1,720,958 research outputs found
Identification of a Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work deals with the statistical identification of a phase field model [1] for brittle fracture in random heterogeneous elastic media. Such a phase field model is typically parameterized by the critical energy release rate (or fracture toughness) and the regularization length (describing the actual width of the smeared crack representation) which are considered as deterministic and homogeneous parameters to be identified. We consider a random heterogeneous material for which the apparent elasticity properties at a given mesoscale are modeled as a non-Gaussian tensor-valued random field [2].The identification of the fracture properties of a cracking heterogeneous elastic material requires solving a challenging statistical inverse problem. An identification method with an ad hoc cost function is specifically developed for solving this statistical inverse problem. The performances of the proposed identification method are illustrated on a classical benchmark problem for brittle fracture.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media: Forward Numerical Simulations and Sensitivity Analysis
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work addresses the forward numerical simulation of a phase field model [1] for brittle fracture in random heterogeneous elastic materials. Such a phase field model is classically parameterized by the fracture toughness (or critical energy release rate in the sense of Griffith) and the regularization parameter (corresponding to the actual width of the smeared/diffusivecrack representation) which are considered as deterministic and homogeneous parameters. At a given mesoscale, the material is considered as random and heterogeneous with apparent elasticity properties. Various classes of stochastic models and associated random generators for non-Gaussian tensor-valued random elasticity fields with statistical fluctuations in a given material symmetry class and in the (purely) anisotropic class have been proposed [2]. In the present work, we focus on two particular classes of stochastic models, namely (i) the class of random elasticity fields exhibiting almost surely isotropic symmetry properties, and (ii) the class of purely anisotropic random elasticity fields with an isotropic mean elasticity field and anisotropic statistical fluctuations (around the isotropic mean function). A sensitivity analysis is carried out to study the influence of the (hyper)parameters of the aforementioned stochastic models on some statistical quantities of interest related to the force-displacement curve for identification purposes. The proposed approach is illustrated on a classical benchmark problem for brittle fracture, namely a two-dimensional single-edge notched/cracked specimen under pure shear loading.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media: Forward Numerical Simulations and Sensitivity Analysis
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work addresses the forward numerical simulation of a phase field model [1] for brittle fracture in random heterogeneous elastic materials. Such a phase field model is classically parameterized by the fracture toughness (or critical energy release rate in the sense of Griffith) and the regularization parameter (corresponding to the actual width of the smeared/diffusivecrack representation) which are considered as deterministic and homogeneous parameters. At a given mesoscale, the material is considered as random and heterogeneous with apparent elasticity properties. Various classes of stochastic models and associated random generators for non-Gaussian tensor-valued random elasticity fields with statistical fluctuations in a given material symmetry class and in the (purely) anisotropic class have been proposed [2]. In the present work, we focus on two particular classes of stochastic models, namely (i) the class of random elasticity fields exhibiting almost surely isotropic symmetry properties, and (ii) the class of purely anisotropic random elasticity fields with an isotropic mean elasticity field and anisotropic statistical fluctuations (around the isotropic mean function). A sensitivity analysis is carried out to study the influence of the (hyper)parameters of the aforementioned stochastic models on some statistical quantities of interest related to the force-displacement curve for identification purposes. The proposed approach is illustrated on a classical benchmark problem for brittle fracture, namely a two-dimensional single-edge notched/cracked specimen under pure shear loading.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
Identification of a Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work deals with the statistical identification of a phase field model [1] for brittle fracture in random heterogeneous elastic media. Such a phase field model is typically parameterized by the critical energy release rate (or fracture toughness) and the regularization length (describing the actual width of the smeared crack representation) which are considered as deterministic and homogeneous parameters to be identified. We consider a random heterogeneous material for which the apparent elasticity properties at a given mesoscale are modeled as a non-Gaussian tensor-valued random field [2].The identification of the fracture properties of a cracking heterogeneous elastic material requires solving a challenging statistical inverse problem. An identification method with an ad hoc cost function is specifically developed for solving this statistical inverse problem. The performances of the proposed identification method are illustrated on a classical benchmark problem for brittle fracture.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
Identification of a Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work deals with the statistical identification of a phase field model [1] for brittle fracture in random heterogeneous elastic media. Such a phase field model is typically parameterized by the critical energy release rate (or fracture toughness) and the regularization length (describing the actual width of the smeared crack representation) which are considered as deterministic and homogeneous parameters to be identified. We consider a random heterogeneous material for which the apparent elasticity properties at a given mesoscale are modeled as a non-Gaussian tensor-valued random field [2].The identification of the fracture properties of a cracking heterogeneous elastic material requires solving a challenging statistical inverse problem. An identification method with an ad hoc cost function is specifically developed for solving this statistical inverse problem. The performances of the proposed identification method are illustrated on a classical benchmark problem for brittle fracture.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
Phase Field Model for Brittle Fracture in Random Heterogeneous Elastic Media: Forward Numerical Simulations and Sensitivity Analysis
No full textInternational audienceWithin the framework of linear elasticity theory and fracture mechanics, this work addresses the forward numerical simulation of a phase field model [1] for brittle fracture in random heterogeneous elastic materials. Such a phase field model is classically parameterized by the fracture toughness (or critical energy release rate in the sense of Griffith) and the regularization parameter (corresponding to the actual width of the smeared/diffusivecrack representation) which are considered as deterministic and homogeneous parameters. At a given mesoscale, the material is considered as random and heterogeneous with apparent elasticity properties. Various classes of stochastic models and associated random generators for non-Gaussian tensor-valued random elasticity fields with statistical fluctuations in a given material symmetry class and in the (purely) anisotropic class have been proposed [2]. In the present work, we focus on two particular classes of stochastic models, namely (i) the class of random elasticity fields exhibiting almost surely isotropic symmetry properties, and (ii) the class of purely anisotropic random elasticity fields with an isotropic mean elasticity field and anisotropic statistical fluctuations (around the isotropic mean function). A sensitivity analysis is carried out to study the influence of the (hyper)parameters of the aforementioned stochastic models on some statistical quantities of interest related to the force-displacement curve for identification purposes. The proposed approach is illustrated on a classical benchmark problem for brittle fracture, namely a two-dimensional single-edge notched/cracked specimen under pure shear loading.REFERENCES[1] J.-Y. Wu, V.P. Nguyen, C.T. Nguyen, D. Sutula, S. Sinaie, and S.P.A. Bordas. Chapter One - Phase-field modeling of fracture. volume 53 of Advances in Applied Mechanics, pages 1–183. Elsevier, 2020.[2] C. Soize. Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering, volume 47 of Interdisciplinary Applied Mathematics. Springer International Publishing, 1st edition, 2017
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
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
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