The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Francesco Miniati - One of the best experts on this subject based on the ideXlab platform.
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the matryoshka run a eulerian Refinement Strategy to study the statistics of turbulence in virialized cosmic structures
The Astrophysical Journal, 2014Co-Authors: Francesco MiniatiAbstract:We study the statistical properties of turbulence driven by structure formation in a massive merging galaxy cluster at redshift z = 0. The development of turbulence is ensured as the largest eddy turnover time is much shorter than the Hubble time independent of mass and redshift. We achieve a large dynamic range of spatial scales through a novel Eulerian Refinement Strategy where the cluster volume is refined with progressively finer uniform nested grids during gravitational collapse. This provides an unprecedented resolution of 7.3 h –1 kpc across the virial volume. The probability density functions of various velocity-derived quantities exhibit the features characteristic of fully developed compressible turbulence observed in dedicated periodic-box simulations. Shocks generate only 60% of the total vorticity within the R vir/3 region and 40% beyond that. We compute second- and third-order longitudinal and transverse structure functions for both solenoidal and compressional components in the cluster core, virial region, and beyond. The structure functions exhibit a well-defined inertial range of turbulent cascade. The injection scale is comparable to the virial radius but increases toward the outskirts. Within R vir/3, the spectral slope of the solenoidal component is close to Kolmogorov's, but for the compressional component is substantially steeper and close to Burgers's; the flow is mostly solenoidal and statistically rigorously, which is consistent with fully developed homogeneous and isotropic turbulence. Small-scale anisotropy appears due to numerical artifact. Toward the virial region, the flow becomes increasingly compressional, the structure functions become flatter, and modest genuine anisotropy appear particularly close to the injection scale. In comparison, mesh adaptivity based on Lagrangian Refinement and the same finest resolution leads to a lack of turbulent power on a small scales, an excess thereof on large scales, and unreliable density-weighted structure functions.
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the matryoshka run eulerian Refinement Strategy to study statistics of turbulence in virialized cosmic structures
arXiv: Cosmology and Nongalactic Astrophysics, 2013Co-Authors: Francesco MiniatiAbstract:We study the statistical properties of turbulence driven by structure formation in a massive merging galaxy cluster at z=0. The development of turbulence is ensured as the largest eddy turnover time is much shorter than the Hubble time independent of mass and redshift. We achieve a large dynamic range of spatial scales through a novel Eulerian Refinement Strategy where the cluster volume is refined with progressively finer uniform nested grids during gravitational collapse. This provides an unprecedented resolution of 7.3 h^{-1} kpc across the virial volume. The probability density functions of various velocity derived quantities exhibit the features characteristic of fully developed compressible turbulence observed in dedicated periodic-box simulations. Shocks generate only 60% of the total vorticity within \rvir/3 region and 40% beyond that. We compute second and third order, longitudinal and transverse, structure functions for both solenoidal and compressional components, in the cluster core, virial region and beyond. The structure functions exhibit a well defined inertial range. The injection scale is comparable to the virial radius but increases towards the outskirts. Within \rvir/3, the spectral slope of the solenoidal component is close to Kolmogorov's, but for the compressional component is substantially steeper and close to Burgers'; the flow is mostly solenoidal and statistically rigorously consistent with fully developed, homogeneous and isotropic turbulence. Small scale anisotropy appears due to numerical artifact. Towards the virial region, the flow becomes compressional, the structure functions flatter and modest genuine anisotropy appear. In comparison, mesh adaptivity based on Lagrangian Refinement and the same finest resolution, leads to lack of turbulent power on small scale and excess thereof on large scales, and unreliable density weighted structure functions.
