Clustering and phase behaviour of attractive active particles with hydrodynamics.

Science.gov (United States)

Navarro, Ricard Matas; Fielding, Suzanne M

2015-10-14

We simulate clustering, phase separation and hexatic ordering in a monolayered suspension of active squirming disks subject to an attractive Lennard-Jones-like pairwise interaction potential, taking hydrodynamic interactions between the particles fully into account. By comparing the hydrodynamic case with counterpart simulations for passive and active Brownian particles, we elucidate the relative roles of self-propulsion, interparticle attraction, and hydrodynamic interactions in determining clustering and phase behaviour. Even in the presence of an attractive potential, we find that hydrodynamic interactions strongly suppress the motility induced phase separation that might a priori have been expected in a highly active suspension. Instead, we find only a weak tendency for the particles to form stringlike clusters in this regime. At lower activities we demonstrate phase behaviour that is broadly equivalent to that of the counterpart passive system at low temperatures, characterized by regimes of gas-liquid, gas-solid and liquid-solid phase coexistence. In this way, we suggest that a dimensionless quantity representing the level of activity relative to the strength of attraction plays the role of something like an effective non-equilibrium temperature, counterpart to the (dimensionless) true thermodynamic temperature in the passive system. However there are also some important differences from the equilibrium case, most notably with regards the degree of hexatic ordering, which we discuss carefully.

Radioactive Particle Tracking (RPT): The Powerful Industrial Radiotracer Techniques for Hydrodynamics and Flow Visualization Studies

International Nuclear Information System (INIS)

Mohd Amirul Syafiq Mohd Yunos

2016-01-01

Full text: Radioactive particle tracking (RPT) techniques have been widely applied in the field of chemical engineering, especially in hydrodynamics in multiphase reactors. This technique is widely used to monitor the motion of the flow inside a reactor by using a single radioactive particle tracer that is neutrally buoyant with respect to the phase is used as a tracker. The particle moves inside the volume of interest and its positions are determined by an array of scintillation detectors counting in coming photons. Particle position reconstruction algorithms have been traditionally used to map measured counts rate into the coordinates by solving a minimization problem between measured events and calibration data. RPT have been used to validate respective-scale CFD models to partial success. This presentation described an introduction to radioactive particle tracking and summarizing a history of such developments and the current state of this method in Malaysian Nuclear Agency, with a perspective towards the future and how these investigations may help scale-up developments. (author)

An efficient particle Fokker–Planck algorithm for rarefied gas flows

Energy Technology Data Exchange (ETDEWEB)

Gorji, M. Hossein; Jenny, Patrick

2014-04-01

This paper is devoted to the algorithmic improvement and careful analysis of the Fokker–Planck kinetic model derived by Jenny et al. [1] and Gorji et al. [2]. The motivation behind the Fokker–Planck based particle methods is to gain efficiency in low Knudsen rarefied gas flow simulations, where conventional direct simulation Monte Carlo (DSMC) becomes expensive. This can be achieved due to the fact that the resulting model equations are continuous stochastic differential equations in velocity space. Accordingly, the computational particles evolve along independent stochastic paths and thus no collision needs to be calculated. Therefore the computational cost of the solution algorithm becomes independent of the Knudsen number. In the present study, different computational improvements were persuaded in order to augment the method, including an accurate time integration scheme, local time stepping and noise reduction. For assessment of the performance, gas flow around a cylinder and lid driven cavity flow were studied. Convergence rates, accuracy and computational costs were compared with respect to DSMC for a range of Knudsen numbers (from hydrodynamic regime up to above one). In all the considered cases, the model together with the proposed scheme give rise to very efficient yet accurate solution algorithms.

Water Flow Simulation using Smoothed Particle Hydrodynamics (SPH)

Science.gov (United States)

Vu, Bruce; Berg, Jared; Harris, Michael F.

2014-01-01

Simulation of water flow from the rainbird nozzles has been accomplished using the Smoothed Particle Hydrodynamics (SPH). The advantage of using SPH is that no meshing is required, thus the grid quality is no longer an issue and accuracy can be improved.

Stochastic-hydrodynamic model of halo formation in charged particle beams

Directory of Open Access Journals (Sweden)

Nicola Cufaro Petroni

2003-03-01

Full Text Available The formation of the beam halo in charged particle accelerators is studied in the framework of a stochastic-hydrodynamic model for the collective motion of the particle beam. In such a stochastic-hydrodynamic theory the density and the phase of the charged beam obey a set of coupled nonlinear hydrodynamic equations with explicit time-reversal invariance. This leads to a linearized theory that describes the collective dynamics of the beam in terms of a classical Schrödinger equation. Taking into account space-charge effects, we derive a set of coupled nonlinear hydrodynamic equations. These equations define a collective dynamics of self-interacting systems much in the same spirit as in the Gross-Pitaevskii and Landau-Ginzburg theories of the collective dynamics for interacting quantum many-body systems. Self-consistent solutions of the dynamical equations lead to quasistationary beam configurations with enhanced transverse dispersion and transverse emittance growth. In the limit of a frozen space-charge core it is then possible to determine and study the properties of stationary, stable core-plus-halo beam distributions. In this scheme the possible reproduction of the halo after its elimination is a consequence of the stationarity of the transverse distribution which plays the role of an attractor for every other distribution.

Thermo-hydrodynamic lubrication in hydrodynamic bearings

CERN Document Server

Bonneau, Dominique; Souchet, Dominique

2014-01-01

This Series provides the necessary elements to the development and validation of numerical prediction models for hydrodynamic bearings. This book describes the thermo-hydrodynamic and the thermo-elasto-hydrodynamic lubrication. The algorithms are methodically detailed and each section is thoroughly illustrated.

Hydrodynamic interaction of a self-propelling particle with a wall : Comparison between an active Janus particle and a squirmer model.

Science.gov (United States)

Shen, Zaiyi; Würger, Alois; Lintuvuori, Juho S

2018-03-27

Using lattice Boltzmann simulations we study the hydrodynamics of an active spherical particle near a no-slip wall. We develop a computational model for an active Janus particle, by considering different and independent mobilities on the two hemispheres and compare the behaviour to a standard squirmer model. We show that the topology of the far-field hydrodynamic nature of the active Janus particle is similar to the standard squirmer model, but in the near-field the hydrodynamics differ. In order to study how the near-field effects affect the interaction between the particle and a flat wall, we compare the behaviour of a Janus swimmer and a squirmer near a no-slip surface via extensive numerical simulations. Our results show generally a good agreement between these two models, but they reveal some key differences especially with low magnitudes of the squirming parameter [Formula: see text]. Notably the affinity of the particles to be trapped at a surface is increased for the active Janus particles when compared to standard squirmers. Finally, we find that when the particle is trapped on the surface, the velocity parallel to the surface exceeds the bulk swimming speed and scales linearly with [Formula: see text].

Neptune: An astrophysical smooth particle hydrodynamics code for massively parallel computer architectures

Science.gov (United States)

Sandalski, Stou

Smooth particle hydrodynamics is an efficient method for modeling the dynamics of fluids. It is commonly used to simulate astrophysical processes such as binary mergers. We present a newly developed GPU accelerated smooth particle hydrodynamics code for astrophysical simulations. The code is named neptune after the Roman god of water. It is written in OpenMP parallelized C++ and OpenCL and includes octree based hydrodynamic and gravitational acceleration. The design relies on object-oriented methodologies in order to provide a flexible and modular framework that can be easily extended and modified by the user. Several pre-built scenarios for simulating collisions of polytropes and black-hole accretion are provided. The code is released under the MIT Open Source license and publicly available at http://code.google.com/p/neptune-sph/.

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

Science.gov (United States)

Pereira Marinho, Eraldo

2014-03-01

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

International Nuclear Information System (INIS)

Marinho, Eraldo Pereira

2014-01-01

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation

From particle to kinetic and hydrodynamic descriptions of flocking

OpenAIRE

Ha, Seung-Yeal; Tadmor, Eitan

2008-01-01

We discuss the Cucker-Smale's (C-S) particle model for flocking, deriving precise conditions for flocking to occur when pairwise interactions are sufficiently strong long range. We then derive a Vlasov-type kinetic model for the C-S particle model and prove it exhibits time-asymptotic flocking behavior for arbitrary compactly supported initial data. Finally, we introduce a hydrodynamic description of flocking based on the C-S Vlasov-type kinetic model and prove flocking behavior \\emph{without...

Investigation of the hydrodynamic behavior of diatom aggregates using particle image velocimetry.

Science.gov (United States)

Xiao, Feng; Li, Xiaoyan; Lam, Kitming; Wang, Dongsheng

2012-01-01

The hydrodynamic behavior of diatom aggregates has a significant influence on the interactions and flocculation kinetics of algae. However, characterization of the hydrodynamics of diatoms and diatom aggregates in water is rather difficult. In this laboratory study, an advanced visualization technique in particle image velocimetry (PIV) was employed to investigate the hydrodynamic properties of settling diatom aggregates. The experiments were conducted in a settling column filled with a suspension of fluorescent polymeric beads as seed tracers. A laser light sheet was generated by the PIV setup to illuminate a thin vertical planar region in the settling column, while the motions of particles were recorded by a high speed charge-coupled device (CCD) camera. This technique was able to capture the trajectories of the tracers when a diatom aggregate settled through the tracer suspension. The PIV results indicated directly the curvilinear feature of the streamlines around diatom aggregates. The rectilinear collision model largely overestimated the collision areas of the settling particles. Algae aggregates appeared to be highly porous and fractal, which allowed streamlines to penetrate into the aggregate interior. The diatom aggregates have a fluid collection efficiency of 10%-40%. The permeable feature of aggregates can significantly enhance the collisions and flocculation between the aggregates and other small particles including algal cells in water.

Coupling of smooth particle hydrodynamics with the finite element method

International Nuclear Information System (INIS)

Attaway, S.W.; Heinstein, M.W.; Swegle, J.W.

1994-01-01

A gridless technique called smooth particle hydrodynamics (SPH) has been coupled with the transient dynamics finite element code ppercase[pronto]. In this paper, a new weighted residual derivation for the SPH method will be presented, and the methods used to embed SPH within ppercase[pronto] will be outlined. Example SPH ppercase[pronto] calculations will also be presented. One major difficulty associated with the Lagrangian finite element method is modeling materials with no shear strength; for example, gases, fluids and explosive biproducts. Typically, these materials can be modeled for only a short time with a Lagrangian finite element code. Large distortions cause tangling of the mesh, which will eventually lead to numerical difficulties, such as negative element area or ''bow tie'' elements. Remeshing will allow the problem to continue for a short while, but the large distortions can prevent a complete analysis. SPH is a gridless Lagrangian technique. Requiring no mesh, SPH has the potential to model material fracture, large shear flows and penetration. SPH computes the strain rate and the stress divergence based on the nearest neighbors of a particle, which are determined using an efficient particle-sorting technique. Embedding the SPH method within ppercase[pronto] allows part of the problem to be modeled with quadrilateral finite elements, while other parts are modeled with the gridless SPH method. SPH elements are coupled to the quadrilateral elements through a contact-like algorithm. ((orig.))

IUTAM symposium on hydrodynamic diffusion of suspended particles

Energy Technology Data Exchange (ETDEWEB)

Davis, R.H. [ed.

1995-12-31

Hydrodynamic diffusion refers to the fluctuating motion of nonBrownian particles (or droplets or bubbles) which occurs in a dispersion due to multiparticle interactions. For example, in a concentrated sheared suspension, particles do not move along streamlines but instead exhibit fluctuating motions as they tumble around each other. This leads to a net migration of particles down gradients in particle concentration and in shear rate, due to the higher frequency of encounters of a test particle with other particles on the side of the test particle which has higher concentration or shear rate. As another example, suspended particles subject to sedimentation, centrifugation, or fluidization, do not generally move relative to the fluid with a constant velocity, but instead experience diffusion-like fluctuations in velocity due to interactions with neighboring particles and the resulting variation in the microstructure or configuration of the suspended particles. In flowing granular materials, the particles interact through direct collisions or contacts (rather than through the surrounding fluid); these collisions also cause the particles to undergo fluctuating motions characteristic of diffusion processes. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

Smoothed Particle Hydrodynamics Coupled with Radiation Transfer

Science.gov (United States)

Susa, Hajime

2006-04-01

We have constructed a brand-new radiation hydrodynamics solver based upon Smoothed Particle Hydrodynamics, which works on a parallel computer system. The code is designed to investigate the formation and evolution of first-generation objects at z ≳ 10, where the radiative feedback from various sources plays important roles. The code can compute the fraction of chemical species e, H+, H, H-, H2, and H+2 by by fully implicit time integration. It also can deal with multiple sources of ionizing radiation, as well as radiation at Lyman-Werner band. We compare the results for a few test calculations with the results of one-dimensional simulations, in which we find good agreements with each other. We also evaluate the speedup by parallelization, which is found to be almost ideal, as long as the number of sources is comparable to the number of processors.

Assessment of finite element and smoothed particles hydrodynamics methods for modeling serrated chip formation in hardened steel

Directory of Open Access Journals (Sweden)

Usama Umer

2016-05-01

Full Text Available This study aims to perform comparative analyses in modeling serrated chip morphologies using traditional finite element and smoothed particles hydrodynamics methods. Although finite element models are being employed in predicting machining performance variables for the last two decades, many drawbacks and limitations exist with the current finite element models. The problems like excessive mesh distortions, high numerical cost of adaptive meshing techniques, and need of geometric chip separation criteria hinder its practical implementation in metal cutting industries. In this study, a mesh free method, namely, smoothed particles hydrodynamics, is implemented for modeling serrated chip morphology while machining AISI H13 hardened tool steel. The smoothed particles hydrodynamics models are compared with the traditional finite element models, and it has been found that the smoothed particles hydrodynamics models have good capabilities in handling large distortions and do not need any geometric or mesh-based chip separation criterion.

Launch Environment Water Flow Simulations Using Smoothed Particle Hydrodynamics

Science.gov (United States)

Vu, Bruce T.; Berg, Jared J.; Harris, Michael F.; Crespo, Alejandro C.

2015-01-01

This paper describes the use of Smoothed Particle Hydrodynamics (SPH) to simulate the water flow from the rainbird nozzle system used in the sound suppression system during pad abort and nominal launch. The simulations help determine if water from rainbird nozzles will impinge on the rocket nozzles and other sensitive ground support elements.

Numerical simulations of glass impacts using smooth particle hydrodynamics

International Nuclear Information System (INIS)

Mandell, D.A.; Wingate, C.A.

1995-01-01

As part of a program to develop advanced hydrocode design tools, we have implemented a brittle fracture model for glass into the SPHINX smooth particle hydrodynamics code. We have evaluated this model and the code by predicting data from one-dimensional flyer plate impacts into glass. Since fractured glass properties, which are needed in the model, are not available, we did sensitivity studies of these properties, as well as sensitivity studies to determine the number of particles needed in the calculations. The numerical results are in good agreement with the data

Particle swarm genetic algorithm and its application

International Nuclear Information System (INIS)

Liu Chengxiang; Yan Changxiang; Wang Jianjun; Liu Zhenhai

2012-01-01

To solve the problems of slow convergence speed and tendency to fall into the local optimum of the standard particle swarm optimization while dealing with nonlinear constraint optimization problem, a particle swarm genetic algorithm is designed. The proposed algorithm adopts feasibility principle handles constraint conditions and avoids the difficulty of penalty function method in selecting punishment factor, generates initial feasible group randomly, which accelerates particle swarm convergence speed, and introduces genetic algorithm crossover and mutation strategy to avoid particle swarm falls into the local optimum Through the optimization calculation of the typical test functions, the results show that particle swarm genetic algorithm has better optimized performance. The algorithm is applied in nuclear power plant optimization, and the optimization results are significantly. (authors)

A Coulomb collision algorithm for weighted particle simulations

Science.gov (United States)

Miller, Ronald H.; Combi, Michael R.

1994-01-01

A binary Coulomb collision algorithm is developed for weighted particle simulations employing Monte Carlo techniques. Charged particles within a given spatial grid cell are pair-wise scattered, explicitly conserving momentum and implicitly conserving energy. A similar algorithm developed by Takizuka and Abe (1977) conserves momentum and energy provided the particles are unweighted (each particle representing equal fractions of the total particle density). If applied as is to simulations incorporating weighted particles, the plasma temperatures equilibrate to an incorrect temperature, as compared to theory. Using the appropriate pairing statistics, a Coulomb collision algorithm is developed for weighted particles. The algorithm conserves energy and momentum and produces the appropriate relaxation time scales as compared to theoretical predictions. Such an algorithm is necessary for future work studying self-consistent multi-species kinetic transport.

Hydrodynamic limit of a nongradient interacting particle process

International Nuclear Information System (INIS)

Wick, W.D.

1989-01-01

A simple example of a nongradient stochastic interacting particle system is analyzed. In this model, symmetric simple exclusion in one dimension in a periodic environment, the dynamical term in the Green-Kubo formula contributes to the bulk diffusion constant. The law of large numbers for the density field and the central limit theorem for the density fluctuation field are proven, and the Green-Kubo expression for the diffusion constant is computed exactly. The hydrodynamic equation for the model turns out to be linear

The RAGE radiation-hydrodynamic code

International Nuclear Information System (INIS)

Gittings, Michael; Clover, Michael; Betlach, Thomas; Byrne, Nelson; Ranta, Dale; Weaver, Robert; Coker, Robert; Dendy, Edward; Hueckstaedt, Robert; New, Kim; Oakes, W Rob; Stefan, Ryan

2008-01-01

We describe RAGE, the 'radiation adaptive grid Eulerian' radiation-hydrodynamics code, including its data structures, its parallelization strategy and performance, its hydrodynamic algorithm(s), its (gray) radiation diffusion algorithm, and some of the considerable amount of verification and validation efforts. The hydrodynamics is a basic Godunov solver, to which we have made significant improvements to increase the advection algorithm's robustness and to converge stiffnesses in the equation of state. Similarly, the radiation transport is a basic gray diffusion, but our treatment of the radiation-material coupling, wherein we converge nonlinearities in a novel manner to allow larger timesteps and more robust behavior, can be applied to any multi-group transport algorithm

A generalized transport-velocity formulation for smoothed particle hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Zhang, Chi; Hu, Xiangyu Y., E-mail: xiangyu.hu@tum.de; Adams, Nikolaus A.

2017-05-15

The standard smoothed particle hydrodynamics (SPH) method suffers from tensile instability. In fluid-dynamics simulations this instability leads to particle clumping and void regions when negative pressure occurs. In solid-dynamics simulations, it results in unphysical structure fragmentation. In this work the transport-velocity formulation of Adami et al. (2013) is generalized for providing a solution of this long-standing problem. Other than imposing a global background pressure, a variable background pressure is used to modify the particle transport velocity and eliminate the tensile instability completely. Furthermore, such a modification is localized by defining a shortened smoothing length. The generalized formulation is suitable for fluid and solid materials with and without free surfaces. The results of extensive numerical tests on both fluid and solid dynamics problems indicate that the new method provides a unified approach for multi-physics SPH simulations.

The RAGE radiation-hydrodynamic code

Energy Technology Data Exchange (ETDEWEB)

Gittings, Michael; Clover, Michael; Betlach, Thomas; Byrne, Nelson; Ranta, Dale [Science Applications International Corp. MS A-1, 10260 Campus Point Drive, San Diego, CA 92121 (United States); Weaver, Robert; Coker, Robert; Dendy, Edward; Hueckstaedt, Robert; New, Kim; Oakes, W Rob [Los Alamos National Laboratory, MS T087, PO Box 1663, Los Alamos, NM 87545 (United States); Stefan, Ryan [TaylorMade-adidas Golf, 5545 Fermi Court, Carlsbad, CA 92008-7324 (United States)], E-mail: michael.r.clover@saic.com

2008-10-01

We describe RAGE, the 'radiation adaptive grid Eulerian' radiation-hydrodynamics code, including its data structures, its parallelization strategy and performance, its hydrodynamic algorithm(s), its (gray) radiation diffusion algorithm, and some of the considerable amount of verification and validation efforts. The hydrodynamics is a basic Godunov solver, to which we have made significant improvements to increase the advection algorithm's robustness and to converge stiffnesses in the equation of state. Similarly, the radiation transport is a basic gray diffusion, but our treatment of the radiation-material coupling, wherein we converge nonlinearities in a novel manner to allow larger timesteps and more robust behavior, can be applied to any multi-group transport algorithm.

A multi-frame particle tracking algorithm robust against input noise

International Nuclear Information System (INIS)

Li, Dongning; Zhang, Yuanhui; Sun, Yigang; Yan, Wei

2008-01-01

The performance of a particle tracking algorithm which detects particle trajectories from discretely recorded particle positions could be substantially hindered by the input noise. In this paper, a particle tracking algorithm is developed which is robust against input noise. This algorithm employs the regression method instead of the extrapolation method usually employed by existing algorithms to predict future particle positions. If a trajectory cannot be linked to a particle at a frame, the algorithm can still proceed by trying to find a candidate at the next frame. The connectivity of tracked trajectories is inspected to remove the false ones. The algorithm is validated with synthetic data. The result shows that the algorithm is superior to traditional algorithms in the aspect of tracking long trajectories

Hydrodynamic Impacts on Dissolution, Transport and Absorption from Thousands of Drug Particles Moving within the Intestines

Science.gov (United States)

Behafarid, Farhad; Brasseur, James G.

2017-11-01

Following tablet disintegration, clouds of drug particles 5-200 μm in diameter pass through the intestines where drug molecules are absorbed into the blood. Release rate depends on particle size, drug solubility, local drug concentration and the hydrodynamic environment driven by patterned gut contractions. To analyze the dynamics underlying drug release and absorption, we use a 3D lattice Boltzmann model of the velocity and concentration fields driven by peristaltic contractions in vivo, combined with a mathematical model of dissolution-rate from each drug particle transported through the grid. The model is empirically extended for hydrodynamic enhancements to release rate by local convection and shear-rate, and incorporates heterogeneity in bulk concentration. Drug dosage and solubility are systematically varied along with peristaltic wave speed and volume. We predict large hydrodynamic enhancements (35-65%) from local shear-rate with minimal enhancement from convection. With high permeability boundary conditions, a quasi-equilibrium balance between release and absorption is established with volume and wave-speed dependent transport time scale, after an initial transient and before a final period of dissolution/absorption. Supported by FDA.

Smoothed particle hydrodynamic simulations of expanding HII regions

Science.gov (United States)

Bisbas, Thomas G.

2009-09-01

This thesis deals with numerical simulations of expanding ionized regions, known as HII regions. We implement a new three dimensional algorithm in Smoothed Particle Hydrodynamics for including the dynamical effects of the interaction between ionizing radiation and the interstellar medium. This interaction plays a crucial role in star formation at all epochs. We study the influence of ionizing radiation in spherically symmetric clouds. In particular, we study the spherically symmetric expansion of an HII region inside a uniform-density, non-self-gravitating cloud. We examine the ability of our algorithm to reproduce the known theoretical solution and we find that the agreement is very good. We also study the spherically symmetric expansion inside a uniform-density, self-gravitating cloud. We propose a new differential equation of motion for the expanding shell that includes the effects of gravity. Comparing its numerical solution with the simulations, we find that the equation predicts the position of the shell accurately. We also study the expansion of an off-centre HII region inside a uniform-density, non- self-gravitating cloud. This results in an evolution known as the rocket effect, where the ionizing radiation pushes and accelerates the cloud away from the exciting star leading to its dispersal. During this evolution, cometary knots appear as a result of Rayleigh-Taylor and Vishniac instabilities. The knots are composed of a dense head with a conic tail behind them, a structure that points towards the ionizing source. Our simulations show that these knots are very reminiscent of the observed structures in planetary nebula, such as in the Helix nebula. The last part of this thesis is dedicated to the study of cores ionized by an exciting source which is placed outside and far away from them. The evolution of these cores is known as radiation driven compression (or implosion). We perform simulations and compare our findings with results of other workers and we

Fast algorithm for two-dimensional data table use in hydrodynamic and radiative-transfer codes

International Nuclear Information System (INIS)

Slattery, W.L.; Spangenberg, W.H.

1982-01-01

A fast algorithm for finding interpolated atomic data in irregular two-dimensional tables with differing materials is described. The algorithm is tested in a hydrodynamic/radiative transfer code and shown to be of comparable speed to interpolation in regularly spaced tables, which require no table search. The concepts presented are expected to have application in any situation with irregular vector lengths. Also, the procedures that were rejected either because they were too slow or because they involved too much assembly coding are described

Smoothed particle hydrodynamics model for phase separating fluid mixtures. I. General equations

NARCIS (Netherlands)

Thieulot, C; Janssen, LPBM; Espanol, P

We present a thermodynamically consistent discrete fluid particle model for the simulation of a recently proposed set of hydrodynamic equations for a phase separating van der Waals fluid mixture [P. Espanol and C.A.P. Thieulot, J. Chem. Phys. 118, 9109 (2003)]. The discrete model is formulated by

Concatenating algorithms for parallel numerical simulations coupling radiation hydrodynamics with neutron transport

International Nuclear Information System (INIS)

Mo Zeyao

2004-11-01

Multiphysics parallel numerical simulations are usually essential to simplify researches on complex physical phenomena in which several physics are tightly coupled. It is very important on how to concatenate those coupled physics for fully scalable parallel simulation. Meanwhile, three objectives should be balanced, the first is efficient data transfer among simulations, the second and the third are efficient parallel executions and simultaneously developments of those simulation codes. Two concatenating algorithms for multiphysics parallel numerical simulations coupling radiation hydrodynamics with neutron transport on unstructured grid are presented. The first algorithm, Fully Loosely Concatenation (FLC), focuses on the independence of code development and the independence running with optimal performance of code. The second algorithm. Two Level Tightly Concatenation (TLTC), focuses on the optimal tradeoffs among above three objectives. Theoretical analyses for communicational complexity and parallel numerical experiments on hundreds of processors on two parallel machines have showed that these two algorithms are efficient and can be generalized to other multiphysics parallel numerical simulations. In especial, algorithm TLTC is linearly scalable and has achieved the optimal parallel performance. (authors)

A Novel Particle Swarm Optimization Algorithm for Global Optimization.

Science.gov (United States)

Wang, Chun-Feng; Liu, Kui

2016-01-01

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms.

Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

OpenAIRE

Yumin, Dong; Li, Zhao

2014-01-01

Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the a...

Single Particle Optical Sizing (SPOS). II. Hydrodynamic forces and application to aggregating dispersions.

NARCIS (Netherlands)

Pelssers, E.G.M.; Cohen Stuart, M.A.; Fleer, G.J.

1990-01-01

The shear and extension forces occurring during the hydrodynamic focusing in our SPOS instrument which is described in the preceding paper ([1.]), are analyzed and compared with estimates for the binding forces between particles in salt coagulation and polymer flocculation. It is found that the

Thermal Fluctuations in Smooth Dissipative Particle Dynamics simulation of mesoscopic thermal systems

Science.gov (United States)

Gatsonis, Nikolaos; Yang, Jun

2013-11-01

The SDPD-DV is implemented in our work for arbitrary 3D wall bounded geometries. The particle position and momentum equations are integrated with a velocity-Verlet algorithm and the entropy equation is integrated with a Runge-Kutta algorithm. Simulations of nitrogen gas are performed to evaluate the effects of timestep and particle scale on temperature, self-diffusion coefficient and shear viscosity. The hydrodynamic fluctuations in temperature, density, pressure and velocity from the SDPD-DV simulations are evaluated and compared with theoretical predictions. Steady planar thermal Couette flows are simulated and compared with analytical solutions. Simulations cover the hydrodynamic and mesocopic regime and show thermal fluctuations and their dependence on particle size.

Smoothed-particle-hydrodynamics modeling of dissipation mechanisms in gravity waves.

Science.gov (United States)

Colagrossi, Andrea; Souto-Iglesias, Antonio; Antuono, Matteo; Marrone, Salvatore

2013-02-01

The smoothed-particle-hydrodynamics (SPH) method has been used to study the evolution of free-surface Newtonian viscous flows specifically focusing on dissipation mechanisms in gravity waves. The numerical results have been compared with an analytical solution of the linearized Navier-Stokes equations for Reynolds numbers in the range 50-5000. We found that a correct choice of the number of neighboring particles is of fundamental importance in order to obtain convergence towards the analytical solution. This number has to increase with higher Reynolds numbers in order to prevent the onset of spurious vorticity inside the bulk of the fluid, leading to an unphysical overdamping of the wave amplitude. This generation of spurious vorticity strongly depends on the specific kernel function used in the SPH model.

Brownian dynamics with hydrodynamic interactions

International Nuclear Information System (INIS)

Ermak, D.L.; McCammon, J.A.

1978-01-01

A method for simulating the Brownian dynamics of N particles with the inclusion of hydrodynamic interactions is described. The particles may also be subject to the usual interparticle or external forces (e.g., electrostatic) which have been included in previous methods for simulating Brownian dynamics of particles in the absence of hydrodynamic interactions. The present method is derived from the Langevin equations for the N particle assembly, and the results are shown to be consistent with the corresponding Fokker--Planck results. Sample calculations on small systems illustrate the importance of including hydrodynamic interactions in Brownian dynamics simulations. The method should be useful for simulation studies of diffusion limited reactions, polymer dynamics, protein folding, particle coagulation, and other phenomena in solution

A dynamic global and local combined particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Chen Qunxian

2009-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems, but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems.

Weighted Flow Algorithms (WFA) for stochastic particle coagulation

International Nuclear Information System (INIS)

DeVille, R.E.L.; Riemer, N.; West, M.

2011-01-01

Stochastic particle-resolved methods are a useful way to compute the time evolution of the multi-dimensional size distribution of atmospheric aerosol particles. An effective approach to improve the efficiency of such models is the use of weighted computational particles. Here we introduce particle weighting functions that are power laws in particle size to the recently-developed particle-resolved model PartMC-MOSAIC and present the mathematical formalism of these Weighted Flow Algorithms (WFA) for particle coagulation and growth. We apply this to an urban plume scenario that simulates a particle population undergoing emission of different particle types, dilution, coagulation and aerosol chemistry along a Lagrangian trajectory. We quantify the performance of the Weighted Flow Algorithm for number and mass-based quantities of relevance for atmospheric sciences applications.

Weighted Flow Algorithms (WFA) for stochastic particle coagulation

Science.gov (United States)

DeVille, R. E. L.; Riemer, N.; West, M.

2011-09-01

Stochastic particle-resolved methods are a useful way to compute the time evolution of the multi-dimensional size distribution of atmospheric aerosol particles. An effective approach to improve the efficiency of such models is the use of weighted computational particles. Here we introduce particle weighting functions that are power laws in particle size to the recently-developed particle-resolved model PartMC-MOSAIC and present the mathematical formalism of these Weighted Flow Algorithms (WFA) for particle coagulation and growth. We apply this to an urban plume scenario that simulates a particle population undergoing emission of different particle types, dilution, coagulation and aerosol chemistry along a Lagrangian trajectory. We quantify the performance of the Weighted Flow Algorithm for number and mass-based quantities of relevance for atmospheric sciences applications.

High-throughput particle manipulation by hydrodynamic, electrokinetic, and dielectrophoretic effects in an integrated microfluidic chip

KAUST Repository

Li, Shunbo; Li, Ming; Bougot-Robin, Kristelle; Cao, Wenbin; Yeung Yeung Chau, Irene; Li, Weihua; Wen, Weijia

2013-01-01

Integrating different steps on a chip for cell manipulations and sample preparation is of foremost importance to fully take advantage of microfluidic possibilities, and therefore make tests faster, cheaper and more accurate. We demonstrated particle manipulation in an integrated microfluidic device by applying hydrodynamic, electroosmotic (EO), electrophoretic (EP), and dielectrophoretic (DEP) forces. The process involves generation of fluid flow by pressure difference, particle trapping by DEP force, and particle redirect by EO and EP forces. Both DC and AC signals were applied, taking advantages of DC EP, EO and AC DEP for on-chip particle manipulation. Since different types of particles respond differently to these signals, variations of DC and AC signals are capable to handle complex and highly variable colloidal and biological samples. The proposed technique can operate in a high-throughput manner with thirteen independent channels in radial directions for enrichment and separation in microfluidic chip. We evaluated our approach by collecting Polystyrene particles, yeast cells, and E. coli bacteria, which respond differently to electric field gradient. Live and dead yeast cells were separated successfully, validating the capability of our device to separate highly similar cells. Our results showed that this technique could achieve fast pre-concentration of colloidal particles and cells and separation of cells depending on their vitality. Hydrodynamic, DC electrophoretic and DC electroosmotic forces were used together instead of syringe pump to achieve sufficient fluid flow and particle mobility for particle trapping and sorting. By eliminating bulky mechanical pumps, this new technique has wide applications for in situ detection and analysis.

High-throughput particle manipulation by hydrodynamic, electrokinetic, and dielectrophoretic effects in an integrated microfluidic chip

KAUST Repository

Li, Shunbo

2013-03-20

Integrating different steps on a chip for cell manipulations and sample preparation is of foremost importance to fully take advantage of microfluidic possibilities, and therefore make tests faster, cheaper and more accurate. We demonstrated particle manipulation in an integrated microfluidic device by applying hydrodynamic, electroosmotic (EO), electrophoretic (EP), and dielectrophoretic (DEP) forces. The process involves generation of fluid flow by pressure difference, particle trapping by DEP force, and particle redirect by EO and EP forces. Both DC and AC signals were applied, taking advantages of DC EP, EO and AC DEP for on-chip particle manipulation. Since different types of particles respond differently to these signals, variations of DC and AC signals are capable to handle complex and highly variable colloidal and biological samples. The proposed technique can operate in a high-throughput manner with thirteen independent channels in radial directions for enrichment and separation in microfluidic chip. We evaluated our approach by collecting Polystyrene particles, yeast cells, and E. coli bacteria, which respond differently to electric field gradient. Live and dead yeast cells were separated successfully, validating the capability of our device to separate highly similar cells. Our results showed that this technique could achieve fast pre-concentration of colloidal particles and cells and separation of cells depending on their vitality. Hydrodynamic, DC electrophoretic and DC electroosmotic forces were used together instead of syringe pump to achieve sufficient fluid flow and particle mobility for particle trapping and sorting. By eliminating bulky mechanical pumps, this new technique has wide applications for in situ detection and analysis.

Partially linearized algorithms in gyrokinetic particle simulation

Energy Technology Data Exchange (ETDEWEB)

Dimits, A.M.; Lee, W.W.

1990-10-01

In this paper, particle simulation algorithms with time-varying weights for the gyrokinetic Vlasov-Poisson system have been developed. The primary purpose is to use them for the removal of the selected nonlinearities in the simulation of gradient-driven microturbulence so that the relative importance of the various nonlinear effects can be assessed. It is hoped that the use of these procedures will result in a better understanding of the transport mechanisms and scaling in tokamaks. Another application of these algorithms is for the improvement of the numerical properties of the simulation plasma. For instance, implementations of such algorithms (1) enable us to suppress the intrinsic numerical noise in the simulation, and (2) also make it possible to regulate the weights of the fast-moving particles and, in turn, to eliminate the associated high frequency oscillations. Examples of their application to drift-type instabilities in slab geometry are given. We note that the work reported here represents the first successful use of the weighted algorithms in particle codes for the nonlinear simulation of plasmas.

Partially linearized algorithms in gyrokinetic particle simulation

International Nuclear Information System (INIS)

Dimits, A.M.; Lee, W.W.

1990-10-01

In this paper, particle simulation algorithms with time-varying weights for the gyrokinetic Vlasov-Poisson system have been developed. The primary purpose is to use them for the removal of the selected nonlinearities in the simulation of gradient-driven microturbulence so that the relative importance of the various nonlinear effects can be assessed. It is hoped that the use of these procedures will result in a better understanding of the transport mechanisms and scaling in tokamaks. Another application of these algorithms is for the improvement of the numerical properties of the simulation plasma. For instance, implementations of such algorithms (1) enable us to suppress the intrinsic numerical noise in the simulation, and (2) also make it possible to regulate the weights of the fast-moving particles and, in turn, to eliminate the associated high frequency oscillations. Examples of their application to drift-type instabilities in slab geometry are given. We note that the work reported here represents the first successful use of the weighted algorithms in particle codes for the nonlinear simulation of plasmas

Identification of hydrodynamic forces around 3D surrogates using particle image velocimetry in a microfluidic channel

Science.gov (United States)

Afshar, Sepideh; Nath, Shubhankar; Demirci, Utkan; Hasan, Tayyaba; Scarcelli, Giuliano; Rizvi, Imran; Franco, Walfre

2018-02-01

Previous studies have demonstrated that flow-induced shear stress induces a motile and aggressive tumor phenotype in a microfluidic model of 3D ovarian cancer. However, the magnitude and distribution of the hydrodynamic forces that influence this biological modulation on the 3D cancer nodules are not known. We have developed a series of numerical and experimental tools to identify these forces within a 3D microchannel. In this work, we used particle image velocimetry (PIV) to find the velocity profile using fluorescent micro-spheres as surrogates and nano-particles as tracers, from which hydrodynamic forces can be derived. The fluid velocity is obtained by imaging the trajectory of a range of florescence nano-particles (500-800 μm) via confocal microscopy. Imaging was done at different horizontal planes and with a 50 μm bead as the surrogate. For an inlet current rate of 2 μl/s, the maximum velocity at the center of the channel was 51 μm/s. The velocity profile around the sphere was symmetric which is expected since the flow is dominated by viscous forces as opposed to inertial forces. The confocal PIV was successfully employed in finding the velocity profile in a microchannel with a nodule surrogate; therefore, it seems feasible to use PIV to investigate the hydrodynamic forces around 3D biological models.

A Synchronous-Asynchronous Particle Swarm Optimisation Algorithm

Science.gov (United States)

Ab Aziz, Nor Azlina; Mubin, Marizan; Mohamad, Mohd Saberi; Ab Aziz, Kamarulzaman

2014-01-01

In the original particle swarm optimisation (PSO) algorithm, the particles' velocities and positions are updated after the whole swarm performance is evaluated. This algorithm is also known as synchronous PSO (S-PSO). The strength of this update method is in the exploitation of the information. Asynchronous update PSO (A-PSO) has been proposed as an alternative to S-PSO. A particle in A-PSO updates its velocity and position as soon as its own performance has been evaluated. Hence, particles are updated using partial information, leading to stronger exploration. In this paper, we attempt to improve PSO by merging both update methods to utilise the strengths of both methods. The proposed synchronous-asynchronous PSO (SA-PSO) algorithm divides the particles into smaller groups. The best member of a group and the swarm's best are chosen to lead the search. Members within a group are updated synchronously, while the groups themselves are asynchronously updated. Five well-known unimodal functions, four multimodal functions, and a real world optimisation problem are used to study the performance of SA-PSO, which is compared with the performances of S-PSO and A-PSO. The results are statistically analysed and show that the proposed SA-PSO has performed consistently well. PMID:25121109

Hydrodynamic and thermal modelling of gas-particle flow in fluidized beds

International Nuclear Information System (INIS)

Abdelkawi, O.S; Abdalla, A.M.; Atwan, E.F; Abdelmonem, S.A.; Elshazly, K.M.

2009-01-01

In this study a mathematical model has been developed to simulate two dimensional fluidized bed with uniform fluidization. The model consists of two sub models for hydrodynamic and thermal behavior of fluidized bed on which a FORTRAN program entitled (NEWFLUIDIZED) is devolved. The program is used to predict the volume fraction of gas and particle phases, the velocity of the two phases, the gas pressure and the temperature distribution for two phases. Also the program calculates the heat transfer coefficient. Besides the program predicts the fluidized bed stability and determines the optimum input gas velocity for fluidized bed to achieve the best thermal behavior. The hydrodynamic model is verified by comparing its results with the computational fluid dynamic code MFIX . While the thermal model was tested and compared by the available previous experimental correlations.The model results show good agreement with MFIX results and the thermal model of the present work confirms Zenz and Gunn equations

Smoothed Particle Hydrodynamics Simulations of Dam-Break Flows Around Movable Structures

OpenAIRE

Jian, Wei; Liang, Dongfang; Shao, Songdong; Chen, Ridong; Yang, Kejun

2015-01-01

In this paper, 3D weakly compressible and incompressible Smoothed Particle Hydrodynamics (WCSPH & ISPH) models are used to study dam-break flows impacting on either a fixed or a movable structure. First, the two models’ performances are compared in terms of CPU time efficiency and numerical accuracy, as well as the water surface shapes and pressure fields. Then, they are applied to investigate dam-break flow interactions with structures placed in the path of the flood. The study found that th...

An implicit Smooth Particle Hydrodynamic code

Energy Technology Data Exchange (ETDEWEB)

Knapp, Charles E. [Univ. of New Mexico, Albuquerque, NM (United States)

2000-05-01

An implicit version of the Smooth Particle Hydrodynamic (SPH) code SPHINX has been written and is working. In conjunction with the SPHINX code the new implicit code models fluids and solids under a wide range of conditions. SPH codes are Lagrangian, meshless and use particles to model the fluids and solids. The implicit code makes use of the Krylov iterative techniques for solving large linear-systems and a Newton-Raphson method for non-linear corrections. It uses numerical derivatives to construct the Jacobian matrix. It uses sparse techniques to save on memory storage and to reduce the amount of computation. It is believed that this is the first implicit SPH code to use Newton-Krylov techniques, and is also the first implicit SPH code to model solids. A description of SPH and the techniques used in the implicit code are presented. Then, the results of a number of tests cases are discussed, which include a shock tube problem, a Rayleigh-Taylor problem, a breaking dam problem, and a single jet of gas problem. The results are shown to be in very good agreement with analytic solutions, experimental results, and the explicit SPHINX code. In the case of the single jet of gas case it has been demonstrated that the implicit code can do a problem in much shorter time than the explicit code. The problem was, however, very unphysical, but it does demonstrate the potential of the implicit code. It is a first step toward a useful implicit SPH code.

A multi-parametric particle-pairing algorithm for particle tracking in single and multiphase flows

International Nuclear Information System (INIS)

Cardwell, Nicholas D; Vlachos, Pavlos P; Thole, Karen A

2011-01-01

Multiphase flows (MPFs) offer a rich area of fundamental study with many practical applications. Examples of such flows range from the ingestion of foreign particulates in gas turbines to transport of particles within the human body. Experimental investigation of MPFs, however, is challenging, and requires techniques that simultaneously resolve both the carrier and discrete phases present in the flowfield. This paper presents a new multi-parametric particle-pairing algorithm for particle tracking velocimetry (MP3-PTV) in MPFs. MP3-PTV improves upon previous particle tracking algorithms by employing a novel variable pair-matching algorithm which utilizes displacement preconditioning in combination with estimated particle size and intensity to more effectively and accurately match particle pairs between successive images. To improve the method's efficiency, a new particle identification and segmentation routine was also developed. Validation of the new method was initially performed on two artificial data sets: a traditional single-phase flow published by the Visualization Society of Japan (VSJ) and an in-house generated MPF data set having a bi-modal distribution of particles diameters. Metrics of the measurement yield, reliability and overall tracking efficiency were used for method comparison. On the VSJ data set, the newly presented segmentation routine delivered a twofold improvement in identifying particles when compared to other published methods. For the simulated MPF data set, measurement efficiency of the carrier phases improved from 9% to 41% for MP3-PTV as compared to a traditional hybrid PTV. When employed on experimental data of a gas–solid flow, the MP3-PTV effectively identified the two particle populations and reported a vector efficiency and velocity measurement error comparable to measurements for the single-phase flow images. Simultaneous measurement of the dispersed particle and the carrier flowfield velocities allowed for the calculation of

Comparing semi-analytic particle tagging and hydrodynamical simulations of the Milky Way's stellar halo

Science.gov (United States)

Cooper, Andrew P.; Cole, Shaun; Frenk, Carlos S.; Le Bret, Theo; Pontzen, Andrew

2017-08-01

Particle tagging is an efficient, but approximate, technique for using cosmological N-body simulations to model the phase-space evolution of the stellar populations predicted, for example, by a semi-analytic model of galaxy formation. We test the technique developed by Cooper et al. (which we call stings here) by comparing particle tags with stars in a smooth particle hydrodynamic (SPH) simulation. We focus on the spherically averaged density profile of stars accreted from satellite galaxies in a Milky Way (MW)-like system. The stellar profile in the SPH simulation can be recovered accurately by tagging dark matter (DM) particles in the same simulation according to a prescription based on the rank order of particle binding energy. Applying the same prescription to an N-body version of this simulation produces a density profile differing from that of the SPH simulation by ≲10 per cent on average between 1 and 200 kpc. This confirms that particle tagging can provide a faithful and robust approximation to a self-consistent hydrodynamical simulation in this regime (in contradiction to previous claims in the literature). We find only one systematic effect, likely due to the collisionless approximation, namely that massive satellites in the SPH simulation are disrupted somewhat earlier than their collisionless counterparts. In most cases, this makes remarkably little difference to the spherically averaged distribution of their stellar debris. We conclude that, for galaxy formation models that do not predict strong baryonic effects on the present-day DM distribution of MW-like galaxies or their satellites, differences in stellar halo predictions associated with the treatment of star formation and feedback are much more important than those associated with the dynamical limitations of collisionless particle tagging.

