11,204 research outputs found
A Change Support Model for Distributed Collaborative Work
Distributed collaborative software development tends to make artifacts and
decisions inconsistent and uncertain. We try to solve this problem by providing
an information repository to reflect the state of works precisely, by managing
the states of artifacts/products made through collaborative work, and the
states of decisions made through communications. In this paper, we propose
models and a tool to construct the artifact-related part of the information
repository, and explain the way to use the repository to resolve
inconsistencies caused by concurrent changes of artifacts. We first show the
model and the tool to generate the dependency relationships among UML model
elements as content of the information repository. Next, we present the model
and the method to generate change support workflows from the information
repository. These workflows give us the way to efficiently modify the
change-related artifacts for each change request. Finally, we define
inconsistency patterns that enable us to be aware of the possibility of
inconsistency occurrences. By combining this mechanism with version control
systems, we can make changes safely. Our models and tool are useful in the
maintenance phase to perform changes safely and efficiently.Comment: 10 pages, 13 figures, 4 table
Accurate lubrication corrections for spherical and non-spherical particles in discretized fluid simulations
Discretized fluid solvers coupled to a Newtonian dynamics method are a
popular tool to study suspension flow. As any simulation technique with finite
resolution, the lattice Boltzmann method, when coupled to discrete particles
using the momentum exchange method, resolves the diverging lubrication
interactions between surfaces near contact only insufficiently. For spheres, it
is common practice to account for surface-normal lubrication forces by means of
an explicit correction term. A method that additionally covers all further
singular interactions for spheres is present in the literature as well as a
link-based approach that allows for more general shapes but does not capture
non-normal interactions correctly. In this paper, lattice-independent
lubrication corrections for aspherical particles are outlined, taking into
account all leading divergent interaction terms. An efficient implementation
for arbitrary spheroids is presented and compared to purely normal and
link-based models. Good consistency with Stokesian dynamics simulations of
spheres is found. The non-normal interactions affect the viscosity of
suspensions of spheres at volume fractions \Phi >= 0.3 but already at \Phi >=
0.2 for spheroids. Regarding shear-induced diffusion of spheres, a distinct
effect is found at 0.1 <= \Phi <= 0.5 and even increasing the resolution of the
radius to 8 lattice units is no substitute for an accurate modeling of
non-normal interactions.Comment: 19 pages, 10 figure
From patterned response dependency to structured covariate dependency: categorical-pattern-matching
Data generated from a system of interest typically consists of measurements
from an ensemble of subjects across multiple response and covariate features,
and is naturally represented by one response-matrix against one
covariate-matrix. Likely each of these two matrices simultaneously embraces
heterogeneous data types: continuous, discrete and categorical. Here a matrix
is used as a practical platform to ideally keep hidden dependency among/between
subjects and features intact on its lattice. Response and covariate dependency
is individually computed and expressed through mutliscale blocks via a newly
developed computing paradigm named Data Mechanics. We propose a categorical
pattern matching approach to establish causal linkages in a form of information
flows from patterned response dependency to structured covariate dependency.
The strength of an information flow is evaluated by applying the combinatorial
information theory. This unified platform for system knowledge discovery is
illustrated through five data sets. In each illustrative case, an information
flow is demonstrated as an organization of discovered knowledge loci via
emergent visible and readable heterogeneity. This unified approach
fundamentally resolves many long standing issues, including statistical
modeling, multiple response, renormalization and feature selections, in data
analysis, but without involving man-made structures and distribution
assumptions. The results reported here enhance the idea that linking patterns
of response dependency to structures of covariate dependency is the true
philosophical foundation underlying data-driven computing and learning in
sciences.Comment: 32 pages, 10 figures, 3 box picture
Methodology for tidal turbine representation in ocean circulation model
The present method proposes the use and adaptation of ocean circulation models as an assessment tool framework for tidal current turbine (TCT) array layout optimization. By adapting both momentum and turbulence transport equations of an existing model, the present TCT representation method is proposed to extend the actuator disc concept to 3-D large-scale ocean circulation models. Through the reproduction of experimental flume tests and grid dependency tests, this method has shown its numerical coherence as well as its ability to simulate accurately both momentum and turbulent turbine-induced perturbations in both near and far wakes in a relatively short period of computation time. Consequently the present TCT representation method is a very promising basis for the development of a TCT array layout optimization tool
Effects of near wall modeling in the Improved-Delayed-Detached-Eddy-Simulation (IDDES) methodology
The present study aims to assess the effects of two different underlying RANS models on overall behavior of the IDDES methodology when applied to different flow configurations ranging from fully attached (plane channel flow) to separated flows (periodic hill flow). This includes investigating prediction accuracy of first and second order statistics, response to grid refinement, grey area dynamics and triggering mechanism. Further, several criteria have been investigated to assess reliability and quality of the methodology when operating in scale resolving mode. It turns out that irrespective of the near wall modeling strategy, the IDDES methodology does not satisfy all criteria required to make this methodology reliable when applied to various flow configurations at different Reynolds numbers with different grid resolutions. Further, it is found that using more advanced underlying RANS model to improve prediction accuracy of the near wall dynamics results in extension of the grey area, which may delay the transition to scale resolving mode. This systematic study for attached and separated flows suggests that the shortcomings of IDDES methodology mostly lie in inaccurate prediction of the dynamics inside the grey area and demands further investigation in this direction to make this methodology capable of dealing with different flow situations reliably
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