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In this paper, static and dynamic properties of the smoothed dissipative particle dynamics (SDPD) method are investigated. We study the effect of method parameters on SDPD fluid properties, such as structure, speed of sound, and transport coefficients, and show that a proper choice of parameters leads to a well-behaved and accurate fluid model. In particular, the speed of sound, the radial distribution function (RDF), shear-thinning of viscosity, the mean-squared displacement ( 〈 R 2 〉 ∝ t ), and the Schmidt number ( S c ∼ O ( 10 3 ) − O ( 10 4 ) ) can be controlled, such that the model exhibits a fluid-like behavior for a wide range of temperatures in simulations. Furthermore, in addition to the consideration of fluid density variations for fluid compressibility, a more challenging test of incompressibility is performed by considering the Poisson ratio and divergence of velocity field in an elongational flow. Finally, as an example of complex-fluid flow, we present the applicability and validity of the SDPD method with an appropriate choice of parameters for the simulation of cellular blood flow in irregular geometries. In conclusion, the results demonstrate that the SDPD method is able to approximate well a nearly incompressible fluid behavior, which includes hydrodynamic interactions and consistent thermal fluctuations, thereby providing, a powerful approach for simulations of complex mesoscopic systems.

Microorganisms naturally move in microstructured fluids. Using the simulation method of multi-particle collision dynamics, we study in two dimensions an undulatory Taylor line swimming in a microchannel and in a cubic lattice of obstacles, which represent simple forms of a microstructured environment. In the microchannel the Taylor line swims at an acute angle along a channel wall with a clearly enhanced swimming speed due to hydrodynamic interactions with the bounding wall. While in a dilute obstacle lattice swimming speed is also enhanced, a dense obstacle lattice gives rise to geometric swimming. This new type of swimming is characterized by a drastically increased swimming speed. Since the Taylor line has to fit into the free space of the obstacle lattice, the swimming speed is close to the phase velocity of the bending wave traveling along the Taylor line. While adjusting its swimming motion within the lattice, the Taylor line chooses a specific swimming direction, which we classify by a lattice vector. When plotting the swimming velocity versus the magnitude of the lattice vector, all our data collapse on a single master curve. Finally, we also report more complex trajectories within the obstacle lattice.

The deformation of red blood cells in microvessels was investigated numerically for various vessel diameters, hematocrits, and shear rates. We simulated blood flow in circular channels with diameters ranging from 9 to 50 μm, hematocrits from 20% to 45%, and shear rates from 20 to 150 s(-1) using a particle-based model with parallel computing. The apparent viscosity predicted by the simulation was in good agreement with previous experimental results. We quantified the deformation of red blood cells as a function of radial position. The numerical results demonstrated that because of the shape transition in response to local shear stress and the wall effect, the radial variation of red blood cell deformation in relatively large microvessels could be classified into three different regions: near-center, middle, and near-wall regions. Effects of the local shear stress and wall varied with vessel diameter, hematocrit, and shear rate.

We developed a numerical method for large-scale simulations of cellular flow in microvessels. We employed a particle method, where all blood components were modeled using a finite number of particles. Red blood cell deformation was modeled by a spring network of membrane particles. A domain decomposition method was used for parallel implementation on distributed memory systems. In a strong scaling test up to 64 CPU cores, we obtained a linear speedup with the number of CPU cores, and demonstrated that our model can simulate O(10 3 ) red blood cells in vessels a few tens of micrometers in diameter. For quantitative validation, we analyzed the Fahraeus effect and the formation of a cell-depleted peripheral layer. Simulations were performed for tube hematocrit ranging from 20 to 45%, and microvessel diameters from 9 to 50 μm. Our numerical results were in good agreement with previous experimental results both for the discharge hematocrit and cell-depleted peripheral layer thickness.

The flagellate Trypanosoma brucei, which causes the sleeping sickness when infecting a mammalian host, goes through an intricate life cycle. It has a rather complex propulsion mechanism and swims in diverse microenvironments. These continuously exert selective pressure, to which the trypanosome adjusts with its architecture and behavior. As a result, the trypanosome assumes a diversity of complex morphotypes during its life cycle. However, although cell biology has detailed form and function of most of them, experimental data on the dynamic behavior and development of most morphotypes is lacking. Here we show that simulation science can predict intermediate cell designs by conducting specific and controlled modifications of an accurate, nature-inspired cell model, which we developed using information from live cell analyses. The cell models account for several important characteristics of the real trypanosomal morphotypes, such as the geometry and elastic properties of the cell body, and their swimming mechanism using an eukaryotic flagellum. We introduce an elastic network model for the cell body, including bending rigidity and simulate swimming in a fluid environment, using the mesoscale simulation technique called multi-particle collision dynamics. The in silico trypanosome of the bloodstream form displays the characteristic in vivo rotational and translational motility pattern that is crucial for survival and virulence in the vertebrate host. Moreover, our model accurately simulates the trypanosome's tumbling and backward motion. We show that the distinctive course of the attached flagellum around the cell body is one important aspect to produce the observed swimming behavior in a viscous fluid, and also required to reach the maximal swimming velocity. Changing details of the flagellar attachment generates less efficient swimmers. We also simulate different morphotypes that occur during the parasite's development in the tsetse fly, and predict a flagellar course we have not been able to measure in experiments so far., Author Summary Typanosoma brucei is a uni-cellular parasite that causes the sleeping sickness, a deadly disease for humans that also occurs in livestock. Injected into the mammalian host by the tsetse fly, the trypanosome travels through the blood stream, where it proliferates, and ultimately can be taken up again by a fly during a bloodmeal. In the tsetse fly, it continues its development with several morphological changes to the cell body plan. During its life cycle, the trypanosome meets different microenvironments, such as the mammalian's bloodstream and the tsetse fly's midgut, proventriculus, foregut, and salivary gland. The cell body of the trypanosome has the shape of a spindle along which an eukaryotic flagellum is attached. We have developed an accurate, in silico model trypanosome using information from live cell analyses. Performing computer simulations, we are able to reproduce all motility patterns of the blood-stream form in typical cell culture medium. Modifying the cell design, we show that the helical course of the flagellar attachment optimizes the trypanosome's swimming speed. We also design trypanosomal morphotypes that occur in the tsetse fly. Simulation science thereby provides an investigative tool to systematically explore the morphologcial diversity during the trypanosome's life cycle even beyond experimental capabilities.