A parallel implementation of the Stokesian Dynamics method applied to the simulation of colloidal suspensions

A scalable parallel Stokesian Dynamics method for the simulation of colloidal suspensions

Large and complex systems from the EMC point of view are objects that contain different structures requiring individually composed methods for modeling as well as calculation. Automobiles, aircraft, or PCBs with devices are large and complex systems. The paper describes activities that were done to handle automotive EMC problems with computer simulations. A set of methods was compiled to allow, in a first stage, a fast calculation model generation, and, to apply in a second stage with minimum user interaction, accurate and fast multi step hybrid methods. The paper focuses less on the methods themselves, but more on the completeness of the process chain that is required to do successful simulations of automobiles or other large systems.

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

A new Stokesian dynamics (SD) algorithm for Brownian suspensions is presented. The implementation is based on the recently developed accelerated Stokesian dynamics (ASD) simulation method [Sierou and Brady, J. Fluid Mech. 448, 115 (2001)] for non-Brownian particles. As in ASD, the many-body long-range hydrodynamic interactions are computed using fast Fourier transforms, and the resistance matrix is inverted iteratively, in order to keep the computational cost O(N log N). A fast method for computing the Brownian forces acting on the particles is applied by splitting them into near- and far-field contributions to avoid the O(N3) computation of the square root of the full resistance matrix. For the near-field part, representing the forces as a sum of pairwise contributions reduces the cost to O(N); and for the far-field part, a Chebyshev polynomial approximation for the inverse of the square root of the mobility matrix results in an O(N1.25 log N) computational cost. The overall scaling of the method is thus roughly of O(N1.25 log N) and makes possible the simulation of large systems, which are necessary for studying long-time dynamical properties and/or polydispersity effects in colloidal dispersions. In this work the method is applied to study the rheology of concentrated colloidal suspensions, and results are compared with conventional SD. Also, a faster approximate method is presented and its accuracy discussed.

Molecular dynamics simulation is currently a theoretical technique eligible in simulating of a wide range of systems, from soft condensed matter to biological systems. Excellent outcomes have resulted from using this technique; however, the implementation of this approach remains computationally expensive to some extent. Novel computing technologies may help reducing the computational simulation time, particularly, by using Graphical Processing Units (GPUs). Calculations on GPUs make possible to carry out simulations of large and complex molecular systems at a significantly reduced time. In this manuscript, the implementations of measure-preserving geometric integrator in the canonical ensemble coded in Compute Unified Device Architecture (CUDA) language are presented. The performance and validation of our High-throughput Molecular Dynamics (HIMD) code was done by calculating the thermodynamic properties of a Lennard-Jones fluid. From our tested systems, an excellent agreement was achieved with the reported of literature, compared with calculations carried out on Central Processing Units (CPUs). The implementation of the HIMD code performs time integration on Nosé-Hoover chains (NHC) faster in comparison to the NHC method implemented in LAMMPS code tested with one CPU vs one GPU. Along this work, the scope and limitations in performing simulations by using our HIMD code under rigorous statistical thermodynamics in the canonical ensemble are discussed and analyzed.KeywordsMolecular Dynamics (MD)Graphical Processing Units (GPUs)Nosé-Hoover Chains (NHC)Canonical Ensemble (NVT)

This paper discusses a fully decentralized algorithm able to create an adaptive swarm of autonomous mobile robots from the viewpoint of computational physics. To this end, we particularly focus on Stokesian Dynamics method. Simulation results indicate that the proposed algorithm can control the shape of the swarm appropriately according to the current situation without losing the coherence of the swarm.

A colloidal suspension containing a high concentration of metallic nanoparticles (NPs) finds potential applications in flexible electronic printing, nanofluids, healthcare, antifouling coating, and so on. Here, we demonstrate a generic, easily scalable, simple, and contamination-free cryogenic temperature grinding method, which can effectively be used to prepare pristine NPs that can be stabilized in polar liquids in high concentrations. These surfactant-free pristine NPs have been found to remain dispersed in different polar liquids (CH3OH, C2H5OH, glycol, etc.) for weeks. The long-term stability of the NPs in these liquids has been investigated using zeta potential, in situ Fourier transform infrared spectroscopy, indicating electrostatic stabilization for ultrapure, surfactant-free NPs. Furthermore, stabilization of the NPs has been probed with detailed calculations using the Derjaguin Landau Verwey Overbeek theory as well as atomistic molecular dynamics simulation (MD). Experimental measurements along with theoretical calculations categorically indicate that the electrostatic energy is helping these NPs to be stabilized in a polar liquid.

