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Dive into the research topics where Yu-Hang Tang is active.

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Featured researches published by Yu-Hang Tang.


Journal of Computational Physics | 2014

Energy-conserving dissipative particle dynamics with temperature-dependent properties

Zhen Li; Yu-Hang Tang; Huan Lei; Bruce Caswell; George Em Karniadakis

The dynamic properties of fluid, including diffusivity and viscosity, are temperature-dependent and can significantly influence the flow dynamics of mesoscopic non-isothermal systems. To capture the correct temperature-dependence of a fluid, an energy-conserving dissipative particle dynamics (eDPD) model is developed by expressing the weighting terms of the dissipative force and the random force as functions of temperature. The diffusivity and viscosity of liquid water at various temperatures ranging from 273 K to 373 K are used as examples for verifying the proposed model. Simulations of a Poiseuille flow and a steady case of heat conduction for reproducing the Fourier law are carried out to validate the present eDPD formulation and the thermal boundary conditions. Results show that the present eDPD model recovers the standard DPD model when isothermal fluid systems are considered. For non-isothermal fluid systems, the present model can predict the diffusivity and viscosity consistent with available experimental data of liquid water at various temperatures. Moreover, an analytical formula for determining the mesoscopic heat friction is proposed. The validity of the formula is confirmed by reproducing the experimental data for Prandtl number of liquid water at various temperatures. The proposed method is demonstrated in water but it can be readily extended to other liquids.


Interface Focus | 2016

Patient-specific blood rheology in sickle-cell anaemia

Xuejin Li; E. Du; Huan Lei; Yu-Hang Tang; Ming Dao; S. Suresh; George Em Karniadakis

Sickle-cell anaemia (SCA) is an inherited blood disorder exhibiting heterogeneous cell morphology and abnormal rheology, especially under hypoxic conditions. By using a multiscale red blood cell (RBC) model with parameters derived from patient-specific data, we present a mesoscopic computational study of the haemodynamic and rheological characteristics of blood from SCA patients with hydroxyurea (HU) treatment (on-HU) and those without HU treatment (off-HU). We determine the shear viscosity of blood in health as well as in different states of disease. Our results suggest that treatment with HU improves or worsens the rheological characteristics of blood in SCA depending on the degree of hypoxia. However, on-HU groups always have higher levels of haematocrit-to-viscosity ratio (HVR) than off-HU groups, indicating that HU can indeed improve the oxygen transport potential of blood. Our patient-specific computational simulations suggest that the HVR level, rather than the shear viscosity of sickle RBC suspensions, may be a more reliable indicator in assessing the response to HU treatment.


Chemical Communications | 2014

Large-scale dissipative particle dynamics simulations of self-assembled amphiphilic systems

Xuejin Li; Yu-Hang Tang; Haojun Liang; George Em Karniadakis

We present large-scale simulation results on the self-assembly of amphiphilic systems in bulk solution and under soft confinement. Self-assembled unilamellar and multilamellar vesicles are formed from amphiphilic molecules in bulk solution. The system is simulated by placing amphiphilic molecules inside large unilamellar vesicles (LUVs) and the dynamic soft confinement-induced self-assembled vesicles are investigated. Moreover, the self-assembly of sickle hemoglobin (HbS) is simulated in a crowded and fluctuating intracellular space and our results demonstrate that the HbS self-assembles into polymer fibers causing the LUV shape to be distorted.


ieee international conference on high performance computing data and analytics | 2015

The in-silico lab-on-a-chip: petascale and high-throughput simulations of microfluidics at cell resolution

Diego Rossinelli; Yu-Hang Tang; Kirill Lykov; Dmitry Alexeev; Massimo Bernaschi; Panagiotis E. Hadjidoukas; Mauro Bisson; Wayne Joubert; Christian Conti; George Em Karniadakis; Massimiliano Fatica; Igor V. Pivkin; Petros Koumoutsakos

We present simulations of blood and cancer cell separation in complex microfluidic channels with subcellular resolution, demonstrating unprecedented time to solution, performing at 65.5% of the available 39.4 PetaInstructions/s in the 18, 688 nodes of the Titan supercomputer. These simulations outperform by one to three orders of magnitude the current state of the art in terms of numbers of simulated cells and computational elements. The computational setup emulates the conditions and the geometric complexity of microfluidic experiments and our results reproduce the experimental findings. These simulations provide sub-micron resolution while accessing time scales relevant to engineering designs. We demonstrate an improvement of up to 45X over competing state-of-the-art solvers, thus establishing the frontiers of simulations by particle based methods. Our simulations redefine the role of computational science for the development of microfluidics -- a technology that is becoming as important to medicine as integrated circuits have been to computers.


Physical Review E | 2016

Analysis of hydrodynamic fluctuations in heterogeneous adjacent multidomains in shear flow.