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block structured adaptive mesh and time Refinement for hybrid hyperbolic n body systems
Journal of Computational Physics, 2007Co-Authors: Francesco Miniati, Phillip ColellaAbstract:We present a new numerical algorithm for the solution of coupled collisional and collisionless systems, based on the block structured adaptive mesh and time Refinement Strategy (AMR). We describe the issues associated with the discretization of the system equations and the synchronization of the numerical solution on the hierarchy of grid levels. We implement a code based on a higher order, conservative and directionally unsplit Godunov's method for hydrodynamics; a symmetric, time centered modified symplectic scheme for collisionless component; and a multilevel, multigrid relaxation algorithm for the elliptic equation coupling the two components. Numerical results that illustrate the accuracy of the code and the relative merit of various implemented schemes are also presented.
Chinwan Chung - One of the best experts on this subject based on the ideXlab platform.
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heuristic approach for early separated filter and Refinement Strategy in spatial query optimization
Journal of Systems and Software, 2002Co-Authors: Hohyun Park, Hyungju Cho, Chinwan ChungAbstract:Recently, we proposed an optimization Strategy for spatial and non-spatial mixed queries. In the Strategy, the filter step and the Refinement step of a spatial operator are regarded as individual algebraic operators, and are early separated at the algebraic level by the query optimizer. By doing so, the optimizer using the Strategy could generate more diverse and efficient plans than the traditional optimizer. We called this optimization Strategy the Early Separated Filter And Refinement (ESFAR).In this paper, we improved the cost model of the ESFAR optimizer considering the real life environment such as the LRU buffer, the clustering of the dataset, and the selectivity of the real data distribution. And we conducted a new experiment for ESFAR by comparing the optimization result generated by the new cost model and the actual execution result using real data. The experimental result showed that our cost model is accurate and our ESFAR optimizer estimates the costs of execution plans well.Since the ESFAR Strategy has more operators and more rules than the traditional one, it consumes more optimization time. In this paper, we apply two existing heuristic algorithms, the iterative improvement (II) and the simulated annealing (SA), to the ESFAR optimizer. Additionally we propose a new heuristic algorithm to find a good initial state of II and SA. Through experiments, we show that the II and SA algorithms in the ESFAR Strategy find a good sub-optimal plan in reasonable time. Mostly the heuristic algorithms find a lower cost plan in less time than the optimal plan generated by the traditional optimizer Especially the II algorithm with the initial state heuristic rapidly finds a plan of a high quality.
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spatial query optimization utilizing early separated filter and Refinement Strategy
Information Systems, 2000Co-Authors: Hohyun Park, Yongju Lee, Chinwan ChungAbstract:Abstract Due to the high complexity and large volume of spatial data, a spatial query is usually processed in two steps, called the filter step and the Refinement step . However, the two-step processing of the spatial query has been considered locally in one spatial predicate evaluation at the query execution level. This paper presents query optimization strategies which exploit the two-step processing of a spatial query at the query optimization level. The first Strategy involves the separation of filter and Refinement steps not in the query execution phase but in the query optimization phase. As the second Strategy, several Refinement operations can be combined in processing a complex query if they were already separated, and as the third Strategy several filter operations can also be combined. We call the optimization technique utilizing these strategies the Early Separated Filter And Refinement (ESFAR). This paper also presents an algebra, which is called the Intermediate Spatial Object Algebra (ISOA), and optimization rules for ESFAR. Through experiments using real data, we compare the ESFAR optimization technique with a traditional optimization technique which does not separate filter and Refinement steps from the query optimization phase. The experimental results show that the ESFAR optimization technique generates more efficient query execution plans than the traditional one in many cases.
W Rachowicz - One of the best experts on this subject based on the ideXlab platform.
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an anisotropic h type mesh Refinement Strategy
Computer Methods in Applied Mechanics and Engineering, 1993Co-Authors: W RachowiczAbstract:Abstract An anisotropic h-type mesh Refinement Strategy for finite element approximations is presented. The Strategy consists of subsecting quadrilateral elements in one of two possible directions. The decision which elements should be subsected and in which direction is based on minimization of interpolation errors. The method is especially suitable for approximate solutions which in some regions display almost one-dimensional behavior, for instance solutions with boundary layers.
