There has been increasing interest in evaluating the performance of existingreinforced concrete (RC) bridges just after natural disasters or man-made eventsespecially when the defects are invisible, or in quantifying ...
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There has been increasing interest in evaluating the performance of existing
reinforced concrete (RC) bridges just after natural disasters or man-made events
especially when the defects are invisible, or in quantifying the improvement after
rehabilitations. In order to obtain an accurate assessment of the reliability of a RC
bridge, it is critical to incorporate information about its current structural properties,
which reflects the possible aging and deterioration. This dissertation proposes to
develop an adaptive reliability analysis of RC bridges incorporating the damage
detection information obtained from nondestructive testing (NDT).
In this study, seismic fragility is used to describe the reliability of a structure
withstanding future seismic demand. It is defined as the conditional probability that a
seismic demand quantity attains or exceeds a specified capacity level for given values of
earthquake intensity. The dissertation first develops a probabilistic capacity model for
RC columns and the capacity model can be used when the flexural stiffness decays nonuniformly
over a column height. Then, a general methodology to construct probabilistic seismic demand models for RC highway bridges with one single-column bent is
presented. Next, a combination of global and local NDT methods is proposed to identify
in-place structural properties. The global NDT uses the dynamic responses of a structure
to assess its global/equivalent structural properties and detect potential damage locations.
The local NDT uses local measurements to identify the local characteristics of the
structure. Measurement and modeling errors are considered in the application of the
NDT methods and the analysis of the NDT data. Then, the information obtained from
NDT is used in the probabilistic capacity and demand models to estimate the seismic
fragility of the bridge. As an illustration, the proposed probabilistic framework is
applied to a reinforced concrete bridge with a one-column bent. The
Cyclic triaxial tests are commonly used to evaluate a soil's potential for liquefaction during seismic events. Following testing, it is necessary to evaluate the validity of the test results. This can be a difficu...
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Cyclic triaxial tests are commonly used to evaluate a soil's potential for liquefaction during seismic events. Following testing, it is necessary to evaluate the validity of the test results. This can be a difficult task unless the engineer has previously acquired a reasonable amount of experience with this type of testing. In order to help evaluate the validity of the test results, a series of eight predictive models have been developed for sands and soils with non-plastic silts. These models predict a mean value of the number of cycles required to cause liquefaction as well as 50 and 95 % prediction intervals. The models were separated by the soil type (sands and soils with less than 30 % non-plastic fines versus soils with 30 % or more non-plastic fines), the definition of liquefaction used (initial liquefaction versus 5 % double-amplitude strain), and the method of specimen preparation (moist tamping, air-pluviation, or slurry-deposition). These models were developed using the data from over 1000 tests collected from the author's files and the literature. Following development, the validity of each model was assessed by examining the statistical parameters of the model, analyzing each model's residuals, and by predictions made using additional data obtained from the literature.
The purpose of the paper is to compare four models by using fuzzy parameters. The four parametric models considered included: Fuzzy Set model, QuickEst Heuristics model, linear regression model, Neural Network model. ...
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The purpose of the paper is to compare four models by using fuzzy parameters. The four parametric models considered included: Fuzzy Set model, QuickEst Heuristics model, linear regression model, Neural Network model. Each of these had been proposed as a cognitive model of human judgment and was applied in this study to the estimation of product selection reasonableness. This study focused on the relationship between quality, price, brand, and service without considering how one would evaluate these components. Empirical results show that the Fuzzy model outperformed all the other models. [ABSTRACT FROM AUTHOR]
Apricot (Prunus armeniaca L.) is one of the most important export crops in Turkey and Turkey is the leading fresh and dried apricot producer all over the world. Malatya province is the main production area in Turkey. ...
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Apricot (Prunus armeniaca L.) is one of the most important export crops in Turkey and Turkey is the leading fresh and dried apricot producer all over the world. Malatya province is the main production area in Turkey. Apricot yield has fluctuations because of climate in Malatya region. The study analyzed the relationship between climate factors and apricot yield by using time series data belong to the climatic variables such as temperature, humidity and precipitation during the time period of 1978-2006. All climatic variables were examined associated with the stages of planting, flowering and harvesting, separately. linearregression method was used to estimate the model parameters. Research model showed that the most magnificence climatic factors on apricot yield were minimum temperature, precipitation and humidity in flowering period and maximum temperature in planting period. The study suggested that choosing suitable apricot variety and protecting the apricot orchards via technical measures in order to reduce adverse effects of fluctuations on climatic variables.
In this paper,we research aggregated mixed estimator of parameter in linear regression model which has additional information,under Aggregated date *** discuss the relative efficiencies of the estimator with respect t...
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In this paper,we research aggregated mixed estimator of parameter in linear regression model which has additional information,under Aggregated date *** discuss the relative efficiencies of the estimator with respect to Peter-Karsten estimator,and obtain its upper bound and lower *** with respect to least square estimator.
In light of properties of the GM (1,1) and the linear regression model,this study established a GM (1,1)-linearregression prediction *** is really a good model for China's GDP forecast because it greatly overcome...
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In light of properties of the GM (1,1) and the linear regression model,this study established a GM (1,1)-linearregression prediction *** is really a good model for China's GDP forecast because it greatly overcomes the defects in the GM (1,1) and the linear regression model and has a better effect.
In this article, we study consumer market segments in four Latin American countries and one U.S. territory by using lifestyle patterns and ethnocentrism. We partition consumer ethnocentrism into low, medium, and high ...
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THIS STUDY RELATES VARIOUS QUANTIFIABLE characteristics of a musical pattern to subjective assessments of a pattern's salience. Via score analysis and listening, twelve music undergraduates examined excerpts taken...
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THIS STUDY RELATES VARIOUS QUANTIFIABLE characteristics of a musical pattern to subjective assessments of a pattern's salience. Via score analysis and listening, twelve music undergraduates examined excerpts taken from Chopin's mazurkas. They were instructed to rate already discovered patterns, giving high ratings to patterns that they thought were noticeable and/or important. Each undergraduate rated thirty specified patterns and ninety patterns were examined in total. Twenty-nine quantifiable attributes (some novel but most proposed previously) were determined for each pattern, such as the number of notes a pattern contained. A model useful for relating participants' ratings to the attributes was determined using variable selection and cross-validation. Individual participants were much poorer than the model at predicting the consensus ratings of other participants. While the favored model contains only three variables, many variables were identified as having some predictive value if considered in isolation. Implications for music psychology, analysis, and information retrieval are discussed.
The maximum likelihood estimation of the iid normal linear regression model where some of the covariates are subject to randomized response is discussed. Randomized response (RR) is an interview technique that can be ...
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The maximum likelihood estimation of the iid normal linear regression model where some of the covariates are subject to randomized response is discussed. Randomized response (RR) is an interview technique that can be used when sensitive questions have to be asked and respondents are reluctant to answer directly. RR variables are described as misclassified categorical variables where conditional misclassification probabilities are known. The likelihood of the linear regression model with RR covariates is derived and a fast and straightforward EM algorithm is developed to obtain maximum likelihood estimates. The basis of the algorithm consists of elementary weighted least-squares steps. A simulation example demonstrates the feasibility of the method. (C) 2005 Elsevier B.V. All rights reserved.
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