A general concurrent algorithm for plasma particle-in-cell simulation codes

International Nuclear Information System (INIS)

Liewer, P.C.; Decyk, V.K.

1989-01-01

We have developed a new algorithm for implementing plasma particle-in-cell (PIC) simulation codes on concurrent processors with distributed memory. This algorithm, named the general concurrent PIC algorithm (GCPIC), has been used to implement an electrostatic PIC code on the 33-node JPL Mark III Hypercube parallel computer. To decompose at PIC code using the GCPIC algorithm, the physical domain of the particle simulation is divided into sub-domains, equal in number to the number of processors, such that all sub-domains have roughly equal numbers of particles. For problems with non-uniform particle densities, these sub-domains will be of unequal physical size. Each processor is assigned a sub-domain and is responsible for updating the particles in its sub-domain. This algorithm has led to a a very efficient parallel implementation of a well-benchmarked 1-dimensional PIC code. The dominant portion of the code, updating the particle positions and velocities, is nearly 100% efficient when the number of particles is increased linearly with the number of hypercube processors used so that the number of particles per processor is constant. For example, the increase in time spent updating particles in going from a problem with 11,264 particles run on 1 processor to 360,448 particles on 32 processors was only 3% (parallel efficiency of 97%). Although implemented on a hypercube concurrent computer, this algorithm should also be efficient for PIC codes on other parallel architectures and for large PIC codes on sequential computers where part of the data must reside on external disks. copyright 1989 Academic Press, Inc

Particle algorithms for population dynamics in flows

International Nuclear Information System (INIS)

Perlekar, Prasad; Toschi, Federico; Benzi, Roberto; Pigolotti, Simone

2011-01-01

We present and discuss particle based algorithms to numerically study the dynamics of population subjected to an advecting flow condition. We discuss few possible variants of the algorithms and compare them in a model compressible flow. A comparison against appropriate versions of the continuum stochastic Fisher equation (sFKPP) is also presented and discussed. The algorithms can be used to study populations genetics in fluid environments.

Optimal configuration of power grid sources based on optimal particle swarm algorithm

Science.gov (United States)

Wen, Yuanhua

2018-04-01

In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.

On the hydrodynamics and the scale-up of flotation processes

International Nuclear Information System (INIS)

Schubert, H.

1986-01-01

In flotation machines, turbulence is process-determining. Macroturbulence is necessary for suspension, microturbulence controls the air dispersion, the rate of the particle-bubble collisions and the stresses on agglomerates. Consequently, the hydrodynamic optimization of flotation processes plays an important role for the flotation efficiency. In the paper the following aspects are considered: the turbulent microprocesses of flotation processes; the integral hydrodynamic characterization of flotation processes; correlations between particle size and optimum hydrodynamics; correlations between flocculation of fine particles and optimum-hydrodynamics; and hydrodynamic scale-up of flotation processes

Explicit symplectic algorithms based on generating functions for charged particle dynamics

Science.gov (United States)

Zhang, Ruili; Qin, Hong; Tang, Yifa; Liu, Jian; He, Yang; Xiao, Jianyuan

2016-07-01

Dynamics of a charged particle in the canonical coordinates is a Hamiltonian system, and the well-known symplectic algorithm has been regarded as the de facto method for numerical integration of Hamiltonian systems due to its long-term accuracy and fidelity. For long-term simulations with high efficiency, explicit symplectic algorithms are desirable. However, it is generally believed that explicit symplectic algorithms are only available for sum-separable Hamiltonians, and this restriction limits the application of explicit symplectic algorithms to charged particle dynamics. To overcome this difficulty, we combine the familiar sum-split method and a generating function method to construct second- and third-order explicit symplectic algorithms for dynamics of charged particle. The generating function method is designed to generate explicit symplectic algorithms for product-separable Hamiltonian with form of H (x ,p ) =pif (x ) or H (x ,p ) =xig (p ) . Applied to the simulations of charged particle dynamics, the explicit symplectic algorithms based on generating functions demonstrate superiorities in conservation and efficiency.

A geometric viewpoint on generalized hydrodynamics

Directory of Open Access Journals (Sweden)

Benjamin Doyon

2018-01-01

Full Text Available Generalized hydrodynamics (GHD is a large-scale theory for the dynamics of many-body integrable systems. It consists of an infinite set of conservation laws for quasi-particles traveling with effective (“dressed” velocities that depend on the local state. We show that these equations can be recast into a geometric dynamical problem. They are conservation equations with state-independent quasi-particle velocities, in a space equipped with a family of metrics, parametrized by the quasi-particles' type and speed, that depend on the local state. In the classical hard rod or soliton gas picture, these metrics measure the free length of space as perceived by quasi-particles; in the quantum picture, they weigh space with the density of states available to them. Using this geometric construction, we find a general solution to the initial value problem of GHD, in terms of a set of integral equations where time appears explicitly. These integral equations are solvable by iteration and provide an extremely efficient solution algorithm for GHD.

Economic dispatch optimization algorithm based on particle diffusion

International Nuclear Information System (INIS)

Han, Li; Romero, Carlos E.; Yao, Zheng

2015-01-01

Highlights: • A dispatch model that considers fuel, emissions control and wind power cost is built. • An optimization algorithm named diffusion particle optimization (DPO) is proposed. • DPO was used to analyze the impact of wind power risk and emissions on dispatch. - Abstract: Due to the widespread installation of emissions control equipment in fossil fuel-fired power plants, the cost of emissions control needs to be considered, together with the plant fuel cost, in providing economic power dispatch of those units to the grid. On the other hand, while using wind power decreases the overall power generation cost for the power grid, it poses a risk to a traditional grid, because of its inherent stochastic characteristics. Therefore, an economic dispatch optimization model needs to consider all of the fuel cost, emissions control cost and wind power cost for each of the generating unit conforming the fleet that meets the required grid power demand. In this study, an optimization algorithm referred as diffusion particle optimization (DPO) is proposed to solve such complex optimization problem. In this algorithm, Brownian motion theory is used to guide the movement of particles so that the particles can search for an optimal solution over the entire definition region. Several benchmark functions and power grid system data were used to test the performance of DPO, and compared to traditional algorithms used for economic dispatch optimization, such as, particle swarm optimization and artificial bee colony algorithm. It was found that DPO has less probability to be trapped in local optimums. According to results of different power systems DPO was able to find economic dispatch solutions with lower costs. DPO was also used to analyze the impact of wind power risk and fossil unit emissions coefficients on power dispatch. The result are encouraging for the use of DPO as a dynamic tool for economic dispatch of the power grid.

Lattice Boltzmann method used to simulate particle motion in a conduit

Directory of Open Access Journals (Sweden)

Dolanský Jindřich

2017-06-01

Full Text Available A three-dimensional numerical simulation of particle motion in a pipe with a rough bed is presented. The simulation based on the Lattice Boltzmann Method (LBM employs the hybrid diffuse bounce-back approach to model moving boundaries. The bed of the pipe is formed by stationary spherical particles of the same size as the moving particles. Particle movements are induced by gravitational and hydrodynamic forces. To evaluate the hydrodynamic forces, the Momentum Exchange Algorithm is used. The LBM unified computational frame makes it possible to simulate both the particle motion and the fluid flow and to study mutual interactions of the carrier liquid flow and particles and the particle–bed and particle–particle collisions. The trajectories of simulated and experimental particles are compared. The Particle Tracking method is used to track particle motion. The correctness of the applied approach is assessed.

Modelling free surface flows with smoothed particle hydrodynamics

Directory of Open Access Journals (Sweden)

L.Di G.Sigalotti

2006-01-01

Full Text Available In this paper the method of Smoothed Particle Hydrodynamics (SPH is extended to include an adaptive density kernel estimation (ADKE procedure. It is shown that for a van der Waals (vdW fluid, this method can be used to deal with free-surface phenomena without difficulties. In particular, arbitrary moving boundaries can be easily handled because surface tension is effectively simulated by the cohesive pressure forces. Moreover, the ADKE method is seen to increase both the accuracy and stability of SPH since it allows the width of the kernel interpolant to vary locally in a way that only the minimum necessary smoothing is applied at and near free surfaces and sharp fluid-fluid interfaces. The method is robust and easy to implement. Examples of its resolving power are given for both the formation of a circular liquid drop under surface tension and the nonlinear oscillation of excited drops.

Hydrodynamic Stability Analysis of Particle-Laden Solid Rocket Motors

Science.gov (United States)

Elliott, T. S.; Majdalani, J.

2014-11-01

Fluid-wall interactions within solid rocket motors can result in parietal vortex shedding giving rise to hydrodynamic instabilities, or unsteady waves, that translate into pressure oscillations. The oscillations can result in vibrations observed by the rocket, rocket subsystems, or payload, which can lead to changes in flight characteristics, design failure, or other undesirable effects. For many years particles have been embedded in solid rocket propellants with the understanding that their presence increases specific impulse and suppresses fluctuations in the flowfield. This study utilizes a two dimensional framework to understand and quantify the aforementioned two-phase flowfield inside a motor case with a cylindrical grain perforation. This is accomplished through the use of linearized Navier-Stokes equations with the Stokes drag equation and application of the biglobal ansatz. Obtaining the biglobal equations for analysis requires quantification of the mean flowfield within the solid rocket motor. To that end, the extended Taylor-Culick form will be utilized to represent the gaseous phase of the mean flowfield while the self-similar form will be employed for the particle phase. Advancing the mean flowfield by quantifying the particle mass concentration with a semi-analytical solution the finalized mean flowfield is combined with the biglobal equations resulting in a system of eight partial differential equations. This system is solved using an eigensolver within the framework yielding the entire spectrum of eigenvalues, frequency and growth rate components, at once. This work will detail the parametric analysis performed to demonstrate the stabilizing and destabilizing effects of particles within solid rocket combustion.

Hydrodynamic Stability Analysis of Particle-Laden Solid Rocket Motors

International Nuclear Information System (INIS)

Elliott, T S; Majdalani, J

2014-01-01

Fluid-wall interactions within solid rocket motors can result in parietal vortex shedding giving rise to hydrodynamic instabilities, or unsteady waves, that translate into pressure oscillations. The oscillations can result in vibrations observed by the rocket, rocket subsystems, or payload, which can lead to changes in flight characteristics, design failure, or other undesirable effects. For many years particles have been embedded in solid rocket propellants with the understanding that their presence increases specific impulse and suppresses fluctuations in the flowfield. This study utilizes a two dimensional framework to understand and quantify the aforementioned two-phase flowfield inside a motor case with a cylindrical grain perforation. This is accomplished through the use of linearized Navier-Stokes equations with the Stokes drag equation and application of the biglobal ansatz. Obtaining the biglobal equations for analysis requires quantification of the mean flowfield within the solid rocket motor. To that end, the extended Taylor-Culick form will be utilized to represent the gaseous phase of the mean flowfield while the self-similar form will be employed for the particle phase. Advancing the mean flowfield by quantifying the particle mass concentration with a semi-analytical solution the finalized mean flowfield is combined with the biglobal equations resulting in a system of eight partial differential equations. This system is solved using an eigensolver within the framework yielding the entire spectrum of eigenvalues, frequency and growth rate components, at once. This work will detail the parametric analysis performed to demonstrate the stabilizing and destabilizing effects of particles within solid rocket combustion

Many Drops Interactions I: Simulation of Coalescence, Flocculation and Fragmentation of Multiple Colliding Drops with Smoothed Particle Hydrodynamics

Directory of Open Access Journals (Sweden)

Alejandro Acevedo-Malavé

2012-06-01

Full Text Available Smoothed Particle Hydrodynamics (SPH is a Lagrangian mesh-free formalism and has been useful to model continuous fluid. This formalism is employed to solve the Navier-Stokes equations by replacing the fluid with a set of particles. These particles are interpolation points from which properties of the fluid can be determined. In this study, the SPH method is applied to simulate the hydrodynamics interaction of many drops, showing some settings for the coalescence, fragmentation and flocculation problem of equally sized liquid drops in three-dimensional spaces. For small velocities the drops interact only through their deformed surfaces and the flocculation of the droplets arises. This result is very different if the collision velocity is large enough for the fragmentation of droplets takes place. We observe that for velocities around 15 mm/ms the coalescence of droplets occurs. The velocity vector fields formed inside the drops during the collision process are shown.

Smoothed Particle Hydro-dynamic Analysis of Improvement in Sludge Conveyance Efficiency of Screw Decanter Centrifuge

Energy Technology Data Exchange (ETDEWEB)

Park, Dae Woong [Korea Testing and Research Institute, Kwachun (Korea, Republic of)

2015-03-15

A centrifuge works on the principle that particles with different densities will separate at a rate proportional to the centrifugal force during high-speed rotation. Dense particles are quickly precipitated, and particles with relatively smaller densities are precipitated more slowly. A decanter-type centrifuge is used to remove, concentrate, and dehydrate sludge in a water treatment process. This is a core technology for measuring the sludge conveyance efficiency improvement. In this study, a smoothed particle hydro-dynamic analysis was performed for a decanter centrifuge used to convey sludge to evaluate the efficiency improvement. This analysis was applied to both the original centrifugal model and the design change model, which was a ball-plate rail model, to evaluate the sludge transfer efficiency.

Smoothed Particle Hydro-dynamic Analysis of Improvement in Sludge Conveyance Efficiency of Screw Decanter Centrifuge

International Nuclear Information System (INIS)

Park, Dae Woong

2015-01-01

A centrifuge works on the principle that particles with different densities will separate at a rate proportional to the centrifugal force during high-speed rotation. Dense particles are quickly precipitated, and particles with relatively smaller densities are precipitated more slowly. A decanter-type centrifuge is used to remove, concentrate, and dehydrate sludge in a water treatment process. This is a core technology for measuring the sludge conveyance efficiency improvement. In this study, a smoothed particle hydro-dynamic analysis was performed for a decanter centrifuge used to convey sludge to evaluate the efficiency improvement. This analysis was applied to both the original centrifugal model and the design change model, which was a ball-plate rail model, to evaluate the sludge transfer efficiency.

Numerical modelling of extreme waves by Smoothed Particle Hydrodynamics

Directory of Open Access Journals (Sweden)

M. H. Dao

2011-02-01

Full Text Available The impact of extreme/rogue waves can lead to serious damage of vessels as well as marine and coastal structures. Such extreme waves in deep water are characterized by steep wave fronts and an energetic wave crest. The process of wave breaking is highly complex and, apart from the general knowledge that impact loadings are highly impulsive, the dynamics of the breaking and impact are still poorly understood. Using an advanced numerical method, the Smoothed Particle Hydrodynamics enhanced with parallel computing is able to reproduce well the extreme waves and their breaking process. Once the waves and their breaking process are modelled successfully, the dynamics of the breaking and the characteristics of their impact on offshore structures could be studied. The computational methodology and numerical results are presented in this paper.

Chaotically encoded particle swarm optimization algorithm and its applications

International Nuclear Information System (INIS)

Alatas, Bilal; Akin, Erhan

2009-01-01

This paper proposes a novel particle swarm optimization (PSO) algorithm, chaotically encoded particle swarm optimization algorithm (CENPSOA), based on the notion of chaos numbers that have been recently proposed for a novel meaning to numbers. In this paper, various chaos arithmetic and evaluation measures that can be used in CENPSOA have been described. Furthermore, CENPSOA has been designed to be effectively utilized in data mining applications.

Effects of Random Values for Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Hou-Ping Dai

2018-02-01

Full Text Available Particle swarm optimization (PSO algorithm is generally improved by adaptively adjusting the inertia weight or combining with other evolution algorithms. However, in most modified PSO algorithms, the random values are always generated by uniform distribution in the range of [0, 1]. In this study, the random values, which are generated by uniform distribution in the ranges of [0, 1] and [−1, 1], and Gauss distribution with mean 0 and variance 1 ( U [ 0 , 1 ] , U [ − 1 , 1 ] and G ( 0 , 1 , are respectively used in the standard PSO and linear decreasing inertia weight (LDIW PSO algorithms. For comparison, the deterministic PSO algorithm, in which the random values are set as 0.5, is also investigated in this study. Some benchmark functions and the pressure vessel design problem are selected to test these algorithms with different types of random values in three space dimensions (10, 30, and 100. The experimental results show that the standard PSO and LDIW-PSO algorithms with random values generated by U [ − 1 , 1 ] or G ( 0 , 1 are more likely to avoid falling into local optima and quickly obtain the global optima. This is because the large-scale random values can expand the range of particle velocity to make the particle more likely to escape from local optima and obtain the global optima. Although the random values generated by U [ − 1 , 1 ] or G ( 0 , 1 are beneficial to improve the global searching ability, the local searching ability for a low dimensional practical optimization problem may be decreased due to the finite particles.

Effects of hydrodynamic interaction on random adhesive loose packings of micron-sized particles

Directory of Open Access Journals (Sweden)

Liu Wenwei

2017-01-01

Full Text Available Random loose packings of monodisperse spherical micron-sized particles under a uniform flow field are investigated via an adhesive discrete-element method with the two-way coupling between the particles and the fluid. Characterized by a dimensionless adhesion parameter, the packing fraction follows the similar law to that without fluid, but results in larger values due to the hydrodynamic compression. The total pressure drop through the packed bed shows a critical behaviour at the packing fraction of ϕ ≈ 0.22 in the present study. The normalized permeability of the packed bed for different parameters increases with the increase of porosities and is also in consistent with the Kozeny-Carman equation.

Computational plasticity algorithm for particle dynamics simulations

Science.gov (United States)

Krabbenhoft, K.; Lyamin, A. V.; Vignes, C.

2018-01-01

The problem of particle dynamics simulation is interpreted in the framework of computational plasticity leading to an algorithm which is mathematically indistinguishable from the common implicit scheme widely used in the finite element analysis of elastoplastic boundary value problems. This algorithm provides somewhat of a unification of two particle methods, the discrete element method and the contact dynamics method, which usually are thought of as being quite disparate. In particular, it is shown that the former appears as the special case where the time stepping is explicit while the use of implicit time stepping leads to the kind of schemes usually labelled contact dynamics methods. The framing of particle dynamics simulation within computational plasticity paves the way for new approaches similar (or identical) to those frequently employed in nonlinear finite element analysis. These include mixed implicit-explicit time stepping, dynamic relaxation and domain decomposition schemes.

A dynamic inertia weight particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Gu Xingsheng

2008-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algorithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 different dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search performance on the benchmark functions significantly

Parametric geometric model and hydrodynamic shape optimization of a flying-wing structure underwater glider

Science.gov (United States)

Wang, Zhen-yu; Yu, Jian-cheng; Zhang, Ai-qun; Wang, Ya-xing; Zhao, Wen-tao

2017-12-01

Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of a design space has become an important topic in the modern design methods. During the design process of an underwater glider's flying-wing structure, a surrogate model is introduced to decrease the computation time for a high precision analysis. By these means, the contradiction between precision and efficiency is solved effectively. Based on the parametric geometry modeling, mesh generation and computational fluid dynamics analysis, a surrogate model is constructed by adopting the design of experiment (DOE) theory to solve the multi-objects design optimization problem of the underwater glider. The procedure of a surrogate model construction is presented, and the Gaussian kernel function is specifically discussed. The Particle Swarm Optimization (PSO) algorithm is applied to hydrodynamic design optimization. The hydrodynamic performance of the optimized flying-wing structure underwater glider increases by 9.1%.

Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

Science.gov (United States)

Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

2015-09-01

The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

Research status on hydrodynamics and particle motion behavior of absorber sphere pneumatic conveying system in HTR-PM

International Nuclear Information System (INIS)

Li Tianjin; Zhang He; Huang Zhiyong; Q, Weiwei; Bo Hanliang

2014-01-01

The absorber sphere pneumatic conveying system in pebble-bed high temperature gas-cooled reactor was a special application of pneumatic conveying technique. The whole conveying process was an intermittent circulation of absorber spheres between the side reflector boring and the sphere storage vessel in the reactor. The absorber spheres were designed to drop into the reflector borings by its own gravity when the sphere discharge valve was opened by the driving mechanism. The absorber spheres in the reflector boring were transported back to the sphere storage vessel when the reactor needs to be started up. The hydrodynamics and particle motion behavior characteristics of the absorber spheres were very important for the design and operation of this special pneumatic conveying system. The whole conveying process of absorber spheres was consisted of four subprocesses, i.e. the spheres discharge from the sphere storage vessel and the side reflector boring, entrainment of spheres in the feeder, conveying of spheres in the transport pipe, gas-solid separation and pile of spheres in the sphere storage vessel. The research status on hydrodynamics and particle motion behavior of the absorber spheres in the pneumatic conveying system of HTR-PM were introduced mainly from the viewpoint of granular flow and gas-solid flow. The experimental systems and apparatus constructed and numerical simulation work conducted for absorber sphere pneumatic conveying process investigation were introduced. Some typical experimental and numerical simulation results of the hydrodynamics and particle motion behavior characteristics of the absorber spheres conveying were briefly reported. (author)

Multi-Algorithm Particle Simulations with Spatiocyte.

Science.gov (United States)

Arjunan, Satya N V; Takahashi, Koichi

2017-01-01

As quantitative biologists get more measurements of spatially regulated systems such as cell division and polarization, simulation of reaction and diffusion of proteins using the data is becoming increasingly relevant to uncover the mechanisms underlying the systems. Spatiocyte is a lattice-based stochastic particle simulator for biochemical reaction and diffusion processes. Simulations can be performed at single molecule and compartment spatial scales simultaneously. Molecules can diffuse and react in 1D (filament), 2D (membrane), and 3D (cytosol) compartments. The implications of crowded regions in the cell can be investigated because each diffusing molecule has spatial dimensions. Spatiocyte adopts multi-algorithm and multi-timescale frameworks to simulate models that simultaneously employ deterministic, stochastic, and particle reaction-diffusion algorithms. Comparison of light microscopy images to simulation snapshots is supported by Spatiocyte microscopy visualization and molecule tagging features. Spatiocyte is open-source software and is freely available at http://spatiocyte.org .

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

Science.gov (United States)

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Kinetic-Monte-Carlo-Based Parallel Evolution Simulation Algorithm of Dust Particles

Directory of Open Access Journals (Sweden)

Xiaomei Hu

2014-01-01

Full Text Available The evolution simulation of dust particles provides an important way to analyze the impact of dust on the environment. KMC-based parallel algorithm is proposed to simulate the evolution of dust particles. In the parallel evolution simulation algorithm of dust particles, data distribution way and communication optimizing strategy are raised to balance the load of every process and reduce the communication expense among processes. The experimental results show that the simulation of diffusion, sediment, and resuspension of dust particles in virtual campus is realized and the simulation time is shortened by parallel algorithm, which makes up for the shortage of serial computing and makes the simulation of large-scale virtual environment possible.

Parallel-vector algorithms for particle simulations on shared-memory multiprocessors

International Nuclear Information System (INIS)

Nishiura, Daisuke; Sakaguchi, Hide

2011-01-01

Over the last few decades, the computational demands of massive particle-based simulations for both scientific and industrial purposes have been continuously increasing. Hence, considerable efforts are being made to develop parallel computing techniques on various platforms. In such simulations, particles freely move within a given space, and so on a distributed-memory system, load balancing, i.e., assigning an equal number of particles to each processor, is not guaranteed. However, shared-memory systems achieve better load balancing for particle models, but suffer from the intrinsic drawback of memory access competition, particularly during (1) paring of contact candidates from among neighboring particles and (2) force summation for each particle. Here, novel algorithms are proposed to overcome these two problems. For the first problem, the key is a pre-conditioning process during which particle labels are sorted by a cell label in the domain to which the particles belong. Then, a list of contact candidates is constructed by pairing the sorted particle labels. For the latter problem, a table comprising the list indexes of the contact candidate pairs is created and used to sum the contact forces acting on each particle for all contacts according to Newton's third law. With just these methods, memory access competition is avoided without additional redundant procedures. The parallel efficiency and compatibility of these two algorithms were evaluated in discrete element method (DEM) simulations on four types of shared-memory parallel computers: a multicore multiprocessor computer, scalar supercomputer, vector supercomputer, and graphics processing unit. The computational efficiency of a DEM code was found to be drastically improved with our algorithms on all but the scalar supercomputer. Thus, the developed parallel algorithms are useful on shared-memory parallel computers with sufficient memory bandwidth.

Application of ant colony Algorithm and particle swarm optimization in architectural design

Science.gov (United States)

Song, Ziyi; Wu, Yunfa; Song, Jianhua

2018-02-01

By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.

An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis

Directory of Open Access Journals (Sweden)

Qihang Wang

2016-07-01

Full Text Available In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.

A Constructive Data Classification Version of the Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Alexandre Szabo

2013-01-01

Full Text Available The particle swarm optimization algorithm was originally introduced to solve continuous parameter optimization problems. It was soon modified to solve other types of optimization tasks and also to be applied to data analysis. In the latter case, however, there are few works in the literature that deal with the problem of dynamically building the architecture of the system. This paper introduces new particle swarm algorithms specifically designed to solve classification problems. The first proposal, named Particle Swarm Classifier (PSClass, is a derivation of a particle swarm clustering algorithm and its architecture, as in most classifiers, is pre-defined. The second proposal, named Constructive Particle Swarm Classifier (cPSClass, uses ideas from the immune system to automatically build the swarm. A sensitivity analysis of the growing procedure of cPSClass and an investigation into a proposed pruning procedure for this algorithm are performed. The proposals were applied to a wide range of databases from the literature and the results show that they are competitive in relation to other approaches, with the advantage of having a dynamically constructed architecture.

Comparison of several algorithms of the electric force calculation in particle plasma models

International Nuclear Information System (INIS)

Lachnitt, J; Hrach, R

2014-01-01

This work is devoted to plasma modelling using the technique of molecular dynamics. The crucial problem of most such models is the efficient calculation of electric force. This is usually solved by using the particle-in-cell (PIC) algorithm. However, PIC is an approximative algorithm as it underestimates the short-range interactions of charged particles. We propose a hybrid algorithm which adds these interactions to PIC. Then we include this algorithm in a set of algorithms which we test against each other in a two-dimensional collisionless magnetized plasma model. Besides our hybrid algorithm, this set includes two variants of pure PIC and the direct application of Coulomb's law. We compare particle forces, particle trajectories, total energy conservation and the speed of the algorithms. We find out that the hybrid algorithm can be a good replacement of direct Coulomb's law application (quite accurate and much faster). It is however probably unnecessary to use it in practical 2D models.

Microflow Cytometers with Integrated Hydrodynamic Focusing

Directory of Open Access Journals (Sweden)

Martin Schmidt

2013-04-01

Full Text Available This study demonstrates the suitability of microfluidic structures for high throughput blood cell analysis. The microfluidic chips exploit fully integrated hydrodynamic focusing based on two different concepts: Two-stage cascade focusing and spin focusing (vortex principle. The sample—A suspension of micro particles or blood cells—is injected into a sheath fluid streaming at a substantially higher flow rate, which assures positioning of the particles in the center of the flow channel. Particle velocities of a few m/s are achieved as required for high throughput blood cell analysis. The stability of hydrodynamic particle positioning was evaluated by measuring the pulse heights distributions of fluorescence signals from calibration beads. Quantitative assessment based on coefficient of variation for the fluorescence intensity distributions resulted in a value of about 3% determined for the micro-device exploiting cascade hydrodynamic focusing. For the spin focusing approach similar values were achieved for sample flow rates being 1.5 times lower. Our results indicate that the performances of both variants of hydrodynamic focusing suit for blood cell differentiation and counting. The potential of the micro flow cytometer is demonstrated by detecting immunologically labeled CD3 positive and CD4 positive T-lymphocytes in blood.

Hydrodynamic Coefficients Identification and Experimental Investigation for an Underwater Vehicle

Directory of Open Access Journals (Sweden)

Shaorong XIE

2014-02-01

Full Text Available Hydrodynamic coefficients are the foundation of unmanned underwater vehicles modeling and controller design. In order to reduce identification complexity and acquire necessary hydrodynamic coefficients for controllers design, the motion of the unmanned underwater vehicle was separated into vertical motion and horizontal motion models. Hydrodynamic coefficients were regarded as mapping parameters from input forces and moments to output velocities and acceleration of the unmanned underwater vehicle. The motion models of the unmanned underwater vehicle were nonlinear and Genetic Algorithm was adopted to identify those hydrodynamic coefficients. To verify the identification quality, velocities and acceleration of the unmanned underwater vehicle was measured using inertial sensor under the same conditions as Genetic Algorithm identification. Curves similarity between measured velocities and acceleration and those identified by Genetic Algorithm were used as optimizing standard. It is found that the curves similarity were high and identified hydrodynamic coefficients of the unmanned underwater vehicle satisfied the measured motion states well.

MODA: a new algorithm to compute optical depths in multidimensional hydrodynamic simulations

Science.gov (United States)

Perego, Albino; Gafton, Emanuel; Cabezón, Rubén; Rosswog, Stephan; Liebendörfer, Matthias

2014-08-01

Aims: We introduce the multidimensional optical depth algorithm (MODA) for the calculation of optical depths in approximate multidimensional radiative transport schemes, equally applicable to neutrinos and photons. Motivated by (but not limited to) neutrino transport in three-dimensional simulations of core-collapse supernovae and neutron star mergers, our method makes no assumptions about the geometry of the matter distribution, apart from expecting optically transparent boundaries. Methods: Based on local information about opacities, the algorithm figures out an escape route that tends to minimize the optical depth without assuming any predefined paths for radiation. Its adaptivity makes it suitable for a variety of astrophysical settings with complicated geometry (e.g., core-collapse supernovae, compact binary mergers, tidal disruptions, star formation, etc.). We implement the MODA algorithm into both a Eulerian hydrodynamics code with a fixed, uniform grid and into an SPH code where we use a tree structure that is otherwise used for searching neighbors and calculating gravity. Results: In a series of numerical experiments, we compare the MODA results with analytically known solutions. We also use snapshots from actual 3D simulations and compare the results of MODA with those obtained with other methods, such as the global and local ray-by-ray method. It turns out that MODA achieves excellent accuracy at a moderate computational cost. In appendix we also discuss implementation details and parallelization strategies.

Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.

Science.gov (United States)

Garro, Beatriz A; Vázquez, Roberto A

2015-01-01

Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.

An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base

Directory of Open Access Journals (Sweden)

Jun Yang

2017-01-01

Full Text Available A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for multi-dimensional optimization problems, but also conceives a new adaptive cooperation mechanism to accomplish the information interaction among swarms and particles. Experiments are conducted on a set of benchmark functions, and the results show its better performance compared with traditional PSO algorithm in aspects of convergence, computational efficiency and avoiding premature convergence.

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

International Nuclear Information System (INIS)

Huang, Xiaobiao; Safranek, James

2014-01-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

Energy Technology Data Exchange (ETDEWEB)

Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Simulations of reactive transport and precipitation with smoothed particle hydrodynamics

Science.gov (United States)

Tartakovsky, Alexandre M.; Meakin, Paul; Scheibe, Timothy D.; Eichler West, Rogene M.

2007-03-01

A numerical model based on smoothed particle hydrodynamics (SPH) was developed for reactive transport and mineral precipitation in fractured and porous materials. Because of its Lagrangian particle nature, SPH has several advantages for modeling Navier-Stokes flow and reactive transport including: (1) in a Lagrangian framework there is no non-linear term in the momentum conservation equation, so that accurate solutions can be obtained for momentum dominated flows and; (2) complicated physical and chemical processes such as surface growth due to precipitation/dissolution and chemical reactions are easy to implement. In addition, SPH simulations explicitly conserve mass and linear momentum. The SPH solution of the diffusion equation with fixed and moving reactive solid-fluid boundaries was compared with analytical solutions, Lattice Boltzmann [Q. Kang, D. Zhang, P. Lichtner, I. Tsimpanogiannis, Lattice Boltzmann model for crystal growth from supersaturated solution, Geophysical Research Letters, 31 (2004) L21604] simulations and diffusion limited aggregation (DLA) [P. Meakin, Fractals, scaling and far from equilibrium. Cambridge University Press, Cambridge, UK, 1998] model simulations. To illustrate the capabilities of the model, coupled three-dimensional flow, reactive transport and precipitation in a fracture aperture with a complex geometry were simulated.

Recent development of hydrodynamic modeling

Science.gov (United States)

Hirano, Tetsufumi

2014-09-01

In this talk, I give an overview of recent development in hydrodynamic modeling of high-energy nuclear collisions. First, I briefly discuss about current situation of hydrodynamic modeling by showing results from the integrated dynamical approach in which Monte-Carlo calculation of initial conditions, quark-gluon fluid dynamics and hadronic cascading are combined. In particular, I focus on rescattering effects of strange hadrons on final observables. Next I highlight three topics in recent development in hydrodynamic modeling. These include (1) medium response to jet propagation in di-jet asymmetric events, (2) causal hydrodynamic fluctuation and its application to Bjorken expansion and (3) chiral magnetic wave from anomalous hydrodynamic simulations. (1) Recent CMS data suggest the existence of QGP response to propagation of jets. To investigate this phenomenon, we solve hydrodynamic equations with source term which exhibits deposition of energy and momentum from jets. We find a large number of low momentum particles are emitted at large angle from jet axis. This gives a novel interpretation of the CMS data. (2) It has been claimed that a matter created even in p-p/p-A collisions may behave like a fluid. However, fluctuation effects would be important in such a small system. We formulate relativistic fluctuating hydrodynamics and apply it to Bjorken expansion. We found the final multiplicity fluctuates around the mean value even if initial condition is fixed. This effect is relatively important in peripheral A-A collisions and p-p/p-A collisions. (3) Anomalous transport of the quark-gluon fluid is predicted when extremely high magnetic field is applied. We investigate this possibility by solving anomalous hydrodynamic equations. We found the difference of the elliptic flow parameter between positive and negative particles appears due to the chiral magnetic wave. Finally, I provide some personal perspective of hydrodynamic modeling of high energy nuclear collisions

Neural Network Algorithm for Particle Loading

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2003-01-01

An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given

Max–min Bin Packing Algorithm and its application in nano-particles filling

International Nuclear Information System (INIS)

Zhu, Dingju

2016-01-01

With regard to existing bin packing algorithms, higher packing efficiency often leads to lower packing speed while higher packing speed leads to lower packing efficiency. Packing speed and packing efficiency of existing bin packing algorithms including NFD, NF, FF, FFD, BF and BFD correlates negatively with each other, thus resulting in the failure of existing bin packing algorithms to satisfy the demand of nano-particles filling for both high speed and high efficiency. The paper provides a new bin packing algorithm, Max–min Bin Packing Algorithm (MM), which realizes both high packing speed and high packing efficiency. MM has the same packing speed as NFD (whose packing speed ranks no. 1 among existing bin packing algorithms); in case that the size repetition rate of objects to be packed is over 5, MM can realize almost the same packing efficiency as BFD (whose packing efficiency ranks No. 1 among existing bin packing algorithms), and in case that the size repetition rate of objects to be packed is over 500, MM can achieve exactly the same packing efficiency as BFD. With respect to application of nano-particles filling, the size repetition rate of nano particles to be packed is usually in thousands or ten thousands, far higher than 5 or 500. Consequently, in application of nano-particles filling, the packing efficiency of MM is exactly equal to that of BFD. Thus the irreconcilable conflict between packing speed and packing efficiency is successfully removed by MM, which leads to MM having better packing effect than any existing bin packing algorithm. In practice, there are few cases when the size repetition of objects to be packed is lower than 5. Therefore the MM is not necessarily limited to nano-particles filling, and can also be widely used in other applications besides nano-particles filling. Especially, MM has significant value in application of nano-particles filling such as nano printing and nano tooth filling.

A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with Time Window

Directory of Open Access Journals (Sweden)

Qi Hu

2013-04-01

Full Text Available State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and the judgment of the local optimal solution. Based on these, a hybrid chaos-particle swarm optimization algorithm (HPSO is proposed to solve VRPTW. The chaos algorithm is employed to re-initialize the particle swarm. An efficient insertion heuristic algorithm is also proposed to build the valid vehicle route in the particle decoding process. A particle swarm premature convergence judgment mechanism is formulated and combined with the chaos algorithm and Gaussian mutation into HPSO when the particle swarm falls into the local convergence. Extensive experiments are carried out to test the parameter settings in the insertion heuristic algorithm and to evaluate that they are corresponding to the data’s real-distribution in the concrete problem. It is also revealed that the HPSO achieves a better performance than the other state-of-the-art algorithms on solving VRPTW.

Behavior of passive admixture in a vortical hydrodynamic field

NARCIS (Netherlands)

Bobrov, R.O.; Kyrylyuk, A.V; Zatovsky, A.V.

2006-01-01

The motion of passive admixture of spherical particles in the stationary hydrodynamic field of a swirling flow is studied. A spherical particle of a given mass in the hydrodynamic field of a swirling flow is located on a certain circular orbit, where the centrifugal force is compensated by the

A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

Science.gov (United States)

Sun, Tao; Xu, Ming-Hai

2017-01-01

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem

Directory of Open Access Journals (Sweden)

Hao Yin

2014-01-01

Full Text Available For SLA-aware service composition problem (SSC, an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively.

Many particle magnetic dipole-dipole and hydrodynamic interactions in magnetizable stent assisted magnetic drug targeting

International Nuclear Information System (INIS)

Cregg, P.J.; Murphy, Kieran; Mardinoglu, Adil; Prina-Mello, Adriele

2010-01-01

The implant assisted magnetic targeted drug delivery system of Aviles, Ebner and Ritter is considered both experimentally (in vitro) and theoretically. The results of a 2D mathematical model are compared with 3D experimental results for a magnetizable wire stent. In this experiment a ferromagnetic, coiled wire stent is implanted to aid collection of particles which consist of single domain magnetic nanoparticles (radius ∼10nm). In order to model the agglomeration of particles known to occur in this system, the magnetic dipole-dipole and hydrodynamic interactions for multiple particles are included. Simulations based on this mathematical model were performed using open source C++ code. Different initial positions are considered and the system performance is assessed in terms of collection efficiency. The results of this model show closer agreement with the measured in vitro experimental results and with the literature. The implications in nanotechnology and nanomedicine are based on the prediction of the particle efficiency, in conjunction with the magnetizable stent, for targeted drug delivery.

Simulating Magnetized Laboratory Plasmas with Smoothed Particle Hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Johnson, Jeffrey N. [Univ. of California, Davis, CA (United States)

2009-01-01

The creation of plasmas in the laboratory continues to generate excitement in the physics community. Despite the best efforts of the intrepid plasma diagnostics community, the dynamics of these plasmas remains a difficult challenge to both the theorist and the experimentalist. This dissertation describes the simulation of strongly magnetized laboratory plasmas with Smoothed Particle Hydrodynamics (SPH), a method born of astrophysics but gaining broad support in the engineering community. We describe the mathematical formulation that best characterizes a strongly magnetized plasma under our circumstances of interest, and we review the SPH method and its application to astrophysical plasmas based on research by Phillips [1], Buerve [2], and Price and Monaghan [3]. Some modifications and extensions to this method are necessary to simulate terrestrial plasmas, such as a treatment of magnetic diffusion based on work by Brookshaw [4] and by Atluri [5]; we describe these changes as we turn our attention toward laboratory experiments. Test problems that verify the method are provided throughout the discussion. Finally, we apply our method to the compression of a magnetized plasma performed by the Compact Toroid Injection eXperiment (CTIX) [6] and show that the experimental results support our computed predictions.

A hand tracking algorithm with particle filter and improved GVF snake model

Science.gov (United States)

Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

2017-07-01

To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

Energy Technology Data Exchange (ETDEWEB)

O' Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2²¹ = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

Science.gov (United States)

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

Machine learning based global particle indentification algorithms at LHCb experiment

CERN Multimedia

Derkach, Denis; Likhomanenko, Tatiana; Rogozhnikov, Aleksei; Ratnikov, Fedor

2017-01-01

One of the most important aspects of data processing at LHC experiments is the particle identification (PID) algorithm. In LHCb, several different sub-detector systems provide PID information: the Ring Imaging CHerenkov (RICH) detector, the hadronic and electromagnetic calorimeters, and the muon chambers. To improve charged particle identification, several neural networks including a deep architecture and gradient boosting have been applied to data. These new approaches provide higher identification efficiencies than existing implementations for all charged particle types. It is also necessary to achieve a flat dependency between efficiencies and spectator variables such as particle momentum, in order to reduce systematic uncertainties during later stages of data analysis. For this purpose, "flat” algorithms that guarantee the flatness property for efficiencies have also been developed. This talk presents this new approach based on machine learning and its performance.

Globally aligned states and hydrodynamic traffic jams in confined suspensions of active asymmetric particles.

Science.gov (United States)

Lefauve, Adrien; Saintillan, David

2014-02-01

Strongly confined active liquids are subject to unique hydrodynamic interactions due to momentum screening and lubricated friction by the confining walls. Using numerical simulations, we demonstrate that two-dimensional dilute suspensions of fore-aft asymmetric polar swimmers in a Hele-Shaw geometry can exhibit a rich variety of novel phase behaviors depending on particle shape, including coherent polarized density waves with global alignment, persistent counterrotating vortices, density shocks and rarefaction waves. We also explain these phenomena using a linear stability analysis and a nonlinear traffic flow model, both derived from a mean-field kinetic theory.

Application of particle swarm optimization algorithm in the heating system planning problem.

Science.gov (United States)

Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

2013-01-01

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem.

Relativistic hydrodynamics

CERN Document Server

Luciano, Rezzolla

2013-01-01

Relativistic hydrodynamics is a very successful theoretical framework to describe the dynamics of matter from scales as small as those of colliding elementary particles, up to the largest scales in the universe. This book provides an up-to-date, lively, and approachable introduction to the mathematical formalism, numerical techniques, and applications of relativistic hydrodynamics. The topic is typically covered either by very formal or by very phenomenological books, but is instead presented here in a form that will be appreciated both by students and researchers in the field. The topics covered in the book are the results of work carried out over the last 40 years, which can be found in rather technical research articles with dissimilar notations and styles. The book is not just a collection of scattered information, but a well-organized description of relativistic hydrodynamics, from the basic principles of statistical kinetic theory, down to the technical aspects of numerical methods devised for the solut...

Fast weighted centroid algorithm for single particle localization near the information limit.

