1,721,062 research outputs found
Bayesian updating methodology for probabilistic model of bridge traffic loads using in-service data of traffic environment
No full textThe traffic environment of a bridge generally varies over its lifetime and can be affected by unexpected changes in the surroundings such as the construction of new roads. Therefore, for accurate estimation of traffic loads, changes in the traffic environment need to be continuously monitored and incorporated into traffic load predictions. To this end, this study first further develops the comprehensive probabilistic model of bridge traffic loads by introducing micro-simulation models to describe accurately congestion state. Next, a Bayesian methodology is proposed to update the parameters of the distributions in the probabilistic model of bridge traffic loads based on in-service data representing the traffic environment. Three Bayesian inference methods are used: conjugate prior distributions, Bayesian linear regression, and Gibbs sampling. Hyper-parameters of the prior model are set up appropriately based on the measurement accuracy and the degrees of belief in the prior model. The proposed Bayesian updating methodology is demonstrated by numerical examples with various scenarios of traffic environment changes and in-service weigh-in-motion (WIM) data measured on a real bridge. The results confirm that the proposed methodology can successfully incorporate changes of the traffic environment into the estimation of traffic load effects on bridges in operation.N
Near-Real-Time Identification of Seismic Damage Using Unsupervised Deep Neural Network
No full textPrompt identification of structural damage is essential for effective postdisaster responses. To this end, this paper proposes a deep neural network (DNN)-based framework to identify seismic damage based on structural response data recorded during an earthquake event. The DNN in the proposed framework is constructed by Variational Autoencoder, which is one of the self-supervised DNNs that can construct the continuous latent space of the input data by learning probabilistic characteristics. The DNN is trained using the flexibility matrices obtained by operational modal analysis (OMA) of simulated structural responses of the target structure under the undamaged state. To consider the load-dependency of OMA results, the undamaged state of the structure is represented by the flexibility matrix, which is closest to that obtained from the measured seismic response in the latent space. The seismic damage of each member is then estimated based on the difference between the two matrices using the flexibility disassembly method. As a numerical example, the proposed method is applied to a 5-story, 5-bay steel frame structure for which structural analyses are first performed under artificial ground motions to create train and test datasets. The proposed framework is verified with the near-real-time simulation using ground motions of El Centro and Kobe earthquakes. The example demonstrates that the proposed DNN-based method can identify seismic damage accurately in near-real-time.N
Quantifying uncertainties and correlations of engineering demand parameters of building structures for regional seismic loss assessment
No full textFor an accurate regional seismic loss assessment, it is essential to quantify the uncertainties and correlations of the engineering demand parameters (EDP) of the building structures. Previous studies predicted the mean EDP of each structure by a regression function of the selected intensity measure (IM), while its variability is described by the "EDP residual." The authors recently proposed a new formulation and Incremental Dynamic Analysis (IDA)-based methods to evaluate the correlation between EDP residuals. This paper proposes an IM-invariant method for estimating the variances and correlations of the EDP residuals of building structures. Based on the EDP residuals of various buildings estimated using the proposed method, primary structural characteristics affecting EDP residuals are identified. In addition, this study develops EDP estimation regression equations using predictive variables defined based on the identified structural characteristics to facilitate consideration of the EDP residual correlation in regional seismic loss assessment. Numerical examples verify the regression models and demonstrate that the proposed method can improve the accuracy of a regional loss assessment by considering the building types in the inventory.N
A Spherically Focused Capacitive‐Film Air‐Coupled Transducer
Full text linkWe have developed, fabricated, and tested spherically focused capacitive‐film air‐coupled ultrasonic transducers, which need no mirror, zone plate, or similar external device. To achieve native focusing, we have employed a flexible copper/polyimide backplate that permits a conformal fit to a spherical fixture whose radius determines the focal length. The backplate is patterned with 40 μm depressions having 80 μm spacings. A spherically deformed 6 μm aluminized Mylar film, conforms to the spherical backplate, completing the transducer. Two transducers have been tested, one having a 1 cm diameter and 2.54 cm focus, and another with a 5 cm diameter and 5.1 cm focus. Both transducers have frequency spectra centered at 805 kHz with — 6dB points at 440 and 1210 kHz. In the focal plane, the beam diameter is 2.7 mm (1 cm transducer) and 1.32 mm (5 cm transducer), when excited with a broadband signal. The focal zone extends from 17 to 34 mm (1 cm transducer) and from 46 to 57 mm (5‐cm transducer). Both transducers’ diffraction behaviors have been successfully modeled as focused piston radiators.This proceeding may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.
This proceeding appeared in Song, Junho, Stephen D. Holland, and D. E. Chimenti. "A Spherically Focused Capacitive‐Film Air‐Coupled Transducer." In AIP Conference Proceedings, vol. 820, no. 1, pp. 908-915. American Institute of Physics, 2006, and may be found at
DOI: 10.1063/1.2184622.
Copyright 2006 American Institute of Physics.
Posted with permission
Probabilistic models based on experimental observations using sparse bayes methodology
Full text linkThe quality of people’s lives depends on safe and reliable infrastructure. However, there exist various types of uncertainties that may influence performance of structures, which could cause unexpected failures. Therefore, it is important to quantify the risk of such failures through systematic treatment of uncertainties and make a risk-informed decision. As an effort to predict uncertain performance of structural elements based on experimental observations, the principle of Bayesian inference has been often used. In this study, the recently proposed Sparse Bayes method is reviewed and tested by use of an experimental database of the shear strengths of reinforced concrete beams without stirrups. The performance of the Sparse Bayes method is demonstrated through comparison with existing methods such as least-square method and penalized least-square method. The Sparse Bayes method is further developed to identify a few representative points in the parameter space by grouping the relevant vectors identified by the method using the k-means clustering algorithm. The study confirms that the Sparse Bayes method has wide applicability, ability to achieve an optimal fitting, and efficiency. Therefore, the method can potentially provide a useful tool to develop powerful probabilistic models for various problems based on experimental observations.Item withdrawn by Laura Spradlin ([email protected]) on 2013-12-13T19:48:29Z
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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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