Πλοήγηση ανά Θέμα "Inference engines"
Αποτελέσματα 21-36 από 36
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Fatigue monitoring and remaining lifetime prognosis using operational vibration measurements
(2019)A framework is presented for real-time monitoring of fatigue damage accumulation and prognosis of the remaining lifetime at hotspot locations of new or existing structures by combining output-only vibration measurements ... -
HIERARCHICAL BAYESIAN INFERENCE FOR QUANTIFICATION OF UNCERTAINTY IN MULTI LEVEL MODELS OF DYNAMICAL SYSTEMS
(2021)Calibration of model parameters is increasingly playing a key role in the process of accurately predicting the responses of full-scale dynamical systems. Such systems often exhibit complexities arising from the assembling ... -
Hierarchical Bayesian Uncertainty Quantification for a Model of the Red Blood Cell
(2021)Simulations of blood flows in microfluidic devices and physiological systems are gaining importance in complementing experimental and clinical studies. The predictive capabilities of these simulations hinge on the parameters ... -
Information-driven modeling of structures using a Bayesian framework
(2018)This work presents a comprehensive Bayesian framework for integrating information from data and models of civil infrastructure systems. In the proposed framework, modeling uncertainties are quantified and propagated through ... -
Model calibration of metsovo bridge using ambient vibration measurements from various construction phases
(2015)Available methods for structural model updating are employed to develop high fidelity models of the soil-foundation-structure of Metsovo bridge using ambient vibration measurements. The Metsovo bridge, the highest bridge ... -
Monitoring gross vehicle weight with a probabilistic and influence line-free bridge weight-in-motion scheme based on a transmissibility-like index
(2022)A new transmissibility-like index defined as the ratio of the frequency responses of the same monitoring location under two different loading conditions was proposed for Gross Vehicle Weights (GVWs) monitoring in this ... -
A Nonlinear Model Inversion Method for Joint System Parameter, Noise, and Input Identification of Civil Structures
(2017)This paper presents a framework for nonlinear system identification of civil structures using sparsely measured dynamic output response of the structure. Using a sequential maximum likelihood estimation (MLE) approach, the ... -
Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost
(2022)This paper proposes an optimal sensor placement (OSP) framework for parameter estimation, virtual sensing, and condition monitoring using information theory. The framework uses a Bayesian OSP method combined with modal ... -
Optimal sensor placement for response predictions using local and global methods
(2020)A Bayesian framework for model-based optimal sensor placement for response predictions is presented. Our interest lies in determining the parameters of the model in order to make predictions about a particular response ... -
Optimal sensor placement for response reconstruction in structural dynamics
(2020)A framework for optimal sensor placement (OSP) for response reconstruction under uncertainty is presented based on information theory. The OSP is selected as the one that maximizes an expected utility function taken as the ... -
Optimization algorithms for system integration
(2008)This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising ... -
Posterior robust optimization for design update based on measurements
(2015)A Bayesian unified framework is proposed for data-informed robust design optimization. Models of uncertainties postulated in conventional robust design optimization are treated as prior uncertainties in a Bayesian context. ... -
Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions
(2019)A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation ... -
Statistics-based Bayesian modeling framework for uncertainty quantification and propagation
(2022)A new Bayesian modeling framework is proposed to account for the uncertainty in the model parameters arising from model and measurements errors, as well as experimental, operational, environmental and manufacturing ... -
Uncertainty calibration of large-order models of bridges using ambient vibration measurements
(2014)A computational efficient Bayesian inference framework based on stochastic simulation algorithms is presented for calibrating the parameters of large-order linear finite element (FE) models of bridges. The effectiveness ... -
A unified sampling-based framework for optimal sensor placement considering parameter and prediction inference
(2021)We present a Bayesian framework for model-based optimal sensor placement. Our interest lies in minimizing the uncertainty on predictions of a particular response quantity of interest, with parameter estimation being an ...