Science.gov (United States)

Fish, Jeremie; Scrimgeour, Jan

2015-07-10

A simple weighting scheme that enhances the localization precision of center of mass calculations for radially symmetric intensity distributions is presented. The algorithm effectively removes the biasing that is common in such center of mass calculations. Localization precision compares favorably with other localization algorithms used in super-resolution microscopy and particle tracking, while significantly reducing the processing time and memory usage. We expect that the algorithm presented will be of significant utility when fast computationally lightweight particle localization or tracking is desired.

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

Science.gov (United States)

Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

An analysis of 1-D smoothed particle hydrodynamics kernels

International Nuclear Information System (INIS)

Fulk, D.A.; Quinn, D.W.

1996-01-01

In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

Hydrodynamic interaction of two particles in confined linear shear flow at finite Reynolds number

Science.gov (United States)

Yan, Yiguang; Morris, Jeffrey F.; Koplik, Joel

2007-11-01

We discuss the hydrodynamic interactions of two solid bodies placed in linear shear flow between parallel plane walls in a periodic geometry at finite Reynolds number. The computations are based on the lattice Boltzmann method for particulate flow, validated here by comparison to previous results for a single particle. Most of our results pertain to cylinders in two dimensions but some examples are given for spheres in three dimensions. Either one mobile and one fixed particle or else two mobile particles are studied. The motion of a mobile particle is qualitatively similar in both cases at early times, exhibiting either trajectory reversal or bypass, depending upon the initial vector separation of the pair. At longer times, if a mobile particle does not approach a periodic image of the second, its trajectory tends to a stable limit point on the symmetry axis. The effect of interactions with periodic images is to produce nonconstant asymptotic long-time trajectories. For one free particle interacting with a fixed second particle within the unit cell, the free particle may either move to a fixed point or take up a limit cycle. Pairs of mobile particles starting from symmetric initial conditions are shown to asymptotically reach either fixed points, or mirror image limit cycles within the unit cell, or to bypass one another (and periodic images) indefinitely on a streamwise periodic trajectory. The limit cycle possibility requires finite Reynolds number and arises as a consequence of streamwise periodicity when the system length is sufficiently short.

A parallel algorithm for 3D particle tracking and Lagrangian trajectory reconstruction

International Nuclear Information System (INIS)

Barker, Douglas; Zhang, Yuanhui; Lifflander, Jonathan; Arya, Anshu

2012-01-01

Particle-tracking methods are widely used in fluid mechanics and multi-target tracking research because of their unique ability to reconstruct long trajectories with high spatial and temporal resolution. Researchers have recently demonstrated 3D tracking of several objects in real time, but as the number of objects is increased, real-time tracking becomes impossible due to data transfer and processing bottlenecks. This problem may be solved by using parallel processing. In this paper, a parallel-processing framework has been developed based on frame decomposition and is programmed using the asynchronous object-oriented Charm++ paradigm. This framework can be a key step in achieving a scalable Lagrangian measurement system for particle-tracking velocimetry and may lead to real-time measurement capabilities. The parallel tracking algorithm was evaluated with three data sets including the particle image velocimetry standard 3D images data set #352, a uniform data set for optimal parallel performance and a computational-fluid-dynamics-generated non-uniform data set to test trajectory reconstruction accuracy, consistency with the sequential version and scalability to more than 500 processors. The algorithm showed strong scaling up to 512 processors and no inherent limits of scalability were seen. Ultimately, up to a 200-fold speedup is observed compared to the serial algorithm when 256 processors were used. The parallel algorithm is adaptable and could be easily modified to use any sequential tracking algorithm, which inputs frames of 3D particle location data and outputs particle trajectories

Hydrodynamic interactions in active colloidal crystal microrheology

OpenAIRE

Weeber, R; Harting, JDR Jens

2012-01-01

In dense colloids it is commonly assumed that hydrodynamic interactions do not play a role. However, a found theoretical quantification is often missing. We present computer simulations that are motivated by experiments where a large colloidal particle is dragged through a colloidal crystal. To qualify the influence of long-ranged hydrodynamics, we model the setup by conventional Langevin dynamics simulations and by an improved scheme with limited hydrodynamic interactions. This scheme signif...

hydrodynamic behavior of particles in a Jet flow of a gas fluidized bed

International Nuclear Information System (INIS)

Mirmomen, L.; Alavi, M.

2005-01-01

Numerous investigations have been devoted towards understanding the hydrodynamics of gas jets in fluidized beds. However, most of them address the problem from macroscopic point of view, which does not reveal the true behavior in the jet region at the single particle level. The present work aims to understand the jet behavior from a more fundamental level, i.e. the individual particle level. A thin rectangular gas fluidized bed, constructed from acrylic glass, with a vertical jet nozzle located at the center of the distributor was used in the work. A high speed camera with a speed up to 10,000 frames per second was used to observe the jet behavior . Analysis of large quantity of images allowed determination of solids flux, solids Velocity and solids concentration in the jet region . The model present in this work has shown better agreement with the experimental data in compare with the previous models presented in the literature

Predicting patchy particle crystals: variable box shape simulations and evolutionary algorithms.

Science.gov (United States)

Bianchi, Emanuela; Doppelbauer, Günther; Filion, Laura; Dijkstra, Marjolein; Kahl, Gerhard

2012-06-07

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an approach based on Monte Carlo simulations in the isobaric-isothermal ensemble and (ii) an optimization technique based on ideas of evolutionary algorithms. We show that the two methods are equally successful and provide consistent results on crystalline phases of patchy particle systems.

On Using Particle Finite Element for Hydrodynamics Problems Solving

Directory of Open Access Journals (Sweden)

E. V. Davidova

2015-01-01

Full Text Available The aim of the present research is to develop software for the Particle Finite Element Method (PFEM and its verification on the model problem of viscous incompressible flow simulation in a square cavity. The Lagrangian description of the medium motion is used: the nodes of the finite element mesh move together with the fluid that allows to consider them as particles of the medium. Mesh cells deform when in time-stepping procedure, so it is necessary to reconstruct the mesh to provide stability of the finite element numerical procedure.Meshing algorithm allows us to obtain the mesh, which satisfies the Delaunay criteria: it is called \\the possible triangles method". This algorithm is based on the well-known Fortune method of Voronoi diagram constructing for a certain set of points in the plane. The graphical representation of the possible triangles method is shown. It is suitable to use generalization of Delaunay triangulation in order to construct meshes with polygonal cells in case of multiple nodes close to be lying on the same circle.The viscous incompressible fluid flow is described by the Navier | Stokes equations and the mass conservation equation with certain initial and boundary conditions. A fractional steps method, which allows us to avoid non-physical oscillations of the pressure, provides the timestepping procedure. Using the finite element discretization and the Bubnov | Galerkin method allows us to carry out spatial discretization.For form functions calculation of finite element mesh with polygonal cells, \

Combinatorial Clustering Algorithm of Quantum-Behaved Particle Swarm Optimization and Cloud Model

Directory of Open Access Journals (Sweden)

Mi-Yuan Shan

2013-01-01

Full Text Available We propose a combinatorial clustering algorithm of cloud model and quantum-behaved particle swarm optimization (COCQPSO to solve the stochastic problem. The algorithm employs a novel probability model as well as a permutation-based local search method. We are setting the parameters of COCQPSO based on the design of experiment. In the comprehensive computational study, we scrutinize the performance of COCQPSO on a set of widely used benchmark instances. By benchmarking combinatorial clustering algorithm with state-of-the-art algorithms, we can show that its performance compares very favorably. The fuzzy combinatorial optimization algorithm of cloud model and quantum-behaved particle swarm optimization (FCOCQPSO in vague sets (IVSs is more expressive than the other fuzzy sets. Finally, numerical examples show the clustering effectiveness of COCQPSO and FCOCQPSO clustering algorithms which are extremely remarkable.

A Novel Chaotic Particle Swarm Optimization Algorithm for Parking Space Guidance

Directory of Open Access Journals (Sweden)

Na Dong

2016-01-01

Full Text Available An evolutionary approach of parking space guidance based upon a novel Chaotic Particle Swarm Optimization (CPSO algorithm is proposed. In the newly proposed CPSO algorithm, the chaotic dynamics is combined into the position updating rules of Particle Swarm Optimization to improve the diversity of solutions and to avoid being trapped in the local optima. This novel approach, that combines the strengths of Particle Swarm Optimization and chaotic dynamics, is then applied into the route optimization (RO problem of parking lots, which is an important issue in the management systems of large-scale parking lots. It is used to find out the optimized paths between any source and destination nodes in the route network. Route optimization problems based on real parking lots are introduced for analyzing and the effectiveness and practicability of this novel optimization algorithm for parking space guidance have been verified through the application results.

A Parallel Implementation of a Smoothed Particle Hydrodynamics Method on Graphics Hardware Using the Compute Unified Device Architecture

International Nuclear Information System (INIS)

Wong Unhong; Wong Honcheng; Tang Zesheng

2010-01-01

The smoothed particle hydrodynamics (SPH), which is a class of meshfree particle methods (MPMs), has a wide range of applications from micro-scale to macro-scale as well as from discrete systems to continuum systems. Graphics hardware, originally designed for computer graphics, now provide unprecedented computational power for scientific computation. Particle system needs a huge amount of computations in physical simulation. In this paper, an efficient parallel implementation of a SPH method on graphics hardware using the Compute Unified Device Architecture is developed for fluid simulation. Comparing to the corresponding CPU implementation, our experimental results show that the new approach allows significant speedups of fluid simulation through handling huge amount of computations in parallel on graphics hardware.

Parallel Global Optimization with the Particle Swarm Algorithm (Preprint)

National Research Council Canada - National Science Library

Schutte, J. F; Reinbolt, J. A; Fregly, B. J; Haftka, R. T; George, A. D

2004-01-01

.... To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the Particle Swarm Optimization (PSO) algorithm...

An integrated Boltzmann+hydrodynamics approach to heavy ion collisions

International Nuclear Information System (INIS)

Petersen, Hannah

2009-01-01

In this thesis the first fully integrated Boltzmann+hydrodynamics approach to relativistic heavy ion reactions has been developed. After a short introduction that motivates the study of heavy ion reactions as the tool to get insights about the QCD phase diagram, the most important theoretical approaches to describe the system are reviewed. The hadron-string transport approach that this work is based on is the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) approach. Predictions for the charged particle multiplicities at LHC energies are made. The next step is the development of a new framework to calculate the baryon number density in a transport approach. Time evolutions of the net baryon number and the quark density have been calculated at AGS, SPS and RHIC energies. Studies of phase diagram trajectories using hydrodynamics are performed. The hybrid approach that has been developed as the main part of this thesis is based on the UrQMD transport approach with an intermediate hydrodynamical evolution for the hot and dense stage of the collision. The full (3+1) dimensional ideal relativistic one fluid dynamics evolution is solved using the SHASTA algorithm. Three different equations of state have been used, namely a hadron gas equation of state without a QGP phase transition, a chiral EoS and a bag model EoS including a strong first order phase transition. For the freeze-out transition from hydrodynamics to the cascade calculation two different set-ups are employed. The parameter dependences of the model are investigated and the time evolution of different quantities is explored. The hybrid model calculation is able to reproduce the experimentally measured integrated as well as transverse momentum dependent v 2 values for charged particles. The multiplicity and mean transverse mass excitation function is calculated for pions, protons and kaons in the energy range from E lab =2-160 A GeV. The HBT correlation of the negatively charged pion source created in

An integrated Boltzmann+hydrodynamics approach to heavy ion collisions

Energy Technology Data Exchange (ETDEWEB)

Petersen, Hannah

2009-04-22

In this thesis the first fully integrated Boltzmann+hydrodynamics approach to relativistic heavy ion reactions has been developed. After a short introduction that motivates the study of heavy ion reactions as the tool to get insights about the QCD phase diagram, the most important theoretical approaches to describe the system are reviewed. The hadron-string transport approach that this work is based on is the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) approach. Predictions for the charged particle multiplicities at LHC energies are made. The next step is the development of a new framework to calculate the baryon number density in a transport approach. Time evolutions of the net baryon number and the quark density have been calculated at AGS, SPS and RHIC energies. Studies of phase diagram trajectories using hydrodynamics are performed. The hybrid approach that has been developed as the main part of this thesis is based on the UrQMD transport approach with an intermediate hydrodynamical evolution for the hot and dense stage of the collision. The full (3+1) dimensional ideal relativistic one fluid dynamics evolution is solved using the SHASTA algorithm. Three different equations of state have been used, namely a hadron gas equation of state without a QGP phase transition, a chiral EoS and a bag model EoS including a strong first order phase transition. For the freeze-out transition from hydrodynamics to the cascade calculation two different set-ups are employed. The parameter dependences of the model are investigated and the time evolution of different quantities is explored. The hybrid model calculation is able to reproduce the experimentally measured integrated as well as transverse momentum dependent v{sub 2} values for charged particles. The multiplicity and mean transverse mass excitation function is calculated for pions, protons and kaons in the energy range from E{sub lab}=2-160 A GeV. The HBT correlation of the negatively charged pion source

Hydrodynamic interactions in active colloidal crystal microrheology.

Science.gov (United States)

Weeber, R; Harting, J

2012-11-01

In dense colloids it is commonly assumed that hydrodynamic interactions do not play a role. However, a found theoretical quantification is often missing. We present computer simulations that are motivated by experiments where a large colloidal particle is dragged through a colloidal crystal. To qualify the influence of long-ranged hydrodynamics, we model the setup by conventional Langevin dynamics simulations and by an improved scheme with limited hydrodynamic interactions. This scheme significantly improves our results and allows to show that hydrodynamics strongly impacts the development of defects, the crystal regeneration, as well as the jamming behavior.

Particle tracing in the magnetosphere: New algorithms and results

International Nuclear Information System (INIS)

Sheldon, R.B.; Gaffey, J.D. Jr.

1993-01-01

The authors present new algorithms for calculating charged-particle trajectories in realistic magnetospheric fields in fast and efficient manners. The scheme is based on a hamiltonian energy conservation principle. It requires that particles conserve the first two adiabatic invariants, and thus also conserve energy. It is applicable for particles ranging in energy from 0.01 to 100 keV, having arbitrary charge, and pitch angle. In addition to rapid particle trajectory calculations, it allows topological boundaries to be located efficiently. The results can be combined with fluid models to provide quantitative models of the time development of the whole convecting plasma model

Hybrid particle swarm optimization algorithm and its application in nuclear engineering

International Nuclear Information System (INIS)

Liu, C.Y.; Yan, C.Q.; Wang, J.J.

2014-01-01

Highlights: • We propose a hybrid particle swarm optimization algorithm (HPSO). • Modified Nelder–Mead simplex search method is applied in HPSO. • The algorithm has a high search precision and rapidly calculation speed. • HPSO can be used in the nuclear engineering optimization design problems. - Abstract: A hybrid particle swarm optimization algorithm with a feasibility-based rule for solving constrained optimization problems has been developed in this research. Firstly, the global optimal solution zone can be obtained through particle swarm optimization process, and then the refined search of the global optimal solution will be achieved through the modified Nelder–Mead simplex algorithm. Simulations based on two well-studied benchmark problems demonstrate the proposed algorithm will be an efficient alternative to solving constrained optimization problems. The vertical electrical heating pressurizer is one of the key components in reactor coolant system. The mathematical model of pressurizer has been established in steady state. The optimization design of pressurizer weight has been carried out through HPSO algorithm. The results show the pressurizer weight can be reduced by 16.92%. The thermal efficiencies of conventional PWR nuclear power plants are about 31–35% so far, which are much lower than fossil fueled plants based in a steam cycle as PWR. The thermal equilibrium mathematic model for nuclear power plant secondary loop has been established. An optimization case study has been conducted to improve the efficiency of the nuclear power plant with the proposed algorithm. The results show the thermal efficiency is improved by 0.5%

A nowcasting technique based on application of the particle filter blending algorithm

Science.gov (United States)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

Large-Scale Description of Interacting One-Dimensional Bose Gases: Generalized Hydrodynamics Supersedes Conventional Hydrodynamics

Science.gov (United States)

Doyon, Benjamin; Dubail, Jérôme; Konik, Robert; Yoshimura, Takato

2017-11-01

The theory of generalized hydrodynamics (GHD) was recently developed as a new tool for the study of inhomogeneous time evolution in many-body interacting systems with infinitely many conserved charges. In this Letter, we show that it supersedes the widely used conventional hydrodynamics (CHD) of one-dimensional Bose gases. We illustrate this by studying "nonlinear sound waves" emanating from initial density accumulations in the Lieb-Liniger model. We show that, at zero temperature and in the absence of shocks, GHD reduces to CHD, thus for the first time justifying its use from purely hydrodynamic principles. We show that sharp profiles, which appear in finite times in CHD, immediately dissolve into a higher hierarchy of reductions of GHD, with no sustained shock. CHD thereon fails to capture the correct hydrodynamics. We establish the correct hydrodynamic equations, which are finite-dimensional reductions of GHD characterized by multiple, disjoint Fermi seas. We further verify that at nonzero temperature, CHD fails at all nonzero times. Finally, we numerically confirm the emergence of hydrodynamics at zero temperature by comparing its predictions with a full quantum simulation performed using the NRG-TSA-abacus algorithm. The analysis is performed in the full interaction range, and is not restricted to either weak- or strong-repulsion regimes.

Hydrodynamics in high-energy nuclear collisions. Quarterly report 3. quarter 1987

International Nuclear Information System (INIS)

Kataja, Markku.

1989-05-01

This thesis is a review of six publications in which we make use of relativistic hydrodynamics to solve the evolution of matter produced in extremely energetic nucleus-nucleus collisions. In the first one of these papers we study the thermodynamics, the hydrodynamics and the decoupling conditions of such matter. We discuss the initial conditions for the flow, the hydrodynamic equations for the transverse expansion of matter assuming cylindrical symmetry and longitudinal boost invariance and finally present a numeric algorithm, which we use to integrate these equations. In the subsequent three papers this framework is utilized to calculate the transverse momentum spectra of hadrons, the dilepon production and the abundance of strange particles in the final state. The bag model equation of state is used to simulate the first-order phase transition between baryonless hadronic matter and quark-gluon plasma. In the fifth paper we include the particle production from decaying color electric field according to the flux tube model for heavy ion collisions. The hadronization is incorporated by introducing an equilibrium 'mixed state' of hadrons gas, plasma and the color field in analogy to the mixed phase described by the ordinary bag model equation of state. In the last paper I apply a 1+2 dimensional numeric code to analyze a 1+3 dimensional cylindrically symmetric flow of matter assumed to be formed in a central O+Pb collision at 200 GeV/nucleon. The flow data is used to calculte the pseudorapidity distribution of transverse energy for the produced pions

Explicit high-order non-canonical symplectic particle-in-cell algorithms for Vlasov-Maxwell systems

International Nuclear Information System (INIS)

Xiao, Jianyuan; Liu, Jian; He, Yang; Zhang, Ruili; Qin, Hong; Sun, Yajuan

2015-01-01

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithms conserve a discrete non-canonical symplectic structure derived from the Lagrangian of the particle-field system, which is naturally discrete in particles. The electromagnetic field is spatially discretized using the method of discrete exterior calculus with high-order interpolating differential forms for a cubic grid. The resulting time-domain Lagrangian assumes a non-canonical symplectic structure. It is also gauge invariant and conserves charge. The system is then solved using a structure-preserving splitting method discovered by He et al. [preprint http://arxiv.org/abs/arXiv:1505.06076 (2015)], which produces five exactly soluble sub-systems, and high-order structure-preserving algorithms follow by combinations. The explicit, high-order, and conservative nature of the algorithms is especially suitable for long-term simulations of particle-field systems with extremely large number of degrees of freedom on massively parallel supercomputers. The algorithms have been tested and verified by the two physics problems, i.e., the nonlinear Landau damping and the electron Bernstein wave

Explicit high-order non-canonical symplectic particle-in-cell algorithms for Vlasov-Maxwell systems

Energy Technology Data Exchange (ETDEWEB)

Xiao, Jianyuan [School of Nuclear Science and Technology and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; Key Laboratory of Geospace Environment, CAS, Hefei, Anhui 230026, China; Qin, Hong [School of Nuclear Science and Technology and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543, USA; Liu, Jian [School of Nuclear Science and Technology and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; Key Laboratory of Geospace Environment, CAS, Hefei, Anhui 230026, China; He, Yang [School of Nuclear Science and Technology and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; Key Laboratory of Geospace Environment, CAS, Hefei, Anhui 230026, China; Zhang, Ruili [School of Nuclear Science and Technology and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; Key Laboratory of Geospace Environment, CAS, Hefei, Anhui 230026, China; Sun, Yajuan [LSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, P.O. Box 2719, Beijing 100190, China

2015-11-01

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithms conserve a discrete non-canonical symplectic structure derived from the Lagrangian of the particle-field system, which is naturally discrete in particles. The electromagnetic field is spatially discretized using the method of discrete exterior calculus with high-order interpolating differential forms for a cubic grid. The resulting time-domain Lagrangian assumes a non-canonical symplectic structure. It is also gauge invariant and conserves charge. The system is then solved using a structure-preserving splitting method discovered by He et al. [preprint arXiv: 1505.06076 (2015)], which produces five exactly soluble sub-systems, and high-order structure-preserving algorithms follow by combinations. The explicit, high-order, and conservative nature of the algorithms is especially suitable for long-term simulations of particle-field systems with extremely large number of degrees of freedom on massively parallel supercomputers. The algorithms have been tested and verified by the two physics problems, i.e., the nonlinear Landau damping and the electron Bernstein wave. (C) 2015 AIP Publishing LLC.

Use of Genetic Algorithms to solve Inverse Problems in Relativistic Hydrodynamics

Science.gov (United States)

Guzmán, F. S.; González, J. A.

2018-04-01

We present the use of Genetic Algorithms (GAs) as a strategy to solve inverse problems associated with models of relativistic hydrodynamics. The signal we consider to emulate an observation is the density of a relativistic gas, measured at a point where a shock is traveling. This shock is generated numerically out of a Riemann problem with mildly relativistic conditions. The inverse problem we propose is the prediction of the initial conditions of density, velocity and pressure of the Riemann problem that gave origin to that signal. For this we use the density, velocity and pressure of the gas at both sides of the discontinuity, as the six genes of an organism, initially with random values within a tolerance. We then prepare an initial population of N of these organisms and evolve them using methods based on GAs. In the end, the organism with the best fitness of each generation is compared to the signal and the process ends when the set of initial conditions of the organisms of a later generation fit the Signal within a tolerance.

Improved multi-objective clustering algorithm using particle swarm optimization.

Science.gov (United States)

Gong, Congcong; Chen, Haisong; He, Weixiong; Zhang, Zhanliang

2017-01-01

Multi-objective clustering has received widespread attention recently, as it can obtain more accurate and reasonable solution. In this paper, an improved multi-objective clustering framework using particle swarm optimization (IMCPSO) is proposed. Firstly, a novel particle representation for clustering problem is designed to help PSO search clustering solutions in continuous space. Secondly, the distribution of Pareto set is analyzed. The analysis results are applied to the leader selection strategy, and make algorithm avoid trapping in local optimum. Moreover, a clustering solution-improved method is proposed, which can increase the efficiency in searching clustering solution greatly. In the experiments, 28 datasets are used and nine state-of-the-art clustering algorithms are compared, the proposed method is superior to other approaches in the evaluation index ARI.

Particle identification algorithms for the PANDA Endcap Disc DIRC

Science.gov (United States)

Schmidt, M.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwarz, C.; Schwiening, J.; Traxler, M.; Böhm, M.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Merle, O.; Rieke, J.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.

2017-12-01

The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5o to 22o. This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

GPU-accelerated algorithms for many-particle continuous-time quantum walks

Science.gov (United States)

Piccinini, Enrico; Benedetti, Claudia; Siloi, Ilaria; Paris, Matteo G. A.; Bordone, Paolo

2017-06-01

Many-particle continuous-time quantum walks (CTQWs) represent a resource for several tasks in quantum technology, including quantum search algorithms and universal quantum computation. In order to design and implement CTQWs in a realistic scenario, one needs effective simulation tools for Hamiltonians that take into account static noise and fluctuations in the lattice, i.e. Hamiltonians containing stochastic terms. To this aim, we suggest a parallel algorithm based on the Taylor series expansion of the evolution operator, and compare its performances with those of algorithms based on the exact diagonalization of the Hamiltonian or a 4th order Runge-Kutta integration. We prove that both Taylor-series expansion and Runge-Kutta algorithms are reliable and have a low computational cost, the Taylor-series expansion showing the additional advantage of a memory allocation not depending on the precision of calculation. Both algorithms are also highly parallelizable within the SIMT paradigm, and are thus suitable for GPGPU computing. In turn, we have benchmarked 4 NVIDIA GPUs and 3 quad-core Intel CPUs for a 2-particle system over lattices of increasing dimension, showing that the speedup provided by GPU computing, with respect to the OPENMP parallelization, lies in the range between 8x and (more than) 20x, depending on the frequency of post-processing. GPU-accelerated codes thus allow one to overcome concerns about the execution time, and make it possible simulations with many interacting particles on large lattices, with the only limit of the memory available on the device.

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

Science.gov (United States)

Wang, Ershen; Jia, Chaoying; Tong, Gang; Qu, Pingping; Lan, Xiaoyu; Pang, Tao

2018-03-01

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.

IMPLANT-ASSOCIATED PATHOLOGY: AN ALGORITHM FOR IDENTIFYING PARTICLES IN HISTOPATHOLOGIC SYNOVIALIS/SLIM DIAGNOSTICS

Directory of Open Access Journals (Sweden)

V. Krenn

2014-01-01

Full Text Available In histopathologic SLIM diagnostic (synovial-like interface membrane, SLIM apart from diagnosing periprosthetic infection particle identification has an important role to play. The differences in particle pathogenesis and variability of materials in endoprosthetics explain the particle heterogeneity that hampers the diagnostic identification of particles. For this reason, a histopathological particle algorithm has been developed. With minimal methodical complexity this histopathological particle algorithm offers a guide to prosthesis material-particle identification. Light microscopic-morphological as well as enzyme-histochemical characteristics and polarization-optical proporties have set and particles are defined by size (microparticles, macroparticles and supra- macroparticles and definitely characterized in accordance with a dichotomous principle. Based on these criteria, identification and validation of the particles was carried out in 120 joint endoprosthesis pathological cases. A histopathological particle score (HPS is proposed that summarizes the most important information for the orthopedist, material scientist and histopathologist concerning particle identification in the SLIM.

The Optimal Wavelengths for Light Absorption Spectroscopy Measurements Based on Genetic Algorithm-Particle Swarm Optimization

Science.gov (United States)

Tang, Ge; Wei, Biao; Wu, Decao; Feng, Peng; Liu, Juan; Tang, Yuan; Xiong, Shuangfei; Zhang, Zheng

2018-03-01

To select the optimal wavelengths in the light extinction spectroscopy measurement, genetic algorithm-particle swarm optimization (GAPSO) based on genetic algorithm (GA) and particle swarm optimization (PSO) is adopted. The change of the optimal wavelength positions in different feature size parameters and distribution parameters is evaluated. Moreover, the Monte Carlo method based on random probability is used to identify the number of optimal wavelengths, and good inversion effects of the particle size distribution are obtained. The method proved to have the advantage of resisting noise. In order to verify the feasibility of the algorithm, spectra with bands ranging from 200 to 1000 nm are computed. Based on this, the measured data of standard particles are used to verify the algorithm.

Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

Science.gov (United States)

Rahmalia, Dinita

2017-08-01

Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

Advective isotope transport by mixing cell and particle tracking algorithms

International Nuclear Information System (INIS)

Tezcan, L.; Meric, T.

1999-01-01

The 'mixing cell' algorithm of the environmental isotope data evaluation is integrated with the three dimensional finite difference ground water flow model (MODFLOW) to simulate the advective isotope transport and the approach is compared with the 'particle tracking' algorithm of the MOC3D, that simulates three-dimensional solute transport with the method of characteristics technique

Algorithms for the optimization of RBE-weighted dose in particle therapy.

Science.gov (United States)

Horcicka, M; Meyer, C; Buschbacher, A; Durante, M; Krämer, M

2013-01-21

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Improved multi-objective clustering algorithm using particle swarm optimization.

Directory of Open Access Journals (Sweden)

Congcong Gong

Full Text Available Multi-objective clustering has received widespread attention recently, as it can obtain more accurate and reasonable solution. In this paper, an improved multi-objective clustering framework using particle swarm optimization (IMCPSO is proposed. Firstly, a novel particle representation for clustering problem is designed to help PSO search clustering solutions in continuous space. Secondly, the distribution of Pareto set is analyzed. The analysis results are applied to the leader selection strategy, and make algorithm avoid trapping in local optimum. Moreover, a clustering solution-improved method is proposed, which can increase the efficiency in searching clustering solution greatly. In the experiments, 28 datasets are used and nine state-of-the-art clustering algorithms are compared, the proposed method is superior to other approaches in the evaluation index ARI.

Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

Directory of Open Access Journals (Sweden)

Wei Li

2015-01-01

Full Text Available We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

Science.gov (United States)

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-05-04

Particle swarm optimization is a powerful metaheuristic population-based global optimization algorithm. However, when applied to non-separable objective functions its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant particle swarm optimization algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates a superior performance across several nonlinear, multimodal benchmark functions compared to the rotation-invariant Particle Swam Optimization (PSO) algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in ReaxFF-lg reactive force field is carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents a better performance compared to a Genetic Algorithm optimization method in the optimization of a ReaxFF-lg correction model parameters. The computational framework is implemented in a standalone C++ code that allows a straightforward development of ReaxFF reactive force fields.

A purely Lagrangian method for simulating the shallow water equations on a sphere using smooth particle hydrodynamics

Science.gov (United States)

Capecelatro, Jesse

2018-03-01

It has long been suggested that a purely Lagrangian solution to global-scale atmospheric/oceanic flows can potentially outperform tradition Eulerian schemes. Meanwhile, a demonstration of a scalable and practical framework remains elusive. Motivated by recent progress in particle-based methods when applied to convection dominated flows, this work presents a fully Lagrangian method for solving the inviscid shallow water equations on a rotating sphere in a smooth particle hydrodynamics framework. To avoid singularities at the poles, the governing equations are solved in Cartesian coordinates, augmented with a Lagrange multiplier to ensure that fluid particles are constrained to the surface of the sphere. An underlying grid in spherical coordinates is used to facilitate efficient neighbor detection and parallelization. The method is applied to a suite of canonical test cases, and conservation, accuracy, and parallel performance are assessed.

Moving charged particles in lattice Boltzmann-based electrokinetics

Science.gov (United States)

Kuron, Michael; Rempfer, Georg; Schornbaum, Florian; Bauer, Martin; Godenschwager, Christian; Holm, Christian; de Graaf, Joost

2016-12-01

The motion of ionic solutes and charged particles under the influence of an electric field and the ensuing hydrodynamic flow of the underlying solvent is ubiquitous in aqueous colloidal suspensions. The physics of such systems is described by a coupled set of differential equations, along with boundary conditions, collectively referred to as the electrokinetic equations. Capuani et al. [J. Chem. Phys. 121, 973 (2004)] introduced a lattice-based method for solving this system of equations, which builds upon the lattice Boltzmann algorithm for the simulation of hydrodynamic flow and exploits computational locality. However, thus far, a description of how to incorporate moving boundary conditions into the Capuani scheme has been lacking. Moving boundary conditions are needed to simulate multiple arbitrarily moving colloids. In this paper, we detail how to introduce such a particle coupling scheme, based on an analogue to the moving boundary method for the pure lattice Boltzmann solver. The key ingredients in our method are mass and charge conservation for the solute species and a partial-volume smoothing of the solute fluxes to minimize discretization artifacts. We demonstrate our algorithm's effectiveness by simulating the electrophoresis of charged spheres in an external field; for a single sphere we compare to the equivalent electro-osmotic (co-moving) problem. Our method's efficiency and ease of implementation should prove beneficial to future simulations of the dynamics in a wide range of complex nanoscopic and colloidal systems that were previously inaccessible to lattice-based continuum algorithms.

Hydrodynamic Cavitation-Assisted Synthesis of Nanocalcite

Directory of Open Access Journals (Sweden)

Shirish H. Sonawane

2010-01-01

Full Text Available A systematic study was made on the synthesis of nanocalcite using a hydrodynamic cavitation reactor. The effects of various parameters such as diameter and geometry of orifice, CO2 flow rate, and Ca(OH2 concentration were investigated. It was observed that the orifice diameter and its geometry had significant effect on the carbonation process. The reaction rate was significantly faster than that observed in a conventional carbonation process. The particle size was significantly affected by the reactor geometry. The results showed that an orifice with 5 holes of 1 mm size resulted in the particle size reduction to 37 nm. The experimental investigation reveals that hydrodynamic cavitation may be more energy efficient.

On kinetic Boltzmann equations and related hydrodynamic flows with dry viscosity

Directory of Open Access Journals (Sweden)

Nikolai N. Bogoliubov (Jr.

2007-01-01

Full Text Available A two-component particle model of Boltzmann-Vlasov type kinetic equations in the form of special nonlinear integro-differential hydrodynamic systems on an infinite-dimensional functional manifold is discussed. We show that such systems are naturally connected with the nonlinear kinetic Boltzmann-Vlasov equations for some one-dimensional particle flows with pointwise interaction potential between particles. A new type of hydrodynamic two-component Benney equations is constructed and their Hamiltonian structure is analyzed.

An Adaptive Cultural Algorithm with Improved Quantum-behaved Particle Swarm Optimization for Sonar Image Detection.

Science.gov (United States)

Wang, Xingmei; Hao, Wenqian; Li, Qiming

2017-12-18

This paper proposes an adaptive cultural algorithm with improved quantum-behaved particle swarm optimization (ACA-IQPSO) to detect the underwater sonar image. In the population space, to improve searching ability of particles, iterative times and the fitness value of particles are regarded as factors to adaptively adjust the contraction-expansion coefficient of the quantum-behaved particle swarm optimization algorithm (QPSO). The improved quantum-behaved particle swarm optimization algorithm (IQPSO) can make particles adjust their behaviours according to their quality. In the belief space, a new update strategy is adopted to update cultural individuals according to the idea of the update strategy in shuffled frog leaping algorithm (SFLA). Moreover, to enhance the utilization of information in the population space and belief space, accept function and influence function are redesigned in the new communication protocol. The experimental results show that ACA-IQPSO can obtain good clustering centres according to the grey distribution information of underwater sonar images, and accurately complete underwater objects detection. Compared with other algorithms, the proposed ACA-IQPSO has good effectiveness, excellent adaptability, a powerful searching ability and high convergence efficiency. Meanwhile, the experimental results of the benchmark functions can further demonstrate that the proposed ACA-IQPSO has better searching ability, convergence efficiency and stability.

Hydrodynamic cavitation: a bottom-up approach to liquid aeration

NARCIS (Netherlands)

Raut, J.S.; Stoyanov, S.D.; Duggal, C.; Pelan, E.G.; Arnaudov, L.N.; Naik, V.M.

2012-01-01

We report the use of hydrodynamic cavitation as a novel, bottom-up method for continuous creation of foams comprising of air microbubbles in aqueous systems containing surface active ingredients, like proteins or particles. The hydrodynamic cavitation was created using a converging-diverging nozzle.

An Improved Particle Swarm Optimization Algorithm and Its Application in the Community Division

Directory of Open Access Journals (Sweden)

Jiang Hao

2016-01-01

Full Text Available With the deepening of the research on complex networks, the method of detecting and classifying social network is springing up. In this essay, the basic particle swarm algorithm is improved based on the GN algorithm. Modularity is taken as a measure of community division [1]. In view of the dynamic network community division, scrolling calculation method is put forward. Experiments show that using the improved particle swarm optimization algorithm can improve the accuracy of the community division and can also get higher value of the modularity in the dynamic community

Noise effect in an improved conjugate gradient algorithm to invert particle size distribution and the algorithm amendment.

Science.gov (United States)

Wei, Yongjie; Ge, Baozhen; Wei, Yaolin

2009-03-20

In general, model-independent algorithms are sensitive to noise during laser particle size measurement. An improved conjugate gradient algorithm (ICGA) that can be used to invert particle size distribution (PSD) from diffraction data is presented. By use of the ICGA to invert simulated data with multiplicative or additive noise, we determined that additive noise is the main factor that induces distorted results. Thus the ICGA is amended by introduction of an iteration step-adjusting parameter and is used experimentally on simulated data and some samples. The experimental results show that the sensitivity of the ICGA to noise is reduced and the inverted results are in accord with the real PSD.

Particle Identification algorithm for the CLIC ILD and CLIC SiD detectors

CERN Document Server

Nardulli, J

2011-01-01

This note describes the algorithm presently used to determine the particle identification performance for single particles for the CLIC ILD and CLIC SiD detector concepts as prepared in the CLIC Conceptual Design Report.

MULTIGRAIN: a smoothed particle hydrodynamic algorithm for multiple small dust grains and gas

Science.gov (United States)

Hutchison, Mark; Price, Daniel J.; Laibe, Guillaume

2018-05-01

We present a new algorithm, MULTIGRAIN, for modelling the dynamics of an entire population of small dust grains immersed in gas, typical of conditions that are found in molecular clouds and protoplanetary discs. The MULTIGRAIN method is more accurate than single-phase simulations because the gas experiences a backreaction from each dust phase and communicates this change to the other phases, thereby indirectly coupling the dust phases together. The MULTIGRAIN method is fast, explicit and low storage, requiring only an array of dust fractions and their derivatives defined for each resolution element.

Research on Multiple Particle Swarm Algorithm Based on Analysis of Scientific Materials

Directory of Open Access Journals (Sweden)

Zhao Hongwei

2017-01-01

Full Text Available This paper proposed an improved particle swarm optimization algorithm based on analysis of scientific materials. The core thesis of MPSO (Multiple Particle Swarm Algorithm is to improve the single population PSO to interactive multi-swarms, which is used to settle the problem of being trapped into local minima during later iterations because it is lack of diversity. The simulation results show that the convergence rate is fast and the search performance is good, and it has achieved very good results.

Hydrodynamically enforced entropic current of Brownian particles with a transverse gravitational force

Science.gov (United States)

Li, Feng-guo; Ai, Bao-quan

2014-04-01

Transport of overdamped Brownian particles in a periodic hydrodynamical channel is investigated in the presence of an asymmetric unbiased force, a transverse gravitational force, and a pressure-driven flow. With the help of the generalized Fick-Jacobs approach, we obtain an analytical expression for the directed current and the generalized potential of mean force. It is found that, when the transverse gravitational force is larger than a certain value, the current is suppressed. Moreover, when the temporal asymmetry parameter of the unbiased force is negative, the current is always negative. However, when the temporal asymmetry parameter is positive, the transverse gravitational force and the pressure drop not only determine the direction of the current but also affect its amplitude. In particular, the competition between the asymmetric unbiased force and the pressure drop can result in multiple current reversals.

Hydrodynamically enforced entropic current of Brownian particles with a transverse gravitational force

International Nuclear Information System (INIS)

Li, Feng-guo; Ai, Bao-quan

2014-01-01

Transport of overdamped Brownian particles in a periodic hydrodynamical channel is investigated in the presence of an asymmetric unbiased force, a transverse gravitational force, and a pressure-driven flow. With the help of the generalized Fick–Jacobs approach, we obtain an analytical expression for the directed current and the generalized potential of mean force. It is found that, when the transverse gravitational force is larger than a certain value, the current is suppressed. Moreover, when the temporal asymmetry parameter of the unbiased force is negative, the current is always negative. However, when the temporal asymmetry parameter is positive, the transverse gravitational force and the pressure drop not only determine the direction of the current but also affect its amplitude. In particular, the competition between the asymmetric unbiased force and the pressure drop can result in multiple current reversals. (paper)

An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm.

Science.gov (United States)

Zhu, Qingling; Lin, Qiuzhen; Chen, Weineng; Wong, Ka-Chun; Coello Coello, Carlos A; Li, Jianqiang; Chen, Jianyong; Zhang, Jun

2017-09-01

The selection of swarm leaders (i.e., the personal best and global best), is important in the design of a multiobjective particle swarm optimization (MOPSO) algorithm. Such leaders are expected to effectively guide the swarm to approach the true Pareto optimal front. In this paper, we present a novel external archive-guided MOPSO algorithm (AgMOPSO), where the leaders for velocity update are all selected from the external archive. In our algorithm, multiobjective optimization problems (MOPs) are transformed into a set of subproblems using a decomposition approach, and then each particle is assigned accordingly to optimize each subproblem. A novel archive-guided velocity update method is designed to guide the swarm for exploration, and the external archive is also evolved using an immune-based evolutionary strategy. These proposed approaches speed up the convergence of AgMOPSO. The experimental results fully demonstrate the superiority of our proposed AgMOPSO in solving most of the test problems adopted, in terms of two commonly used performance measures. Moreover, the effectiveness of our proposed archive-guided velocity update method and immune-based evolutionary strategy is also experimentally validated on more than 30 test MOPs.

A Parallel Adaptive Particle Swarm Optimization Algorithm for Economic/Environmental Power Dispatch

Directory of Open Access Journals (Sweden)

Jinchao Li

2012-01-01

Full Text Available A parallel adaptive particle swarm optimization algorithm (PAPSO is proposed for economic/environmental power dispatch, which can overcome the premature characteristic, the slow-speed convergence in the late evolutionary phase, and lacking good direction in particles’ evolutionary process. A search population is randomly divided into several subpopulations. Then for each subpopulation, the optimal solution is searched synchronously using the proposed method, and thus parallel computing is realized. To avoid converging to a local optimum, a crossover operator is introduced to exchange the information among the subpopulations and the diversity of population is sustained simultaneously. Simulation results show that the proposed algorithm can effectively solve the economic/environmental operation problem of hydropower generating units. Performance comparisons show that the solution from the proposed method is better than those from the conventional particle swarm algorithm and other optimization algorithms.

A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

Directory of Open Access Journals (Sweden)

Weitian Lin

2014-01-01

Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

Behavior of passive admixture in a vortical hydrodynamic field

Directory of Open Access Journals (Sweden)

R.O.Bobrov

2006-01-01

Full Text Available The motion of passive admixture of spherical particles in the stationary hydrodynamic field of a swirling flow is studied. A spherical particle of a given mass in the hydrodynamic field of a swirling flow is located on a certain circular orbit, where the centrifugal force is compensated by the radial drag force due to the sink. This leads to the separation of the host fluid and admixture. A theory of Brownian motion of admixture in dilute solutions with a non-uniform flow is constructed.

