1,721,004 research outputs found
Neural networks weights related to "Super-resolution of turbulence with dynamics in the loss"
No full textA set of routines to train neural networks to perform super-resolution, without necessarily requiring high-resolution data, along with network weights used to generate figures in the publication "Super-resolution of turbulence with dynamics in the loss", (J. Page, Journal of Fluid Mechanics, accepted 2024).
Implementation wraps around the spectral version of JAX-CFD (https://github.com/google/jax-cfd). Neural networks are written in Keras using the JAX backend.
This dataset consists of a series of python scripts and .h5 files of network weights, organised into subdirectories:
code/ # scripts used to train and analyse the networks (python, requires installation of keras + JAX backend, JAX-CFD)
paper_weights/ # weights for the neural networks as documented in the paper.
# subdirectories here point to different Reynolds numbers (100, 1000) with weights at M = 16 and M = 32 coarse-graining
# an additional subdirectory includes networks trained with noisy data
Neural network weights are saved as .h5 files. An example script is included ("load_weights.py") to illustrate how to load into a model.Please see README file for details of directory structure, along with example scripts
Neural networks weights related to "Recurrent patterns as a basis for two-dimensional turbulence: predicting statistics from structures"
No full textThe dataset contains neural network weights (checkpointed in TensorFlow) for two deep-convolutional autoencoders designed to generate low-dimensional representations of snapshots of vorticity in two-dimensional turbulence. The models have the same architecture apart from the size of the inner-most "embedding" layer. Code to construct the model architecture is also included as a python script.
For details of loss function and training protocol please see associated publication "Recurrent patterns as a basis for two-dimensional turbulence: predicting statistics from structures" (accepted in PNAS, 2024)Details of each model included in the dataset are as follows:
- "weights_DNv7a05_Re40_m128_lr0.0005_epoch0498": Size of embedding space = 128. Model trained on 100000 vorticity snapshots at a Reynolds number of Re=40. Adam optimizer with a learning rate 10^{-5}.
- "weights_DNv7a5_Re100_m512_lr0.0005_epoch0478": : Size of embedding space = 512. Model trained on 100000 vorticity snapshots at a Reynolds number of Re=100. Adam optimizer with a learning rate 10^{-5}
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Bursting equilibria and travelling waves in Kolmogorov flow
No full textThis dataset contains equilibrium and travelling wave solutions for 2D Kolmogorov flow (monochromatically forced with wavenumber n=4) at a Reynolds number Re=40. These solutions are also documented in the manuscript “Revealing the state space of turbulence using machine learning” (in review) and have all been obtained from within intermittent bursting events.
Each solution is stored in a binary file containing a single record (a scalar vorticity field of dimension 128x128). Example python scripts are included which demonstrate how the files can be read and visualised
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Exact coherent structures in two-dimensional turbulence: computation, data-driven models and connections to inviscid dynamics
Get PDFExact coherent structures (ECSs), such as unstable periodic orbits (UPOs), travelling waves and heteroclinic connections, are postulated to shape and guide the trajectories of a turbulent flow. However, classical methods for finding and converging these objects struggle at high Reynolds numbers (Re) and are limited to statistically steady states. This thesis applies a combination of fluid simulation by differentiable flow solvers and gradient-based optimisation of scalar loss functions to improve upon and expand the application areas of these methods. The results reveal new understanding of naturally forming vortex crystals, the connections of Navier-Stokes ECSs to solutions of the inviscid Euler equation and the number of degrees of freedom required to represent weakly turbulent Kolmogorov flows. Firstly, we study vortex crystal configurations in rotating superfluids, which are observed experimentally to undergo a sequence of dissipative transitions through a series of metastable states en route to the free-energy minimising configuration. A systematic exploration of the free-energy landscape within a point-vortex approximation in the unbounded domain is achieved by the convergence of thousands of unique vortex crystals with numbers of vortices ranging from 10 to 30 using gradient based optimisation. We present new methods for computing homoclinic connections between crystals and non-dynamical energy-minimising pathways between states to investigate experimental observations of crystal transitions. As part of the search, new continuous families of vortex crystals arranged in double-ring configurations are discovered, which are often global minimisers of the free energy and become discrete sets of equal-energy solutions when the system is confined to a rotating disk. In a second problem, we investigate the ability for UPOs to reconstruct turbulent statistics away from the Re value at which they were converged, beginning with two large libraries of UPOs at Re = 40 and Re = 100 in two-dimensional Kolmogorov flow. Arclength continuation of these UPOs up to Re = O(1000) is performed, and the contribution of each UPO to the reconstruction of turbulent statistics is tracked as a function of Re. The analysis indicates that many branches rapidly become dynamically irrelevant, and we identify a subset of these ECSs which connect directly with solutions of the Euler equation in the inviscid limit. Motivated by this connection, the UPOs are labelled with representative exact solutions of the point vortex system, which are found via gradient-based optimisation. The point vortex UPOs are converged to model the dominant turbulent vortical interactions, and identify a wide range of simpler dynamical processes within the UPO collection, such as slowly-propagating crystals, tripolar structures and bound states. Finally, motivated by the recent interest in applying data-driven methods to two-dimensional turbulence, robust low-order representations of turbulent Kolmogorov flow are constructed using a deep convolutional autoencoder combined with a complete symmetry-reduction pre-processing step. These models are used to estimate a scaling of Re¹/³ for the dimensionality of the chaotic attractor, which is much weaker than the known bounds of Re⁴/³ on the global attractor. Low-dimensional visualisations demonstrate the partitioning of the autoencoder latent spaces into distinct dynamical regions, identifying multiple high dissipation `bursting' clusters and common routes towards and away from these bursting events at Re = 40. The libraries of UPOs in Kolmogorov flow are distinct from the chaotic attractor in these low-dimensional projections, in contrast to simpler projections in terms of summary statistics of the flow. This suggests that these solutions may not have belonged to the chaotic attractor, even before they were continued upwards in Re
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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