1,720,965 research outputs found
Indentation and Puncturing of Pristine and Flawed Soft Membranes
No full textThis paper investigates the mechanical behavior of soft elastomeric membranes under indentation by a rigid spherical object, with a particular focus on the failure mechanisms leading to puncture. The study examines both pristine membranes and those with pre-existing flaws, such as cracks, to explore how these imperfections affect the mechanical response and failure characteristics. An analytical axisymmetric model, based on a nonlinear solution for a hyperelastic, incompressible membrane, is presented. The prediction of the model are validated with experimental data obtained from indentation tests on silicone membranes. The study considers both stretch-based and energy-based criteria for fracture, providing insight into the conditions necessary for membrane failure and crack propagation
Bayesian-based model updating using natural frequency data for historic masonry towers
No full textModel updating procedures are commonly used to identify numerical models of a structure to be subsequently used for reliable assessment of its behaviour under environmental loads. In the case of historic masonry buildings, the uncertainties that are involved in the knowledge process (material properties, geometry, boundary conditions, etc.) can severely affect the matching between the experimental data and the corresponding model output. To account for the different sources of uncertainties that are involved in the model updating procedure for historic confined masonry towers, this paper proposes an application of the Bayesian paradigm. Effects of parameter uncertainty, observation errors and model inadequacy are explored by comparing the output of the numerical model against real measured modal data. The proposed methodology aims at obtaining the posterior distribution of unknown quantities to estimate their uncertainty and to identify values of the parameters to be used in the numerical model for subsequent analyses. The comparison among the updated distributions related to different initial probabilistic modelling assumptions (prior distributions, measurement errors and modelling uncertainties) shows significant improvements of the predictive capabilities with a considerable reduction of the initial uncertainties, which confirm the potential of the proposed approach
Approximate Bayesian Computation for structural identification of ancient tie-rods using noisy modal data
No full textMasonry arches and vaults are common historic structural elements that frequently experience asymmetric loading due to seismic action or abutment settlements. Over the past few decades, numerous studies have sought to enhance our understanding of the structural behavior of these elements for the purpose of preventive conservation. The assessment of the structural performance of existing constructions typically relies on effective numerical models guided by a set of unknown input parameters, including geometry, mechanical characteristics, physical properties, and boundary conditions. These parameters can be estimated through deterministic optimization functions aimed at minimizing the discrepancy between the output of a numerical model and the measured dynamic and/or static structural response. However, deterministic approaches overlook uncertainties associated with both input parameters and measurements. In this context, the Bayesian approach proves valuable for estimating unknown numerical model parameters and their associated uncertainties (posterior distributions). This involves updating prior knowledge of model parameters (prior distributions) based on current measurements and explicitly considering all sources of uncertainties affecting observed quantities through likelihood functions. However, two significant challenges arise: the likelihood function may be unknown or too complex to evaluate, and the computational costs for approximating the posterior distribution can be prohibitive. This study addresses these challenges by employing Approximate Bayesian Computation (ABC) to handle the intractable likelihood function. Additionally, the computational burden is mitigated through the use of accurate surrogate models such as Polynomial Chaos Expansions (PCE) and Artificial Neural Networks (ANN). The research focuses on setting up numerical models for simple structural systems (tie-rods) and inferring unknown input parameters, such as mechanical properties and boundary conditions, through Bayesian updating based on observed structural responses (modal data, strains, displacements). The main novelties of this research regard, on the one hand, the proposal of a methodology for obtaining a reliable estimate of the axial force in ancient tie-rods accounting for different sources of uncertainty and, on the other hand, the application of ABC to obtain the structural identification inverse problem solution
Dependence of stiffness on water content in hydrogels: A statistical mechanics-based framework
No full textHydrogels are polymers that can uptake large amounts of water within their molecular network. Thanks to their physical, chemical, and mechanical properties, which are close to those of biological materials, hydrogels can be conveniently employed in a variety of fields, ranging from soft robots to biomedical applications. The microstructure of dry hydrogels comprises chains that are chemically cross-linked and interact with one another through intermolecular hydrogen bonds. In the present paper, we derive a model that describes the influence of water content on the overall stiffness of hydrogels. Broadly, water uptake in a hydrogel has three main consequences: (1) the presence of (compliant) liquid which softens the gel, (2) the stretching of the chains to accommodate water molecules leads to entropic stiffening, and (3) water molecules dissociate intermolecular bonds, resulting in entropic gain and significant softening. In this work, we derive a microscopically motivated model that accounts for these three effects and captures the influence of water molecules on the stiffness of hydrogels. To validate the model, we perform compression tests on superabsorbent polymers that swell to >100 times in volume and employ Hertzian contact theory to determine the stiffness. The model is in agreement with the experimental findings. To enable one to control the mechanical properties, we employ the model to investigate the role of pertinent microscopic quantities such as chain length and the number of intermolecular hydrogen bonds on the overall stiffness. The findings from this work pave the way to the microstructural design of hydrogels with tunable water content dependent stiffness
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
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