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

Science.gov (United States)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

An algorithm for predicting the hydrodynamic and mass transfer parameters in bubble column and slurry bubble column reactors

Energy Technology Data Exchange (ETDEWEB)

Lemoine, Romain; Behkish, Arsam; Sehabiague, Laurent; Heintz, Yannick J.; Morsi, Badie I. [Chemical and Petroleum Engineering Department, University of Pittsburgh, Pittsburgh, PA 15261 (United States); Oukaci, Rachid [Energy Technology Partners, Pittsburgh, PA 15238 (United States)

2008-04-15

A large number of experimental data points obtained in our laboratory as well as from the literature, covering wide ranges of reactor geometry (column diameter, gas distributor type/open area), physicochemical properties (liquid and gas densities and molecular weights, liquid viscosity and surface tension, gas diffusivity, solid particles size/density), and operating variables (superficial gas velocity, temperature and pressure, solid loading, impurities concentration, mixtures) were used to develop empirical as well as Back-Propagation Neural Network (BPNN) correlations in order to predict the hydrodynamic and mass transfer parameters in bubble column reactors (BCRs) and slurry bubble column reactors (SBCRs). The empirical and BPNN correlations developed were incorporated in an algorithm for predicting gas holdups ({epsilon}{sub G}, {epsilon}{sub G-Small}, {epsilon}{sub G-Large}); volumetric liquid-side mass transfer coefficients (k{sub L}a, k{sub L}a{sub -Small,} k{sub L}a{sub -Large}); Sauter mean bubble diameters (d{sub S}, d{sub S-Small}, d{sub S-Large}){sub ;} gas-liquid interfacial areas (a, a{sub Small}, a{sub Large}); and liquid-side mass transfer coefficients (k{sub L}, k{sub L-Large}, k{sub L-Small}) for total, small and large gas bubbles in BCRs and SBCRs. The developed algorithm was used to predict the effects of reactor diameter and solid (alumina) loading on the hydrodynamic and mass transfer parameters in the Fisher-Tropsch (F-T) synthesis for the hydrogenation of carbon monoxide in a SBCR, and to predict the effects of presence of organic impurities (which decrease the liquid surface tension) and air superficial mass velocity in the Loprox process for the wet air oxidation of organic pollutants in a BCR. In the F-T process, the predictions showed that increasing the reactor diameter from 0.1 to 7.0 m and/or increasing the alumina loading from 25 to 50 wt.% significantly decreased {epsilon}{sub G,} k{sub L}a{sub H2} and k{sub L}a{sub CO} and

Coupled incompressible Smoothed Particle Hydrodynamics model for continuum-based modelling sediment transport

Science.gov (United States)

Pahar, Gourabananda; Dhar, Anirban

2017-04-01

A coupled solenoidal Incompressible Smoothed Particle Hydrodynamics (ISPH) model is presented for simulation of sediment displacement in erodible bed. The coupled framework consists of two separate incompressible modules: (a) granular module, (b) fluid module. The granular module considers a friction based rheology model to calculate deviatoric stress components from pressure. The module is validated for Bagnold flow profile and two standardized test cases of sediment avalanching. The fluid module resolves fluid flow inside and outside porous domain. An interaction force pair containing fluid pressure, viscous term and drag force acts as a bridge between two different flow modules. The coupled model is validated against three dambreak flow cases with different initial conditions of movable bed. The simulated results are in good agreement with experimental data. A demonstrative case considering effect of granular column failure under full/partial submergence highlights the capability of the coupled model for application in generalized scenario.

Variational Algorithms for Test Particle Trajectories

Science.gov (United States)

Ellison, C. Leland; Finn, John M.; Qin, Hong; Tang, William M.

2015-11-01

The theory of variational integration provides a novel framework for constructing conservative numerical methods for magnetized test particle dynamics. The retention of conservation laws in the numerical time advance captures the correct qualitative behavior of the long time dynamics. For modeling the Lorentz force system, new variational integrators have been developed that are both symplectic and electromagnetically gauge invariant. For guiding center test particle dynamics, discretization of the phase-space action principle yields multistep variational algorithms, in general. Obtaining the desired long-term numerical fidelity requires mitigation of the multistep method's parasitic modes or applying a discretization scheme that possesses a discrete degeneracy to yield a one-step method. Dissipative effects may be modeled using Lagrange-D'Alembert variational principles. Numerical results will be presented using a new numerical platform that interfaces with popular equilibrium codes and utilizes parallel hardware to achieve reduced times to solution. This work was supported by DOE Contract DE-AC02-09CH11466.

The Improved Locating Algorithm of Particle Filter Based on ROS Robot

Science.gov (United States)

Fang, Xun; Fu, Xiaoyang; Sun, Ming

2018-03-01

This paperanalyzes basic theory and primary algorithm of the real-time locating system and SLAM technology based on ROS system Robot. It proposes improved locating algorithm of particle filter effectively reduces the matching time of laser radar and map, additional ultra-wideband technology directly accelerates the global efficiency of FastSLAM algorithm, which no longer needs searching on the global map. Meanwhile, the re-sampling has been largely reduced about 5/6 that directly cancels the matching behavior on Roboticsalgorithm.

Model of Collective Fish Behavior with Hydrodynamic Interactions

Science.gov (United States)

Filella, Audrey; Nadal, François; Sire, Clément; Kanso, Eva; Eloy, Christophe

2018-05-01

Fish schooling is often modeled with self-propelled particles subject to phenomenological behavioral rules. Although fish are known to sense and exploit flow features, these models usually neglect hydrodynamics. Here, we propose a novel model that couples behavioral rules with far-field hydrodynamic interactions. We show that (1) a new "collective turning" phase emerges, (2) on average, individuals swim faster thanks to the fluid, and (3) the flow enhances behavioral noise. The results of this model suggest that hydrodynamic effects should be considered to fully understand the collective dynamics of fish.

GPUs, a new tool of acceleration in CFD: efficiency and reliability on smoothed particle hydrodynamics methods.

Directory of Open Access Journals (Sweden)

Alejandro C Crespo

Full Text Available Smoothed Particle Hydrodynamics (SPH is a numerical method commonly used in Computational Fluid Dynamics (CFD to simulate complex free-surface flows. Simulations with this mesh-free particle method far exceed the capacity of a single processor. In this paper, as part of a dual-functioning code for either central processing units (CPUs or Graphics Processor Units (GPUs, a parallelisation using GPUs is presented. The GPU parallelisation technique uses the Compute Unified Device Architecture (CUDA of nVidia devices. Simulations with more than one million particles on a single GPU card exhibit speedups of up to two orders of magnitude over using a single-core CPU. It is demonstrated that the code achieves different speedups with different CUDA-enabled GPUs. The numerical behaviour of the SPH code is validated with a standard benchmark test case of dam break flow impacting on an obstacle where good agreement with the experimental results is observed. Both the achieved speed-ups and the quantitative agreement with experiments suggest that CUDA-based GPU programming can be used in SPH methods with efficiency and reliability.

A Novel Adaptive Particle Swarm Optimization Algorithm with Foraging Behavior in Optimization Design

Directory of Open Access Journals (Sweden)

Liu Yan

2018-01-01

Full Text Available The method of repeated trial and proofreading is generally used to the convention reducer design, but these methods is low efficiency and the size of the reducer is often large. Aiming the problems, this paper presents an adaptive particle swarm optimization algorithm with foraging behavior, in this method, the bacterial foraging process is introduced into the adaptive particle swarm optimization algorithm, which can provide the function of particle chemotaxis, swarming, reproduction, elimination and dispersal, to improve the ability of local search and avoid premature behavior. By test verification through typical function and the application of the optimization design in the structure of the reducer with discrete and continuous variables, the results are shown that the new algorithm has the advantages of good reliability, strong searching ability and high accuracy. It can be used in engineering design, and has a strong applicability.

Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

NARCIS (Netherlands)

Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

Particle simulation algorithms with short-range forces in MHD and fluid flow

International Nuclear Information System (INIS)

Cable, S.; Tajima, T.; Umegaki, K.

1992-07-01

Attempts are made to develop numerical algorithms for handling fluid flows involving liquids and liquid-gas mixtures. In these types of systems, the short-range intermolecular interactions are important enough to significantly alter behavior predicted on the basis of standard fluid mechanics and magnetohydrodynamics alone. We have constructed a particle-in-cell (PIC) code for the purpose of studying the effects of these interactions. Of the algorithms considered, the one which has been successfully implemented is based on a MHD particle code developed by Brunel et al. In the version presented here, short range forces are included in particle motion by, first, calculating the forces between individual particles and then, to prevent aliasing, interpolating these forces to the computational grid points, then interpolating the forces back to the particles. The code has been used to model a simple two-fluid Rayleigh-Taylor instability. Limitations to the accuracy of the code exist at short wavelengths, where the effects of the short-range forces would be expected to be most pronounced

Hydrodynamics of quark-gluon plasmas

International Nuclear Information System (INIS)

Blaizot, J.P.

1986-06-01

This paper reviews some aspects of the hydrodynamics of quark-gluon plasmas. Various stages of ultra-relativistic heavy ion collisions are described. Several estimates of the maximum energy density expected to be achieved in these collisions are compared. Discontinuities which may be induced in the hydrodynamic flow by a phase transition are described and a convenient numerical method designed to deal with such discontinuous flows is briefly presented. Finally, the correlations between particle transverse momenta and multiplicities are analyzed and one discusses to which extent these correlations could signal the occurrence of a phase transition in heavy ion collisions

Filter-Feeding Zoobenthos and Hydrodynamics

DEFF Research Database (Denmark)

Riisgård, Hans Ulrik; Larsen, Poul Scheel

2017-01-01

interplay between benthic filter feeders and hydrodynamics. Starting from the general concept of grazing potential and typical data on benthic population densities its realization is considered, first at the level of the individual organism through the processes of pumping and trapping of food particles...

Soliton Gases and Generalized Hydrodynamics

Science.gov (United States)

Doyon, Benjamin; Yoshimura, Takato; Caux, Jean-Sébastien

2018-01-01

We show that the equations of generalized hydrodynamics (GHD), a hydrodynamic theory for integrable quantum systems at the Euler scale, emerge in full generality in a family of classical gases, which generalize the gas of hard rods. In this family, the particles, upon colliding, jump forward or backward by a distance that depends on their velocities, reminiscent of classical soliton scattering. This provides a "molecular dynamics" for GHD: a numerical solver which is efficient, flexible, and which applies to the presence of external force fields. GHD also describes the hydrodynamics of classical soliton gases. We identify the GHD of any quantum model with that of the gas of its solitonlike wave packets, thus providing a remarkable quantum-classical equivalence. The theory is directly applicable, for instance, to integrable quantum chains and to the Lieb-Liniger model realized in cold-atom experiments.

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

Science.gov (United States)

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

3D head pose estimation and tracking using particle filtering and ICP algorithm

KAUST Repository

Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge

2010-01-01

This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

Science.gov (United States)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with

Lorentz covariant canonical symplectic algorithms for dynamics of charged particles

Science.gov (United States)

Wang, Yulei; Liu, Jian; Qin, Hong

2016-12-01

In this paper, the Lorentz covariance of algorithms is introduced. Under Lorentz transformation, both the form and performance of a Lorentz covariant algorithm are invariant. To acquire the advantages of symplectic algorithms and Lorentz covariance, a general procedure for constructing Lorentz covariant canonical symplectic algorithms (LCCSAs) is provided, based on which an explicit LCCSA for dynamics of relativistic charged particles is built. LCCSA possesses Lorentz invariance as well as long-term numerical accuracy and stability, due to the preservation of a discrete symplectic structure and the Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which are difficult to handle in traditional construction procedures of symplectic algorithms, LCCSA provides a perfect explicit canonical symplectic solution by implementing the discretization in 4-spacetime. We also show that LCCSA has built-in energy-based adaptive time steps, which can optimize the computation performance when the Lorentz factor varies.

Hydrodynamic chromatography coupled to single-particle ICP-MS for the simultaneous characterization of AgNPs and determination of dissolved Ag in plasma and blood of burn patients.

Science.gov (United States)

Roman, Marco; Rigo, Chiara; Castillo-Michel, Hiram; Munivrana, Ivan; Vindigni, Vincenzo; Mičetić, Ivan; Benetti, Federico; Manodori, Laura; Cairns, Warren R L

2016-07-01

Silver nanoparticles (AgNPs) are increasingly used in medical devices as innovative antibacterial agents, but no data are currently available on their chemical transformations and fate in vivo in the human body, particularly on their potential to reach the circulatory system. To study the processes involving AgNPs in human plasma and blood, we developed an analytical method based on hydrodynamic chromatography (HDC) coupled to inductively coupled plasma mass spectrometry (ICP-MS) in single-particle detection mode. An innovative algorithm was implemented to deconvolute the signals of dissolved Ag and AgNPs and to extrapolate a multiparametric characterization of the particles in the same chromatogram. From a single injection, the method provides the concentration of dissolved Ag and the distribution of AgNPs in terms of hydrodynamic diameter, mass-derived diameter, number and mass concentration. This analytical approach is robust and suitable to study quantitatively the dynamics and kinetics of AgNPs in complex biological fluids, including processes such as agglomeration, dissolution and formation of protein coronas. The method was applied to study the transformations of AgNP standards and an AgNP-coated dressing in human plasma, supported by micro X-ray fluorescence (μXRF) and micro X-ray absorption near-edge spectroscopy (μXANES) speciation analysis and imaging, and to investigate, for the first time, the possible presence of AgNPs in the blood of three burn patients treated with the same dressing. Together with our previous studies, the results strongly support the hypothesis that the systemic mobilization of the metal after topical administration of AgNPs is driven by their dissolution in situ. Graphical Abstract Simplified scheme of the combined analytical approach adopted for studying the chemical dynamics of AgNPs in human plasma/blood.

Plasmas in particle accelerators: a hydrodynamic model of three-dimensional electrostatic instabilities

International Nuclear Information System (INIS)

Krafft, G.A.; Mark, J.W.K.; Wang, T.S.F.

1983-01-01

In an earlier paper, closed hydrodynamic equations were derived with possible application to the simulation of beam plasmas relevant to designs of heavy ion accelerators for inertial confinement fusion energy applications. The closure equations involved a novel feature of anisotropic stresses even transverse to the beam. A related hydrodynamic model is used in this paper to examine further the boundaries of validity of such hydrodynamic approximations. It is also proposed as a useful tool to provide an economic means for searching the large parameter space relevant to three-dimensional stability problems involving coupling of longitudinal and transverse motions in the presence of wall impedance

Hydrodynamic effects on phase transition in active matter

Science.gov (United States)

Gidituri, Harinadha; Akella, V. S.; Panchagnula, Mahesh; Vedantam, Srikanth; Multiphase flow physics lab Team

2017-11-01

Organized motion of active (self-propelled) objects are ubiquitous in nature. The objective of this study to investigate the effect of hydrodynamics on the coherent structures in active and passive particle mixtures. We use a mesoscopic method Dissipative Particle Dynamics (DPD). The system shows three different states viz. meso-turbulent (disordered state), polar flock and vortical (ordered state) for different values of activity and volume fraction of active particles. From our numerical simulations we construct a phase diagram between activity co-efficient, volume fraction and viscosity of the passive fluid. Transition from vortical to polar is triggered by increasing the viscosity of passive fluid which causes strong short-range hydrodynamic interactions. However, as the viscosity of the fluid decreases, both vortical and meso-turbulent states transition to polar flock phase. We also calculated the diffusion co-efficients via mean square displacement (MSD) for passive and active particles. We observe ballistic and diffusive regimes in the present system.

Inverse estimation of the spheroidal particle size distribution using Ant Colony Optimization algorithms in multispectral extinction technique

Science.gov (United States)

He, Zhenzong; Qi, Hong; Wang, Yuqing; Ruan, Liming

2014-10-01

Four improved Ant Colony Optimization (ACO) algorithms, i.e. the probability density function based ACO (PDF-ACO) algorithm, the Region ACO (RACO) algorithm, Stochastic ACO (SACO) algorithm and Homogeneous ACO (HACO) algorithm, are employed to estimate the particle size distribution (PSD) of the spheroidal particles. The direct problems are solved by the extended Anomalous Diffraction Approximation (ADA) and the Lambert-Beer law. Three commonly used monomodal distribution functions i.e. the Rosin-Rammer (R-R) distribution function, the normal (N-N) distribution function, and the logarithmic normal (L-N) distribution function are estimated under dependent model. The influence of random measurement errors on the inverse results is also investigated. All the results reveal that the PDF-ACO algorithm is more accurate than the other three ACO algorithms and can be used as an effective technique to investigate the PSD of the spheroidal particles. Furthermore, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution functions to retrieve the PSD of spheroidal particles using PDF-ACO algorithm. The investigation shows a reasonable agreement between the original distribution function and the general distribution function when only considering the variety of the length of the rotational semi-axis.

STAR FORMATION AND FEEDBACK IN SMOOTHED PARTICLE HYDRODYNAMIC SIMULATIONS. II. RESOLUTION EFFECTS

International Nuclear Information System (INIS)

Christensen, Charlotte R.; Quinn, Thomas; Bellovary, Jillian; Stinson, Gregory; Wadsley, James

2010-01-01

We examine the effect of mass and force resolution on a specific star formation (SF) recipe using a set of N-body/smooth particle hydrodynamic simulations of isolated galaxies. Our simulations span halo masses from 10 9 to 10 13 M sun , more than 4 orders of magnitude in mass resolution, and 2 orders of magnitude in the gravitational softening length, ε, representing the force resolution. We examine the total global SF rate, the SF history, and the quantity of stellar feedback and compare the disk structure of the galaxies. Based on our analysis, we recommend using at least 10 4 particles each for the dark matter (DM) and gas component and a force resolution of ε ∼ 10 -3 R vir when studying global SF and feedback. When the spatial distribution of stars is important, the number of gas and DM particles must be increased to at least 10 5 of each. Low-mass resolution simulations with fixed softening lengths show particularly weak stellar disks due to two-body heating. While decreasing spatial resolution in low-mass resolution simulations limits two-body effects, density and potential gradients cannot be sustained. Regardless of the softening, low-mass resolution simulations contain fewer high density regions where SF may occur. Galaxies of approximately 10 10 M sun display unique sensitivity to both mass and force resolution. This mass of galaxy has a shallow potential and is on the verge of forming a disk. The combination of these factors gives this galaxy the potential for strong gas outflows driven by supernova feedback and makes it particularly sensitive to any changes to the simulation parameters.

Introduction to physics mechanics, hydrodynamics thermodynamics

CERN Document Server

Frauenfelder, P

2013-01-01

Introduction of Physics: Mechanics , Hydrodynamics, Thermodynamics covers the principles of matter and its motion through space and time, as well as the related concepts of energy and force. This book is composed of eleven chapters, and begins with an introduction to the basic principles of mechanics, hydrodynamics, and thermodynamics. The subsequent chapters deal with the statics of rigid bodies and the dynamics of particles and rigid bodies. These topics are followed by discussions on elasticity, mechanics of fluids, the basic concept of thermodynamic, kinetic theory, and crystal structure o

Genetic particle swarm parallel algorithm analysis of optimization arrangement on mistuned blades

Science.gov (United States)

Zhao, Tianyu; Yuan, Huiqun; Yang, Wenjun; Sun, Huagang

2017-12-01

This article introduces a method of mistuned parameter identification which consists of static frequency testing of blades, dichotomy and finite element analysis. A lumped parameter model of an engine bladed-disc system is then set up. A bladed arrangement optimization method, namely the genetic particle swarm optimization algorithm, is presented. It consists of a discrete particle swarm optimization and a genetic algorithm. From this, the local and global search ability is introduced. CUDA-based co-evolution particle swarm optimization, using a graphics processing unit, is presented and its performance is analysed. The results show that using optimization results can reduce the amplitude and localization of the forced vibration response of a bladed-disc system, while optimization based on the CUDA framework can improve the computing speed. This method could provide support for engineering applications in terms of effectiveness and efficiency.

A decoupled power flow algorithm using particle swarm optimization technique

International Nuclear Information System (INIS)

Acharjee, P.; Goswami, S.K.

2009-01-01

A robust, nondivergent power flow method has been developed using the particle swarm optimization (PSO) technique. The decoupling properties between the power system quantities have been exploited in developing the power flow algorithm. The speed of the power flow algorithm has been improved using a simple perturbation technique. The basic power flow algorithm and the improvement scheme have been designed to retain the simplicity of the evolutionary approach. The power flow is rugged, can determine the critical loading conditions and also can handle the flexible alternating current transmission system (FACTS) devices efficiently. Test results on standard test systems show that the proposed method can find the solution when the standard power flows fail.

Application of Dynamic Mutated Particle Swarm Optimization Algorithm to Design Water Distribution Networks

Directory of Open Access Journals (Sweden)

Kazem Mohammadi- Aghdam

2015-10-01

Full Text Available This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO method for designing water distribution networks (WDNs. The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO. The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms.

Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

Directory of Open Access Journals (Sweden)

Ye Tian

2014-01-01

Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

Impact of hydrodynamics on effective interactions in suspensions of active and passive matter.

Science.gov (United States)

Krafnick, Ryan C; García, Angel E

2015-02-01

Passive particles exhibit unique properties when immersed in an active bath of self-propelling entities. In particular, an effective attraction can appear between particles that repel each other when in a passive solution. Here we numerically study the effect of hydrodynamics on an active-passive hybrid system, where we observe qualitative differences as compared to simulations with excluded volume effects alone. The results shed light on an existing discrepancy in pair lifetimes between simulation and experiment, due to the hydrodynamically enhanced stability of coupled passive particles.

Frequency-dependent hydrodynamic interaction between two solid spheres

Science.gov (United States)

Jung, Gerhard; Schmid, Friederike

2017-12-01

Hydrodynamic interactions play an important role in many areas of soft matter science. In simulations with implicit solvent, various techniques such as Brownian or Stokesian dynamics explicitly include hydrodynamic interactions a posteriori by using hydrodynamic diffusion tensors derived from the Stokes equation. However, this equation assumes the interaction to be instantaneous which is an idealized approximation and only valid on long time scales. In the present paper, we go one step further and analyze the time-dependence of hydrodynamic interactions between finite-sized particles in a compressible fluid on the basis of the linearized Navier-Stokes equation. The theoretical results show that at high frequencies, the compressibility of the fluid has a significant impact on the frequency-dependent pair interactions. The predictions of hydrodynamic theory are compared to molecular dynamics simulations of two nanocolloids in a Lennard-Jones fluid. For this system, we reconstruct memory functions by extending the inverse Volterra technique. The simulation data agree very well with the theory, therefore, the theory can be used to implement dynamically consistent hydrodynamic interactions in the increasingly popular field of non-Markovian modeling.

Smooth particle hydrodynamic modeling and validation for impact bird substitution

Science.gov (United States)

Babu, Arun; Prasad, Ganesh

2018-04-01

Bird strike events incidentally occur and can at times be fatal for air frame structures. Federal Aviation Regulations (FAR) and such other ones mandates aircrafts to be modeled to withstand various levels of bird hit damages. The subject matter of this paper is numerical modeling of a soft body geometry for realistically substituting an actual bird for carrying out simulations of bird hit on target structures. Evolution of such a numerical code to effect an actual bird behavior through impact is much desired for making use of the state of the art computational facilities in simulating bird strike events. Validity, of simulations depicting bird hits, is largely dependent on the correctness of the bird model. In an impact, a set of complex and coupled dynamic interaction exists between the target and the impactor. To simplify this problem, impactor response needs to be decoupled from that of the target. This can be done by assuming and modeling the target as noncompliant. Bird is assumed as fluidic in a impact. Generated stresses in the bird body are significant than its yield stresses. Hydrodynamic theory is most ideal for describing this problem. Impactor literally flows steadily over the target for most part of this problem. The impact starts with an initial shock and falls into a radial release shock regime. Subsequently a steady flow is established in the bird body and this phase continues till the whole length of the bird body is turned around. Initial shock pressure and steady state pressure are ideal variables for comparing and validating the bird model. Spatial discretization of the bird is done using Smooth Particle Hydrodynamic (SPH) approach. This Discrete Element Model (DEM) offers significant advantages over other contemporary approaches. Thermodynamic state variable relations are established using Polynomial Equation of State (EOS). ANSYS AUTODYN is used to perform the explicit dynamic simulation of the impact event. Validation of the shock and steady

Hybrid Optimization Algorithm of Particle Swarm Optimization and Cuckoo Search for Preventive Maintenance Period Optimization

Directory of Open Access Journals (Sweden)

Jianwen Guo

2016-01-01

Full Text Available All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO and cuckoo search (CS algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test functions show that the proposed algorithm exhibits more outstanding performance than particle swarm optimization and cuckoo search. Experiment results show that the proposed algorithm has advantages of strong optimization ability and fast convergence speed to solve the PMPOM problem.

New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.

Science.gov (United States)

Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng

2016-05-16

The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.

Development of stress boundary conditions in smoothed particle hydrodynamics (SPH) for the modeling of solids deformation

Science.gov (United States)

Douillet-Grellier, Thomas; Pramanik, Ranjan; Pan, Kai; Albaiz, Abdulaziz; Jones, Bruce D.; Williams, John R.

2017-10-01

This paper develops a method for imposing stress boundary conditions in smoothed particle hydrodynamics (SPH) with and without the need for dummy particles. SPH has been used for simulating phenomena in a number of fields, such as astrophysics and fluid mechanics. More recently, the method has gained traction as a technique for simulation of deformation and fracture in solids, where the meshless property of SPH can be leveraged to represent arbitrary crack paths. Despite this interest, application of boundary conditions within the SPH framework is typically limited to imposed velocity or displacement using fictitious dummy particles to compensate for the lack of particles beyond the boundary interface. While this is enough for a large variety of problems, especially in the case of fluid flow, for problems in solid mechanics there is a clear need to impose stresses upon boundaries. In addition to this, the use of dummy particles to impose a boundary condition is not always suitable or even feasibly, especially for those problems which include internal boundaries. In order to overcome these difficulties, this paper first presents an improved method for applying stress boundary conditions in SPH with dummy particles. This is then followed by a proposal of a formulation which does not require dummy particles. These techniques are then validated against analytical solutions to two common problems in rock mechanics, the Brazilian test and the penny-shaped crack problem both in 2D and 3D. This study highlights the fact that SPH offers a good level of accuracy to solve these problems and that results are reliable. This validation work serves as a foundation for addressing more complex problems involving plasticity and fracture propagation.

Digital signal processing algorithms for nuclear particle spectroscopy

International Nuclear Information System (INIS)

Zejnalova, O.; Zejnalov, Sh.; Hambsch, F.J.; Oberstedt, S.

2007-01-01

Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms are provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter on the final signal-to-noise ratio of the spectrometer is considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionization chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore the influence of the pile-up elimination scheme on the final resolution of the spectrometer is investigated in terms of the distance between pile-up pulses. The efficiency of the developed algorithms is compared with other signal processing schemes published in literature

Local anisotropy effects in the hydrodynamical theory of multiparticle production

International Nuclear Information System (INIS)

Gorenshtejn, M.I.; Sinyukov, Yu.M.

1983-01-01

The stage of final particle formation in the hydrodynamic theory of multiparticle production is analysed. It is shown, that secondary particle spectrum of the fluid element decay to be anisotropic in the rest frame system of this element

Hydrodynamic characteristics of a two-phase gas-liquid flow upward through a fixed bed of spherical particles

Directory of Open Access Journals (Sweden)

VELIZAR D. STANKOVIC

2001-01-01

Full Text Available The influence of an electrochemically generated gas phase on the hydrodynamic characteristics of a three-phase system has been examined. The two-phase fluid, (gas-liquid, in which the liquid phase is the continuous one, flows through a packed bed with glass spheres. The influence of the liquid velocity was examined, as well as the gas velocity and particle diameter on the pressure drop through the fixed bed. It was found that with increasing liquid velocity (wl = 0.0162–0.03 m/s, the relative pressure drop decreases through the fixed bed. With increasing current density, the pressure drop increases, since greater gas quantities stay behind in the fixed bed. Besides, it was found that with decreasing diameter of the glass particles, the relative pressure drop also decreases. The relationship betweeen the experimentally obtained friction factor and the Reynolds number was established.

Local anisotropy effects in the hydrodynamical theory of multiparticle production

International Nuclear Information System (INIS)

Gorenstein, M.I.; Sinyukov, Yu.M.

1984-01-01

The stage of secondary particle formation in the hydrodynamic theory of multiparticle production is analysed. We find out that the secondary particle spectrum of the fluid element decay is anisotropic in the rest frame system of this element. (orig.)

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

International Nuclear Information System (INIS)

Canedo Medeiros, Jose Antonio Carlos; Schirru, Roberto

2008-01-01

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Canedo Medeiros, Jose Antonio Carlos [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: canedo@lmp.ufrj.br; Schirru, Roberto [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: schirru@lmp.ufrj.br

2008-04-15

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results.

A Particle Swarm Optimization Algorithm with Variable Random Functions and Mutation

Institute of Scientific and Technical Information of China (English)

ZHOU Xiao-Jun; YANG Chun-Hua; GUI Wei-Hua; DONG Tian-Xue

2014-01-01

The convergence analysis of the standard particle swarm optimization (PSO) has shown that the changing of random functions, personal best and group best has the potential to improve the performance of the PSO. In this paper, a novel strategy with variable random functions and polynomial mutation is introduced into the PSO, which is called particle swarm optimization algorithm with variable random functions and mutation (PSO-RM). Random functions are adjusted with the density of the population so as to manipulate the weight of cognition part and social part. Mutation is executed on both personal best particle and group best particle to explore new areas. Experiment results have demonstrated the effectiveness of the strategy.

Hydrodynamic slip length as a surface property

Science.gov (United States)

Ramos-Alvarado, Bladimir; Kumar, Satish; Peterson, G. P.

2016-02-01

Equilibrium and nonequilibrium molecular dynamics simulations were conducted in order to evaluate the hypothesis that the hydrodynamic slip length is a surface property. The system under investigation was water confined between two graphite layers to form nanochannels of different sizes (3-8 nm). The water-carbon interaction potential was calibrated by matching wettability experiments of graphitic-carbon surfaces free of airborne hydrocarbon contamination. Three equilibrium theories were used to calculate the hydrodynamic slip length. It was found that one of the recently reported equilibrium theories for the calculation of the slip length featured confinement effects, while the others resulted in calculations significantly hindered by the large margin of error observed between independent simulations. The hydrodynamic slip length was found to be channel-size independent using equilibrium calculations, i.e., suggesting a consistency with the definition of a surface property, for 5-nm channels and larger. The analysis of the individual trajectories of liquid particles revealed that the reason for observing confinement effects in 3-nm nanochannels is the high mobility of the bulk particles. Nonequilibrium calculations were not consistently affected by size but by noisiness in the smallest systems.

Hydrodynamic dispersion of microswimmers in suspension

Science.gov (United States)

Martin, Matthieu; Rafaï, Salima; Peyla, Philippe

2014-11-01

In our laboratory, we study hydrodynamics of suspensions of micro-swimmers. These micro-organisms are unicellular algae Chlamydomonas Rheinhardii which are able to swim by using their flagella. The swimming dynamics of these micro-swimmers can be seen as a random walk, in absence of any kind of interaction. In addition, these algae have the property of being phototactic, i.e. they swim towards the light. Combining this property with a hydrodynamic flow, we were able to reversibly separate algae from the rest of the fluid. But for sufficiently high volume fraction, these active particles interact with each other. We are now interested in how the coupling of hydrodynamic interactions between swimmers and phototaxis can modify the swimming dynamics at the scale of the suspension. To this aim, we conduct experiments in microfluidic devices to study the dispersion of the micro-organisms in a the liquid phase as a function of the volume fraction. We show that the dispersion of an assembly of puller type microswimmers is quantitatively affected by hydrodynamics interactions. Phd student.

Comparing genetic algorithm and particle swarm optimization for solving capacitated vehicle routing problem

Science.gov (United States)

Iswari, T.; Asih, A. M. S.

2018-04-01

In the logistics system, transportation plays an important role to connect every element in the supply chain, but it can produces the greatest cost. Therefore, it is important to make the transportation costs as minimum as possible. Reducing the transportation cost can be done in several ways. One of the ways to minimizing the transportation cost is by optimizing the routing of its vehicles. It refers to Vehicle Routing Problem (VRP). The most common type of VRP is Capacitated Vehicle Routing Problem (CVRP). In CVRP, the vehicles have their own capacity and the total demands from the customer should not exceed the capacity of the vehicle. CVRP belongs to the class of NP-hard problems. These NP-hard problems make it more complex to solve such that exact algorithms become highly time-consuming with the increases in problem sizes. Thus, for large-scale problem instances, as typically found in industrial applications, finding an optimal solution is not practicable. Therefore, this paper uses two kinds of metaheuristics approach to solving CVRP. Those are Genetic Algorithm and Particle Swarm Optimization. This paper compares the results of both algorithms and see the performance of each algorithm. The results show that both algorithms perform well in solving CVRP but still needs to be improved. From algorithm testing and numerical example, Genetic Algorithm yields a better solution than Particle Swarm Optimization in total distance travelled.

A Symmetry Particle Method towards Implicit Non‐Newtonian Fluids

Directory of Open Access Journals (Sweden)

Yalan Zhang

2017-02-01

Full Text Available In this paper, a symmetry particle method, the smoothed particle hydrodynamics (SPH method, is extended to deal with non‐Newtonian fluids. First, the viscous liquid is modeled by a non‐Newtonian fluid flow and the variable viscosity under shear stress is determined by the Carreau‐Yasuda model. Then a pressure correction method is proposed, by correcting density error with individual stiffness parameters for each particle, to ensure the incompressibility of fluid. Finally, an implicit method is used to improve efficiency and stability. It is found that the nonNewtonian behavior can be well displayed in all cases, and the proposed SPH algorithm is stable and efficient.

Hydrodynamical assessment of 200A GeV collisions

International Nuclear Information System (INIS)

Schnedermann, E.; Heinz, U.

1994-01-01

We are analyzing the hydrodynamics of 200A GeV S+S collisions using a new approach which tries to quantify the uncertainties arising from the specific implementation of the hydrodynamical model. Based on a previous phenomenological analysis we use the global hydrodynamics model to show that the amount of initial flow, or initial energy density, cannot be determined from the hadronic momentum spectra. We additionally find that almost always a sizable transverse flow develops, which causes the system to freeze out, thereby limiting the flow velocity in itself. This freeze-out dominance in turn makes a distinction between a plasma and a hadron resonance gas equation of state very difficult, whereas a pure pion gas can easily be ruled out from present data. To complete the picture we also analyze particle multiplicity data, which suggest that chemical equilibrium is not reached with respect to the strange particles. However, the overpopulation of pions seems to be at most moderate, with a pion chemical potential far away from the Bose divergence

Particle mis-identification rate algorithm for the CLIC ILD and CLIC SiD detectors

CERN Document Server

Nardulli, J

2011-01-01

This note describes the algorithm presently used to determine the particle mis- identification rate and gives results for single particles for the CLIC ILD and CLIC SiD detector concepts as prepared for the CLIC Conceptual Design Report.

Dose calculations algorithm for narrow heavy charged-particle beams

Energy Technology Data Exchange (ETDEWEB)

Barna, E A; Kappas, C [Department of Medical Physics, School of Medicine, University of Patras (Greece); Scarlat, F [National Institute for Laser and Plasma Physics, Bucharest (Romania)

1999-12-31

The dose distributional advantages of the heavy charged-particles can be fully exploited by using very efficient and accurate dose calculation algorithms, which can generate optimal three-dimensional scanning patterns. An inverse therapy planning algorithm for dynamically scanned, narrow heavy charged-particle beams is presented in this paper. The irradiation `start point` is defined at the distal end of the target volume, right-down, in a beam`s eye view. The peak-dose of the first elementary beam is set to be equal to the prescribed dose in the target volume, and is defined as the reference dose. The weighting factor of any Bragg-peak is determined by the residual dose at the point of irradiation, calculated as the difference between the reference dose and the cumulative dose delivered at that point of irradiation by all the previous Bragg-peaks. The final pattern consists of the weighted Bragg-peaks irradiation density. Dose distributions were computed using two different scanning steps equal to 0.5 mm, and 1 mm respectively. Very accurate and precise localized dose distributions, conform to the target volume, were obtained. (authors) 6 refs., 3 figs.

Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

Directory of Open Access Journals (Sweden)

Wang Chun-Feng

2014-01-01

Full Text Available Artificial bee colony (ABC algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.

Viscosity and Vorticity in Reduced Magneto-Hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Joseph, Ilon [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-08-12

Magneto-hydrodynamics (MHD) critically relies on viscous forces in order for an accurate determination of the electric eld. For each charged particle species, the Braginskii viscous tensor for a magnetized plasma has the decomposition into matrices with special symmetries.

Smooth Particle Hydrodynamics GPU-Acceleration Tool for Asteroid Fragmentation Simulation

Science.gov (United States)

Buruchenko, Sergey K.; Schäfer, Christoph M.; Maindl, Thomas I.

2017-10-01

The impact threat of near-Earth objects (NEOs) is a concern to the global community, as evidenced by the Chelyabinsk event (caused by a 17-m meteorite) in Russia on February 15, 2013 and a near miss by asteroid 2012 DA14 ( 30 m diameter), on the same day. The expected energy, from either a low-altitude air burst or direct impact, would have severe consequences, especially in populated regions. To mitigate this threat one of the methods is employment of large kinetic-energy impactors (KEIs). The simulation of asteroid target fragmentation is a challenging task which demands efficient and accurate numerical methods with large computational power. Modern graphics processing units (GPUs) lead to a major increase 10 times and more in the performance of the computation of astrophysical and high velocity impacts. The paper presents a new implementation of the numerical method smooth particle hydrodynamics (SPH) using NVIDIA-GPU and the first astrophysical and high velocity application of the new code. The code allows for a tremendous increase in speed of astrophysical simulations with SPH and self-gravity at low costs for new hardware. We have implemented the SPH equations to model gas, liquids and elastic, and plastic solid bodies and added a fragmentation model for brittle materials. Self-gravity may be optionally included in the simulations.

Predicting patchy particle crystals: variable box shape simulations and evolutionary algorithms

NARCIS (Netherlands)

Bianchi, E.; Doppelbauer, G.; Filion, L.C.; Dijkstra, M.; Kahl, G.

2012-01-01

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an approach based on Monte Carlo simulations in the

Explicit symplectic algorithms based on generating functions for relativistic charged particle dynamics in time-dependent electromagnetic field

Science.gov (United States)

Zhang, Ruili; Wang, Yulei; He, Yang; Xiao, Jianyuan; Liu, Jian; Qin, Hong; Tang, Yifa

2018-02-01

Relativistic dynamics of a charged particle in time-dependent electromagnetic fields has theoretical significance and a wide range of applications. The numerical simulation of relativistic dynamics is often multi-scale and requires accurate long-term numerical simulations. Therefore, explicit symplectic algorithms are much more preferable than non-symplectic methods and implicit symplectic algorithms. In this paper, we employ the proper time and express the Hamiltonian as the sum of exactly solvable terms and product-separable terms in space-time coordinates. Then, we give the explicit symplectic algorithms based on the generating functions of orders 2 and 3 for relativistic dynamics of a charged particle. The methodology is not new, which has been applied to non-relativistic dynamics of charged particles, but the algorithm for relativistic dynamics has much significance in practical simulations, such as the secular simulation of runaway electrons in tokamaks.

Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms

Directory of Open Access Journals (Sweden)

Qingjian Ni

2014-01-01

Full Text Available In evolutionary algorithm, population diversity is an important factor for solving performance. In this paper, combined with some population diversity analysis methods in other evolutionary algorithms, three indicators are introduced to be measures of population diversity in PSO algorithms, which are standard deviation of population fitness values, population entropy, and Manhattan norm of standard deviation in population positions. The three measures are used to analyze the population diversity in a relatively new PSO variant—Dynamic Probabilistic Particle Swarm Optimization (DPPSO. The results show that the three measure methods can fully reflect the evolution of population diversity in DPPSO algorithms from different angles, and we also discuss the impact of population diversity on the DPPSO variants. The relevant conclusions of the population diversity on DPPSO can be used to analyze, design, and improve the DPPSO algorithms, thus improving optimization performance, which could also be beneficial to understand the working mechanism of DPPSO theoretically.

Optimization of C4.5 algorithm-based particle swarm optimization for breast cancer diagnosis

Science.gov (United States)

Muslim, M. A.; Rukmana, S. H.; Sugiharti, E.; Prasetiyo, B.; Alimah, S.

2018-03-01

Data mining has become a basic methodology for computational applications in the field of medical domains. Data mining can be applied in the health field such as for diagnosis of breast cancer, heart disease, diabetes and others. Breast cancer is most common in women, with more than one million cases and nearly 600,000 deaths occurring worldwide each year. The most effective way to reduce breast cancer deaths was by early diagnosis. This study aims to determine the level of breast cancer diagnosis. This research data uses Wisconsin Breast Cancer dataset (WBC) from UCI machine learning. The method used in this research is the algorithm C4.5 and Particle Swarm Optimization (PSO) as a feature option and to optimize the algorithm. C4.5. Ten-fold cross-validation is used as a validation method and a confusion matrix. The result of this research is C4.5 algorithm. The particle swarm optimization C4.5 algorithm has increased by 0.88%.

Magnetic particle tracking for nonspherical particles in a cylindrical fluidized bed

NARCIS (Netherlands)

Buist, K.A.; Jayaprakash, P.; Kuipers, J.A.M.; Deen, N.G.; Padding, J.T.

2017-01-01

In granular flow operations, often particles are nonspherical. This has inspired a vast amount of research in understanding the behavior of these particles. Various models are being developed to study the hydrodynamics involving nonspherical particles. Experiments however are often limited to obtain

GPU implementation of discrete particle swarm optimization algorithm for endmember extraction from hyperspectral image

Science.gov (United States)

Yu, Chaoyin; Yuan, Zhengwu; Wu, Yuanfeng

2017-10-01

Hyperspectral image unmixing is an important part of hyperspectral data analysis. The mixed pixel decomposition consists of two steps, endmember (the unique signatures of pure ground components) extraction and abundance (the proportion of each endmember in each pixel) estimation. Recently, a Discrete Particle Swarm Optimization algorithm (DPSO) was proposed for accurately extract endmembers with high optimal performance. However, the DPSO algorithm shows very high computational complexity, which makes the endmember extraction procedure very time consuming for hyperspectral image unmixing. Thus, in this paper, the DPSO endmember extraction algorithm was parallelized, implemented on the CUDA (GPU K20) platform, and evaluated by real hyperspectral remote sensing data. The experimental results show that with increasing the number of particles the parallelized version obtained much higher computing efficiency while maintain the same endmember exaction accuracy.

CRKSPH: A new meshfree hydrodynamics method with applications to astrophysics

Science.gov (United States)

Owen, John Michael; Raskin, Cody; Frontiere, Nicholas

2018-01-01

The study of astrophysical phenomena such as supernovae, accretion disks, galaxy formation, and large-scale structure formation requires computational modeling of, at a minimum, hydrodynamics and gravity. Developing numerical methods appropriate for these kinds of problems requires a number of properties: shock-capturing hydrodynamics benefits from rigorous conservation of invariants such as total energy, linear momentum, and mass; lack of obvious symmetries or a simplified spatial geometry to exploit necessitate 3D methods that ideally are Galilean invariant; the dynamic range of mass and spatial scales that need to be resolved can span many orders of magnitude, requiring methods that are highly adaptable in their space and time resolution. We have developed a new Lagrangian meshfree hydrodynamics method called Conservative Reproducing Kernel Smoothed Particle Hydrodynamics, or CRKSPH, in order to meet these goals. CRKSPH is a conservative generalization of the meshfree reproducing kernel method, combining the high-order accuracy of reproducing kernels with the explicit conservation of mass, linear momentum, and energy necessary to study shock-driven hydrodynamics in compressible fluids. CRKSPH's Lagrangian, particle-like nature makes it simple to combine with well-known N-body methods for modeling gravitation, similar to the older Smoothed Particle Hydrodynamics (SPH) method. Indeed, CRKSPH can be substituted for SPH in existing SPH codes due to these similarities. In comparison to SPH, CRKSPH is able to achieve substantially higher accuracy for a given number of points due to the explicitly consistent (and higher-order) interpolation theory of reproducing kernels, while maintaining the same conservation principles (and therefore applicability) as SPH. There are currently two coded implementations of CRKSPH available: one in the open-source research code Spheral, and the other in the high-performance cosmological code HACC. Using these codes we have applied

Fractional order Darwinian particle swarm optimization applications and evaluation of an evolutionary algorithm

CERN Document Server

Couceiro, Micael

2015-01-01

This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, suc

Granular Gases: Probing the Boundaries of Hydrodynamics

International Nuclear Information System (INIS)

Goldhirsch, I.

