Behmanesh et al., 2015 - Google Patents
Probabilistic identification of simulated damage on the Dowling Hall footbridge through Bayesian finite element model updatingBehmanesh et al., 2015
View PDF- Document ID
- 18256353628712538900
- Author
- Behmanesh I
- Moaveni B
- Publication year
- Publication venue
- Structural Control and Health Monitoring
External Links
Snippet
This paper presents a probabilistic damage identification study on a full‐scale structure, the Dowling Hall footbridge, through a Bayesian finite element (FE) model updating. The footbridge is located at Tufts University and is equipped with a continuous monitoring system …
- 238000000034 method 0 abstract description 20
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Behmanesh et al. | Probabilistic identification of simulated damage on the Dowling Hall footbridge through Bayesian finite element model updating | |
Rebba et al. | Validation of models with multivariate output | |
Hou et al. | Sparse Bayesian learning for structural damage detection using expectation–maximization technique | |
Prudencio et al. | A computational framework for dynamic data‐driven material damage control, based on Bayesian inference and model selection | |
Lee et al. | Bayesian-network-based system identification of spatial distribution of structural parameters | |
Jin et al. | Adaptive Markov chain Monte Carlo algorithms for Bayesian inference: recent advances and comparative study | |
US9933353B2 (en) | Method for assessing corroded pipeline defect growth from partial inspection data and devices thereof | |
Saito et al. | Bayesian model selection for ARX models and its application to structural health monitoring | |
Bhuyan et al. | Vibration‐based damage localization with load vectors under temperature changes | |
Aghagholizadeh et al. | A review of model updating methods for civil infrastructure systems | |
Jesus et al. | Modular Bayesian damage detection for complex civil infrastructure | |
Tabrizian et al. | Charged system search algorithm utilized for structural damage detection | |
Lin et al. | Finite element model validation of bridge based on structural health monitoring—Part II: Uncertainty propagation and model validation | |
Papadimitriou | Bayesian uncertainty quantification and propagation (UQ+ P): state-of-the-art tools for linear and nonlinear structural dynamics models | |
Fan et al. | Reliability‐based design of axially loaded drilled shafts using Monte Carlo method | |
Zheng et al. | Bayesian probabilistic framework for damage identification of steel truss bridges under joint uncertainties | |
Kamali et al. | A demand-capacity approach to define failure thresholds in anomaly detection monitoring systems | |
Souza et al. | Impact of damping models in damage identification | |
Chencho et al. | Structural damage quantification using ensemble‐based extremely randomised trees and impulse response functions | |
Simon et al. | Vibration-based structural health monitoring of a reinforced concrete beam subject to varying ambient temperatures using Bayesian methods | |
Behmanesh et al. | Hierarchical Bayesian model updating for probabilistic damage identification | |
Goi et al. | Bridge damage detection using ambient loads by bayesian hypothesis testing for a parametric subspace of an autoregressive model | |
Simoen et al. | Bayesian parameter estimation | |
Laborde et al. | Spacecraft base-sine vibration test data uncertainties investigation based on stochastic scatter approach | |
Sim et al. | Reliability-based evaluation of the performance of the damage locating vector method |