simulations because experiments usually measure the macroscale efects with large quantities of cells [4–7]. So far, most RBC simulations have tended to target a relatively small number of cells [3, 8, 9]. However, it is ofen said that biological systems, such as cells, are “complex Hindawi Scientifica Volume 2017, Article ID 6524156, 10 pages https://doi.org/10.1155/2017/6524156