1999-01-01

The dissipative nature of the particle interactions in granular systems renders granular gases mesoscopic and bearing some similarities to regular gases in the ''continuum transition regime'' where shear rates and/or thermal gradients are very large). The following properties of granular gases support the above claim: (i). Mean free times are of the same order as macroscopic time scales (inverse shear rates); (ii). Mean free paths can be macroscopic and comparable to the system's dimensions; (iii). Typical flows are supersonic; (iv). Shear rates are typically ''large''; (v). Stress fields are scale (resolution) dependent; (vi). Burnett and super-Burnett corrections to both the constitutive relations and the boundary conditions are of importance; (vii). Single particle distribution functions can be far from Gaussian. It is concluded that while hydrodynamic descriptions of granular gases are relevant, they are probing the boundaries of applicability of hydrodynamics and perhaps slightly beyond

A fast sorting algorithm for a hypersonic rarefied flow particle simulation on the connection machine

Science.gov (United States)

Dagum, Leonardo

1989-01-01

The data parallel implementation of a particle simulation for hypersonic rarefied flow described by Dagum associates a single parallel data element with each particle in the simulation. The simulated space is divided into discrete regions called cells containing a variable and constantly changing number of particles. The implementation requires a global sort of the parallel data elements so as to arrange them in an order that allows immediate access to the information associated with cells in the simulation. Described here is a very fast algorithm for performing the necessary ranking of the parallel data elements. The performance of the new algorithm is compared with that of the microcoded instruction for ranking on the Connection Machine.

A self-adaptive chaotic particle swarm algorithm for short term hydroelectric system scheduling in deregulated environment

International Nuclear Information System (INIS)

Jiang Chuanwen; Bompard, Etorre

2005-01-01

This paper proposes a short term hydroelectric plant dispatch model based on the rule of maximizing the benefit. For the optimal dispatch model, which is a large scale nonlinear planning problem with multi-constraints and multi-variables, this paper proposes a novel self-adaptive chaotic particle swarm optimization algorithm to solve the short term generation scheduling of a hydro-system better in a deregulated environment. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed approach introduces chaos mapping and an adaptive scaling term into the particle swarm optimization algorithm, which increases its convergence rate and resulting precision. The new method has been examined and tested on a practical hydro-system. The results are promising and show the effectiveness and robustness of the proposed approach in comparison with the traditional particle swarm optimization algorithm

A fuzzy controller design for nuclear research reactors using the particle swarm optimization algorithm

International Nuclear Information System (INIS)

Coban, Ramazan

2011-01-01

Research highlights: → A closed-loop fuzzy logic controller based on the particle swarm optimization algorithm was proposed for controlling the power level of nuclear research reactors. → The proposed control system was tested for various initial and desired power levels, and it could control the reactor successfully for most situations. → The proposed controller is robust against the disturbances. - Abstract: In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.

Efficiencies of dynamic Monte Carlo algorithms for off-lattice particle systems with a single impurity

KAUST Repository

Novotny, M.A.; Watanabe, Hiroshi; Ito, Nobuyasu

2010-01-01

The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing

Techno-economic optimization of a shell and tube heat exchanger by genetic and particle swarm algorithms

International Nuclear Information System (INIS)

Sadeghzadeh, H.; Ehyaei, M.A.; Rosen, M.A.

2015-01-01

Highlights: • Calculating pressure drop and heat transfer coefficient by Delaware method. • The accuracy of the Delaware method is more than the Kern method. • The results of the PSO are better than the results of the GA. • The optimization results suggest that yields the best and most economic optimization. - Abstract: The use of genetic and particle swarm algorithms in the design of techno-economically optimum shell-and-tube heat exchangers is demonstrated. A cost function (including costs of the heat exchanger based on surface area and power consumption to overcome pressure drops) is the objective function, which is to be minimized. Selected decision variables include tube diameter, central baffles spacing and shell diameter. The Delaware method is used to calculate the heat transfer coefficient and the shell-side pressure drop. The accuracy and efficiency of the suggested algorithm and the Delaware method are investigated. A comparison of the results obtained by the two algorithms shows that results obtained with the particle swarm optimization method are superior to those obtained with the genetic algorithm method. By comparing these results with those from various references employing the Kern method and other algorithms, it is shown that the Delaware method accompanied by genetic and particle swarm algorithms achieves more optimum results, based on assessments for two case studies

Jets/MET Performance with the combination of Particle flow algorithm and SoftKiller

CERN Document Server

Yamamoto, Kohei

2017-01-01

The main purpose of my work is to study the performance of the combination of Particle flow algorithm(PFlow) and SoftKiller(SK), “PF+SK”. ATLAS experiment currently employes Topological clusters(Topo) for jet reconstruction, but we want to replace it with more effective one, PFlow. PFlow provides us with another method to reconstruct jets[1]. With this algorithm, we combine the energy deposits in calorimeters with the measurement in ID tracker. This strategy enables us to claim these consistent measurements in a detector come from same particles and avoid double counting. SK is a simple and effective way of suppressing pile-up[2]. This way, we divide rapidity-azimuthal plane into square patches and eliminate particles lower than the threshold "#$%, which is derived from each ",' so that the median of " density becomes zero. Practically, this is equal to gradually increasing "#$% till exactly half of patches becomes empty. Because there is no official calibration on PF+SK so far, we have t...

Optimization of the reflux ratio for a stage distillation column based on an improved particle swarm algorithm

DEFF Research Database (Denmark)

Ren, Jingzheng; Tan, Shiyu; Dong, Lichun

2010-01-01

A mathematical model relating operation profits with reflux ratio of a stage distillation column was established. In order to optimize the reflux ratio by solving the nonlinear objective function, an improved particle swarm algorithm was developed and has been proved to be able to enhance...... the searching ability of basic particle swarm algorithm significantly. An example of utilizing the improved algorithm to solve the mathematical model was demonstrated; the result showed that it is efficient and convenient to optimize the reflux ratio for a distillation column by using the mathematical model...

A highly scalable particle tracking algorithm using partitioned global address space (PGAS) programming for extreme-scale turbulence simulations

Science.gov (United States)

Buaria, D.; Yeung, P. K.

2017-12-01

A new parallel algorithm utilizing a partitioned global address space (PGAS) programming model to achieve high scalability is reported for particle tracking in direct numerical simulations of turbulent fluid flow. The work is motivated by the desire to obtain Lagrangian information necessary for the study of turbulent dispersion at the largest problem sizes feasible on current and next-generation multi-petaflop supercomputers. A large population of fluid particles is distributed among parallel processes dynamically, based on instantaneous particle positions such that all of the interpolation information needed for each particle is available either locally on its host process or neighboring processes holding adjacent sub-domains of the velocity field. With cubic splines as the preferred interpolation method, the new algorithm is designed to minimize the need for communication, by transferring between adjacent processes only those spline coefficients determined to be necessary for specific particles. This transfer is implemented very efficiently as a one-sided communication, using Co-Array Fortran (CAF) features which facilitate small data movements between different local partitions of a large global array. The cost of monitoring transfer of particle properties between adjacent processes for particles migrating across sub-domain boundaries is found to be small. Detailed benchmarks are obtained on the Cray petascale supercomputer Blue Waters at the University of Illinois, Urbana-Champaign. For operations on the particles in a 81923 simulation (0.55 trillion grid points) on 262,144 Cray XE6 cores, the new algorithm is found to be orders of magnitude faster relative to a prior algorithm in which each particle is tracked by the same parallel process at all times. This large speedup reduces the additional cost of tracking of order 300 million particles to just over 50% of the cost of computing the Eulerian velocity field at this scale. Improving support of PGAS models on

A neuro-fuzzy inference system tuned by particle swarm optimization algorithm for sensor monitoring

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Mauro Vitor de [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil). Div. de Instrumentacao e Confiabilidade Humana]. E-mail: mvitor@ien.gov.br; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Lab. de Monitoracao de Processos

2005-07-01

A neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm has been developed for monitor the relevant sensor in a nuclear plant using the information of other sensors. The antecedent parameters of the ANFIS that estimates the relevant sensor signal are optimized by a PSO algorithm and consequent parameters use a least-squares algorithm. The proposed sensor-monitoring algorithm was demonstrated through the estimation of the nuclear power value in a pressurized water reactor using as input to the ANFIS six other correlated signals. The obtained results are compared to two similar ANFIS using one gradient descendent (GD) and other genetic algorithm (GA), as antecedent parameters training algorithm. (author)

A neuro-fuzzy inference system tuned by particle swarm optimization algorithm for sensor monitoring

International Nuclear Information System (INIS)

Oliveira, Mauro Vitor de; Schirru, Roberto

2005-01-01

A neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm has been developed for monitor the relevant sensor in a nuclear plant using the information of other sensors. The antecedent parameters of the ANFIS that estimates the relevant sensor signal are optimized by a PSO algorithm and consequent parameters use a least-squares algorithm. The proposed sensor-monitoring algorithm was demonstrated through the estimation of the nuclear power value in a pressurized water reactor using as input to the ANFIS six other correlated signals. The obtained results are compared to two similar ANFIS using one gradient descendent (GD) and other genetic algorithm (GA), as antecedent parameters training algorithm. (author)

Innovations in ILC detector design using a particle flow algorithm approach

International Nuclear Information System (INIS)

Magill, S.; High Energy Physics

2007-01-01

The International Linear Collider (ILC) is a future e + e - collider that will produce particles with masses up to the design center-of-mass (CM) energy of 500 GeV. The ILC complements the Large Hadron Collider (LHC) which, although colliding protons at 14 TeV in the CM, will be luminosity-limited to particle production with masses up to ∼1-2 TeV. At the ILC, interesting cross-sections are small, but there are no backgrounds from underlying events, so masses should be able to be measured by hadronic decays to dijets (∼80% BR) as well as in leptonic decay modes. The precise measurement of jets will require major detector innovations, in particular to the calorimeter, which will be optimized to reconstruct final state particle 4-vectors--called the particle flow algorithm approach to jet reconstruction

Ef: Software for Nonrelativistic Beam Simulation by Particle-in-Cell Algorithm

Science.gov (United States)

Boytsov, A. Yu.; Bulychev, A. A.

2018-04-01

Understanding of particle dynamics is crucial in construction of electron guns, ion sources and other types of nonrelativistic beam devices. Apart from external guiding and focusing systems, a prominent role in evolution of such low-energy beams is played by particle-particle interaction. Numerical simulations taking into account these effects are typically accomplished by a well-known particle-in-cell method. In practice, for convenient work a simulation program should not only implement this method, but also support parallelization, provide integration with CAD systems and allow access to details of the simulation algorithm. To address the formulated requirements, development of a new open source code - Ef - has been started. It's current features and main functionality are presented. Comparison with several analytical models demonstrates good agreement between the numerical results and the theory. Further development plans are discussed.

Ef: Software for Nonrelativistic Beam Simulation by Particle-in-Cell Algorithm

Directory of Open Access Journals (Sweden)

Boytsov A. Yu.

2018-01-01

Full Text Available Understanding of particle dynamics is crucial in construction of electron guns, ion sources and other types of nonrelativistic beam devices. Apart from external guiding and focusing systems, a prominent role in evolution of such low-energy beams is played by particle-particle interaction. Numerical simulations taking into account these effects are typically accomplished by a well-known particle-in-cell method. In practice, for convenient work a simulation program should not only implement this method, but also support parallelization, provide integration with CAD systems and allow access to details of the simulation algorithm. To address the formulated requirements, development of a new open source code - Ef - has been started. It's current features and main functionality are presented. Comparison with several analytical models demonstrates good agreement between the numerical results and the theory. Further development plans are discussed.

Relativistic hydrodynamics, heavy ion reactions and antiproton annihilation

International Nuclear Information System (INIS)

Strottman, D.

1985-01-01

The application of relativistic hydrodynamics to relativistic heavy ions and antiproton annihilation is summarized. Conditions for validity of hydrodynamics are presented. Theoretical results for inclusive particle spectra, pion production and flow analysis are given for medium energy heavy ions. The two-fluid model is introduced and results presented for reactions from 800 MeV per nucleon to 15 GeV on 15 GeV per nucleon. Temperatures and densities attained in antiproton annihilation are given. Finally, signals which might indicate the presence of a quark-gluon plasma are briefly surveyed

A particle swarm optimization algorithm for beam angle selection in intensity-modulated radiotherapy planning

International Nuclear Information System (INIS)

Li Yongjie; Yao Dezhong; Yao, Jonathan; Chen Wufan

2005-01-01

Automatic beam angle selection is an important but challenging problem for intensity-modulated radiation therapy (IMRT) planning. Though many efforts have been made, it is still not very satisfactory in clinical IMRT practice because of overextensive computation of the inverse problem. In this paper, a new technique named BASPSO (Beam Angle Selection with a Particle Swarm Optimization algorithm) is presented to improve the efficiency of the beam angle optimization problem. Originally developed as a tool for simulating social behaviour, the particle swarm optimization (PSO) algorithm is a relatively new population-based evolutionary optimization technique first introduced by Kennedy and Eberhart in 1995. In the proposed BASPSO, the beam angles are optimized using PSO by treating each beam configuration as a particle (individual), and the beam intensity maps for each beam configuration are optimized using the conjugate gradient (CG) algorithm. These two optimization processes are implemented iteratively. The performance of each individual is evaluated by a fitness value calculated with a physical objective function. A population of these individuals is evolved by cooperation and competition among the individuals themselves through generations. The optimization results of a simulated case with known optimal beam angles and two clinical cases (a prostate case and a head-and-neck case) show that PSO is valid and efficient and can speed up the beam angle optimization process. Furthermore, the performance comparisons based on the preliminary results indicate that, as a whole, the PSO-based algorithm seems to outperform, or at least compete with, the GA-based algorithm in computation time and robustness. In conclusion, the reported work suggested that the introduced PSO algorithm could act as a new promising solution to the beam angle optimization problem and potentially other optimization problems in IMRT, though further studies need to be investigated

A Combination of Genetic Algorithm and Particle Swarm Optimization for Vehicle Routing Problem with Time Windows.

Science.gov (United States)

Xu, Sheng-Hua; Liu, Ji-Ping; Zhang, Fu-Hao; Wang, Liang; Sun, Li-Jian

2015-08-27

A combination of genetic algorithm and particle swarm optimization (PSO) for vehicle routing problems with time windows (VRPTW) is proposed in this paper. The improvements of the proposed algorithm include: using the particle real number encoding method to decode the route to alleviate the computation burden, applying a linear decreasing function based on the number of the iterations to provide balance between global and local exploration abilities, and integrating with the crossover operator of genetic algorithm to avoid the premature convergence and the local minimum. The experimental results show that the proposed algorithm is not only more efficient and competitive with other published results but can also obtain more optimal solutions for solving the VRPTW issue. One new well-known solution for this benchmark problem is also outlined in the following.

A general method for generating bathymetric data for hydrodynamic computer models

Science.gov (United States)

Burau, J.R.; Cheng, R.T.

1989-01-01

To generate water depth data from randomly distributed bathymetric data for numerical hydrodymamic models, raw input data from field surveys, water depth data digitized from nautical charts, or a combination of the two are sorted to given an ordered data set on which a search algorithm is used to isolate data for interpolation. Water depths at locations required by hydrodynamic models are interpolated from the bathymetric data base using linear or cubic shape functions used in the finite-element method. The bathymetric database organization and preprocessing, the search algorithm used in finding the bounding points for interpolation, the mathematics of the interpolation formulae, and the features of the automatic generation of water depths at hydrodynamic model grid points are included in the analysis. This report includes documentation of two computer programs which are used to: (1) organize the input bathymetric data; and (2) to interpolate depths for hydrodynamic models. An example of computer program operation is drawn from a realistic application to the San Francisco Bay estuarine system. (Author 's abstract)

Lagrangian particle method for compressible fluid dynamics

Science.gov (United States)

Samulyak, Roman; Wang, Xingyu; Chen, Hsin-Chiang

2018-06-01

A new Lagrangian particle method for solving Euler equations for compressible inviscid fluid or gas flows is proposed. Similar to smoothed particle hydrodynamics (SPH), the method represents fluid cells with Lagrangian particles and is suitable for the simulation of complex free surface/multiphase flows. The main contributions of our method, which is different from SPH in all other aspects, are (a) significant improvement of approximation of differential operators based on a polynomial fit via weighted least squares approximation and the convergence of prescribed order, (b) a second-order particle-based algorithm that reduces to the first-order upwind method at local extremal points, providing accuracy and long term stability, and (c) more accurate resolution of entropy discontinuities and states at free interfaces. While the method is consistent and convergent to a prescribed order, the conservation of momentum and energy is not exact and depends on the convergence order. The method is generalizable to coupled hyperbolic-elliptic systems. Numerical verification tests demonstrating the convergence order are presented as well as examples of complex multiphase flows.

A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems

International Nuclear Information System (INIS)

Huang, Chia-Ling

2015-01-01

This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. - Highlights: • This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. • Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. • Four systems are introduced and the results demonstrate the PSSO performs particularly well

Multi-objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm

Science.gov (United States)

Cui, Xue; Gao, Jian; Feng, Yunbin; Zou, Chenlu; Liu, Huanlei

2018-01-01

In this paper, an optimization model with the minimum active power loss and minimum voltage deviation of node and maximum static voltage stability margin as the optimization objective is proposed for the reactive power optimization problems. By defining the index value of reactive power compensation, the optimal reactive power compensation node was selected. The particle swarm optimization algorithm was improved, and the selection pool of global optimal and the global optimal of probability (p-gbest) were introduced. A set of Pareto optimal solution sets is obtained by this algorithm. And by calculating the fuzzy membership value of the pareto optimal solution sets, individuals with the smallest fuzzy membership value were selected as the final optimization results. The above improved algorithm is used to optimize the reactive power of IEEE14 standard node system. Through the comparison and analysis of the results, it has been proven that the optimization effect of this algorithm was very good.

Algorithm of Data Reduce in Determination of Aerosol Particle Size Distribution at Damps/C

International Nuclear Information System (INIS)

Muhammad-Priyatna; Otto-Pribadi-Ruslanto

2001-01-01

The analysis had to do for algorithm of data reduction on Damps/C (Differential Mobility Particle Sizer with Condensation Particle Counter) system, this is for determine aerosol particle size distribution with range 0,01 μm to 1 μm in diameter. Damps/C (Differential Mobility Particle Sizer with Condensation Particle Counter) system contents are software and hardware. The hardware used determine of mobilities of aerosol particle and so the software used determine aerosol particle size distribution in diameter. The mobilities and diameter particle had connection in the electricity field. That is basic program for reduction of data and particle size conversion from particle mobility become particle diameter. The analysis to get transfer function value, Ω, is 0.5. The data reduction program to do conversation mobility basis become diameter basis with number efficiency correction, transfer function value, and poly charge particle. (author)

Canonical algorithms for numerical integration of charged particle motion equations

Science.gov (United States)

Efimov, I. N.; Morozov, E. A.; Morozova, A. R.

2017-02-01

A technique for numerically integrating the equation of charged particle motion in a magnetic field is considered. It is based on the canonical transformations of the phase space in Hamiltonian mechanics. The canonical transformations make the integration process stable against counting error accumulation. The integration algorithms contain a minimum possible amount of arithmetics and can be used to design accelerators and devices of electron and ion optics.

A Novel Path Planning for Robots Based on Rapidly-Exploring Random Tree and Particle Swarm Optimizer Algorithm

Directory of Open Access Journals (Sweden)

Zhou Feng

2013-09-01

Full Text Available A based on Rapidly-exploring Random Tree(RRT and Particle Swarm Optimizer (PSO for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.

Parameter estimation of fractional-order chaotic systems by using quantum parallel particle swarm optimization algorithm.

Directory of Open Access Journals (Sweden)

Yu Huang

Full Text Available Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.

Inverse Estimation of Surface Radiation Properties Using Repulsive Particle Swarm Optimization Algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyun Ho [Sejong University, Sejong (Korea, Republic of); Kim, Ki Wan [Agency for Defense Development, Daejeon (Korea, Republic of)

2014-09-15

The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface and gas radiation. In the present study, unknown radiation properties were estimated using an inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure. For efficiency, a repulsive particle swarm optimization (RPSO) algorithm, which is a relatively recent heuristic search method, was used as inverse solver. By comparing the convergence rates and accuracies with the results of a genetic algorithm (GA), the performances of the proposed RPSO algorithm as an inverse solver was verified when applied to the inverse analysis of the surface radiation problem.

Inverse Estimation of Surface Radiation Properties Using Repulsive Particle Swarm Optimization Algorithm

International Nuclear Information System (INIS)

Lee, Kyun Ho; Kim, Ki Wan

2014-01-01

The heat transfer mechanism for radiation is directly related to the emission of photons and electromagnetic waves. Depending on the participation of the medium, the radiation can be classified into two forms: surface and gas radiation. In the present study, unknown radiation properties were estimated using an inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure. For efficiency, a repulsive particle swarm optimization (RPSO) algorithm, which is a relatively recent heuristic search method, was used as inverse solver. By comparing the convergence rates and accuracies with the results of a genetic algorithm (GA), the performances of the proposed RPSO algorithm as an inverse solver was verified when applied to the inverse analysis of the surface radiation problem

Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Directory of Open Access Journals (Sweden)

Ayang Xiao

2014-01-01

Full Text Available Due to the fact that vastly different variables and constraints are simultaneously considered, truss layout optimization is a typical difficult constrained mixed-integer nonlinear program. Moreover, the computational cost of truss analysis is often quite expensive. In this paper, a novel fitness estimation based particle swarm optimization algorithm with an adaptive penalty function approach (FEPSO-AP is proposed to handle this problem. FEPSO-AP adopts a special fitness estimate strategy to evaluate the similar particles in the current population, with the purpose to reduce the computational cost. Further more, a laconic adaptive penalty function is employed by FEPSO-AP, which can handle multiple constraints effectively by making good use of historical iteration information. Four benchmark examples with fixed topologies and up to 44 design dimensions were studied to verify the generality and efficiency of the proposed algorithm. Numerical results of the present work compared with results of other state-of-the-art hybrid algorithms shown in the literature demonstrate that the convergence rate and the solution quality of FEPSO-AP are essentially competitive.

A simple algorithm for measuring particle size distributions on an uneven background from TEM images

DEFF Research Database (Denmark)

Gontard, Lionel Cervera; Ozkaya, Dogan; Dunin-Borkowski, Rafal E.

2011-01-01

Nanoparticles have a wide range of applications in science and technology. Their sizes are often measured using transmission electron microscopy (TEM) or X-ray diffraction. Here, we describe a simple computer algorithm for measuring particle size distributions from TEM images in the presence of a...... application to images of heterogeneous catalysts is presented.......Nanoparticles have a wide range of applications in science and technology. Their sizes are often measured using transmission electron microscopy (TEM) or X-ray diffraction. Here, we describe a simple computer algorithm for measuring particle size distributions from TEM images in the presence...

Smoothed particle hydrodynamics model for Landau-Lifshitz-Navier-Stokes and advection-diffusion equations.

Science.gov (United States)

Kordilla, Jannes; Pan, Wenxiao; Tartakovsky, Alexandre

2014-12-14

We propose a novel smoothed particle hydrodynamics (SPH) discretization of the fully coupled Landau-Lifshitz-Navier-Stokes (LLNS) and stochastic advection-diffusion equations. The accuracy of the SPH solution of the LLNS equations is demonstrated by comparing the scaling of velocity variance and the self-diffusion coefficient with kinetic temperature and particle mass obtained from the SPH simulations and analytical solutions. The spatial covariance of pressure and velocity fluctuations is found to be in a good agreement with theoretical models. To validate the accuracy of the SPH method for coupled LLNS and advection-diffusion equations, we simulate the interface between two miscible fluids. We study formation of the so-called "giant fluctuations" of the front between light and heavy fluids with and without gravity, where the light fluid lies on the top of the heavy fluid. We find that the power spectra of the simulated concentration field are in good agreement with the experiments and analytical solutions. In the absence of gravity, the power spectra decay as the power -4 of the wavenumber-except for small wavenumbers that diverge from this power law behavior due to the effect of finite domain size. Gravity suppresses the fluctuations, resulting in much weaker dependence of the power spectra on the wavenumber. Finally, the model is used to study the effect of thermal fluctuation on the Rayleigh-Taylor instability, an unstable dynamics of the front between a heavy fluid overlaying a light fluid. The front dynamics is shown to agree well with the analytical solutions.

An optimization method of relativistic backward wave oscillator using particle simulation and genetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Chen, Zaigao; Wang, Jianguo [Key Laboratory for Physical Electronics and Devices of the Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Northwest Institute of Nuclear Technology, P.O. Box 69-12, Xi' an, Shaanxi 710024 (China); Wang, Yue; Qiao, Hailiang; Zhang, Dianhui [Northwest Institute of Nuclear Technology, P.O. Box 69-12, Xi' an, Shaanxi 710024 (China); Guo, Weijie [Key Laboratory for Physical Electronics and Devices of the Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

2013-11-15

Optimal design method of high-power microwave source using particle simulation and parallel genetic algorithms is presented in this paper. The output power, simulated by the fully electromagnetic particle simulation code UNIPIC, of the high-power microwave device is given as the fitness function, and the float-encoding genetic algorithms are used to optimize the high-power microwave devices. Using this method, we encode the heights of non-uniform slow wave structure in the relativistic backward wave oscillators (RBWO), and optimize the parameters on massively parallel processors. Simulation results demonstrate that we can obtain the optimal parameters of non-uniform slow wave structure in the RBWO, and the output microwave power enhances 52.6% after the device is optimized.

Hydrodynamic discrimination of wakes caused by objects of different size or shape in a harbour seal (Phoca vitulina)

DEFF Research Database (Denmark)

Wieskotten, S.; Mauck, B.; Miersch, L.

2011-01-01

Harbour seals can use their mystacial vibrissae to detect and track hydrodynamic wakes. We investigated the ability of a harbour seal to discriminate objects of different size or shape by their hydrodynamic signature and used particle image velocimetry to identify the hydrodynamic parameters...... that a seal may be using to do so. Hydrodynamic trails were generated by different sized or shaped paddles that were moved in the calm water of an experimental box to produce a characteristic signal. In a two-alternative forced-choice procedure the blindfolded subject was able to discriminate size differences...... of down to 3.6. cm (Weber fraction 0.6) when paddles were moved at the same speed. Furthermore the subject distinguished hydrodynamic signals generated by flat, cylindrical, triangular or undulated paddles of the same width. Particle image velocimetry measurements demonstrated that the seal could have...

Optimization of Multipurpose Reservoir Operation with Application Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Elahe Fallah Mehdipour

2012-12-01

Full Text Available Optimal operation of multipurpose reservoirs is one of the complex and sometimes nonlinear problems in the field of multi-objective optimization. Evolutionary algorithms are optimization tools that search decision space using simulation of natural biological evolution and present a set of points as the optimum solutions of problem. In this research, application of multi-objective particle swarm optimization (MOPSO in optimal operation of Bazoft reservoir with different objectives, including generating hydropower energy, supplying downstream demands (drinking, industry and agriculture, recreation and flood control have been considered. In this regard, solution sets of the MOPSO algorithm in bi-combination of objectives and compromise programming (CP using different weighting and power coefficients have been first compared that the MOPSO algorithm in all combinations of objectives is more capable than the CP to find solution with appropriate distribution and these solutions have dominated the CP solutions. Then, ending points of solution set from the MOPSO algorithm and nonlinear programming (NLP results have been compared. Results showed that the MOPSO algorithm with 0.3 percent difference from the NLP results has more capability to present optimum solutions in the ending points of solution set.

Ultrasonic particle image velocimetry for improved flow gradient imaging: algorithms, methodology and validation

International Nuclear Information System (INIS)

Niu Lili; Qian Ming; Yu Wentao; Jin Qiaofeng; Ling Tao; Zheng Hairong; Wan Kun; Gao Shen

2010-01-01

This paper presents a new algorithm for ultrasonic particle image velocimetry (Echo PIV) for improving the flow velocity measurement accuracy and efficiency in regions with high velocity gradients. The conventional Echo PIV algorithm has been modified by incorporating a multiple iterative algorithm, sub-pixel method, filter and interpolation method, and spurious vector elimination algorithm. The new algorithms' performance is assessed by analyzing simulated images with known displacements, and ultrasonic B-mode images of in vitro laminar pipe flow, rotational flow and in vivo rat carotid arterial flow. Results of the simulated images show that the new algorithm produces much smaller bias from the known displacements. For laminar flow, the new algorithm results in 1.1% deviation from the analytically derived value, and 8.8% for the conventional algorithm. The vector quality evaluation for the rotational flow imaging shows that the new algorithm produces better velocity vectors. For in vivo rat carotid arterial flow imaging, the results from the new algorithm deviate 6.6% from the Doppler-measured peak velocities averagely compared to 15% of that from the conventional algorithm. The new Echo PIV algorithm is able to effectively improve the measurement accuracy in imaging flow fields with high velocity gradients.

Axisymmetric charge-conservative electromagnetic particle simulation algorithm on unstructured grids: Application to microwave vacuum electronic devices

Science.gov (United States)

Na, Dong-Yeop; Omelchenko, Yuri A.; Moon, Haksu; Borges, Ben-Hur V.; Teixeira, Fernando L.

2017-10-01

We present a charge-conservative electromagnetic particle-in-cell (EM-PIC) algorithm optimized for the analysis of vacuum electronic devices (VEDs) with cylindrical symmetry (axisymmetry). We exploit the axisymmetry present in the device geometry, fields, and sources to reduce the dimensionality of the problem from 3D to 2D. Further, we employ 'transformation optics' principles to map the original problem in polar coordinates with metric tensor diag (1 ,ρ2 , 1) to an equivalent problem on a Cartesian metric tensor diag (1 , 1 , 1) with an effective (artificial) inhomogeneous medium introduced. The resulting problem in the meridian (ρz) plane is discretized using an unstructured 2D mesh considering TEϕ-polarized fields. Electromagnetic field and source (node-based charges and edge-based currents) variables are expressed as differential forms of various degrees, and discretized using Whitney forms. Using leapfrog time integration, we obtain a mixed E - B finite-element time-domain scheme for the full-discrete Maxwell's equations. We achieve a local and explicit time update for the field equations by employing the sparse approximate inverse (SPAI) algorithm. Interpolating field values to particles' positions for solving Newton-Lorentz equations of motion is also done via Whitney forms. Particles are advanced using the Boris algorithm with relativistic correction. A recently introduced charge-conserving scatter scheme tailored for 2D unstructured grids is used in the scatter step. The algorithm is validated considering cylindrical cavity and space-charge-limited cylindrical diode problems. We use the algorithm to investigate the physical performance of VEDs designed to harness particle bunching effects arising from the coherent (resonance) Cerenkov electron beam interactions within micro-machined slow wave structures.

Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity.

Science.gov (United States)

Qi, Xin; Ju, Guohao; Xu, Shuyan

2018-04-10

The phase diversity (PD) technique needs optimization algorithms to minimize the error metric and find the global minimum. Particle swarm optimization (PSO) is very suitable for PD due to its simple structure, fast convergence, and global searching ability. However, the traditional PSO algorithm for PD still suffers from the stagnation problem (premature convergence), which can result in a wrong solution. In this paper, the stagnation problem of the traditional PSO algorithm for PD is illustrated first. Then, an explicit strategy is proposed to solve this problem, based on an in-depth understanding of the inherent optimization mechanism of the PSO algorithm. Specifically, a criterion is proposed to detect premature convergence; then a redistributing mechanism is proposed to prevent premature convergence. To improve the efficiency of this redistributing mechanism, randomized Halton sequences are further introduced to ensure the uniform distribution and randomness of the redistributed particles in the search space. Simulation results show that this strategy can effectively solve the stagnation problem of the PSO algorithm for PD, especially for large-scale and high-dimension wavefront sensing and noisy conditions. This work is further verified by an experiment. This work can improve the robustness and performance of PD wavefront sensing.

The Study on Food Sensory Evaluation based on Particle Swarm Optimization Algorithm

OpenAIRE

Hairong Wang; Huijuan Xu

2015-01-01

In this study, it explores the procedures and methods of the system for establishing food sensory evaluation based on particle swarm optimization algorithm, by means of explaining the interpretation of sensory evaluation and sensory analysis, combined with the applying situation of sensory evaluation in food industry.

Design of Wire Antennas by Using an Evolved Particle Swarm Optimization Algorithm

NARCIS (Netherlands)

Lepelaars, E.S.A.M.; Zwamborn, A.P.M.; Rogovic, A.; Marasini, C.; Monorchio, A.

2007-01-01

A Particle Swarm Optimization (PSO) algorithm has been used in conjunction with a full-wave numerical code based on the Method of Moments (MoM) to design and optimize wire antennas. The PSO is a robust stochastic evolutionary numerical technique that is very effective in optimizing multidimensional

Hydrodynamic Torques and Rotations of Superparamagnetic Bead Dimers

Science.gov (United States)

Pease, Christopher; Etheridge, J.; Wijesinghe, H. S.; Pierce, C. J.; Prikockis, M. V.; Sooryakumar, R.

Chains of micro-magnetic particles are often rotated with external magnetic fields for many lab-on-a-chip technologies such as transporting beads or mixing fluids. These applications benefit from faster responses of the actuated particles. In a rotating magnetic field, the magnetization of superparamagnetic beads, created from embedded magnetic nano-particles within a polymer matrix, is largely characterized by induced dipoles mip along the direction of the field. In addition there is often a weak dipole mop that orients out-of-phase with the external rotating field. On a two-bead dimer, the simplest chain of beads, mop contributes a torque Γm in addition to the torque from mip. For dimers with beads unbound to each other, mop rotates individual beads which generate an additional hydrodynamic torque on the dimer. Whereas, mop directly torques bound dimers. Our results show that Γm significantly alters the average frequency-dependent dimer rotation rate for both bound and unbound monomers and, when mop exceeds a critical value, increases the maximum dimer rotation frequency. Models that include magnetic and hydrodynamics torques provide good agreement with the experimental findings over a range of field frequencies.

Setting value optimization method in integration for relay protection based on improved quantum particle swarm optimization algorithm

Science.gov (United States)

Yang, Guo Sheng; Wang, Xiao Yang; Li, Xue Dong

2018-03-01

With the establishment of the integrated model of relay protection and the scale of the power system expanding, the global setting and optimization of relay protection is an extremely difficult task. This paper presents a kind of application in relay protection of global optimization improved particle swarm optimization algorithm and the inverse time current protection as an example, selecting reliability of the relay protection, selectivity, quick action and flexibility as the four requires to establish the optimization targets, and optimizing protection setting values of the whole system. Finally, in the case of actual power system, the optimized setting value results of the proposed method in this paper are compared with the particle swarm algorithm. The results show that the improved quantum particle swarm optimization algorithm has strong search ability, good robustness, and it is suitable for optimizing setting value in the relay protection of the whole power system.

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

Science.gov (United States)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

Spin current evolution in the separated spin-up and spin-down quantum hydrodynamics

International Nuclear Information System (INIS)

Trukhanova, Mariya Iv.

2015-01-01

We have developed a method of quantum hydrodynamics (QHD) that describes particles with spin-up and with spin-down in separate. We have derived the equation of the spin current evolution as a part of the set of the quantum hydrodynamics equations that treat particles with different projection of spin on the preferable direction as two different species. We have studied orthogonal propagation of waves in the external magnetic field and determined the contribution of quantum corrections due to the Bohm potential and to magnetization energy of particles with different projections of spin in the spin-current wave dispersion. We have analyzed the limits of weak and strong magnetic fields. - Highlights: • We derive the spin current equation for particles with different projection of spin. • We predict the contribution of Bohm potential to the dynamics of spin current. • We derive the spin-current wave in the system of spin-polarized particles. • We study the propagation of spin-acoustic wave in magnetized dielectrics.

Hydrodynamic predictions for 5.44 TeV Xe+Xe collisions

Science.gov (United States)

Giacalone, Giuliano; Noronha-Hostler, Jacquelyn; Luzum, Matthew; Ollitrault, Jean-Yves

2018-03-01

We argue that relativistic hydrodynamics is able to make robust predictions for soft particle production in Xe+Xe collisions at the CERN Large Hadron Collider (LHC). The change of system size from Pb+Pb to Xe+Xe provides a unique opportunity to test the scaling laws inherent to fluid dynamics. Using event-by-event hydrodynamic simulations, we make quantitative predictions for several observables: mean transverse momentum, anisotropic flow coefficients, and their fluctuations. Results are shown as a function of collision centrality.

Fully implicit Particle-in-cell algorithms for multiscale plasma simulation

Energy Technology Data Exchange (ETDEWEB)

Chacon, Luis [Los Alamos National Laboratory

2015-07-16

The outline of the paper is as follows: Particle-in-cell (PIC) methods for fully ionized collisionless plasmas, explicit vs. implicit PIC, 1D ES implicit PIC (charge and energy conservation, moment-based acceleration), and generalization to Multi-D EM PIC: Vlasov-Darwin model (review and motivation for Darwin model, conservation properties (energy, charge, and canonical momenta), and numerical benchmarks). The author demonstrates a fully implicit, fully nonlinear, multidimensional PIC formulation that features exact local charge conservation (via a novel particle mover strategy), exact global energy conservation (no particle self-heating or self-cooling), adaptive particle orbit integrator to control errors in momentum conservation, and canonical momenta (EM-PIC only, reduced dimensionality). The approach is free of numerical instabilities: ω_peΔt >> 1, and Δx >> λ_D. It requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant CPU gains (vs explicit PIC) have been demonstrated. The method has much potential for efficiency gains vs. explicit in long-time-scale applications. Moment-based acceleration is effective in minimizing N_FE, leading to an optimal algorithm.

The Splashback Radius of Halos from Particle Dynamics. I. The SPARTA Algorithm

Science.gov (United States)

Diemer, Benedikt

2017-07-01

Motivated by the recent proposal of the splashback radius as a physical boundary of dark-matter halos, we present a parallel computer code for Subhalo and PARticle Trajectory Analysis (SPARTA). The code analyzes the orbits of all simulation particles in all host halos, billions of orbits in the case of typical cosmological N-body simulations. Within this general framework, we develop an algorithm that accurately extracts the location of the first apocenter of particles after infall into a halo, or splashback. We define the splashback radius of a halo as the smoothed average of the apocenter radii of individual particles. This definition allows us to reliably measure the splashback radii of 95% of host halos above a resolution limit of 1000 particles. We show that, on average, the splashback radius and mass are converged to better than 5% accuracy with respect to mass resolution, snapshot spacing, and all free parameters of the method.

Introduction to hydrodynamics

International Nuclear Information System (INIS)

Wilkins, M.L.

1979-01-01

Various aspects of hydrodynamics and elastic--plastic flow are introduced for the purpose of defining hydrodynamic terms and explaining what some of the important hydrodynamic concepts are. The first part covers hydrodynamic theory; and discussed fundamental hydrodynamic equations, discontinuities, and shock, detonation, and elastic--plastic waves. The second part deals with applications of hydrodynamic theory to material equations of state, spall, Taylor instabilities, and detonation pressure measurements

Pion interferometry theory for the hydrodynamic stage of multiple processes

International Nuclear Information System (INIS)

Makhlin, A.N.; Sinyukov, Yu.M.

1986-01-01

The double pion inclusive cross section for identical particles is described in hydrodynamical theory of multiparticle production. The pion interferometry theory is developed for the case when secondary particles are generated against the background of internal relativistic motion of radiative hadron matter. The connection between correlation functions in various schemes of experiment is found within the framework of relativistic Wigner functions formalism

Integrable hydrodynamics of Calogero-Sutherland model: bidirectional Benjamin-Ono equation

International Nuclear Information System (INIS)

Abanov, Alexander G; Bettelheim, Eldad; Wiegmann, Paul

2009-01-01

We develop a hydrodynamic description of the classical Calogero-Sutherland liquid: a Calogero-Sutherland model with an infinite number of particles and a non-vanishing density of particles. The hydrodynamic equations, being written for the density and velocity fields of the liquid, are shown to be a bidirectional analog of the Benjamin-Ono equation. The latter is known to describe internal waves of deep stratified fluids. We show that the bidirectional Benjamin-Ono equation appears as a real reduction of the modified KP hierarchy. We derive the chiral nonlinear equation which appears as a chiral reduction of the bidirectional equation. The conventional Benjamin-Ono equation is a degeneration of the chiral nonlinear equation at large density. We construct multi-phase solutions of the bidirectional Benjamin-Ono equations and of the chiral nonlinear equations

Particle swarm optimizer for weighting factor selection in intensity-modulated radiation therapy optimization algorithms.

Science.gov (United States)

Yang, Jie; Zhang, Pengcheng; Zhang, Liyuan; Shu, Huazhong; Li, Baosheng; Gui, Zhiguo

2017-01-01

In inverse treatment planning of intensity-modulated radiation therapy (IMRT), the objective function is typically the sum of the weighted sub-scores, where the weights indicate the importance of the sub-scores. To obtain a high-quality treatment plan, the planner manually adjusts the objective weights using a trial-and-error procedure until an acceptable plan is reached. In this work, a new particle swarm optimization (PSO) method which can adjust the weighting factors automatically was investigated to overcome the requirement of manual adjustment, thereby reducing the workload of the human planner and contributing to the development of a fully automated planning process. The proposed optimization method consists of three steps. (i) First, a swarm of weighting factors (i.e., particles) is initialized randomly in the search space, where each particle corresponds to a global objective function. (ii) Then, a plan optimization solver is employed to obtain the optimal solution for each particle, and the values of the evaluation functions used to determine the particle's location and the population global location for the PSO are calculated based on these results. (iii) Next, the weighting factors are updated based on the particle's location and the population global location. Step (ii) is performed alternately with step (iii) until the termination condition is reached. In this method, the evaluation function is a combination of several key points on the dose volume histograms. Furthermore, a perturbation strategy - the crossover and mutation operator hybrid approach - is employed to enhance the population diversity, and two arguments are applied to the evaluation function to improve the flexibility of the algorithm. In this study, the proposed method was used to develop IMRT treatment plans involving five unequally spaced 6MV photon beams for 10 prostate cancer cases. The proposed optimization algorithm yielded high-quality plans for all of the cases, without human

Efficiencies of dynamic Monte Carlo algorithms for off-lattice particle systems with a single impurity

KAUST Repository

Novotny, M.A.

2010-02-01

The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing Markov Chains method are given. Simulation results are presented to confirm the theoretical efficiencies. © 2010.

A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm.

Science.gov (United States)

Amoshahy, Mohammad Javad; Shamsi, Mousa; Sedaaghi, Mohammad Hossein

2016-01-01

Particle swarm optimization (PSO) is an evolutionary computing method based on intelligent collective behavior of some animals. It is easy to implement and there are few parameters to adjust. The performance of PSO algorithm depends greatly on the appropriate parameter selection strategies for fine tuning its parameters. Inertia weight (IW) is one of PSO's parameters used to bring about a balance between the exploration and exploitation characteristics of PSO. This paper proposes a new nonlinear strategy for selecting inertia weight which is named Flexible Exponential Inertia Weight (FEIW) strategy because according to each problem we can construct an increasing or decreasing inertia weight strategy with suitable parameters selection. The efficacy and efficiency of PSO algorithm with FEIW strategy (FEPSO) is validated on a suite of benchmark problems with different dimensions. Also FEIW is compared with best time-varying, adaptive, constant and random inertia weights. Experimental results and statistical analysis prove that FEIW improves the search performance in terms of solution quality as well as convergence rate.

Multiple R&D projects scheduling optimization with improved particle swarm algorithm.

Science.gov (United States)

Liu, Mengqi; Shan, Miyuan; Wu, Juan

2014-01-01

For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.