Xin Bian; Mingge Deng; Yu-Hang Tang; George Em Karniadakis

We analyze hydrodynamic fluctuations of a hybrid simulation under shear flow. The hybrid simulation is based on the Navier-Stokes (NS) equations on one domain and dissipative particle dynamics (DPD) on the other. The two domains overlap, and there is an artificial boundary for each one within the overlapping region. To impose the artificial boundary of the NS solver, a simple spatial-temporal averaging is performed on the DPD simulation. In the artificial boundary of the particle simulation, four popular strategies of constraint dynamics are implemented, namely the Maxwell buffer [Hadjiconstantinou and Patera, Int. J. Mod. Phys. C 08, 967 (1997)], the relaxation dynamics [O’Connell and Thompson, Phys. Rev. E 52, R5792 (1995)], the least constraint dynamics [Nie et al.,J. Fluid Mech. 500, 55 (2004); Werder et al., J. Comput. Phys. 205, 373 (2005)], and the flux imposition [Flekkøy et al., Europhys. Lett. 52, 271 (2000)], to achieve a target mean value given by the NS solver. Going beyond the mean flow field of the hybrid simulations, we investigate the hydrodynamic fluctuations in the DPD domain. Toward that end, we calculate the transversal autocorrelation functions of the fluctuating variables in k space to evaluate the generation, transport, and dissipation of fluctuations in the presence of a hybrid interface. We quantify the unavoidable errors in the fluctuations, due to both the truncation of the domain and the constraint dynamics performed in the artificial boundary. Furthermore, we compare the four methods of constraint dynamics and demonstrate how to reduce the errors in fluctuations. The analysis and findings of this work are directly applicable to other hybrid simulations of fluid flow with thermal fluctuations.


Computer Physics Communications | 2017

GPU-accelerated red blood cells simulations with transport dissipative particle dynamics

Ansel L. Blumers; Yu-Hang Tang; Zhen Li; Xuejin Li; George Em Karniadakis

Mesoscopic numerical simulations provide a unique approach for the quantification of the chemical influences on red blood cell functionalities. The transport Dissipative Particles Dynamics (tDPD) method can lead to such effective multiscale simulations due to its ability to simultaneously capture mesoscopic advection, diffusion, and reaction. In this paper, we present a GPU-accelerated red blood cell simulation package based on a tDPD adaptation of our red blood cell model, which can correctly recover the cell membrane viscosity, elasticity, bending stiffness, and cross-membrane chemical transport. The package essentially processes all computational workloads in parallel by GPU, and it incorporates multi-stream scheduling and non-blocking MPI communications to improve inter-node scalability. Our code is validated for accuracy and compared against the CPU counterpart for speed. Strong scaling and weak scaling are also presented to characterizes scalability. We observe a speedup of 10.1 on one GPU over all 16 cores within a single node, and a weak scaling efficiency of 91% across 256 nodes. The program enables quick-turnaround and high-throughput numerical simulations for investigating chemical-driven red blood cell phenomena and disorders.


Archive | 2017

Dissipative Particle Dynamics: Foundation, Evolution, Implementation, and Applications

Zhen Li; Xin Bian; Xuejin Li; Mingge Deng; Yu-Hang Tang; Bruce Caswell; George Em Karniadakis

Dissipative particle dynamics (DPD) is a particle-based Lagrangian method for simulating dynamic and rheological properties of simple and complex fluids at mesoscopic length and time scales. In this chapter, we present the DPD technique, beginning from its original ad hoc formulation and subsequent theoretical developments. Next, we introduce various extensions of the DPD method that can model non-isothermal processes, diffusion-reaction systems, and ionic fluids. We also present a brief review of programming algorithms for constructing efficient DPD simulation codes as well as existing software packages. Finally, we demonstrate the effectiveness of DPD to solve particle-fluid problems, which may not be tractable by continuum or atomistic approaches.


Journal of Computational Physics | 2018

A dissipative particle dynamics method for arbitrarily complex geometries

Zhen Li; Xin Bian; Yu-Hang Tang; George Em Karniadakis

Dissipative particle dynamics (DPD) is an effective Lagrangian method for modeling complex fluids in the mesoscale regime but so far it has been limited to relatively simple geometries. Here, we formulate a local detection method for DPD involving arbitrarily shaped geometric three-dimensional domains. By introducing an indicator variable of boundary volume fraction (BVF) for each fluid particle, the boundary of arbitrary-shape objects is detected on-the-fly for the moving fluid particles using only the local particle configuration. Therefore, this approach eliminates the need of an analytical description of the boundary and geometry of objects in DPD simulations and makes it possible to load the geometry of a system directly from experimental images or computer-aided designs/drawings. More specifically, the BVF of a fluid particle is defined by the weighted summation over its neighboring particles within a cutoff distance. Wall penetration is inferred from the value of the BVF and prevented by a predictor-corrector algorithm. The no-slip boundary condition is achieved by employing effective dissipative coefficients for liquid-solid interactions. Quantitative evaluations of the new method are performed for the plane Poiseuille flow, the plane Couette flow and the Wannier flow in a cylindrical domain and compared with their corresponding analytical solutions and (high-order) spectral element solution of the Navier–Stokes equations. We verify that the proposed method yields correct no-slip boundary conditions for velocity and generates negligible fluctuations of density and temperature in the vicinity of the wall surface. Moreover, we construct a very complex 3D geometry – the “Brown Pacman” microfluidic device – to explicitly demonstrate how to construct a DPD system with complex geometry directly from loading a graphical image. Subsequently, we simulate the flow of a surfactant solution through this complex microfluidic device using the new method. Its effectiveness is demonstrated by examining the rich dynamics of surfactant micelles, which are flowing around multiple small cylinders and stenotic regions in the microfluidic device without wall penetration. In addition to stationary arbitrary-shape objects, the new method is particularly useful for problems involving moving and deformable boundaries, because it only uses local information of neighboring particles and satisfies the desired boundary conditions on-the-fly.


Computer Physics Communications | 2014

Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications☆

Yu-Hang Tang; George Em Karniadakis


Journal of Computational Physics | 2015

Multiscale Universal Interface

Yu-Hang Tang; Shuhei Kudo; Xin Bian; Zhen Li; George Em Karniadakis

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E. Du

Florida Atlantic University

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