Hohyun Park - One of the best experts on this subject based on the ideXlab platform.
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heuristic approach for early separated filter and Refinement Strategy in spatial query optimization
Journal of Systems and Software, 2002Co-Authors: Hohyun Park, Hyungju Cho, Chinwan ChungAbstract:Recently, we proposed an optimization Strategy for spatial and non-spatial mixed queries. In the Strategy, the filter step and the Refinement step of a spatial operator are regarded as individual algebraic operators, and are early separated at the algebraic level by the query optimizer. By doing so, the optimizer using the Strategy could generate more diverse and efficient plans than the traditional optimizer. We called this optimization Strategy the Early Separated Filter And Refinement (ESFAR).In this paper, we improved the cost model of the ESFAR optimizer considering the real life environment such as the LRU buffer, the clustering of the dataset, and the selectivity of the real data distribution. And we conducted a new experiment for ESFAR by comparing the optimization result generated by the new cost model and the actual execution result using real data. The experimental result showed that our cost model is accurate and our ESFAR optimizer estimates the costs of execution plans well.Since the ESFAR Strategy has more operators and more rules than the traditional one, it consumes more optimization time. In this paper, we apply two existing heuristic algorithms, the iterative improvement (II) and the simulated annealing (SA), to the ESFAR optimizer. Additionally we propose a new heuristic algorithm to find a good initial state of II and SA. Through experiments, we show that the II and SA algorithms in the ESFAR Strategy find a good sub-optimal plan in reasonable time. Mostly the heuristic algorithms find a lower cost plan in less time than the optimal plan generated by the traditional optimizer Especially the II algorithm with the initial state heuristic rapidly finds a plan of a high quality.
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spatial query optimization utilizing early separated filter and Refinement Strategy
Information Systems, 2000Co-Authors: Hohyun Park, Yongju Lee, Chinwan ChungAbstract:Abstract Due to the high complexity and large volume of spatial data, a spatial query is usually processed in two steps, called the filter step and the Refinement step . However, the two-step processing of the spatial query has been considered locally in one spatial predicate evaluation at the query execution level. This paper presents query optimization strategies which exploit the two-step processing of a spatial query at the query optimization level. The first Strategy involves the separation of filter and Refinement steps not in the query execution phase but in the query optimization phase. As the second Strategy, several Refinement operations can be combined in processing a complex query if they were already separated, and as the third Strategy several filter operations can also be combined. We call the optimization technique utilizing these strategies the Early Separated Filter And Refinement (ESFAR). This paper also presents an algebra, which is called the Intermediate Spatial Object Algebra (ISOA), and optimization rules for ESFAR. Through experiments using real data, we compare the ESFAR optimization technique with a traditional optimization technique which does not separate filter and Refinement steps from the query optimization phase. The experimental results show that the ESFAR optimization technique generates more efficient query execution plans than the traditional one in many cases.
Marie Postel - One of the best experts on this subject based on the ideXlab platform.
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adaptive mesh Refinement Strategy for a non conservative transport problem
Mathematical Modelling and Numerical Analysis, 2014Co-Authors: Benjamin Aymard, Frederique Clement, Marie PostelAbstract:Long time simulations of transport equations raise computational challenges since they require both a large domain of calculation and sufficient accuracy. It is therefore advantageous, in terms of computational costs, to use a time varying adaptive mesh, with small cells in the region of interest and coarser cells where the solution is smooth. Biological models involving cell dynamics fall for instance within this framework and are often non conservative to account for cell division. In that case the threshold controlling the spatial adaptivity may have to be time-dependent in order to keep up with the progression of the solution. In this article we tackle the difficulties arising when applying a Multiresolution method to a transport equation with discontinuous fluxes modeling localized mitosis. The analysis of the numerical method is performed on a simplified model and numerical scheme. An original threshold Strategy is proposed and validated thanks to extensive numerical tests. It is then applied to a biological model in both cases of distributed and localized mitosis.