A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting

International Nuclear Information System (INIS)

Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo

2008-01-01

In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)

Numerical Analysis Study of Sarawak Barrage River Bed Erosion and Scouring by Using Smooth Particle Hydrodynamic (SPH)

Science.gov (United States)

Zainol, M. R. R. M. A.; Kamaruddin, M. A.; Zawawi, M. H.; Wahab, K. A.

2017-11-01

Smooth Particle Hydrodynamic is the three-dimensional (3D) model. In this research work, three cases and one validation have been simulate using DualSPHysics. Study area of this research work was at Sarawak Barrage. The cases have different water level at the downstream. This study actually to simulate riverbed erosion and scouring properties by using multi-phases cases which use sand as sediment and water. The velocity and the scouring profile have been recorded as the result and shown in the result chapter. The result of the validation is acceptable where the scouring profile and the velocity were slightly different between laboratory experiment and simulation. Hence, it can be concluded that the simulation by using SPH can be used as the alternative to simulate the real cases.

Dilepton production in schematic causal viscous hydrodynamics

International Nuclear Information System (INIS)

Song, Taesoo; Han, Kyong Chol; Ko, Che Ming

2011-01-01

Assuming that in the hot dense matter produced in relativistic heavy-ion collisions, the energy density, entropy density, and pressure as well as the azimuthal and space-time rapidity components of the shear tensor are uniform in the direction transversal to the reaction plane, we derive a set of schematic equations from the Isreal-Stewart causal viscous hydrodynamics. These equations are then used to describe the evolution dynamics of relativistic heavy-ion collisions by taking the shear viscosity to entropy density ratio of 1/4π for the initial quark-gluon plasma (QGP) phase and of 10 times this value for the later hadron-gas (HG) phase. Using the production rate evaluated with particle distributions that take into account the viscous effect, we study dilepton production in central heavy-ion collisions. Compared with results from the ideal hydrodynamics, we find that although the dilepton invariant mass spectra from the two approaches are similar, the transverse momentum spectra are significantly enhanced at high transverse momenta by the viscous effect. We also study the transverse momentum dependence of dileptons produced from QGP for a fixed transverse mass, which is essentially absent in the ideal hydrodynamics, and find that this so-called transverse mass scaling is violated in the viscous hydrodynamics, particularly at high transverse momenta.

Simulations of Model Microswimmers with Fully Resolved Hydrodynamics

Science.gov (United States)

Oyama, Norihiro; Molina, John J.; Yamamoto, Ryoichi

2017-10-01

Swimming microorganisms, which include bacteria, algae, and spermatozoa, play a fundamental role in most biological processes. These swimmers are a special type of active particle, that continuously convert local energy into propulsive forces, thereby allowing them to move through their surrounding fluid medium. While the size, shape, and propulsion mechanism vary from one organism to the next, they share certain general characteristics: they exhibit force-free motion and they swim at a small Reynolds number. To study the dynamics of such systems, we use the squirmer model, which provides an ideal representation of swimmers as spheroidal particles that propel owing to a modified boundary condition at their surface. We have considered the single-particle and many-particle dynamics of swimmers in bulk and confined systems using the smoothed profile method, which allows us to efficiently solve the coupled particle-fluid problem. For the single-particle dynamics, we studied the diffusive behavior caused by the swimming of the particles. At short-time scales, the diffusion is caused by the hydrodynamic interactions, whereas at long-time scales, it is determined by the particle-particle collisions. Thus, the short-time diffusion will be the same for both swimmers and inert tracer particles. We then investigated the dynamics of confined microswimmers using cylindrical and parallel-plate confining walls. For the cylindrical confinement, we find evidence of an order/disorder phase transition which depends on the specific type of swimmers and the size of the cylinder. Under parallel-plane walls, some swimmers exhibit wavelike modes, which lead to traveling density waves that bounce back and forth between the walls. From an analysis of the bulk systems, we can show that this wavelike motion can be understood as a pseudoacoustic mode and is a consequence of the intrinsic swimming properties of the particles. The results presented here, together with the simulation method that

The Monte Carlo photoionization and moving-mesh radiation hydrodynamics code CMACIONIZE

Science.gov (United States)

Vandenbroucke, B.; Wood, K.

2018-04-01

We present the public Monte Carlo photoionization and moving-mesh radiation hydrodynamics code CMACIONIZE, which can be used to simulate the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given type, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code, but also as a moving-mesh code.

Hydrodynamic Limit of Multiple SLE

Science.gov (United States)

Hotta, Ikkei; Katori, Makoto

2018-04-01

Recently del Monaco and Schleißinger addressed an interesting problem whether one can take the limit of multiple Schramm-Loewner evolution (SLE) as the number of slits N goes to infinity. When the N slits grow from points on the real line R in a simultaneous way and go to infinity within the upper half plane H, an ordinary differential equation describing time evolution of the conformal map g_t(z) was derived in the N → ∞ limit, which is coupled with a complex Burgers equation in the inviscid limit. It is well known that the complex Burgers equation governs the hydrodynamic limit of the Dyson model defined on R studied in random matrix theory, and when all particles start from the origin, the solution of this Burgers equation is given by the Stieltjes transformation of the measure which follows a time-dependent version of Wigner's semicircle law. In the present paper, first we study the hydrodynamic limit of the multiple SLE in the case that all slits start from the origin. We show that the time-dependent version of Wigner's semicircle law determines the time evolution of the SLE hull, K_t \\subset H\\cup R, in this hydrodynamic limit. Next we consider the situation such that a half number of the slits start from a>0 and another half of slits start from -a exact solutions, we will discuss the universal long-term behavior of the multiple SLE and its hull K_t in the hydrodynamic limit.

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

A subzone reconstruction algorithm for efficient staggered compatible remapping

Energy Technology Data Exchange (ETDEWEB)

Starinshak, D.P., E-mail: starinshak1@llnl.gov; Owen, J.M., E-mail: mikeowen@llnl.gov

2015-09-01

Staggered-grid Lagrangian hydrodynamics algorithms frequently make use of subzonal discretization of state variables for the purposes of improved numerical accuracy, generality to unstructured meshes, and exact conservation of mass, momentum, and energy. For Arbitrary Lagrangian–Eulerian (ALE) methods using a geometric overlay, it is difficult to remap subzonal variables in an accurate and efficient manner due to the number of subzone–subzone intersections that must be computed. This becomes prohibitive in the case of 3D, unstructured, polyhedral meshes. A new procedure is outlined in this paper to avoid direct subzonal remapping. The new algorithm reconstructs the spatial profile of a subzonal variable using remapped zonal and nodal representations of the data. The reconstruction procedure is cast as an under-constrained optimization problem. Enforcing conservation at each zone and node on the remapped mesh provides the set of equality constraints; the objective function corresponds to a quadratic variation per subzone between the values to be reconstructed and a set of target reference values. Numerical results for various pure-remapping and hydrodynamics tests are provided. Ideas for extending the algorithm to staggered-grid radiation-hydrodynamics are discussed as well as ideas for generalizing the algorithm to include inequality constraints.

An extended dissipative particle dynamics model

CERN Document Server

Cotter, C J

2003-01-01

The method of dissipative particle dynamics (DPD) was introduced by Hoogerbrugge & Koelman to study meso-scale material processes. The theoretical investigation of the DPD method was initiated by Espanol who used a Fokker-Planck formulation of the DPD method and applied the Mori-Zwanzig projection operator calculus to obtain the equations of hydrodynamics for DPD. A current limitation of DPD is that it requires a clear separation of scales between the resolved and unresolved processes. In this note, we suggest a simple extension of DPD that allows for inclusion of unresolved processes with exponentially decaying variance for any value of the decay rate. The main point of the extension is that it is as easy to implement as DPD in a numerical algorithm.

CMacIonize: Monte Carlo photoionisation and moving-mesh radiation hydrodynamics

Science.gov (United States)

Vandenbroucke, Bert; Wood, Kenneth

2018-02-01

CMacIonize simulates the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given time, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code and also as a moving-mesh code.

A comparative analysis of particle swarm optimization and differential evolution algorithms for parameter estimation in nonlinear dynamic systems

International Nuclear Information System (INIS)

Banerjee, Amit; Abu-Mahfouz, Issam

2014-01-01

The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm

A tracking algorithm for the reconstruction of the daughters of long-lived particles in LHCb

CERN Document Server

Dendek, Adam Mateusz

2018-01-01

A tracking algorithm for the reconstruction of the daughters of long-lived particles in LHCb 5 Jun 2018, 16:00 1h 30m Library, Centro San Domenico () LHC experiments Posters session Speaker Katharina Mueller (Universitaet Zuerich (CH)) Description The LHCb experiment at CERN operates a high precision and robust tracking system to reach its physics goals, including precise measurements of CP-violation phenomena in the heavy flavour quark sector and searches for New Physics beyond the Standard Model. The track reconstruction procedure is performed by a number of algorithms. One of these, PatLongLivedTracking, is optimised to reconstruct "downstream tracks", which are tracks originating from decays outside the LHCb vertex detector of long-lived particles, such as Ks or Λ0. After an overview of the LHCb tracking system, we provide a detailed description of the LHCb downstream track reconstruction algorithm. Its computational intelligence part is described in details, including the adaptation of the employed...

Final Report. Hydrodynamics by high-energy-density plasma flow and hydrodynamics and radiative hydrodynamics with astrophysical application

International Nuclear Information System (INIS)

R Paul Drake

2004-01-01

OAK-B135 This is the final report from the project Hydrodynamics by High-Energy-Density Plasma Flow and Hydrodynamics and Radiation Hydrodynamics with Astrophysical Applications. This project supported a group at the University of Michigan in the invention, design, performance, and analysis of experiments using high-energy-density research facilities. The experiments explored compressible nonlinear hydrodynamics, in particular at decelerating interfaces, and the radiation hydrodynamics of strong shock waves. It has application to supernovae, astrophysical jets, shock-cloud interactions, and radiative shock waves

Hydrodynamic model research in Waseda group

International Nuclear Information System (INIS)

Muroya, Shin

2010-01-01

Constructing 'High Energy Material Science' had been proposed by Namiki as the guiding principle for the scientists of the high energy physics group lead by himself in Waseda University when the author started to study multiple particle production in 1980s toward the semi-phenomenological model for the quark gluon plasma (QGP). Their strategy was based on three stages to build an intermediate one between the fundamental theory of QCD and the phenomenological model. The quantum theoretical Langevin equation was taken up as the semi-phenomenological model at the intermediate stage and the Landau hydrodynamic model was chosen as the phenomenological model to focus on the 'phase transition' of QGP. A review is given here over the quantum theoretical Langevin equation formalism developed there and followed by the further progress with the 1+1 dimensional viscous fluid model as well as the hydrodynamic model with cylindrical symmetry. The developments of the baryon fluid model and Hanbury-Brown Twiss effect are also reviewed. After 1995 younger generation physicists came to the group to develop those models further. Activities by Hirano, Nonaka and Morita beyond the past generation's hydrodynamic model are picked up briefly. (S. Funahashi)

Disruptive Innovation in Numerical Hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Waltz, Jacob I. [Los Alamos National Laboratory

2012-09-06

We propose the research and development of a high-fidelity hydrodynamic algorithm for tetrahedral meshes that will lead to a disruptive innovation in the numerical modeling of Laboratory problems. Our proposed innovation has the potential to reduce turnaround time by orders of magnitude relative to Advanced Simulation and Computing (ASC) codes; reduce simulation setup costs by millions of dollars per year; and effectively leverage Graphics Processing Unit (GPU) and future Exascale computing hardware. If successful, this work will lead to a dramatic leap forward in the Laboratory's quest for a predictive simulation capability.

Data Assimilation in Air Contaminant Dispersion Using a Particle Filter and Expectation-Maximization Algorithm

Directory of Open Access Journals (Sweden)

Rongxiao Wang

2017-09-01

Full Text Available The accurate prediction of air contaminant dispersion is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in chemical industry parks. Conventional atmospheric dispersion models can seldom give accurate predictions due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion models, two data assimilation methods (i.e., the typical particle filter & the combination of a particle filter and expectation-maximization algorithm are proposed to assimilate the virtual Unmanned Aerial Vehicle (UAV observations with measurement error into the atmospheric dispersion model. Two emission cases with different dimensions of state parameters are considered. To test the performances of the proposed methods, two numerical experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model predictions when the dimension of state parameters is relatively low. In contrast, when the dimension of state parameters becomes higher, the method of particle filter combining the expectation-maximization algorithm performs better in terms of the parameter estimation accuracy. Therefore, the proposed data assimilation methods are able to effectively support air quality monitoring and emergency management in chemical industry parks.

Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Weizhe Zhang

2014-01-01

Full Text Available Energy consumption in computer systems has become a more and more important issue. High energy consumption has already damaged the environment to some extent, especially in heterogeneous multiprocessors. In this paper, we first formulate and describe the energy-aware real-time task scheduling problem in heterogeneous multiprocessors. Then we propose a particle swarm optimization (PSO based algorithm, which can successfully reduce the energy cost and the time for searching feasible solutions. Experimental results show that the PSO-based energy-aware metaheuristic uses 40%–50% less energy than the GA-based and SFLA-based algorithms and spends 10% less time than the SFLA-based algorithm in finding the solutions. Besides, it can also find 19% more feasible solutions than the SFLA-based algorithm.

RPYFMM: Parallel adaptive fast multipole method for Rotne-Prager-Yamakawa tensor in biomolecular hydrodynamics simulations

Science.gov (United States)

Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.

2018-06-01

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

Fluctuating nonlinear hydrodynamics of flocking

Science.gov (United States)

Yadav, Sunil Kumar; Das, Shankar P.

2018-03-01

Starting from a microscopic model, the continuum field theoretic description of the dynamics of a system of active ingredients or "particles" is presented. The equations of motion for the respective collective densities of mass and momentum follow exactly from that of a single element in the flock. The single-particle dynamics has noise and anomalous momentum dependence in its frictional terms. The equations for the collective densities are averaged over a local equilibrium distribution to obtain the corresponding coarse grained equations of fluctuating nonlinear hydrodynamics (FNH). The latter are the equations used frequently for describing active systems on the basis of intuitive arguments. The transport coefficients which appear in the macroscopic FNH equations are determined in terms of the parameters of the microscopic dynamics.

A Hard Constraint Algorithm to Model Particle Interactions in DNA-laden Flows

Energy Technology Data Exchange (ETDEWEB)

Trebotich, D; Miller, G H; Bybee, M D

2006-08-01

We present a new method for particle interactions in polymer models of DNA. The DNA is represented by a bead-rod polymer model and is fully-coupled to the fluid. The main objective in this work is to implement short-range forces to properly model polymer-polymer and polymer-surface interactions, specifically, rod-rod and rod-surface uncrossing. Our new method is based on a rigid constraint algorithm whereby rods elastically bounce off one another to prevent crossing, similar to our previous algorithm used to model polymer-surface interactions. We compare this model to a classical (smooth) potential which acts as a repulsive force between rods, and rods and surfaces.

Optimization of heat pump system in indoor swimming pool using particle swarm algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Wen-Shing; Kung, Chung-Kuan [Department of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, 1, Section 3, Chung-Hsiao East Road, Taipei (China)

2008-09-15

When it comes to indoor swimming pool facilities, a large amount of energy is required to heat up low-temperature outdoor air before it is being introduced indoors to maintain indoor humidity. Since water is evaporated from the pool surface, the exhausted air contains more water and specific enthalpy. In response to this indoor air, heat pump is generally used in heat recovery for indoor swimming pools. To reduce the cost in energy consumption, this paper utilizes particle swarm algorithm to optimize the design of heat pump system. The optimized parameters include continuous parameters and discrete parameters. The former consists of outdoor air mass flow and heat conductance of heat exchangers; the latter comprises compressor type and boiler type. In a case study, life cycle energy cost is considered as an objective function. In this regard, the optimized outdoor air flow and the optimized design for heating system can be deduced by using particle swarm algorithm. (author)

Optimization of Reinforced Concrete Reservoir with Circumferential Stiffeners Strips by Particle Swarm Algorithm

Directory of Open Access Journals (Sweden)

GholamReza Havaei

2015-09-01

Full Text Available Reinforced concrete reservoirs (RCR have been used extensively in municipal and industrial facilities for several decades. The design of these structures requires that attention be given not only to strength requirements, but to serviceability requirements as well. These types of structures will be square, round, and oval reinforced concrete structures which may be above, below, or partially below ground. The main challenge is to design concrete liquid containing structures which will resist the extremes of seasonal temperature changes, a variety of loading conditions, and remain liquid tight for useful life of 50 to 60 years. In this study, optimization is performed by particle swarm algorithm basd on structural design. Firstly by structural analysis all range of shell thickness and areas of rebar find. In the second step by parameter identification system interchange algorithm, source code which developed in particle swarm algorithm by MATLAB software linked to analysis software. Therefore best and optimized thicknesses and total area of bars for each element find. Lastly with circumferential stiffeners structure optimize and show 19% decrease in weight of rebar, 20% decrease in volume of concrete, and 13% minimum cost reduction in construction procedure compared with conventional 10,000 m3 RCR structures.

Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life

KAUST Repository

Zenil, Hector

2018-02-18

We demonstrate the way to apply and exploit the concept of \\\\textit{algorithmic information dynamics} in the characterization and classification of dynamic and persistent patterns, motifs and colliding particles in, without loss of generalization, Conway\\'s Game of Life (GoL) cellular automaton as a case study. We analyze the distribution of prevailing motifs that occur in GoL from the perspective of algorithmic probability. We demonstrate how the tools introduced are an alternative to computable measures such as entropy and compression algorithms which are often nonsensitive to small changes and features of non-statistical nature in the study of evolving complex systems and their emergent structures.

Numerical simulation of the hydrodynamics within octagonal tanks in recirculating aquaculture systems

Science.gov (United States)

Liu, Yao; Liu, Baoliang; Lei, Jilin; Guan, Changtao; Huang, Bin

2017-07-01

A three-dimensional numerical model was established to simulate the hydrodynamics within an octagonal tank of a recirculating aquaculture system. The realizable k- ɛ turbulence model was applied to describe the flow, the discrete phase model (DPM) was applied to generate particle trajectories, and the governing equations are solved using the finite volume method. To validate this model, the numerical results were compared with data obtained from a full-scale physical model. The results show that: (1) the realizable k- ɛ model applied for turbulence modeling describes well the flow pattern in octagonal tanks, giving an average relative error of velocities between simulated and measured values of 18% from contour maps of velocity magnitudes; (2) the DPM was applied to obtain particle trajectories and to simulate the rate of particle removal from the tank. The average relative error of the removal rates between simulated and measured values was 11%. The DPM can be used to assess the self-cleaning capability of an octagonal tank; (3) a comprehensive account of the hydrodynamics within an octagonal tank can be assessed from simulations. The velocity distribution was uniform with an average velocity of 15 cm/s; the velocity reached 0.8 m/s near the inlet pipe, which can result in energy losses and cause wall abrasion; the velocity in tank corners was more than 15 cm/s, which suggests good water mixing, and there was no particle sedimentation. The percentage of particle removal for octagonal tanks was 90% with the exception of a little accumulation of ≤ 5 mm particle in the area between the inlet pipe and the wall. This study demonstrated a consistent numerical model of the hydrodynamics within octagonal tanks that can be further used in their design and optimization as well as promote the wide use of computational fluid dynamics in aquaculture engineering.

MISR Dark Water aerosol retrievals: operational algorithm sensitivity to particle non-sphericity

Directory of Open Access Journals (Sweden)

O. V. Kalashnikova

2013-08-01

Full Text Available The aim of this study is to theoretically investigate the sensitivity of the Multi-angle Imaging SpectroRadiometer (MISR operational (version 22 Dark Water retrieval algorithm to aerosol non-sphericity over the global oceans under actual observing conditions, accounting for current algorithm assumptions. Non-spherical (dust aerosol models, which were introduced in version 16 of the MISR aerosol product, improved the quality and coverage of retrievals in dusty regions. Due to the sensitivity of the retrieval to the presence of non-spherical aerosols, the MISR aerosol product has been successfully used to track the location and evolution of mineral dust plumes from the Sahara across the Atlantic, for example. However, the MISR global non-spherical aerosol optical depth (AOD fraction product has been found to have several climatological artifacts superimposed on valid detections of mineral dust, including high non-spherical fraction in the Southern Ocean and seasonally variable bands of high non-sphericity. In this paper we introduce a formal approach to examine the ability of the operational MISR Dark Water algorithm to distinguish among various spherical and non-spherical particles as a function of the variable MISR viewing geometry. We demonstrate the following under the criteria currently implemented: (1 Dark Water retrieval sensitivity to particle non-sphericity decreases for AOD below about 0.1 primarily due to an unnecessarily large lower bound imposed on the uncertainty in MISR observations at low light levels, and improves when this lower bound is removed; (2 Dark Water retrievals are able to distinguish between the spherical and non-spherical particles currently used for all MISR viewing geometries when the AOD exceeds 0.1; (3 the sensitivity of the MISR retrievals to aerosol non-sphericity varies in a complex way that depends on the sampling of the scattering phase function and the contribution from multiple scattering; and (4 non

A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm

Science.gov (United States)

Shamsi, Mousa; Sedaaghi, Mohammad Hossein

2016-01-01

Particle swarm optimization (PSO) is an evolutionary computing method based on intelligent collective behavior of some animals. It is easy to implement and there are few parameters to adjust. The performance of PSO algorithm depends greatly on the appropriate parameter selection strategies for fine tuning its parameters. Inertia weight (IW) is one of PSO’s parameters used to bring about a balance between the exploration and exploitation characteristics of PSO. This paper proposes a new nonlinear strategy for selecting inertia weight which is named Flexible Exponential Inertia Weight (FEIW) strategy because according to each problem we can construct an increasing or decreasing inertia weight strategy with suitable parameters selection. The efficacy and efficiency of PSO algorithm with FEIW strategy (FEPSO) is validated on a suite of benchmark problems with different dimensions. Also FEIW is compared with best time-varying, adaptive, constant and random inertia weights. Experimental results and statistical analysis prove that FEIW improves the search performance in terms of solution quality as well as convergence rate. PMID:27560945

Direct numerical simulations of agglomeration of circular colloidal particles in two-dimensional shear flow

International Nuclear Information System (INIS)

Choi, Young Joon; Djilali, Ned

2016-01-01

Colloidal agglomeration of nanoparticles in shear flow is investigated by solving the fluid-particle and particle-particle interactions in a 2D system. We use an extended finite element method in which the dynamics of the particles is solved in a fully coupled manner with the flow, allowing an accurate description of the fluid-particle interfaces without the need of boundary-fitted meshes or of empirical correlations to account for the hydrodynamic interactions between the particles. Adaptive local mesh refinement using a grid deformation method is incorporated with the fluid-structure interaction algorithm, and the particle-particle interaction at the microscopic level is modeled using the Lennard-Jones potential. Motivated by the process used in fabricating fuel cell catalysts from a colloidal ink, the model is applied to investigate agglomeration of colloidal particles under external shear flow in a sliding bi-periodic Lees-Edwards frame with varying shear rates and particle fraction ratios. Both external shear and particle fraction are found to have a crucial impact on the structure formation of colloidal particles in a suspension. Segregation intensity and graph theory are used to analyze the underlying agglomeration patterns and structures, and three agglomeration regimes are identified

Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model

International Nuclear Information System (INIS)

Hong, W.-C.

2009-01-01

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. Recently, support vector regression (SVR), with nonlinear mapping capabilities of forecasting, has been successfully employed to solve nonlinear regression and time series problems. However, it is still lack of systematic approaches to determine appropriate parameter combination for a SVR model. This investigation elucidates the feasibility of applying chaotic particle swarm optimization (CPSO) algorithm to choose the suitable parameter combination for a SVR model. The empirical results reveal that the proposed model outperforms the other two models applying other algorithms, genetic algorithm (GA) and simulated annealing algorithm (SA). Finally, it also provides the theoretical exploration of the electric load forecasting support system (ELFSS)

Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm

International Nuclear Information System (INIS)

Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei

2014-01-01

Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches

A novel robust and efficient algorithm for charge particle tracking in high background flux

International Nuclear Information System (INIS)

Fanelli, C; Cisbani, E; Dotto, A Del

2015-01-01

The high luminosity that will be reached in the new generation of High Energy Particle and Nuclear physics experiments implies large high background rate and large tracker occupancy, representing therefore a new challenge for particle tracking algorithms. For instance, at Jefferson Laboratory (JLab) (VA,USA), one of the most demanding experiment in this respect, performed with a 12 GeV electron beam, is characterized by a luminosity up to 10 39 cm -2 s -1 . To this scope, Gaseous Electron Multiplier (GEM) based trackers are under development for a new spectrometer that will operate at these high rates in the Hall A of JLab. Within this context, we developed a new tracking algorithm, based on a multistep approach: (i) all hardware - time and charge - information are exploited to minimize the number of hits to associate; (ii) a dedicated Neural Network (NN) has been designed for a fast and efficient association of the hits measured by the GEM detector; (iii) the measurements of the associated hits are further improved in resolution through the application of Kalman filter and Rauch- Tung-Striebel smoother. The algorithm is shortly presented along with a discussion of the promising first results. (paper)

The hydrodynamic behaviour of gas—solid trickle flow over a regularly stacked packing

NARCIS (Netherlands)

Verver, A.B.; van Swaaij, Willibrordus Petrus Maria

1986-01-01

The hydrodynamic properties of counter-current gas—solid flow over a regularly stacked packing at trickle flow conditions have been studied. The flow properties of the solids phase were examined, using five types of solid particles with a mean particle diameter ranging from 70 to 880 μm and a

Conceptual Site Model for Newark Bay—Hydrodynamics and Sediment Transport

Directory of Open Access Journals (Sweden)

Parmeshwar L. Shrestha

2014-02-01

Full Text Available A conceptual site model (CSM has been developed for the Newark Bay Study Area (NBSA as part of the Remedial Investigation/Feasibility Study (RI/FS for this New Jersey site. The CSM is an evolving document that describes the influence of physical, chemical and biological processes on contaminant fate and transport. The CSM is initiated at the start of a project, updated during site activities, and used to inform sampling and remediation planning. This paper describes the hydrodynamic and sediment transport components of the CSM for the NBSA. Hydrodynamic processes are influenced by freshwater inflows, astronomical forcing through two tidal straits, meteorological conditions, and anthropogenic activities such as navigational dredging. Sediment dynamics are driven by hydrodynamics, waves, sediment loading from freshwater sources and the tidal straits, sediment size gradation, sediment bed properties, and particle-to-particle interactions. Cohesive sediment transport is governed by advection, dispersion, aggregation, settling, consolidation, and erosion. Noncohesive sediment transport is governed by advection, dispersion, settling, armoring, and transport in suspension and along the bed. The CSM will inform the development and application of a numerical model that accounts for all key variables to adequately describe the NBSA’s historical, current, and future physical conditions.

Modelling multi-phase liquid-sediment scour and resuspension induced by rapid flows using Smoothed Particle Hydrodynamics (SPH) accelerated with a Graphics Processing Unit (GPU)

Science.gov (United States)

Fourtakas, G.; Rogers, B. D.

2016-06-01

A two-phase numerical model using Smoothed Particle Hydrodynamics (SPH) is applied to two-phase liquid-sediments flows. The absence of a mesh in SPH is ideal for interfacial and highly non-linear flows with changing fragmentation of the interface, mixing and resuspension. The rheology of sediment induced under rapid flows undergoes several states which are only partially described by previous research in SPH. This paper attempts to bridge the gap between the geotechnics, non-Newtonian and Newtonian flows by proposing a model that combines the yielding, shear and suspension layer which are needed to predict accurately the global erosion phenomena, from a hydrodynamics prospective. The numerical SPH scheme is based on the explicit treatment of both phases using Newtonian and the non-Newtonian Bingham-type Herschel-Bulkley-Papanastasiou constitutive model. This is supplemented by the Drucker-Prager yield criterion to predict the onset of yielding of the sediment surface and a concentration suspension model. The multi-phase model has been compared with experimental and 2-D reference numerical models for scour following a dry-bed dam break yielding satisfactory results and improvements over well-known SPH multi-phase models. With 3-D simulations requiring a large number of particles, the code is accelerated with a graphics processing unit (GPU) in the open-source DualSPHysics code. The implementation and optimisation of the code achieved a speed up of x58 over an optimised single thread serial code. A 3-D dam break over a non-cohesive erodible bed simulation with over 4 million particles yields close agreement with experimental scour and water surface profiles.

Optimal Sensor Placement for Latticed Shell Structure Based on an Improved Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Xun Zhang

2014-01-01

Full Text Available Optimal sensor placement is a key issue in the structural health monitoring of large-scale structures. However, some aspects in existing approaches require improvement, such as the empirical and unreliable selection of mode and sensor numbers and time-consuming computation. A novel improved particle swarm optimization (IPSO algorithm is proposed to address these problems. The approach firstly employs the cumulative effective modal mass participation ratio to select mode number. Three strategies are then adopted to improve the PSO algorithm. Finally, the IPSO algorithm is utilized to determine the optimal sensors number and configurations. A case study of a latticed shell model is implemented to verify the feasibility of the proposed algorithm and four different PSO algorithms. The effective independence method is also taken as a contrast experiment. The comparison results show that the optimal placement schemes obtained by the PSO algorithms are valid, and the proposed IPSO algorithm has better enhancement in convergence speed and precision.

Stochastic Hydrodynamic Synchronization in Rotating Energy Landscapes

OpenAIRE

Koumakis, N.; Di Leonardo, R.

2013-01-01

Hydrodynamic synchronization provides a general mechanism for the spontaneous emergence of coherent beating states in independently driven mesoscopic oscillators. A complete physical picture of those phenomena is of definite importance to the understanding of biological cooperative motions of cilia and flagella. Moreover, it can potentially suggest novel routes to exploit synchronization in technological applications of soft matter. We demonstrate that driving colloidal particles in rotating ...

Comparison between Genetic Algorithms and Particle Swarm Optimization Methods on Standard Test Functions and Machine Design

DEFF Research Database (Denmark)

Nica, Florin Valentin Traian; Ritchie, Ewen; Leban, Krisztina Monika

2013-01-01

, genetic algorithm and particle swarm are shortly presented in this paper. These two algorithms are tested to determine their performance on five different benchmark test functions. The algorithms are tested based on three requirements: precision of the result, number of iterations and calculation time....... Both algorithms are also tested on an analytical design process of a Transverse Flux Permanent Magnet Generator to observe their performances in an electrical machine design application.......Nowadays the requirements imposed by the industry and economy ask for better quality and performance while the price must be maintained in the same range. To achieve this goal optimization must be introduced in the design process. Two of the best known optimization algorithms for machine design...

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Directory of Open Access Journals (Sweden)

Yudong Zhang

2015-01-01

Full Text Available Particle swarm optimization (PSO is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO, population topology (as fully connected, von Neumann, ring, star, random, etc., hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization, extensions (to multiobjective, constrained, discrete, and binary optimization, theoretical analysis (parameter selection and tuning, and convergence analysis, and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms. On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

Activity-induced clustering in model dumbbell swimmers: the role of hydrodynamic interactions.

Science.gov (United States)

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

Hydrodynamic modelling for relativistic heavy-ion collisions at RHIC ...

Indian Academy of Sciences (India)

model, to describe the microscopic evolution and decoupling of the hadronic ... progress on hydrodynamic modelling, investigation on the flow data and the ... and to describe and predict the soft particle physics in relativistic heavy-ion collisions [4]. It is based on the conservation laws of energy, momentum and net charge ...

Simplified particle swarm optimization algorithm - doi: 10.4025/actascitechnol.v34i1.9679

Directory of Open Access Journals (Sweden)

Ricardo Paupitz Barbosa dos Santos

2011-11-01

Full Text Available Real ants and bees are considered social insects, which present some remarkable characteristics that can be used, as inspiration, to solve complex optimization problems. This field of study is known as swarm intelligence. Therefore, this paper presents a new algorithm that can be understood as a simplified version of the well known Particle Swarm Optimization (PSO. The proposed algorithm allows saving some computational effort and obtains a considerable performance in the optimization of nonlinear functions. We employed four nonlinear benchmark functions, Sphere, Schwefel, Schaffer and Ackley functions, to test and validate the new proposal. Some simulated results were used in order to clarify the efficiency of the proposed algorithm.

An analysis of 3D particle path integration algorithms

International Nuclear Information System (INIS)

Darmofal, D.L.; Haimes, R.

1996-01-01

Several techniques for the numerical integration of particle paths in steady and unsteady vector (velocity) fields are analyzed. Most of the analysis applies to unsteady vector fields, however, some results apply to steady vector field integration. Multistep, multistage, and some hybrid schemes are considered. It is shown that due to initialization errors, many unsteady particle path integration schemes are limited to third-order accuracy in time. Multistage schemes require at least three times more internal data storage than multistep schemes of equal order. However, for timesteps within the stability bounds, multistage schemes are generally more accurate. A linearized analysis shows that the stability of these integration algorithms are determined by the eigenvalues of the local velocity tensor. Thus, the accuracy and stability of the methods are interpreted with concepts typically used in critical point theory. This paper shows how integration schemes can lead to erroneous classification of critical points when the timestep is finite and fixed. For steady velocity fields, we demonstrate that timesteps outside of the relative stability region can lead to similar integration errors. From this analysis, guidelines for accurate timestep sizing are suggested for both steady and unsteady flows. In particular, using simulation data for the unsteady flow around a tapered cylinder, we show that accurate particle path integration requires timesteps which are at most on the order of the physical timescale of the flow

A consistent description of kinetics and hydrodynamics of quantum Bose-systems

Directory of Open Access Journals (Sweden)

P.A.Hlushak

2004-01-01

Full Text Available A consistent approach to the description of kinetics and hydrodynamics of many-Boson systems is proposed. The generalized transport equations for strongly and weakly nonequilibrium Bose systems are obtained. Here we use the method of nonequilibrium statistical operator by D.N. Zubarev. New equations for the time distribution function of the quantum Bose system with a separate contribution from both the kinetic and potential energies of particle interactions are obtained. The generalized transport coefficients are determined accounting for the consistent description of kinetic and hydrodynamic processes.

Petascale algorithms for reactor hydrodynamics

International Nuclear Information System (INIS)

Fischer, P.; Lottes, J.; Pointer, W.D.; Siegel, A.

2008-01-01

We describe recent algorithmic developments that have enabled large eddy simulations of reactor flows on up to P = 65, 000 processors on the IBM BG/P at the Argonne Leadership Computing Facility. Petascale computing is expected to play a pivotal role in the design and analysis of next-generation nuclear reactors. Argonne's SHARP project is focused on advanced reactor simulation, with a current emphasis on modeling coupled neutronics and thermal-hydraulics (TH). The TH modeling comprises a hierarchy of computational fluid dynamics approaches ranging from detailed turbulence computations, using DNS (direct numerical simulation) and LES (large eddy simulation), to full core analysis based on RANS (Reynolds-averaged Navier-Stokes) and subchannel models. Our initial study is focused on LES of sodium-cooled fast reactor cores. The aim is to leverage petascale platforms at DOE's Leadership Computing Facilities (LCFs) to provide detailed information about heat transfer within the core and to provide baseline data for less expensive RANS and subchannel models.

An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Kai Hu

2015-01-01

Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.

Performance analysis of multidimensional wavefront algorithms with application to deterministic particle transport

International Nuclear Information System (INIS)

Hoisie, A.; Lubeck, O.; Wasserman, H.

1998-01-01

The authors develop a model for the parallel performance of algorithms that consist of concurrent, two-dimensional wavefronts implemented in a message passing environment. The model, based on a LogGP machine parameterization, combines the separate contributions of computation and communication wavefronts. They validate the model on three important supercomputer systems, on up to 500 processors. They use data from a deterministic particle transport application taken from the ASCI workload, although the model is general to any wavefront algorithm implemented on a 2-D processor domain. They also use the validated model to make estimates of performance and scalability of wavefront algorithms on 100-TFLOPS computer systems expected to be in existence within the next decade as part of the ASCI program and elsewhere. In this context, the authors analyze two problem sizes. Their model shows that on the largest such problem (1 billion cells), inter-processor communication performance is not the bottleneck. Single-node efficiency is the dominant factor

A combination of genetic algorithm and particle swarm optimization method for solving traveling salesman problem

Directory of Open Access Journals (Sweden)

Keivan Borna

2015-12-01

Full Text Available Traveling salesman problem (TSP is a well-established NP-complete problem and many evolutionary techniques like particle swarm optimization (PSO are used to optimize existing solutions for that. PSO is a method inspired by the social behavior of birds. In PSO, each member will change its position in the search space, according to personal or social experience of the whole society. In this paper, we combine the principles of PSO and crossover operator of genetic algorithm to propose a heuristic algorithm for solving the TSP more efficiently. Finally, some experimental results on our algorithm are applied in some instances in TSPLIB to demonstrate the effectiveness of our methods which also show that our algorithm can achieve better results than other approaches.

Boundary layer noise subtraction in hydrodynamic tunnel using robust principal component analysis.

Science.gov (United States)

Amailland, Sylvain; Thomas, Jean-Hugh; Pézerat, Charles; Boucheron, Romuald

2018-04-01

The acoustic study of propellers in a hydrodynamic tunnel is of paramount importance during the design process, but can involve significant difficulties due to the boundary layer noise (BLN). Indeed, advanced denoising methods are needed to recover the acoustic signal in case of poor signal-to-noise ratio. The technique proposed in this paper is based on the decomposition of the wall-pressure cross-spectral matrix (CSM) by taking advantage of both the low-rank property of the acoustic CSM and the sparse property of the BLN CSM. Thus, the algorithm belongs to the class of robust principal component analysis (RPCA), which derives from the widely used principal component analysis. If the BLN is spatially decorrelated, the proposed RPCA algorithm can blindly recover the acoustical signals even for negative signal-to-noise ratio. Unfortunately, in a realistic case, acoustic signals recorded in a hydrodynamic tunnel show that the noise may be partially correlated. A prewhitening strategy is then considered in order to take into account the spatially coherent background noise. Numerical simulations and experimental results show an improvement in terms of BLN reduction in the large hydrodynamic tunnel. The effectiveness of the denoising method is also investigated in the context of acoustic source localization.

Inversion of particle size distribution by spectral extinction technique using the attractive and repulsive particle swarm optimization algorithm

Directory of Open Access Journals (Sweden)

Qi Hong

2015-01-01

Full Text Available The particle size distribution (PSD plays an important role in environmental pollution detection and human health protection, such as fog, haze and soot. In this study, the Attractive and Repulsive Particle Swarm Optimization (ARPSO algorithm and the basic PSO were applied to retrieve the PSD. The spectral extinction technique coupled with the Anomalous Diffraction Approximation (ADA and the Lambert-Beer Law were employed to investigate the retrieval of the PSD. Three commonly used monomodal PSDs, i.e. the Rosin-Rammer (R-R distribution, the normal (N-N distribution, the logarithmic normal (L-N distribution were studied in the dependent model. Then, an optimal wavelengths selection algorithm was proposed. To study the accuracy and robustness of the inverse results, some characteristic parameters were employed. The research revealed that the ARPSO showed more accurate and faster convergence rate than the basic PSO, even with random measurement error. Moreover, the investigation also demonstrated that the inverse results of four incident laser wavelengths showed more accurate and robust than those of two wavelengths. The research also found that if increasing the interval of the selected incident laser wavelengths, inverse results would show more accurate, even in the presence of random error.

Colloid-colloid hydrodynamic interaction around a bend in a quasi-one-dimensional channel.

Science.gov (United States)

Liepold, Christopher; Zarcone, Ryan; Heumann, Tibor; Rice, Stuart A; Lin, Binhua

2017-07-01

We report a study of how a bend in a quasi-one-dimensional (q1D) channel containing a colloid suspension at equilibrium that exhibits single-file particle motion affects the hydrodynamic coupling between colloid particles. We observe both structural and dynamical responses as the bend angle becomes more acute. The structural response is an increasing depletion of particles in the vicinity of the bend and an increase in the nearest-neighbor separation in the pair correlation function for particles on opposite sides of the bend. The dynamical response monitored by the change in the self-diffusion [D_{11}(x)] and coupling [D_{12}(x)] terms of the pair diffusion tensor reveals that the pair separation dependence of D_{12} mimics that of the pair correlation function just as in a straight q1D channel. We show that the observed behavior is a consequence of the boundary conditions imposed on the q1D channel: both the single-file motion and the hydrodynamic flow must follow the channel around the bend.

Hydrodynamically Coupled Brownian Dynamics simulations for flow on non-Newtonian fluids

NARCIS (Netherlands)

Ahuja, Vishal Raju

2018-01-01

This thesis deals with model development for particle-based flow simulations of non-Newtonian fluids such as polymer solutions. A novel computational technique called Hydrodynamically Coupled Brownian Dynamics (HCBD) is presented in this thesis. This technique essentially couples the Brownian motion

Correlated particle dynamics in concentrated quasi-two-dimensional suspensions

International Nuclear Information System (INIS)

Diamant, H; Cui, B; Lin, B; Rice, S A

2005-01-01

We investigate theoretically and experimentally how the hydrodynamically correlated lateral motion of particles in a suspension confined between two surfaces is affected by the suspension concentration. Despite the long range of the correlations (decaying as 1/r 2 with the inter-particle distance r), the concentration effect is present only at short inter-particle distances for which the static pair correlation is nonuniform. This is in sharp contrast with the effect of hydrodynamic screening in unconfined suspensions, where increasing the concentration changes the prefactor of the large-distance correlation

Hydrodynamic models for slurry bubble column reactors

Energy Technology Data Exchange (ETDEWEB)

Gidaspow, D. [IIT Center, Chicago, IL (United States)

1995-12-31

The objective of this investigation is to convert a {open_quotes}learning gas-solid-liquid{close_quotes} fluidization model into a predictive design model. This model is capable of predicting local gas, liquid and solids hold-ups and the basic flow regimes: the uniform bubbling, the industrially practical churn-turbulent (bubble coalescence) and the slugging regimes. Current reactor models incorrectly assume that the gas and the particle hold-ups (volume fractions) are uniform in the reactor. They must be given in terms of empirical correlations determined under conditions that radically differ from reactor operation. In the proposed hydrodynamic approach these hold-ups are computed from separate phase momentum balances. Furthermore, the kinetic theory approach computes the high slurry viscosities from collisions of the catalyst particles. Thus particle rheology is not an input into the model.

From cell extracts to fish schools to granular layers: the universal hydrodynamics of self-driven systems

Science.gov (United States)

Ramaswamy, Sriram

2007-03-01

Collections of self-driven or ``active'' particles are now recognised as a distinct kind of nonequilibrium matter, and an understanding of their phases, hydrodynamics, mechanical response, and correlations is a vital and rapidly developing part of the statistical physics of soft-matter systems far from equilibrium. My talk will review our recent results, from theory, simulation and experiment, on order, fluctuations, and flow instabilities in collections of active particles, in suspension or on a solid surface. Our work, which began by adapting theories of flocking to include the hydrodynamics of the ambient fluid, provides the theoretical framework for understanding active matter in all its diversity: contractile filaments in cell extracts, crawling or dividing cells, collectively swimming bacteria, fish schools, and agitated monolayers of orientable granular particles.

FPGA Implementation of an Efficient Algorithm for the Calculation of Charged Particle Trajectories in Cosmic Ray Detectors

Science.gov (United States)

Villar, Xabier; Piso, Daniel; Bruguera, Javier D.

