1,720,955 research outputs found
Gradient Information and Regularization for Gene Expression Programming to Develop Data-Driven Physics Closure Models
Full text linkLearning accurate numerical constants when developing algebraic models is a
known challenge for evolutionary algorithms, such as Gene Expression
Programming (GEP). This paper introduces the concept of adaptive symbols to the
GEP framework by Weatheritt and Sandberg (2016) to develop advanced physics
closure models. Adaptive symbols utilize gradient information to learn locally
optimal numerical constants during model training, for which we investigate two
types of nonlinear optimization algorithms. The second contribution of this
work is implementing two regularization techniques to incentivize the
development of implementable and interpretable closure models. We apply
regularization to ensure small magnitude numerical constants and devise a novel
complexity metric that supports the development of low complexity models via
custom symbol complexities and multi-objective optimization. This extended
framework is employed to four use cases, namely rediscovering Sutherland's
viscosity law, developing laminar flame speed combustion models and training
two types of fluid dynamics turbulence models. The model prediction accuracy
and the convergence speed of training are improved significantly across all of
the more and less complex use cases, respectively. The two regularization
methods are essential for developing implementable closure models and we
demonstrate that the developed turbulence models substantially improve
simulations over state-of-the-art models
Advancing Evolutionary Machine Learning Algorithms for Turbulence Model Development
No full text© 2023 Fabian WaschkowskiThe increasing availability of high-fidelity computational fluid dynamics (CFD) data and the success stories of machine learning algorithms in the last decade inspired the development of turbulence closure models from data. The goal of data-driven turbulence modeling is improving well-known shortcomings of traditional turbulence models, e.g. based on the linear eddy viscosity concept. On the path towards developing closure models that are applicable in industrial CFD solvers and robust for a wide variety of flow problems, the current data-driven frameworks have various limitations, including inaccurate modeling, deriving non-implementable models, optimization of only a single training objective and not considering the interaction of different closure models.
In this thesis, we advance the Gene Expression Programming (GEP) framework [1], which implements an evolutionary algorithm and derives algebraic closure models via symbolic regression, to eliminate these limitations. A new symbol type for GEP is introduced to exploit gradient information for developing algebraic models with accurate numerical constants. Regularization of the model constants and complexity is devised to incentivize the development of implementable and interpretable models. To this end, a novel model complexity metric based on symbol-specific complexity values is defined. Multi-objective optimization is realized via the NSGA-II algorithm [2] to balance the objectives of interest after training and explore the objective function space. The consistency between coupled closure models, e.g. the Reynolds stress and turbulent heat flux models, is considered via simultaneous multi-expression training.
These advanced capabilities are applied to several challenging flow problems. For a wall-mounted square cylinder flow, gradient-informed training and two regularization techniques yield accurate and implementable closure models, which result in turbulence kinetic energy predictions on level with high-fidelity simulation data. The state-of-the-art closure models for a periodic hill flow are outperformed by 10% and steps for further improvement are identified. For a vertical natural convection flow, multi-expression training achieves excellent mean flow predictions while multi-objective optimization allows the selection of physically plausible closure models. Lastly, the robustness of the derived closure models to a wide range of characteristic parameter values is demonstrated
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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