Quantum Monte Carlo (QMC) methods are often used to calculate properties of many body quantum systems. The main cost of many QMC methods, for example the variational Monte Carlo (VMC) method, is in constructing a sequence of Slater matrices and computing the ratios of determinants for successive Slater matrices. Recent work has improved the scaling of constructing Slater matrices for insulators so that the cost of constructing Slater matrices in these systems is now linear in the number of particles, whereas computing determinant ratios remains cubic in the number of particles. With the long term aim of simulating much larger systems, we improve the scaling of computing the determinant ratios in the VMC method for simulating insulators by using preconditioned iterative solvers. The main contribution of this paper is the development of a method to efficiently compute for the Slater matrices a sequence of preconditioners that make the iterative solver converge rapidly. This involves cheap preconditioner updates, an effective reordering strategy, and a cheap method to monitor instability of ILUTP preconditioners. Using the resulting preconditioned iterative solvers to compute determinant ratios of consecutive Slater matrices reduces the scaling of QMC algorithms from O(n^3) per sweep to roughly O(n^2), where n is the number of particles, and a sweep is a sequence of n steps, each attempting to move a distinct particle. We demonstrate experimentally that we can achieve the improved scaling without increasing statistical errors. Our results show that preconditioned iterative solvers can dramatically reduce the cost of VMC for large(r) systems.

Introduction: Previous studies have shown that a Monte Carlo method for the transportations photon beam in medical linear accelerator is a good way. Strip of simulation can be used to measure the dose distribution in phantoms and patients' body. EGSnrc Code is the only code written for use in the field of radiation therapy that has many subset codes that BEAMnrc code is an important one, in which transferred electrons and photons simulation takes place in the head of medical device. DBS technique (Directional Bremsstrahlung Splitting) is a technique that applies a braking radiation in collision. In this study will be discussed to evaluate the effect of this technique on simulation time and particle number of phase-space data and its effect on output spectrum photon beam (6MV) Siemens accelerator Primus model Materials and Methods: : Beginning the geometry of accelerator was stimulated according to its specifications by using the appropriate combination code BEAMnrc. Scoring plane that get phase-space data, in parts of the device such as: target, it was determined the flattening filter by using BEAMDP program to extract their average energy and output spectra in these parts. Also the other side of the research, simulation parameters and output spectra were compared by changing the amount of DBS. Results: Due to the importance of time in fast Mont Carlo, in the simulation with low history of DBS. Considering the time and quality of the spectrum, DBS can be useful. Conclusion: The results show that by changing the number of DBS from 1 to 1000, the amount of simulation time (Elapsed Time) and CPU time and number of particles into phase- space file, respectively have been 7.1, 7 and 36.9 times.

Relationship between the amount of fine particles and the maximum size of flocs in a weight equivalent suspension of quartz and fluorite

Current simulation tools for multibody dynamics are not problem dependent, they use the same modeling process to all cases regardless of their characteristics. In addition, real-time simulation of small multibody systems is achievable by existing simulation tools, however, real-time simulation of large and complex systems is not possible with existing methods. This is a challenge that needs to be addressed before further advances in mechanical simulation with hardware-in-the-loop and man-in-the-loop, as well as virtual prototyping are made possible. This paper addresses the issue of how the modeling process-dependent versus independent coordinates, and descriptor form versus state-space form of the equations of motion-affects the dynamic simulation of multibody systems and how it may be taken into account and added to the concept of intelligent simulation. With this new concept all the factors involved in the simulation process — modeling, equations, solution, etc. — are chosen and combined depending upon the characteristics of the system to be simulated. It is envisioned that this concept will lead to faster and more robust real-time simulators.

Since its development, Stokesian dynamics has been a leading approach for the dynamic simulation of suspensions of particles at arbitrary concentrations with full hydrodynamic interactions. Although developed originally for the simulation of passive particle suspensions, the Stokesian dynamics framework is equally well suited to the analysis and dynamic simulation of suspensions of active particles, as we elucidate here. We show how the reciprocal theorem can be used to formulate the exact dynamics for a suspension of arbitrary active particles, and then show how the Stokesian dynamics method provides a rigorous way to approximate and compute the dynamics of dense active suspensions where many-body hydrodynamic interactions are important.

Brownian Dynamics Simulations of Ferromagnetic Colloidal Dispersions in a Simple Shear Flow

The Monte Carlo method, which has recently been widely used to predict the illuminance distribution of a room arranged in a complicated way with furniture, is an easier algorithm than others and is suited to simulating the various states of lighting in a room. The accuracy of the illuminance distribution calculation is affected by the number of particles that substitute for the luminous flux of the light source and by the number of elements of the room surfaces. Therefore, we investigated the optimal number of the particles and elements considering the CPU time and error rate of the illuminance calculation when a shadow caster assumed to be a worker's head was set at an arbitrary position in a rectangular parallel-piped model room. A new method, which uses the incident particles on the surrounding elements of the calculation point, was developed to decrease the CPU time and calculation error. We examined various reflectances of the room surfaces, positions and diameters of the shadow caster. As a result, using only 1/10 the CPU time of previous methods, we found that the optimal number of particles is five million and the optimal number of elements each surface of a room is 40×40 to 60×60.

Initial noise and quiet start (Q.S.) in electromagnetic particle simulation codes