2014-02-01

This paper presents an FPGA implementation of an algorithm, previously published, for the the reconstruction of cosmic rays' trajectories and the determination of the time of arrival and velocity of the particles. The accuracy and precision issues of the algorithm have been analyzed to propose a suitable implementation. Thus, a 32-bit fixed-point format has been used for the representation of the data values. Moreover, the dependencies among the different operations have been taken into account to obtain a highly parallel and efficient hardware implementation. The final hardware architecture requires 18 cycles to process every particle, and has been exhaustively simulated to validate all the design decisions. The architecture has been mapped over different commercial FPGAs, with a frequency of operation ranging from 300 MHz to 1.3 GHz, depending on the FPGA being used. Consequently, the number of particle trajectories processed per second is between 16 million and 72 million. The high number of particle trajectories calculated per second shows that the proposed FPGA implementation might be used also in high rate environments such as those found in particle and nuclear physics experiments.

Experimental investigation on the hydrodynamics of a gas–liquid–solid fluidized bed using vibration signature and pressure fluctuation analyses

International Nuclear Information System (INIS)

Sheikhi, Amir; Sotudeh-Gharebagh, Rahmat; Mostoufi, Navid; Zarghami, Reza

2013-01-01

Highlights: • Bed shell vibration fluctuation is introduced as a novel non-invasive monitoring method in three-phase fluidized beds. • Analyses of vibration signatures and pressure fluctuations were performed to characterize gas–liquid–solid fluidized beds. • These enabled further investigation on the dual effect of solid particles on the local and global bed hydrodynamics. -- Abstract: Simultaneous analyses of vibration signatures and pressure fluctuations were performed to investigate the hydrodynamics of a conventional three-phase gas–liquid–solid fluidized bed over a wide range of operating conditions. Non-intrusive vibration signature and pressure fluctuation signals were acquired by means of accelerometers and a piezoresistive pressure transducer, respectively. Comprehensive study on the standard deviation of pressure fluctuations was conducted simultaneously with two new statistical analyses on the pressure fluctuations, namely signal energy and average cycle frequency, which presented a new method of determining minimum liquid-fluidization velocity. This enabled further investigation on the dual effect of solid particles on the local hydrodynamics in the three-phase beds. The vibration analysis of the bed was introduced as a novel and non-invasive tool, which proved to be a robust representative of the global governing regimes suggesting a new approach on the dual effect of solid particles on the bed global hydrodynamics. These methods can pave the way towards the non-invasive hydrodynamic characterization of industrial three-phase reactors

High-Order Curvilinear Finite Element Methods for Lagrangian Hydrodynamics [High Order Curvilinear Finite Elements for Lagrangian Hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Dobrev, Veselin A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kolev, Tzanio V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rieben, Robert N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2012-09-20

The numerical approximation of the Euler equations of gas dynamics in a movingLagrangian frame is at the heart of many multiphysics simulation algorithms. Here, we present a general framework for high-order Lagrangian discretization of these compressible shock hydrodynamics equations using curvilinear finite elements. This method is an extension of the approach outlined in [Dobrev et al., Internat. J. Numer. Methods Fluids, 65 (2010), pp. 1295--1310] and can be formulated for any finite dimensional approximation of the kinematic and thermodynamic fields, including generic finite elements on two- and three-dimensional meshes with triangular, quadrilateral, tetrahedral, or hexahedral zones. We discretize the kinematic variables of position and velocity using a continuous high-order basis function expansion of arbitrary polynomial degree which is obtained via a corresponding high-order parametric mapping from a standard reference element. This enables the use of curvilinear zone geometry, higher-order approximations for fields within a zone, and a pointwise definition of mass conservation which we refer to as strong mass conservation. Moreover, we discretize the internal energy using a piecewise discontinuous high-order basis function expansion which is also of arbitrary polynomial degree. This facilitates multimaterial hydrodynamics by treating material properties, such as equations of state and constitutive models, as piecewise discontinuous functions which vary within a zone. To satisfy the Rankine--Hugoniot jump conditions at a shock boundary and generate the appropriate entropy, we introduce a general tensor artificial viscosity which takes advantage of the high-order kinematic and thermodynamic information available in each zone. Finally, we apply a generic high-order time discretization process to the semidiscrete equations to develop the fully discrete numerical algorithm. Our method can be viewed as the high-order generalization of the so-called staggered

Local lubrication model for spherical particles within incompressible Navier-Stokes flows

Science.gov (United States)

Lambert, B.; Weynans, L.; Bergmann, M.

2018-03-01

The lubrication forces are short-range hydrodynamic interactions essential to describe suspension of the particles. Usually, they are underestimated in direct numerical simulations of particle-laden flows. In this paper, we propose a lubrication model for a coupled volume penalization method and discrete element method solver that estimates the unresolved hydrodynamic forces and torques in an incompressible Navier-Stokes flow. Corrections are made locally on the surface of the interacting particles without any assumption on the global particle shape. The numerical model has been validated against experimental data and performs as well as existing numerical models that are limited to spherical particles.

Local lubrication model for spherical particles within incompressible Navier-Stokes flows.

Science.gov (United States)

Lambert, B; Weynans, L; Bergmann, M

2018-03-01

The lubrication forces are short-range hydrodynamic interactions essential to describe suspension of the particles. Usually, they are underestimated in direct numerical simulations of particle-laden flows. In this paper, we propose a lubrication model for a coupled volume penalization method and discrete element method solver that estimates the unresolved hydrodynamic forces and torques in an incompressible Navier-Stokes flow. Corrections are made locally on the surface of the interacting particles without any assumption on the global particle shape. The numerical model has been validated against experimental data and performs as well as existing numerical models that are limited to spherical particles.

Parallel Implementation of Isothermal and Isoenergetic Dissipative Particle Dynamics using Shardlow-like Splitting Algorithms

Czech Academy of Sciences Publication Activity Database

Larentzos, J.P.; Brennan, J.K.; Moore, J.D.; Lísal, Martin; Mattson, w.D.

2014-01-01

Roč. 185, č. 7 (2014), s. 1987-1998 ISSN 0010-4655 Grant - others:ARL(US) W911NF-10-2-0039 Institutional support: RVO:67985858 Keywords : dissipative particle dynamics * shardlow splitting algorithm * numerical integration Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.112, year: 2014

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

Science.gov (United States)

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Zhiwei Ye

2015-01-01

Full Text Available Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Hydrodynamic interaction between bacteria and passive sphere

Science.gov (United States)

Zhang, Bokai; Ding, Yang; Xu, Xinliang

2017-11-01

Understanding hydrodynamic interaction between bacteria and passive sphere is important for identifying rheological properties of bacterial and colloidal suspension. Over the past few years, scientists mainly focused on bacterial influences on tracer particle diffusion or hydrodynamic capture of a bacteria around stationary boundary. Here, we use superposition of singularities and regularized method to study changes in bacterial swimming velocity and passive sphere diffusion, simultaneously. On this basis, we present a simple two-bead model that gives a unified interpretation of passive sphere diffusion and bacterial swimming. The model attributes both variation of passive sphere diffusion and changes of speed of bacteria to an effective mobility. Using the effective mobility of bacterial head and tail as an input function, the calculations are consistent with simulation results at a broad range of tracer diameters, incident angles and bacterial shapes.

Transversal expansion study in the Landau hydrodynamic

International Nuclear Information System (INIS)

Pottag, F.W.

1984-01-01

The system of equations in the frame of Landau's hydrodynamical model for multiparticle production at high energies is studied. Taking as a first approximation the one-dimensional exact due to Khalatnikov, and a special set of curvilinear coordinates, the radial part is separated from the longitudinal one in the equations of motion, and a system of partial differential equations (non-linear, hyperbolic) is obtained for the radial part. These equations are solved numerically by the method of caracteristics. The hydrodynamical variables are obtained over all the three-dimensional-flow region as well as its variation with the mass of the initially expanding system. Both, the transverse rapidity distribution of the fluid and the inclusive particle distribution at 90 0 in the center of mass system, are calculated. The last one is compared with recent experimental data. (author) [pt

Particle swarm optimization algorithm based low cost magnetometer calibration

Science.gov (United States)

Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.

2011-12-01

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments

Correlations between the transverse and longitudinal momenta of secondary particles in hydrodynamic theory

International Nuclear Information System (INIS)

Tarasov, Y.A.

1987-01-01

Hydrodynamic theory is used to calculate the dependence of the transverse momenta p-bar/sub perpendicular/ on the Feynman variable x and rapidity y for pions, kaons, and antiprotons at ISR and collider energies. Quantitative agreement with the experimental data (at ISR energies) is found. The values of p-bar/sub perpendicular/ (y) are determined by the profile of the ''hardening'' temperature as a function of the rapidity, and this profile is calculated in the hydrodynamic theory. The experimental data fit this profile well. The dependence p-bar/sub perpendicular/ (x) for π - mesons has the shape of a seagull wing. In the calculations the contribution of the Riemannian traveling wave is taken into account. For collider energies there are no experimental data, and the theoretical results play the role of predictions

Thermal–Hydrodynamic Behaviour of Coated Pivoted Pad Thrust Bearings: Comparison between Babbitt, PTFE and DLC

OpenAIRE

Konstantinos Katsaros; Dimitrios A. Bompos; Pantelis G. Nikolakopoulos; Stephanos Theodossiades

2018-01-01

The hydrodynamic lubrication and thermal analysis of tilting pad thrust bearings has been a major subject for many studies in the field of tribology. There is only a limited number of studies regarding thrust bearings with coated surfaces. The purpose of this study is to build a parametric, iterative algorithm in order to perform a complete thermal and hydrodynamic lubrication analysis for pivoted pad thrust bearings with coatings. The analytical model is mainly based on the energy, continuit...

Centrality dependence of multiplicity, transverse energy, and elliptic flow from hydrodynamics

Energy Technology Data Exchange (ETDEWEB)

Kolb, Peter F.; Heinz, Ulrich; Huovinen, Pasi; Eskola, Kari J.; Tuominen, Kimmo

2001-03-21

The centrality dependence of the charged multiplicity, transverse energy, and elliptic flow coefficient is studied in a hydrodynamic model, using a variety of different initializations which model the initial energy or entropy production process as a hard or soft process, respectively. While the charged multiplicity depends strongly on the chosen initialization, the p{sub T}-integrated elliptic flow for charged particles as a function of charged particle multiplicity and the p{sub T}-differential elliptic flow for charged particles in minimum bias events turn out to be almost independent of the initialization.

An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization.

Science.gov (United States)

Yang, Zhen-Lun; Wu, Angus; Min, Hua-Qing

2015-01-01

An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators. The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration. A comprehensive simulation study is conducted on a set of twelve benchmark functions. Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate.

On the role of cavitation in particle collection in flotation - A critical review. II

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z.A.; Xu, Z.H.; Finch, J.A.; Masliyah, J.H.; Chow, R.S. [Alberta Research Council, Edmonton, AB (Canada)

2009-04-15

Research in applying hydrodynamic cavitation to recovery of natural resources during the last decade is reviewed. The existence and formation of tiny bubbles or gas nuclei (diameter from microns down to nano sizes) in natural water were verified from both direct and in-direct measurements, providing a foundation for applying hydrodynamic cavitation to flotation systems. The interactions between tiny bubbles and fine particles in aqueous slurry were analysed. Tiny bubbles generated by hydrodynamic cavitation increased contact angle of solids and hence attachment force, bridge fine particles to form aggregates, minimize slime coating, remove oxidation layers on particle surfaces, and in hence reduce reagents consumption. Experiments revealed that the energy dissipation levels for cavity formation in a flowing liquid could be much lower than predicted, depending on the content of dissolved gases, presence of free gas nuclei and design of cavitation tubes. Application of hydrodynamic cavitation to fine and coarse particle flotation, high intensity conditioning, oil agglomeration of fine coal, and oil sands processing has confirmed the role of tiny bubbles formed by cavitation in improving recovery efficiency. Increased flotation kinetics by hydrodynamic cavitation could be attributed to a dual role: some collapsing cavity bubbles serving to break interfacial layers on particle surfaces while other cavity bubbles attaching to those freshly exposed mineral surfaces. The role of water vapor and other gases within cavity bubbles in particle-bubble attachment remains to be explored. Incorporating hydrodynamic cavitation into flotation systems to take advantage of its unique features is expected to develop the next generation of flotation machines.

On the influence of the hydrodynamic interactions on the aggregation rate of magnetic spheres in a dilute suspension

International Nuclear Information System (INIS)

Cunha, F.R.; Couto, H.L.G.

2011-01-01

Magnetostatic attraction may lead to formation of aggregates in stable colloidal magnetic suspensions and magneto-rheological suspensions. The aggregation problem of magnetic composites under differential sedimentation is a key problem in the control of the instability of non-Brownian suspensions. Against these attractive forces are the electrostatic repulsion and the hydrodynamic interactions acting as stabilizing effects to the suspension. This work concerns an investigation of the pairwise interaction of magnetic particles in a dilute sedimenting suspension. We focus attention on suspensions where the Peclet number is large (negligible Brownian motion) and where the Reynolds number (negligible inertia) is small. The suspension is composed of magnetic micro-spheres of different radius and density immersed in a Newtonian fluid moving under the action of gravity. The theoretical calculations are based on direct computations of the hydrodynamic and the magnetic interactions among the rigid spheres in the regime of low particle Reynolds number. From the limiting trajectory in which aggregation occurs, we calculate the collision efficiency, representing the dimensionless rate at which aggregates are formed. The numerical results show clear evidence that the hydrodynamic interactions are of fundamental relevance in the process of magnetic particle aggregation. We compare the stabilizing effects between electrostatic repulsion and hydrodynamic interactions.

On the influence of the hydrodynamic interactions on the aggregation rate of magnetic spheres in a dilute suspension

Energy Technology Data Exchange (ETDEWEB)

Cunha, F.R., E-mail: frcunha@unb.b [Universidade de Brasilia, Faculdade de Tecnologia, Depto. de Engenharia Mecanica, Grupo de Mecanica dos Fluidos de Escoamentos Complexos - VORTEX, Campus Universitario Darcy Ribeiro, 70910-900, Brasilia, DF (Brazil); Couto, H.L.G. [Universidade de Brasilia, Faculdade de Tecnologia, Depto. de Engenharia Mecanica, Grupo de Mecanica dos Fluidos de Escoamentos Complexos - VORTEX, Campus Universitario Darcy Ribeiro, 70910-900, Brasilia, DF (Brazil)

2011-01-15

Magnetostatic attraction may lead to formation of aggregates in stable colloidal magnetic suspensions and magneto-rheological suspensions. The aggregation problem of magnetic composites under differential sedimentation is a key problem in the control of the instability of non-Brownian suspensions. Against these attractive forces are the electrostatic repulsion and the hydrodynamic interactions acting as stabilizing effects to the suspension. This work concerns an investigation of the pairwise interaction of magnetic particles in a dilute sedimenting suspension. We focus attention on suspensions where the Peclet number is large (negligible Brownian motion) and where the Reynolds number (negligible inertia) is small. The suspension is composed of magnetic micro-spheres of different radius and density immersed in a Newtonian fluid moving under the action of gravity. The theoretical calculations are based on direct computations of the hydrodynamic and the magnetic interactions among the rigid spheres in the regime of low particle Reynolds number. From the limiting trajectory in which aggregation occurs, we calculate the collision efficiency, representing the dimensionless rate at which aggregates are formed. The numerical results show clear evidence that the hydrodynamic interactions are of fundamental relevance in the process of magnetic particle aggregation. We compare the stabilizing effects between electrostatic repulsion and hydrodynamic interactions.

Computational Flow Modeling of Hydrodynamics in Multiphase Trickle-Bed Reactors

Science.gov (United States)

Lopes, Rodrigo J. G.; Quinta-Ferreira, Rosa M.

2008-05-01

This study aims to incorporate most recent multiphase models in order to investigate the hydrodynamic behavior of a TBR in terms of pressure drop and liquid holdup. Taking into account transport phenomena such as mass and heat transfer, an Eulerian k-fluid model was developed resulting from the volume averaging of the continuity and momentum equations and solved for a 3D representation of the catalytic bed. Computational fluid dynamics (CFD) model predicts hydrodynamic parameters quite well if good closures for fluid/fluid and fluid/particle interactions are incorporated in the multiphase model. Moreover, catalytic performance is investigated with the catalytic wet oxidation of a phenolic pollutant.

Fast readout algorithm for cylindrical beam position monitors providing good accuracy for particle bunches with large offsets

Science.gov (United States)

Thieberger, P.; Gassner, D.; Hulsart, R.; Michnoff, R.; Miller, T.; Minty, M.; Sorrell, Z.; Bartnik, A.

2018-04-01

A simple, analytically correct algorithm is developed for calculating "pencil" relativistic beam coordinates using the signals from an ideal cylindrical particle beam position monitor (BPM) with four pickup electrodes (PUEs) of infinitesimal widths. The algorithm is then applied to simulations of realistic BPMs with finite width PUEs. Surprisingly small deviations are found. Simple empirically determined correction terms reduce the deviations even further. The algorithm is then tested with simulations for non-relativistic beams. As an example of the data acquisition speed advantage, a Field Programmable Gate Array-based BPM readout implementation of the new algorithm has been developed and characterized. Finally, the algorithm is tested with BPM data from the Cornell Preinjector.

Transverse-momentum distribution of particles according to the hydrodynamical model

International Nuclear Information System (INIS)

Yogiro, H.

1977-12-01

A fit to the transverse-momentum distribution is performed, in the context of the hydrodynamical model. By fixing a (total-energy-independent) dissociation temperature T and a transverse fluid-rapidity distribution whose width increases logarithmically with s, the existing data can be reproduced in all the P1 interval (where ω dsigma divided by d vector P varies by a factor of 10 -10 ) including their energy dependence. The final inclusive cross section appears to be approximately factorized in the longitudinal and the transverse rapidities, as verified experimentally

A low-dispersion, exactly energy-charge-conserving semi-implicit relativistic particle-in-cell algorithm

Science.gov (United States)

Chen, Guangye; Luis, Chacon; Bird, Robert; Stark, David; Yin, Lin; Albright, Brian

2017-10-01

Leap-frog based explicit algorithms, either ``energy-conserving'' or ``momentum-conserving'', do not conserve energy discretely. Time-centered fully implicit algorithms can conserve discrete energy exactly, but introduce large dispersion errors in the light-wave modes, regardless of timestep sizes. This can lead to intolerable simulation errors where highly accurate light propagation is needed (e.g. laser-plasma interactions, LPI). In this study, we selectively combine the leap-frog and Crank-Nicolson methods to produce a low-dispersion, exactly energy-and-charge-conserving PIC algorithm. Specifically, we employ the leap-frog method for Maxwell equations, and the Crank-Nicolson method for particle equations. Such an algorithm admits exact global energy conservation, exact local charge conservation, and preserves the dispersion properties of the leap-frog method for the light wave. The algorithm has been implemented in a code named iVPIC, based on the VPIC code developed at LANL. We will present numerical results that demonstrate the properties of the scheme with sample test problems (e.g. Weibel instability run for 107 timesteps, and LPI applications.

PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

Science.gov (United States)

Chen, Shuangqing; Wei, Lixin; Guan, Bing

2018-01-01

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems. PMID:29675036

Computational study of scattering of a zero-order Bessel beam by large nonspherical homogeneous particles with the multilevel fast multipole algorithm

Science.gov (United States)

Yang, Minglin; Wu, Yueqian; Sheng, Xinqing; Ren, Kuan Fang

2017-12-01

Computation of scattering of shaped beams by large nonspherical particles is a challenge in both optics and electromagnetics domains since it concerns many research fields. In this paper, we report our new progress in the numerical computation of the scattering diagrams. Our algorithm permits to calculate the scattering of a particle of size as large as 110 wavelengths or 700 in size parameter. The particle can be transparent or absorbing of arbitrary shape, smooth or with a sharp surface, such as the Chebyshev particles or ice crystals. To illustrate the capacity of the algorithm, a zero order Bessel beam is taken as the incident beam, and the scattering of ellipsoidal particles and Chebyshev particles are taken as examples. Some special phenomena have been revealed and examined. The scattering problem is formulated with the combined tangential formulation and solved iteratively with the aid of the multilevel fast multipole algorithm, which is well parallelized with the message passing interface on the distributed memory computer platform using the hybrid partitioning strategy. The numerical predictions are compared with the results of the rigorous method for a spherical particle to validate the accuracy of the approach. The scattering diagrams of large ellipsoidal particles with various parameters are examined. The effect of aspect ratios, as well as half-cone angle of the incident zero-order Bessel beam and the off-axis distance on scattered intensity, is studied. Scattering by asymmetry Chebyshev particle with size parameter larger than 700 is also given to show the capability of the method for computing scattering by arbitrary shaped particles.

LC HCAL Absorber And Active Media Comparisons Using a Particle-Flow Algorithm

International Nuclear Information System (INIS)

Magill, Steve; Kuhlmann, S.

2006-01-01

We compared Stainless Steel (SS) to Tungsten (W) as absorber for the HCAL in simulation using single particles (pions) and a Particle-Flow Algorithm applied to e + e - -> Z -> qqbar events. We then used the PFA to evaluate the performance characteristics of a LC HCAL using W absorber and comparing scintillator and RPC as active media. The W/Scintillator HCAL performs better than the SS/Scintillator version due to finer λ I sampling and narrower showers in the dense absorber. The W/Scintillator HCAL performs better than the W/RPC HCAL except in the number of unused hits in the PFA. Since this represents the confusion term in the PFA response, additional tuning and optimization of a W/RPC HCAL might significantly improve this HCAL configuration

Development and Verification of Smoothed Particle Hydrodynamics Code for Analysis of Tsunami near NPP

Energy Technology Data Exchange (ETDEWEB)

Jo, Young Beom; Kim, Eung Soo [Seoul National Univ., Seoul (Korea, Republic of)

2014-10-15

It becomes more complicated when considering the shape and phase of the ground below the seawater. Therefore, some different attempts are required to precisely analyze the behavior of tsunami. This paper introduces an on-going activities on code development in SNU based on an unconventional mesh-free fluid analysis method called Smoothed Particle Hydrodynamics (SPH) and its verification work with some practice simulations. This paper summarizes the on-going development and verification activities on Lagrangian mesh-free SPH code in SNU. The newly developed code can cover equation of motions and heat conduction equation so far, and verification of each models is completed. In addition, parallel computation using GPU is now possible, and GUI is also prepared. If users change input geometry or input values, they can simulate for various conditions geometries. A SPH method has large advantages and potential in modeling of free surface, highly deformable geometry and multi-phase problems that traditional grid-based code has difficulties in analysis. Therefore, by incorporating more complex physical models such as turbulent flow, phase change, two-phase flow, and even solid mechanics, application of the current SPH code is expected to be much more extended including molten fuel behaviors in the sever accident.

Tuning Bacterial Hydrodynamics with Magnetic Fields: A Path to Bacterial Robotics

Science.gov (United States)

Pierce, Christopher; Mumper, Eric; Brangham, Jack; Wijesinghe, Hiran; Lower, Stephen; Lower, Brian; Yang, Fengyuan; Sooryakumar, Ratnasingham

Magnetotactic Bacteria (MTB) are a group of motile prokaryotes that synthesize chains of lipid-bound, magnetic nano-particles. In this study, the innate magnetism of these flagellated swimmers is exploited to explore their hydrodynamics near confining surfaces, using the magnetic field as a tuning parameter. With weak (Gauss), uniform, external, magnetic ?elds and the field gradients arising from micro-magnetic surface patterns, the relative strength of hydrodynamic, magnetic and ?agellar force components is tuned through magnetic control of the bacteria's orientation and position. In addition to direct measurement of several hydrodynamic quantities related to the motility of individual cells, their tunable dynamics reveal a number of novel, highly controllable swimming behaviors with potential value in micro-robotics applications. Specifically, the experiments permit the MTB cells to be directed along parallel or divergent trajectories, suppress their flagellar forces through magnetic means, and induce transitions between planar, circulating trajectories and drifting, vertically oriented ``top-like'' motion. The implications of the work for fundamental hydrodynamics research as well as bacterially driven robotics applications will be discussed.

A Penalty Method to Model Particle Interactions in DNA-laden Flows

International Nuclear Information System (INIS)

Trebotich, D; Miller, G H; Bybee, M D

2006-01-01

We present a hybrid fluid-particle algorithm to simulate flow and transport of DNA-laden fluids in microdevices. Relevant length scales in microfluidic systems range from characteristic channel sizes of millimeters to micron scale geometric variation (e.g., post arrays) to 10 nanometers for the length of a single rod in a bead-rod polymer representation of a biological material such as DNA. The method is based on a previous fluid-particle algorithm in which long molecules are represented as a chain of connected rods, but in which the physically unrealistic behavior of rod crossing occurred. We have extended this algorithm to include screened Coulombic forces between particles by implementing a Debye-Hueckel potential acting between rods. In the method an unsteady incompressible Newtonian fluid is discretized with a second-order finite difference method in the interior of the Cartesian grid domain; an embedded boundary volume-of-fluid formulation is used near boundaries. The bead-rod polymer model is fully coupled to the solvent through body forces representing hydrodynamic drag and stochastic thermal fluctuations. While intrapolymer interactions are modeled by a soft potential, polymer-structure interactions are treated as perfectly elastic collisions. We demonstrate this method on flow and transport of a polymer through a post array microchannel in 2D where the polymer incorporates more realistic physical parameters of DNA, and compare to previous simulations where rods are allowed to cross. We also show that the method is capable of simulating 3D flow in a packed bed micro-column

A Penalty Method to Model Particle Interactions in DNA-laden Flows

Energy Technology Data Exchange (ETDEWEB)

Trebotich, D; Miller, G H; Bybee, M D

2006-10-06

We present a hybrid fluid-particle algorithm to simulate flow and transport of DNA-laden fluids in microdevices. Relevant length scales in microfluidic systems range from characteristic channel sizes of millimeters to micron scale geometric variation (e.g., post arrays) to 10 nanometers for the length of a single rod in a bead-rod polymer representation of a biological material such as DNA. The method is based on a previous fluid-particle algorithm in which long molecules are represented as a chain of connected rods, but in which the physically unrealistic behavior of rod crossing occurred. We have extended this algorithm to include screened Coulombic forces between particles by implementing a Debye-Hueckel potential acting between rods. In the method an unsteady incompressible Newtonian fluid is discretized with a second-order finite difference method in the interior of the Cartesian grid domain; an embedded boundary volume-of-fluid formulation is used near boundaries. The bead-rod polymer model is fully coupled to the solvent through body forces representing hydrodynamic drag and stochastic thermal fluctuations. While intrapolymer interactions are modeled by a soft potential, polymer-structure interactions are treated as perfectly elastic collisions. We demonstrate this method on flow and transport of a polymer through a post array microchannel in 2D where the polymer incorporates more realistic physical parameters of DNA, and compare to previous simulations where rods are allowed to cross. We also show that the method is capable of simulating 3D flow in a packed bed micro-column.

A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements

Science.gov (United States)

Vlasenko, Andrey; Steele, Edward C. C.; Nimmo-Smith, W. Alex M.

2015-06-01

The gaps and noise present in particle image velocimetry (PIV) and particle tracking velocimetry (PTV) measurements affect the accuracy of the data collected. Existing algorithms developed for the restoration of such data are only applicable to experimental measurements collected under well-prepared laboratory conditions (i.e. where the pattern of the velocity flow field is known), and the distribution, size and type of gaps and noise may be controlled by the laboratory set-up. However, in many cases, such as PIV and PTV measurements of arbitrarily turbid coastal waters, the arrangement of such conditions is not possible. When the size of gaps or the level of noise in these experimental measurements become too large, their successful restoration with existing algorithms becomes questionable. Here, we outline a new physics-enabled flow restoration algorithm (PEFRA), specially designed for the restoration of such velocity data. Implemented as a ‘black box’ algorithm, where no user-background in fluid dynamics is necessary, the physical structure of the flow in gappy or noisy data is able to be restored in accordance with its hydrodynamical basis. The use of this is not dependent on types of flow, types of gaps or noise in measurements. The algorithm will operate on any data time-series containing a sequence of velocity flow fields recorded by PIV or PTV. Tests with numerical flow fields established that this method is able to successfully restore corrupted PIV and PTV measurements with different levels of sparsity and noise. This assessment of the algorithm performance is extended with an example application to in situ submersible 3D-PTV measurements collected in the bottom boundary layer of the coastal ocean, where the naturally-occurring plankton and suspended sediments used as tracers causes an increase in the noise level that, without such denoising, will contaminate the measurements.

A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements

International Nuclear Information System (INIS)

Vlasenko, Andrey; Steele, Edward C C; Nimmo-Smith, W Alex M

2015-01-01

The gaps and noise present in particle image velocimetry (PIV) and particle tracking velocimetry (PTV) measurements affect the accuracy of the data collected. Existing algorithms developed for the restoration of such data are only applicable to experimental measurements collected under well-prepared laboratory conditions (i.e. where the pattern of the velocity flow field is known), and the distribution, size and type of gaps and noise may be controlled by the laboratory set-up. However, in many cases, such as PIV and PTV measurements of arbitrarily turbid coastal waters, the arrangement of such conditions is not possible. When the size of gaps or the level of noise in these experimental measurements become too large, their successful restoration with existing algorithms becomes questionable. Here, we outline a new physics-enabled flow restoration algorithm (PEFRA), specially designed for the restoration of such velocity data. Implemented as a ‘black box’ algorithm, where no user-background in fluid dynamics is necessary, the physical structure of the flow in gappy or noisy data is able to be restored in accordance with its hydrodynamical basis. The use of this is not dependent on types of flow, types of gaps or noise in measurements. The algorithm will operate on any data time-series containing a sequence of velocity flow fields recorded by PIV or PTV. Tests with numerical flow fields established that this method is able to successfully restore corrupted PIV and PTV measurements with different levels of sparsity and noise. This assessment of the algorithm performance is extended with an example application to in situ submersible 3D-PTV measurements collected in the bottom boundary layer of the coastal ocean, where the naturally-occurring plankton and suspended sediments used as tracers causes an increase in the noise level that, without such denoising, will contaminate the measurements. (paper)

Universal hydrodynamic flow in holographic planar shock collisions

Energy Technology Data Exchange (ETDEWEB)

Chesler, Paul M. [Department of Physics, Harvard University,Cambridge MA 02138 (United States); Kilbertus, Niki [Institut für Theoretische Physik, Universität Regensburg,D-93040 Regensburg (Germany); Schee, Wilke van der [Center for Theoretical Physics, MIT,Cambridge MA 02139 (United States)

2015-11-20

We study the collision of planar shock waves in AdS{sub 5} as a function of shock profile. In the dual field theory the shock waves describe planar sheets of energy whose collision results in the formation of a plasma which behaves hydrodynamically at late times. We find that the post-collision stress tensor near the light cone exhibits transient non-universal behavior which depends on both the shock width and the precise functional form of the shock profile. However, over a large range of shock widths, including those which yield qualitative different behavior near the future light cone, and for different shock profiles, we find universal behavior in the subsequent hydrodynamic evolution. Additionally, we compute the rapidity distribution of produced particles and find it to be well described by a Gaussian.

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Laxmi A. Bewoor

2017-10-01

Full Text Available The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.

A benchmark study of the Signed-particle Monte Carlo algorithm for the Wigner equation

Directory of Open Access Journals (Sweden)

Muscato Orazio

2017-12-01

Full Text Available The Wigner equation represents a promising model for the simulation of electronic nanodevices, which allows the comprehension and prediction of quantum mechanical phenomena in terms of quasi-distribution functions. During these years, a Monte Carlo technique for the solution of this kinetic equation has been developed, based on the generation and annihilation of signed particles. This technique can be deeply understood in terms of the theory of pure jump processes with a general state space, producing a class of stochastic algorithms. One of these algorithms has been validated successfully by numerical experiments on a benchmark test case.

Discovery of hydrodynamic behavior in high energy heavy ion collisions

International Nuclear Information System (INIS)

Hamagaki, Hideki

2010-01-01

The objective of high energy heavy ion collision experiments is creating high temperature and high density states to investigate hadron matter properties in such extreme conditions. Since the start of heavy ion collision experiments with BEVALAC, knowledge of the space-time evolution of collision has become indispensable for understanding the hadronic matter properties. This problem is reviewed here from the hydrodynamics view point. Although its importance has been generally recognized since the time of BEVALAC, the hydrodynamic description has not been successful because the hydrodynamic model assuming non-viscous or small fluid had not been considered to be enough to properly describe the space-time evolution of hadron-hadron collisions until the RHIC experiments. Items of the following titles are picked up and reviewed here: Development of heavy ion accelerations; Space-time evolution of hadron collision process and hydrodynamic model; Chemical freezing and kinematical freezing, including transverse momentum spectra at proton-proton collisions and particle spectra in heavy ion collisions; Elliptical azimuthal angle anisotropy; Discovery of hydrodynamic flow at BEVALAC; Problems of incident beam dependence of v2; Elliptic azimuthal angle anisotropy at RHIC; What is it that carries the elliptic anisotropy? Discussion of attainment of thermodynamical equilibrium state at RHIC; and finally investigations of fluid properties other than azimuthal anisotropy, such as, Fluid properties probed by heavy quarks and Observing QCD fluid responses. (S. Funahashi)

Modeling the ultrasonic testing echoes by a combination of particle swarm optimization and Levenberg–Marquardt algorithms

International Nuclear Information System (INIS)

Gholami, Ali; Honarvar, Farhang; Moghaddam, Hamid Abrishami

2017-01-01

This paper presents an accurate and easy-to-implement algorithm for estimating the parameters of the asymmetric Gaussian chirplet model (AGCM) used for modeling echoes measured in ultrasonic nondestructive testing (NDT) of materials. The proposed algorithm is a combination of particle swarm optimization (PSO) and Levenberg–Marquardt (LM) algorithms. PSO does not need an accurate initial guess and quickly converges to a reasonable output while LM needs a good initial guess in order to provide an accurate output. In the combined algorithm, PSO is run first to provide a rough estimate of the output and this result is consequently inputted to the LM algorithm for more accurate estimation of parameters. To apply the algorithm to signals with multiple echoes, the space alternating generalized expectation maximization (SAGE) is used. The proposed combined algorithm is robust and accurate. To examine the performance of the proposed algorithm, it is applied to a number of simulated echoes having various signal to noise ratios. The combined algorithm is also applied to a number of experimental ultrasonic signals. The results corroborate the accuracy and reliability of the proposed combined algorithm. (paper)

Hydrodynamic determination of the moving direction of an artificial fin by a harbour seal (Phoca vitulina).

Science.gov (United States)

Wieskotten, S; Dehnhardt, G; Mauck, B; Miersch, L; Hanke, W

2010-07-01

Harbour seals can use their vibrissal system to detect and follow hydrodynamic trails left by moving objects. In this study we determined the maximum time after which a harbour seal could indicate the moving direction of an artificial fish tail and analysed the hydrodynamic parameters allowing the discrimination. Hydrodynamic trails were generated using a fin-like paddle moving from left to right or from right to left in the calm water of an experimental box. The blindfolded seal was able to recognise the direction of the paddle movement when the hydrodynamic trail was up to 35 s old. Particle Image Velocimetry (PIV) revealed that the seal might have perceived and used two different hydrodynamic parameters to determine the moving direction of the fin-like paddle. The structure and spatial arrangement of the vortices in the hydrodynamic trail and high water velocities between two counter-rotating vortices are characteristic of the movement direction and are within the sensory range of the seal.

The particle swarm optimization algorithm applied to nuclear systems surveillance test planning

International Nuclear Information System (INIS)

Siqueira, Newton Norat

2006-12-01

This work shows a new approach to solve availability maximization problems in electromechanical systems, under periodic preventive scheduled tests. This approach uses a new Optimization tool called PSO developed by Kennedy and Eberhart (2001), Particle Swarm Optimization, integrated with probabilistic safety analysis model. Two maintenance optimization problems are solved by the proposed technique, the first one is a hypothetical electromechanical configuration and the second one is a real case from a nuclear power plant (Emergency Diesel Generators). For both problem PSO is compared to a genetic algorithm (GA). In the experiments made, PSO was able to obtain results comparable or even slightly better than those obtained b GA. Therefore, the PSO algorithm is simpler and its convergence is faster, indicating that PSO is a good alternative for solving such kind of problems. (author)

Elasto-hydrodynamic lubrication

CERN Document Server

Dowson, D; Hopkins, D W

1977-01-01

Elasto-Hydrodynamic Lubrication deals with the mechanism of elasto-hydrodynamic lubrication, that is, the lubrication regime in operation over the small areas where machine components are in nominal point or line contact. The lubrication of rigid contacts is discussed, along with the effects of high pressure on the lubricant and bounding solids. The governing equations for the solution of elasto-hydrodynamic problems are presented.Comprised of 13 chapters, this volume begins with an overview of elasto-hydrodynamic lubrication and representation of contacts by cylinders, followed by a discussio

Elementary classical hydrodynamics

CERN Document Server

Chirgwin, B H; Langford, W J; Maxwell, E A; Plumpton, C

1967-01-01

Elementary Classical Hydrodynamics deals with the fundamental principles of elementary classical hydrodynamics, with emphasis on the mechanics of inviscid fluids. Topics covered by this book include direct use of the equations of hydrodynamics, potential flows, two-dimensional fluid motion, waves in liquids, and compressible flows. Some general theorems such as Bernoulli's equation are also considered. This book is comprised of six chapters and begins by introducing the reader to the fundamental principles of fluid hydrodynamics, with emphasis on ways of studying the motion of a fluid. Basic c

Portfolio management using value at risk: A comparison between genetic algorithms and particle swarm optimization

NARCIS (Netherlands)

V.A.F. Dallagnol (V. A F); J.H. van den Berg (Jan); L. Mous (Lonneke)

2009-01-01

textabstractIn this paper, it is shown a comparison of the application of particle swarm optimization and genetic algorithms to portfolio management, in a constrained portfolio optimization problem where no short sales are allowed. The objective function to be minimized is the value at risk

Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling

International Nuclear Information System (INIS)

He Yaoyao; Zhou Jianzhong; Xiang Xiuqiao; Chen Heng; Qin Hui

2009-01-01

The goal of this paper is to present a novel chaotic particle swarm optimization (CPSO) algorithm and compares the efficiency of three one-dimensional chaotic maps within symmetrical region for long-term cascaded hydroelectric system scheduling. The introduced chaotic maps improve the global optimal capability of CPSO algorithm. Moreover, a piecewise linear interpolation function is employed to transform all constraints into restrict upriver water level for implementing the maximum of objective function. Numerical results and comparisons demonstrate the effect and speed of different algorithms on a practical hydro-system.

Navier-Stokes simulation with constraint forces: finite-difference method for particle-laden flows and complex geometries.

Science.gov (United States)

Höfler, K; Schwarzer, S

2000-06-01

Building on an idea of Fogelson and Peskin [J. Comput. Phys. 79, 50 (1988)] we describe the implementation and verification of a simulation technique for systems of non-Brownian particles in fluids at Reynolds numbers up to about 20 on the particle scale. This direct simulation technique fills a gap between simulations in the viscous regime and high-Reynolds-number modeling. It also combines sufficient computational accuracy with numerical efficiency and allows studies of several thousand, in principle arbitrarily shaped, extended and hydrodynamically interacting particles on regular work stations. We verify the algorithm in two and three dimensions for (i) single falling particles and (ii) a fluid flowing through a bed of fixed spheres. In the context of sedimentation we compute the volume fraction dependence of the mean sedimentation velocity. The results are compared with experimental and other numerical results both in the viscous and inertial regime and we find very satisfactory agreement.

A hybrid artificial bee colony algorithm and pattern search method for inversion of particle size distribution from spectral extinction data

Science.gov (United States)

Wang, Li; Li, Feng; Xing, Jian

2017-10-01

In this paper, a hybrid artificial bee colony (ABC) algorithm and pattern search (PS) method is proposed and applied for recovery of particle size distribution (PSD) from spectral extinction data. To be more useful and practical, size distribution function is modelled as the general Johnson's ? function that can overcome the difficulty of not knowing the exact type beforehand encountered in many real circumstances. The proposed hybrid algorithm is evaluated through simulated examples involving unimodal, bimodal and trimodal PSDs with different widths and mean particle diameters. For comparison, all examples are additionally validated by the single ABC algorithm. In addition, the performance of the proposed algorithm is further tested by actual extinction measurements with real standard polystyrene samples immersed in water. Simulation and experimental results illustrate that the hybrid algorithm can be used as an effective technique to retrieve the PSDs with high reliability and accuracy. Compared with the single ABC algorithm, our proposed algorithm can produce more accurate and robust inversion results while taking almost comparative CPU time over ABC algorithm alone. The superiority of ABC and PS hybridization strategy in terms of reaching a better balance of estimation accuracy and computation effort increases its potentials as an excellent inversion technique for reliable and efficient actual measurement of PSD.

Research on Demand Prediction of Fresh Food Supply Chain Based on Improved Particle Swarm Optimization Algorithm

OpenAIRE

He Wang

2015-01-01

Demand prediction of supply chain is an important content and the first premise in supply management of different enterprises and has become one of the difficulties and hot research fields for the researchers related. The paper takes fresh food demand prediction for example and presents a new algorithm for predicting demand of fresh food supply chain. First, the working principle and the root causes of the defects of particle swarm optimization algorithm are analyzed in the study; Second, the...

Hydrodynamic Modelling of Municipal Solid Waste Residues in a Pilot Scale Fluidized Bed Reactor

Directory of Open Access Journals (Sweden)

João Cardoso

2017-11-01

Full Text Available The present study investigates the hydrodynamics and heat transfer behavior of municipal solid waste (MSW gasification in a pilot scale bubbling fluidized bed reactor. A multiphase 2-D numerical model following an Eulerian-Eulerian approach within the FLUENT framework was implemented. User defined functions (UDFs were coupled to improve hydrodynamics and heat transfer phenomena, and to minimize deviations between the experimental and numerical results. A grid independence study was accomplished through comparison of the bed volume fraction profiles and by reasoning the grid accuracy and computational cost. The standard deviation concept was used to determine the mixing quality indexes. Simulated results showed that UDFs improvements increased the accuracy of the mathematical model. Smaller size ratio of the MSW-dolomite mixture revealed a more uniform mixing, and larger ratios enhanced segregation. Also, increased superficial gas velocity promoted the solid particles mixing. Heat transfer within the fluidized bed showed strong dependence on the MSW solid particles sizes, with smaller particles revealing a more effective process.

Study of Parameters Effect on Hydrodynamics of a Gas-Solid Chamber Experimentally and Numerically

Directory of Open Access Journals (Sweden)

Rahimzadeh Hassan

2012-04-01

Full Text Available In this research, gas velocity, initial static bed height and particle size effect on hydrodynamics of a non-reactive gas–solid fluidized bed chamber were studied experimentally and computationally. A multi fluid Eulerian model incorporating the kinetic theory for solid particles was applied to simulate the unsteady state behavior of this chamber and momentum exchange coefficients were calculated by using the Syamlal- O’Brien drag functions. Simulation results were compared with the experimental data in order to validate the CFD model. Pressure drops predicted by the simulations at different particle sizes and initial static bed height were in good agreement with experimental measurements at superficial gas velocity higher than the minimum fluidization velocity. Simulation results also indicated that small bubbles were produced at the bottom of the bed. These bubbles collided with each other as they moved upwards forming larger bubbles. Furthermore, this comparison showed that the model can predict hydrodynamic behavior of gas solid fluidized bed chambers reasonably well.

Kinetic theory of flocking: derivation of hydrodynamic equations.

Science.gov (United States)

Ihle, Thomas

2011-03-01

It is shown how to explicitly coarse-grain the microscopic dynamics of the rule-based Vicsek model for self-propelled agents. The hydrodynamic equations are derived by means of an Enskog-type kinetic theory. Expressions for all transport coefficients are given. The transition from a disordered to a flocking state, which at large particle speeds appears to be a fluctuation-induced first-order phase transition, is studied numerically and analytically.

PARTRACK - A particle tracking algorithm for transport and dispersion of solutes in a sparsely fractured rock

International Nuclear Information System (INIS)

Svensson, Urban

2001-04-01

A particle tracking algorithm, PARTRACK, that simulates transport and dispersion in a sparsely fractured rock is described. The main novel feature of the algorithm is the introduction of multiple particle states. It is demonstrated that the introduction of this feature allows for the simultaneous simulation of Taylor dispersion, sorption and matrix diffusion. A number of test cases are used to verify and demonstrate the features of PARTRACK. It is shown that PARTRACK can simulate the following processes, believed to be important for the problem addressed: the split up of a tracer cloud at a fracture intersection, channeling in a fracture plane, Taylor dispersion and matrix diffusion and sorption. From the results of the test cases, it is concluded that PARTRACK is an adequate framework for simulation of transport and dispersion of a solute in a sparsely fractured rock

Radio Evolution of Supernova Remnants Including Nonlinear Particle Acceleration: Insights from Hydrodynamic Simulations

Science.gov (United States)

Pavlović, Marko Z.; Urošević, Dejan; Arbutina, Bojan; Orlando, Salvatore; Maxted, Nigel; Filipović, Miroslav D.

2018-01-01

We present a model for the radio evolution of supernova remnants (SNRs) obtained by using three-dimensional hydrodynamic simulations coupled with nonlinear kinetic theory of cosmic-ray (CR) acceleration in SNRs. We model the radio evolution of SNRs on a global level by performing simulations for a wide range of the relevant physical parameters, such as the ambient density, supernova (SN) explosion energy, acceleration efficiency, and magnetic field amplification (MFA) efficiency. We attribute the observed spread of radio surface brightnesses for corresponding SNR diameters to the spread of these parameters. In addition to our simulations of Type Ia SNRs, we also considered SNR radio evolution in denser, nonuniform circumstellar environments modified by the progenitor star wind. These simulations start with the mass of the ejecta substantially higher than in the case of a Type Ia SN and presumably lower shock speed. The magnetic field is understandably seen as very important for the radio evolution of SNRs. In terms of MFA, we include both resonant and nonresonant modes in our large-scale simulations by implementing models obtained from first-principles, particle-in-cell simulations and nonlinear magnetohydrodynamical simulations. We test the quality and reliability of our models on a sample consisting of Galactic and extragalactic SNRs. Our simulations give Σ ‑ D slopes between ‑4 and ‑6 for the full Sedov regime. Recent empirical slopes obtained for the Galactic samples are around ‑5, while those for the extragalactic samples are around ‑4.

Interaction of Microphysical Aerosol Processes with Hydrodynamics Mixing

KAUST Repository

Alshaarawi, Amjad

2015-12-15

This work is concerned with the interaction between condensing aerosol dynamics and hydrodynamic mixing within ow configurations in which aerosol particles form (nucleate) from a supersaturated vapor and supersaturation is induced by the mixing of two streams (a saturated stream and a cold one). Two canonical hydrodynamic configurations are proposed for the investigation. The First is the steady one-dimensional opposed-ow configuration. The setup consists of the two (saturated and cold) streams owing from opposite nozzles. A mixing layer is established across a stagnation plane in the center where nucleation and other aerosol dynamics are triggered. The second is homogeneous isotropic turbulence in a three-dimensional periodic domain. Patches of a hot saturated gas mix with patches of a cold one. A mixing layer forms across the growing interface where the aerosol dynamics of interest occur. In both configurations, a unique analogy is observed. The results reveal a complex response to variations in the mixing rates. Depending on the mixing rate, the response of the number density falls into one of two regimes. For fast mixing rates, the maximum reached number density of the condensing droplets increases with the hydrodynamic time. We refer to this as the nucleation regime. On the contrary, for low mixing rates, the maximum reached number density decreases with the hydrodynamic time. We refer to this as the consumption regime. It is shown that vapor scavenging by the aerosol phase is key to explaining the transition between these two regimes.

Thermo-hydrodynamic design of fluidized bed combustors estimating metal wastage

CERN Document Server

Lyczkowski, Robert W; Bouillard, Jacques X; Folga, Stephen M

2012-01-01

Thermo-Hydrodynamic Design of Fluidized Bed Combustors: Estimating Metal Wastage is a unique volume that finds that the most sensitive parameters affecting metal wastage are superficial fluidizing velocity, particle diameter, and particle sphericity.  Gross consistencies between disparate data sources using different techniques were found when the erosion rates are compared on the same basis using the concept of renormalization.  The simplified mechanistic models and correlations, when validated, can be used to renormalize any experimental data so they can be compared on a consistent basis using a master equation.

An L-stable method for solving stiff hydrodynamics

Science.gov (United States)

Li, Shengtai

2017-07-01

We develop a new method for simulating the coupled dynamics of gas and multi-species dust grains. The dust grains are treated as pressure-less fluids and their coupling with gas is through stiff drag terms. If an explicit method is used, the numerical time step is subject to the stopping time of the dust particles, which can become extremely small for small grains. The previous semi-implicit method [1] uses second-order trapezoidal rule (TR) on the stiff drag terms and it works only for moderately small size of the dust particles. This is because TR method is only A-stable not L-stable. In this work, we use TR-BDF2 method [2] for the stiff terms in the coupled hydrodynamic equations. The L-stability of TR-BDF2 proves essential in treating a number of dust species. The combination of TR-BDF2 method with the explicit discretization of other hydro terms can solve a wide variety of stiff hydrodynamics equations accurately and efficiently. We have implemented our method in our LA-COMPASS (Los Alamos Computational Astrophysics Suite) package. We have applied the code to simulate some dusty proto-planetary disks and obtained very good match with astronomical observations.

Cell-centered particle weighting algorithm for PIC simulations in a non-uniform 2D axisymmetric mesh

Science.gov (United States)

Araki, Samuel J.; Wirz, Richard E.

2014-09-01

Standard area weighting methods for particle-in-cell simulations result in systematic errors on particle densities for a non-uniform mesh in cylindrical coordinates. These errors can be significantly reduced by using weighted cell volumes for density calculations. A detailed description on the corrected volume calculations and cell-centered weighting algorithm in a non-uniform mesh is provided. The simple formulas for the corrected volume can be used for any type of quadrilateral and/or triangular mesh in cylindrical coordinates. Density errors arising from the cell-centered weighting algorithm are computed for radial density profiles of uniform, linearly decreasing, and Bessel function in an adaptive Cartesian mesh and an unstructured mesh. For all the density profiles, it is shown that the weighting algorithm provides a significant improvement for density calculations. However, relatively large density errors may persist at outermost cells for monotonically decreasing density profiles. A further analysis has been performed to investigate the effect of the density errors in potential calculations, and it is shown that the error at the outermost cell does not propagate into the potential solution for the density profiles investigated.

Nonlocal effects in nonisothermal hydrodynamics from the perspective of beyond-equilibrium thermodynamics

NARCIS (Netherlands)

Hütter, M.; Brader, J.M.

2009-01-01

We examine the origins of nonlocality in a nonisothermal hydrodynamic formulation of a one-component fluid of particles that exhibit long-range correlations, e.g., due to a spherically symmetric, long-range interaction potential. In order to furnish the continuum modeling with physical understanding

Lozenge Tiling Dynamics and Convergence to the Hydrodynamic Equation

Science.gov (United States)

Laslier, Benoît; Toninelli, Fabio Lucio

2018-03-01

We study a reversible continuous-time Markov dynamics of a discrete (2 + 1)-dimensional interface. This can be alternatively viewed as a dynamics of lozenge tilings of the {L× L} torus, or as a conservative dynamics for a two-dimensional system of interlaced particles. The particle interlacement constraints imply that the equilibrium measures are far from being product Bernoulli: particle correlations decay like the inverse distance squared and interface height fluctuations behave on large scales like a massless Gaussian field. We consider a particular choice of the transition rates, originally proposed in Luby et al. (SIAM J Comput 31:167-192, 2001): in terms of interlaced particles, a particle jump of length n that preserves the interlacement constraints has rate 1/(2 n). This dynamics presents special features: the average mutual volume between two interface configurations decreases with time (Luby et al. 2001) and a certain one-dimensional projection of the dynamics is described by the heat equation (Wilson in Ann Appl Probab 14:274-325, 2004). In this work we prove a hydrodynamic limit: after a diffusive rescaling of time and space, the height function evolution tends as L\\to∞ to the solution of a non-linear parabolic PDE. The initial profile is assumed to be C 2 differentiable and to contain no "frozen region". The explicit form of the PDE was recently conjectured (Laslier and Toninelli in Ann Henri Poincaré Theor Math Phys 18:2007-2043, 2017) on the basis of local equilibrium considerations. In contrast with the hydrodynamic equation for the Langevin dynamics of the Ginzburg-Landau model (Funaki and Spohn in Commun Math Phys 85:1-36, 1997; Nishikawa in Commun Math Phys 127:205-227, 2003), here the mobility coefficient turns out to be a non-trivial function of the interface slope.

Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm

Directory of Open Access Journals (Sweden)

KeKe Gen

2015-01-01

Full Text Available The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs. Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping, which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC. The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and

Vectorizing and macrotasking Monte Carlo neutral particle algorithms

International Nuclear Information System (INIS)

Heifetz, D.B.

1987-04-01

Monte Carlo algorithms for computing neutral particle transport in plasmas have been vectorized and macrotasked. The techniques used are directly applicable to Monte Carlo calculations of neutron and photon transport, and Monte Carlo integration schemes in general. A highly vectorized code was achieved by calculating test flight trajectories in loops over arrays of flight data, isolating the conditional branches to as few a number of loops as possible. A number of solutions are discussed to the problem of gaps appearing in the arrays due to completed flights, which impede vectorization. A simple and effective implementation of macrotasking is achieved by dividing the calculation of the test flight profile among several processors. A tree of random numbers is used to ensure reproducible results. The additional memory required for each task may preclude using a larger number of tasks. In future machines, the limit of macrotasking may be possible, with each test flight, and split test flight, being a separate task

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

Directory of Open Access Journals (Sweden)

Narinder Singh

2017-01-01

Full Text Available A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO and Grey Wolf Optimizer (GWO. The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum.

Fractionation of Magnetic Microspheres in a Microfluidic Spiral: Interplay between Magnetic and Hydrodynamic Forces.

Directory of Open Access Journals (Sweden)

S Dutz

Full Text Available Magnetic forces and curvature-induced hydrodynamic drag have both been studied and employed in continuous microfluidic particle separation and enrichment schemes. Here we combine the two. We investigate consequences of applying an outwardly directed magnetic force to a dilute suspension of magnetic microspheres circulating in a spiral microfluidic channel. This force is realized with an array of permanent magnets arranged to produce a magnetic field with octupolar symmetry about the spiral axis. At low flow rates particles cluster around an apparent streamline of the flow near the outer wall of the turn. At high flow rates this equilibrium is disrupted by the induced secondary (Dean flow and a new equilibrium is established near the inner wall of the turn. A model incorporating key forces involved in establishing these equilibria is described, and is used to extract quantitative information about the magnitude of local Dean drag forces from experimental data. Steady-state fractionation of suspensions by particle size under the combined influence of magnetic and hydrodynamic forces is demonstrated. Extensions of this work could lead to new continuous microscale particle sorting and enrichment processes with improved fidelity and specificity.

Simulation of impact ballistic of Cu-10wt%Sn frangible bullet using smoothed particle hydrodynamics

Science.gov (United States)

Hidayat, Mas Irfan P.; Widyastuti, Simaremare, Peniel

2018-04-01

Frangible bullet is designed to disintegrate upon impact against a hard target. Understanding the impact response and performance of frangible bullet is therefore of highly interest. In this paper, simulation of impact ballistic of Cu-IOwt%Sn frangible bullet using smoothed particle hydrodynamics (SPH) method is presented. The frangible bullet is impacted against a hard, cylindrical stainless steel target. Effect of variability of the frangible bullet material properties due to the variation of sintering temperature in its manufacturing process to the bullet frangibility factor (FF) is investigated numerically. In addition, the bullet kinetic energy during impact as well as its ricochet and fragmentation are also examined and simulated. Failure criterion based upon maximum strain is employed in the simulation. It is shown that the SPH simulation can produce good estimation for kinetic energy of bullet after impact, thus giving the FF prediction with respect to the variation of frangible bullet material properties. In comparison to explicit finite element (FE) simulation, in which only material/element deletion is shown, convenience in showing frangible bullet fragmentation is shown using the SPH simulation. As a result, the effect of sintering temperature to the way of the frangible bullet fragmented can be also observed clearly.

Classifying and modelling spiral structures in hydrodynamic simulations of astrophysical discs

Science.gov (United States)

Forgan, D. H.; Ramón-Fox, F. G.; Bonnell, I. A.

2018-05-01

We demonstrate numerical techniques for automatic identification of individual spiral arms in hydrodynamic simulations of astrophysical discs. Building on our earlier work, which used tensor classification to identify regions that were `spiral-like', we can now obtain fits to spirals for individual arm elements. We show this process can even detect spirals in relatively flocculent spiral patterns, but the resulting fits to logarithmic `grand-design' spirals are less robust. Our methods not only permit the estimation of pitch angles, but also direct measurements of the spiral arm width and pattern speed. In principle, our techniques will allow the tracking of material as it passes through an arm. Our demonstration uses smoothed particle hydrodynamics simulations, but we stress that the method is suitable for any finite-element hydrodynamics system. We anticipate our techniques will be essential to studies of star formation in disc galaxies, and attempts to find the origin of recently observed spiral structure in protostellar discs.

Development of an opto-hydrodynamic process to remove nanoparticles from solid surfaces

Science.gov (United States)

Ahn, Daehwan; Ha, Jeonghong; Kim, Dongsik

2013-01-01

We developed a surface cleaning process to remove nanoscale contaminants as small as 10 nm from solid surfaces using a laser-induced micro liquid jet. In the process, laser-induced breakdown of a micron-sized water droplet (∼10 nl) produces a high-speed jet with speeds up to 1600 m/s liquid jet via an explosive vaporization process. Impingement of the liquid jet with atomized droplets on the contaminated substrate removes the nanoparticles under the hydrodynamic drag forces. The process parameters, including the incident laser energy and the position of the droplet relative to the laser focus, were optimized to maximize the cleaning power. Polystyrene latex particles 20, 30, or 90 nm in diameter and Al2O3 particles 10-50 nm in diameter were used to demonstrate the cleaning performance of the opto-hydrodynamic cleaning technique. The proposed cleaning process is expected to be useful for selectively cleaning local areas with minimal exposure to water.

Particle Swarm Optimization

Science.gov (United States)

Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

2002-01-01

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

Science.gov (United States)

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Jiaxi Wang

2016-01-01

Full Text Available The shunting schedule of electric multiple units depot (SSED is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality.

An algorithm for the reconstruction of high-energy neutrino-induced particle showers and its application to the ANTARES neutrino telescope

NARCIS (Netherlands)

Albert, A.; André, M.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J.-J.; Avgitas, T.; Baret, B.; Barrios-Martí, J.; Basa, S.; Bertin, V.; Biagi, S.; Bormuth, R.; Bourret, S.; Bouwhuis, M.C.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Celli, S.; Chiarusi, T.; Circella, M.; Coelho, C.O.A.; Coleiro, A.; Coniglione, R.; Costantini, H.; Coyle, P.; Creusot, A.; Deschamps, A.; De Bonis, G.; Distefano, C.; Di Palma, I.; Domi, A.; Donzaud, C.; Dornic, D.; Drouhin, D.; Eberl, T.; El Bojaddaini, I.; Elsässer, D.; Enzenhofer, A.; Felis, I.; Folger, F.; Fusco, L.A.; Galata, S.; Gay, P.; Giordano, V.; Glotin, H.; Grégoire, T.; Gracia-Ruiz, R.; Graf, K.; Hallmann, S.; van Haren, H.; Heijboer, A.J.; Hello, Y.; Hernandez-Rey, J.J.; Hößl, J.; Hofestädt, J.; Hugon, C.; Illuminati, G.; James, C.W.; de Jong, M.; Jongen, M.; Kadler, M.; Kalekin, O.; Katz, U.; Kießling, D.; Kouchner, A.; Kreter, M.; Kreykenbohm, I.; Kulikovskiy, V.; Lachaud, C.; Lahmann, R.; Lefevre, D.; Leonora, E.; Lotze, M.; Loucatos, S.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martinez-Mora, J.A.; Mele, R.; Melis, K.; Michael, T.; Migliozzi, P.; Moussa, A.; Nezri, E.; Organokov, M.; Pavalas, G.E.; Pellegrino, C.; Perrina, C.; Piattelli, P.; Popa, V.; Pradier, T.; Quinn, L.; Racca, C.; Riccobene, G.; Sanchez-Losa, A.; Saldaña, M.; Salvadori, I.; Samtleben, D.F.E.; Sanguineti, M.; Sapienza, P.; Schussler, F.; Sieger, C.; Spurio, M.; Stolarczyk, T.; Taiuti, M.; Tayalati, Y.; Trovato, A.; Turpin, D.; Tönnis, C.; Vallage, B.; Van Elewyck, V.; Versari, F.; Vivolo, D.; Vizzoca, A.; Wilms, J.; Zornoza, J.D.; Zuniga, J.

2017-01-01

A novel algorithm to reconstruct neutrino-induced particle showers within the ANTARES neutrino telescope is presented. The method achieves a median angular resolution of 6∘ for shower energies below 100 TeV. Applying this algorithm to 6 years of data taken with the ANTARES detector, 8 events with

Modeling NIF experimental designs with adaptive mesh refinement and Lagrangian hydrodynamics

Science.gov (United States)

Koniges, A. E.; Anderson, R. W.; Wang, P.; Gunney, B. T. N.; Becker, R.; Eder, D. C.; MacGowan, B. J.; Schneider, M. B.

2006-06-01

Incorporation of adaptive mesh refinement (AMR) into Lagrangian hydrodynamics algorithms allows for the creation of a highly powerful simulation tool effective for complex target designs with three-dimensional structure. We are developing an advanced modeling tool that includes AMR and traditional arbitrary Lagrangian-Eulerian (ALE) techniques. Our goal is the accurate prediction of vaporization, disintegration and fragmentation in National Ignition Facility (NIF) experimental target elements. Although our focus is on minimizing the generation of shrapnel in target designs and protecting the optics, the general techniques are applicable to modern advanced targets that include three-dimensional effects such as those associated with capsule fill tubes. Several essential computations in ordinary radiation hydrodynamics need to be redesigned in order to allow for AMR to work well with ALE, including algorithms associated with radiation transport. Additionally, for our goal of predicting fragmentation, we include elastic/plastic flow into our computations. We discuss the integration of these effects into a new ALE-AMR simulation code. Applications of this newly developed modeling tool as well as traditional ALE simulations in two and three dimensions are applied to NIF early-light target designs.

Modeling NIF Experimental Designs with Adaptive Mesh Refinement and Lagrangian Hydrodynamics

International Nuclear Information System (INIS)

Koniges, A E; Anderson, R W; Wang, P; Gunney, B N; Becker, R; Eder, D C; MacGowan, B J

2005-01-01

Incorporation of adaptive mesh refinement (AMR) into Lagrangian hydrodynamics algorithms allows for the creation of a highly powerful simulation tool effective for complex target designs with three-dimensional structure. We are developing an advanced modeling tool that includes AMR and traditional arbitrary Lagrangian-Eulerian (ALE) techniques. Our goal is the accurate prediction of vaporization, disintegration and fragmentation in National Ignition Facility (NIF) experimental target elements. Although our focus is on minimizing the generation of shrapnel in target designs and protecting the optics, the general techniques are applicable to modern advanced targets that include three-dimensional effects such as those associated with capsule fill tubes. Several essential computations in ordinary radiation hydrodynamics need to be redesigned in order to allow for AMR to work well with ALE, including algorithms associated with radiation transport. Additionally, for our goal of predicting fragmentation, we include elastic/plastic flow into our computations. We discuss the integration of these effects into a new ALE-AMR simulation code. Applications of this newly developed modeling tool as well as traditional ALE simulations in two and three dimensions are applied to NIF early-light target designs

Modeling Nif experimental designs with adaptive mesh refinement and Lagrangian hydrodynamics

International Nuclear Information System (INIS)

Koniges, A.E.; Anderson, R.W.; Wang, P.; Gunney, B.T.N.; Becker, R.; Eder, D.C.; MacGowan, B.J.; Schneider, M.B.

2006-01-01

Incorporation of adaptive mesh refinement (AMR) into Lagrangian hydrodynamics algorithms allows for the creation of a highly powerful simulation tool effective for complex target designs with three-dimensional structure. We are developing an advanced modeling tool that includes AMR and traditional arbitrary Lagrangian-Eulerian (ALE) techniques. Our goal is the accurate prediction of vaporization, disintegration and fragmentation in National Ignition Facility (NIF) experimental target elements. Although our focus is on minimizing the generation of shrapnel in target designs and protecting the optics, the general techniques are applicable to modern advanced targets that include three-dimensional effects such as those associated with capsule fill tubes. Several essential computations in ordinary radiation hydrodynamics need to be redesigned in order to allow for AMR to work well with ALE, including algorithms associated with radiation transport. Additionally, for our goal of predicting fragmentation, we include elastic/plastic flow into our computations. We discuss the integration of these effects into a new ALE-AMR simulation code. Applications of this newly developed modeling tool as well as traditional ALE simulations in two and three dimensions are applied to NIF early-light target designs. (authors)

An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

Directory of Open Access Journals (Sweden)

Nizar Hadi Abbas

2016-07-01

Full Text Available This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

The hydrodynamic behaviour of gas—solid trickle flow over a regularly stacked packing

OpenAIRE

Verver, A.B.; van Swaaij, Willibrordus Petrus Maria

1986-01-01

The hydrodynamic properties of counter-current gas—solid flow over a regularly stacked packing at trickle flow conditions have been studied. The flow properties of the solids phase were examined, using five types of solid particles with a mean particle diameter ranging from 70 to 880 μm and a particle density from 800 to 7800 kg m−3. Data on the solids hold-up and the pressure drop caused by the solids flow were obtained from experiments in a test column of 0.10 m square cross-section. A part...

Investigation of hydrodynamics and heat transfer in pseudo 2D spouted beds with and without draft plates

Directory of Open Access Journals (Sweden)

S. H. Hosseini

Full Text Available Abstract In the present study, hydrodynamics and gas to particle heat transfer in pseudo two dimensional spouted beds (2DSB with and without draft plates were investigated using the Eulerian-Eulerian approach. The main objective of the study was to provide an understanding of effects of the presence of draft plates on the hydrodynamics and heat transfer behavior of solid particles in the spouted beds. To validate the model, the predicted mean particle vertical velocity at the bed axis, the lateral profiles of vertical particle velocity at different bed heights for both systems, and the particle velocity vector fields in the beds were compared with the experimental measurements. A close agreement between the CFD results and the experimental data was found for both systems. The simulation results showed that the particle volume fraction in the spout and fountain regions of the spouted bed with draft plates is considerably lower than that in a conventional spouted bed (without draft plates. Simulation results also showed significant differences between the temperature distributions of gas and solid phases in spouted beds with and without draft plates.

How Confinement-Induced Structures Alter the Contribution of Hydrodynamic and Short-Ranged Repulsion Forces to the Viscosity of Colloidal Suspensions

Directory of Open Access Journals (Sweden)

Meera Ramaswamy

2017-10-01

Full Text Available Confined systems ranging from the atomic to the granular are ubiquitous in nature. Experiments and simulations of such atomic and granular systems have shown a complex relationship between the microstructural arrangements under confinement, the short-ranged particle stresses, and flow fields. Understanding the same correlation between structure and rheology in the colloidal regime is important due to the significance of such suspensions in industrial applications. Moreover, colloidal suspensions exhibit a wide range of structures under confinement that could considerably modify such force balances and the resulting viscosity. Here, we use a combination of experiments and simulations to elucidate how confinement-induced structures alter the relative contributions of hydrodynamic and short-range repulsive forces to produce up to a tenfold change in the viscosity. In the experiments we use a custom-built confocal rheoscope to image the particle configurations of a colloidal suspension while simultaneously measuring its stress response. We find that as the gap decreases below 15 particle diameters, the viscosity first decreases from its bulk value, shows fluctuations with the gap, and then sharply increases for gaps below 3 particle diameters. These trends in the viscosity are shown to strongly correlate with the suspension microstructure. Further, we compare our experimental results to those from two different simulations techniques, which enables us to determine the relative contributions of hydrodynamic and short-range repulsive stresses to the suspension rheology. The first method uses the lubrication approximation to find the hydrodynamic stress and includes a short-range repulsive force between the particles while the second is a Stokesian dynamics simulation that calculates the full hydrodynamic stress in the suspension. We find that the decrease in the viscosity at moderate confinements has a significant contribution from both the

Invariant description of solutions of hydrodynamic-type systems in hodograph space: hydrodynamic surfaces

International Nuclear Information System (INIS)

Ferapontov, E.V.

2002-01-01

Hydrodynamic surfaces are solutions of hydrodynamic-type systems viewed as non-parametrized submanifolds of the hodograph space. We propose an invariant differential-geometric characterization of hydrodynamic surfaces by expressing the curvature form of the characteristic web in terms of the reciprocal invariants. (author)

Evaluation of Gas Phase Dispersion in Flotation under Predetermined Hydrodynamic Conditions

Science.gov (United States)

Młynarczykowska, Anna; Oleksik, Konrad; Tupek-Murowany, Klaudia

2018-03-01

Results of various investigations shows the relationship between the flotation parameters and gas distribution in a flotation cell. The size of gas bubbles is a random variable with a specific distribution. The analysis of this distribution is useful to make mathematical description of the flotation process. The flotation process depends on many variable factors. These are mainly occurrences like collision of single particle with gas bubble, adhesion of particle to the surface of bubble and detachment process. These factors are characterized by randomness. Because of that it is only possible to talk about the probability of occurence of one of these events which directly affects the speed of the process, thus a constant speed of flotation process. Probability of the bubble-particle collision in the flotation chamber with mechanical pulp agitation depends on the surface tension of the solution, air consumption, degree of pul aeration, energy dissipation and average feed particle size. Appropriate identification and description of the parameters of the dispersion of gas bubbles helps to complete the analysis of the flotation process in a specific physicochemical conditions and hydrodynamic for any raw material. The article presents the results of measurements and analysis of the gas phase dispersion by the size distribution of air bubbles in a flotation chamber under fixed hydrodynamic conditions. The tests were carried out in the Laboratory of Instrumental Methods in Department of Environmental Engineering and Mineral Processing, Faculty of Mining and Geoengineerin, AGH Univeristy of Science and Technology in Krakow.

Particle filters for object tracking: enhanced algorithm and efficient implementations

International Nuclear Information System (INIS)

Abd El-Halym, H.A.

2010-01-01

Object tracking and recognition is a hot research topic. In spite of the extensive research efforts expended, the development of a robust and efficient object tracking algorithm remains unsolved due to the inherent difficulty of the tracking problem. Particle filters (PFs) were recently introduced as a powerful, post-Kalman filter, estimation tool that provides a general framework for estimation of nonlinear/ non-Gaussian dynamic systems. Particle filters were advanced for building robust object trackers capable of operation under severe conditions (small image size, noisy background, occlusions, fast object maneuvers ..etc.). The heavy computational load of the particle filter remains a major obstacle towards its wide use.In this thesis, an Excitation Particle Filter (EPF) is introduced for object tracking. A new likelihood model is proposed. It depends on multiple functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modified the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. This modification is based on re-exciting the particles if their weights fall below a memorized weight value. The proposed enhanced PF is implemented in software and evaluated. Its results are compared with a single likelihood function PF tracker, Particle Swarm Optimization (PSO) tracker, a correlation tracker, as well as, an edge tracker. The experimental results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness, and occlusion compared with other methods Efficient novel hardware architectures of the Sample Important Re sample Filter (SIRF) and the EPF are implemented. Three novel hardware architectures of the SIRF for object tracking are introduced. The first architecture is a two-step sequential PF machine, where particle generation, weight calculation and normalization are carried out in parallel during the first step followed by a sequential re

Prediction of Tibial Rotation Pathologies Using Particle Swarm Optimization and K-Means Algorithms.

Science.gov (United States)

Sari, Murat; Tuna, Can; Akogul, Serkan

2018-03-28

The aim of this article is to investigate pathological subjects from a population through different physical factors. To achieve this, particle swarm optimization (PSO) and K-means (KM) clustering algorithms have been combined (PSO-KM). Datasets provided by the literature were divided into three clusters based on age and weight parameters and each one of right tibial external rotation (RTER), right tibial internal rotation (RTIR), left tibial external rotation (LTER), and left tibial internal rotation (LTIR) values were divided into three types as Type 1, Type 2 and Type 3 (Type 2 is non-pathological (normal) and the other two types are pathological (abnormal)), respectively. The rotation values of every subject in any cluster were noted. Then the algorithm was run and the produced values were also considered. The values of the produced algorithm, the PSO-KM, have been compared with the real values. The hybrid PSO-KM algorithm has been very successful on the optimal clustering of the tibial rotation types through the physical criteria. In this investigation, Type 2 (pathological subjects) is of especially high predictability and the PSO-KM algorithm has been very successful as an operation system for clustering and optimizing the tibial motion data assessments. These research findings are expected to be very useful for health providers, such as physiotherapists, orthopedists, and so on, in which this consequence may help clinicians to appropriately designing proper treatment schedules for patients.

An energy stable algorithm for a quasi-incompressible hydrodynamic phase-field model of viscous fluid mixtures with variable densities and viscosities

Science.gov (United States)

Gong, Yuezheng; Zhao, Jia; Wang, Qi

2017-10-01

A quasi-incompressible hydrodynamic phase field model for flows of fluid mixtures of two incompressible viscous fluids of distinct densities and viscosities is derived by using the generalized Onsager principle, which warrants the variational structure, the mass conservation and energy dissipation law. We recast the model in an equivalent form and discretize the equivalent system in space firstly to arrive at a time-dependent ordinary differential and algebraic equation (DAE) system, which preserves the mass conservation and energy dissipation law at the semi-discrete level. Then, we develop a temporal discretization scheme for the DAE system, where the mass conservation and the energy dissipation law are once again preserved at the fully discretized level. We prove that the fully discretized algorithm is unconditionally energy stable. Several numerical examples, including drop dynamics of viscous fluid drops immersed in another viscous fluid matrix and mixing dynamics of binary polymeric solutions, are presented to show the convergence property as well as the accuracy and efficiency of the new scheme.

Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

International Nuclear Information System (INIS)

An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

2013-01-01

This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

A constriction factor based particle swarm optimisation algorithm to solve the economic dispatch problem including losses

Energy Technology Data Exchange (ETDEWEB)

Young, Steven; Montakhab, Mohammad; Nouri, Hassan

2011-07-15

Economic dispatch (ED) is one of the most important problems to be solved in power generation as fractional percentage fuel reductions represent significant cost savings. ED wishes to optimise the power generated by each generating unit in a system in order to find the minimum operating cost at a required load demand, whilst ensuring both equality and inequality constraints are met. For the process of optimisation, a model must be created for each generating unit. The particle swarm optimisation technique is an evolutionary computation technique with one of the most powerful methods for solving global optimisation problems. The aim of this paper is to add in a constriction factor to the particle swarm optimisation algorithm (CFBPSO). Results show that the algorithm is very good at solving the ED problem and that CFBPSO must be able to work in a practical environment and so a valve point effect with transmission losses should be included in future work.

A new multiple robot path planning algorithm: dynamic distributed particle swarm optimization.

Science.gov (United States)

Ayari, Asma; Bouamama, Sadok

2017-01-01

Multiple robot systems have become a major study concern in the field of robotic research. Their control becomes unreliable and even infeasible if the number of robots increases. In this paper, a new dynamic distributed particle swarm optimization (D 2 PSO) algorithm is proposed for trajectory path planning of multiple robots in order to find collision-free optimal path for each robot in the environment. The proposed approach consists in calculating two local optima detectors, LOD pBest and LOD gBest . Particles which are unable to improve their personal best and global best for predefined number of successive iterations would be replaced with restructured ones. Stagnation and local optima problems would be avoided by adding diversity to the population, without losing the fast convergence characteristic of PSO. Experiments with multiple robots are provided and proved effectiveness of such approach compared with the distributed PSO.

Resolving collisions in Stokes suspensions with an efficient and stable potential-free constrained optimization algorithm

Science.gov (United States)

Yan, Wen; Corona, Eduardo; Veerapaneni, Shravan; Shelley, Michael

2017-11-01

A common challenge in simulating dense suspension of rigid particles in Stokes flow is the numerical instability that arises due to particle collisions. To overcome this problem, often a strong repulsive potential between particles is prescribed. This in turn leads to numerical stiffness and dramatic reduction in stable time-step sizes. In this work, we eliminate such stiffness by introducing contact constraints explicitly and solving the hydrodynamic equations in tandem with a linear complementarity problem with inequality constraints. The Newton's third law of the collision force is explicitly guaranteed to allow consistent calculation of collision stresses. Efficient parallelization for shared-memory and distributed-memory architectures is also implemented. This method can be coupled to any Stokes hydrodynamics solver for particles with various shapes and allows us to simulate 104 107 spheres on a laptop, depending on the cost of the Stokes hydrodynamics solver. We demonstrate its performance on a range of applications from active matter to multi-physics problems.

Numerical study of a stochastic particle algorithm solving a multidimensional population balance model for high shear granulation

International Nuclear Information System (INIS)

Braumann, Andreas; Kraft, Markus; Wagner, Wolfgang

2010-01-01

This paper is concerned with computational aspects of a multidimensional population balance model of a wet granulation process. Wet granulation is a manufacturing method to form composite particles, granules, from small particles and binders. A detailed numerical study of a stochastic particle algorithm for the solution of a five-dimensional population balance model for wet granulation is presented. Each particle consists of two types of solids (containing pores) and of external and internal liquid (located in the pores). Several transformations of particles are considered, including coalescence, compaction and breakage. A convergence study is performed with respect to the parameter that determines the number of numerical particles. Averaged properties of the system are computed. In addition, the ensemble is subdivided into practically relevant size classes and analysed with respect to the amount of mass and the particle porosity in each class. These results illustrate the importance of the multidimensional approach. Finally, the kinetic equation corresponding to the stochastic model is discussed.

Hydrodynamics of circulating and bubbling fluidized beds

International Nuclear Information System (INIS)

Gidaspow, D.P.; Tsuo, Y.P.; Ding, J.

1991-01-01

This paper reports that a review of modeling of the hydrodynamics of fluidization of bubbling beds showed that inviscid two-fluid models were able to predict a great deal of the behavior of bubbling beds because the dominant mechanism of energy dissipation is the drag between the particles and the fluid. The formation, the growth and the bursting of bubbles were predicted. Predicted wall-to-bed heat transfer coefficients and velocity profiles of jets agreed with measurements. Time average porosity distributions agreed with measurements done using gamma-ray densitometers without the use of any adjustable parameters. However, inviscid models could not correctly predict rates of erosion around tubes immersed into fluidized beds. To correctly model such behavior, granular stresses involving solids viscosity were added into the computer model. This viscosity arises due to random collision of particles. Several models fro this viscosity were investigated and the results compared to measurements of solids distributions in two-dimensional beds and to particle velocities reported in the literature. While in the case of bubbling beds the solids viscosity plays the role of a correction, modeling of a circulating fluidized bed (CFB) without a viscosity is not possible. Recent experimental data obtained at IIT and at IGT show that in CFB the solids viscous dissipation is responsible for as much as half of the pressure drop. From such measurement, solids viscosities were computed. These were used in the two fluid hydrodynamic model, to predict radial solids distributions and solids velocities which matched the experimental distributions. Most important, the model predicted cluster formation and transient internal circulation which is responsible for the favorable characteristics of CFBs, such as good wall-to-bed heat transfer. Video tape movies of computations compared favorably with high speed movies of the experiments

Design of application specific long period waveguide grating filters using adaptive particle swarm optimization algorithms

International Nuclear Information System (INIS)

Semwal, Girish; Rastogi, Vipul

2014-01-01

We present design optimization of wavelength filters based on long period waveguide gratings (LPWGs) using the adaptive particle swarm optimization (APSO) technique. We demonstrate optimization of the LPWG parameters for single-band, wide-band and dual-band rejection filters for testing the convergence of APSO algorithms. After convergence tests on the algorithms, the optimization technique has been implemented to design more complicated application specific filters such as erbium doped fiber amplifier (EDFA) amplified spontaneous emission (ASE) flattening, erbium doped waveguide amplifier (EDWA) gain flattening and pre-defined broadband rejection filters. The technique is useful for designing and optimizing the parameters of LPWGs to achieve complicated application specific spectra. (paper)

Modeling of pedestrian evacuation based on the particle swarm optimization algorithm

Science.gov (United States)

Zheng, Yaochen; Chen, Jianqiao; Wei, Junhong; Guo, Xiwei

2012-09-01

By applying the evolutionary algorithm of Particle Swarm Optimization (PSO), we have developed a new pedestrian evacuation model. In the new model, we first introduce the local pedestrian’s density concept which is defined as the number of pedestrians distributed in a certain area divided by the area. Both the maximum velocity and the size of a particle (pedestrian) are supposed to be functions of the local density. An attempt to account for the impact consequence between pedestrians is also made by introducing a threshold of injury into the model. The updating rule of the model possesses heterogeneous spatial and temporal characteristics. Numerical examples demonstrate that the model is capable of simulating the typical features of evacuation captured by CA (Cellular Automata) based models. As contrast to CA-based simulations, in which the velocity (via step size) of a pedestrian in each time step is a constant value and limited in several directions, the new model is more flexible in describing pedestrians’ velocities since they are not limited in discrete values and directions according to the new updating rule.

Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

Science.gov (United States)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

A Particle Swarm Optimization Algorithm for Neural Networks in Recognition of Maize Leaf Diseases

Directory of Open Access Journals (Sweden)

Zhiyong ZHANG

2014-03-01

Full Text Available The neural networks have significance on recognition of crops disease diagnosis? but it has disadvantage of slow convergent speed and shortcoming of local optimum. In order to identify the maize leaf diseases by using machine vision more accurately, we propose an improved particle swarm optimization algorithm for neural networks. With the algorithm, the neural network property is improved. It reasonably confirms threshold and connection weight of neural network, and improves capability of solving problems in the image recognition. At last, an example of the emulation shows that neural network model based on recognizes significantly better than without optimization. Model accuracy has been improved to a certain extent to meet the actual needs of maize leaf diseases recognition.

Hydrodynamic property of the cytoplasm is sufficient to mediate cytoplasmic streaming in the Caenorhabiditis elegans embryo

Science.gov (United States)

Niwayama, Ritsuya; Shinohara, Kyosuke; Kimura, Akatsuki

2011-01-01

Cytoplasmic streaming is a type of intracellular transport widely seen in nature. Cytoplasmic streaming in Caenorhabditis elegans at the one-cell stage is bidirectional; the flow near the cortex (“cortical flow”) is oriented toward the anterior, whereas the flow in the central region (“cytoplasmic flow”) is oriented toward the posterior. Both cortical flow and cytoplasmic flow depend on non-muscle-myosin II (NMY-2), which primarily localizes in the cortex. The manner in which NMY-2 proteins drive cytoplasmic flow in the opposite direction from remote locations has not been fully understood. In this study, we demonstrated that the hydrodynamic properties of the cytoplasm are sufficient to mediate the forces generated by the cortical myosin to drive bidirectional streaming throughout the cytoplasm. We quantified the flow velocities of cytoplasmic streaming using particle image velocimetry (PIV) and conducted a three-dimensional hydrodynamic simulation using the moving particle semiimplicit method. Our simulation quantitatively reconstructed the quantified flow velocity distribution resolved through PIV analysis. Furthermore, our PIV analyses detected microtubule-dependent flows during the pronuclear migration stage. These flows were reproduced via hydrodynamic interactions between moving pronuclei and the cytoplasm. The agreement of flow dynamics in vivo and in simulation indicates that the hydrodynamic properties of the cytoplasm are sufficient to mediate cytoplasmic streaming in C. elegans embryos. PMID:21730185

Interface tracking for 2D hydrodynamics

International Nuclear Information System (INIS)

Bezard, Fabienne

1997-01-01

The aim of this work is to explore new methods to numerically simulate the evolution of interfaces between immiscible fluids in the context of the dynamics of compressible and non-viscous fluids. The methods currently available, to our knowledge, to deal with this type of problem are based on the Lagrange coordinates (that is to say, that follow the material in its displacements) or on the Euler coordinates (fixed during the time). In the case of Eulerian coordinates, the simplest methods involve so-called 'mixing' meshes (that is, containing several fluids). The study that is presented is based on an Eulerian method with Lagrangian interface tracking. This avoids the introduction of any model of mesh of mixture. This method combines some advantages of the previously mentioned methods, notably the precision of the Lagrangian follow-up and the robustness of the Eulerian schemes. This report describes only the algorithms of displacement and regularization of the interface, by clearly presenting the geometry around the interface. These algorithms will then be coupled with the resolution of two-dimensional hydrodynamic equations to solve multi-fluid problems. Some numerical results are proposed to illustrate the good behavior of the interface tracking algorithm [fr

Effects of salinity and particle concentration on sediment hydrodynamics and critical bed-shear-stress for erosion of fine grained sediments used in wetland restoration projects

Science.gov (United States)

Ghose-Hajra, M.; McCorquodale, A.; Mattson, G.; Jerolleman, D.; Filostrat, J.

2015-03-01

Sea-level rise, the increasing number and intensity of storms, oil and groundwater extraction, and coastal land subsidence are putting people and property at risk along Louisiana's coast, with major implications for human safety and economic health of coastal areas. A major goal towards re-establishing a healthy and sustainable coastal ecosystem has been to rebuild Louisiana's disappearing wetlands with fine grained sediments that are dredged or diverted from nearby rivers, channels and lakes to build land in open water areas. A thorough geo-hydrodynamic characterization of the deposited sediments is important in the correct design and a more realistic outcome assessment of the long-term performance measures for ongoing coastal restoration projects. This paper evaluates the effects of salinity and solid particle concentration on the re-suspension characteristics of fine-grained dredged sediments obtained from multiple geographic locations along the Gulf coast. The critical bed-shear-stress for erosion has been evaluated as a function of sedimentation time. The sediment hydrodynamic properties obtained from the laboratory testing were used in a numerical coastal sediment distribution model to aid in evaluating sediment diversions from the Mississippi River into Breton Sound and Barataria Bay.

Effects of salinity and particle concentration on sediment hydrodynamics and critical bed-shear-stress for erosion of fine grained sediments used in wetland restoration projects

Directory of Open Access Journals (Sweden)

M. Ghose-Hajra

2015-03-01

Full Text Available Sea-level rise, the increasing number and intensity of storms, oil and groundwater extraction, and coastal land subsidence are putting people and property at risk along Louisiana’s coast, with major implications for human safety and economic health of coastal areas. A major goal towards re-establishing a healthy and sustainable coastal ecosystem has been to rebuild Louisiana’s disappearing wetlands with fine grained sediments that are dredged or diverted from nearby rivers, channels and lakes to build land in open water areas. A thorough geo-hydrodynamic characterization of the deposited sediments is important in the correct design and a more realistic outcome assessment of the long-term performance measures for ongoing coastal restoration projects. This paper evaluates the effects of salinity and solid particle concentration on the re-suspension characteristics of fine-grained dredged sediments obtained from multiple geographic locations along the Gulf coast. The critical bed-shear-stress for erosion has been evaluated as a function of sedimentation time. The sediment hydrodynamic properties obtained from the laboratory testing were used in a numerical coastal sediment distribution model to aid in evaluating sediment diversions from the Mississippi River into Breton Sound and Barataria Bay.

Hydrodynamic Equations for Flocking Models without Velocity Alignment

Science.gov (United States)