Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/sage/structural-damage-identification-a-random-sampling-high-dimensional-wBaHLtlea7
References (55)
-
H. Niederreiter (1992)
1. Monte Carlo Methods and Quasi-Monte Carlo Methods -
(2016)
2016a) Bottom up surrogate based approach for stochastic frequency response analysis of laminated composite plates -
S. Dey, T. Mukhopadhyay, A. Spickenheuer, S. Adhikari, G. Heinrich (2016)
Bottom up surrogate based approach for stochastic frequency response analysis of laminated composite platesComposite Structures, 140
-
F. Udwadia (2005)
Structural Identification and Damage Detection from Noisy Modal DataJournal of Aerospace Engineering, 18
-
A. Teughels, J. Maeck, G. Roeck (2002)
Damage assessment by FE model updating using damage functionsComputers & Structures, 80
-
T. Dey, T. Mukhopadhyay, A. Chakrabarti, U. Sharma (2015)
Efficient lightweight design of FRP bridge deck, 168
-
Bharadwaj Nanda, D. Maity, D. Maiti (2014)
Crack Assessment in Frame Structures Using Modal Data and Unified Particle Swarm Optimization TechniqueAdvances in Structural Engineering, 17
-
C. Fritzen, D. Jennewein, T. Kiefer (1998)
DAMAGE DETECTION BASED ON MODEL UPDATING METHODSMechanical Systems and Signal Processing, 12
-
T. Mukhopadhyay, T. Dey, R. Chowdhury, A. Chakrabarti, S. Adhikari (2015)
Optimum design of FRP bridge deck: an efficient RS-HDMR based approachStructural and Multidisciplinary Optimization, 52
-
T. Mukhopadhyay, Susmita Naskar, S. Dey, S. Adhikari (2016)
On quantifying the effect of noise in surrogate based stochastic free vibration analysis of laminated composite shallow shellsComposite Structures, 140
-
T. Ziehn, A. Tomlin (2009)
GUI-HDMR - A software tool for global sensitivity analysis of complex modelsEnviron. Model. Softw., 24
-
T. Mukhopadhyay, T. Dey, R. Chowdhury, A. Chakrabarti (2015)
Structural Damage Identification Using Response Surface-Based Multi-objective Optimization: A Comparative StudyArabian Journal for Science and Engineering, 40
-
M. Friswell, J. Penny (2002)
Crack Modeling for Structural Health MonitoringStructural Health Monitoring, 1
-
H. Rabitz, Ömer Aliş (1999)
General foundations of high‐dimensional model representationsJournal of Mathematical Chemistry, 25
-
Genyuan Li, Sheng-Wei Wang, H. Rabitz, Sookyun Wang, P. Jaffé (2002)
Global uncertainty assessments by high dimensional model representations (HDMR)Chemical Engineering Science, 57
-
P. Rousseeuw (1987)
Silhouettes: a graphical aid to the interpretation and validation of cluster analysisJournal of Computational and Applied Mathematics, 20
-
T. Ziehn, A. Tomlin (2008)
Global sensitivity analysis of a 3D street canyon model—Part I: The development of high dimensional model representationsAtmospheric Environment, 42
-
S. Beygzadeh, E. Salajegheh, P. Torkzadeh, J. Salajegheh, S. Naseralavi (2014)
An Improved Genetic Algorithm for Optimal Sensor Placement in Space Structures Damage DetectionInternational Journal of Space Structures, 29
-
J. MacQueen (1967)
Some methods for classification and analysis of multivariate observations, 1
-
Ying Wang, H. Hao (2015)
Damage Identification Scheme Based on Compressive SensingJ. Comput. Civ. Eng., 29
-
Ling Yu, Cheng Li (2014)
A Global Artificial Fish Swarm Algorithm for Structural Damage DetectionAdvances in Structural Engineering, 17
-
Genyuan Li, H. Rabitz, Sheng-Wei Wang, P. Georgopoulos (2003)
Correlation method for variance reduction of Monte Carlo integration in RS‐HDMRJournal of Computational Chemistry, 24
-
S. Fang, Ricardo Perera (2009)
A response surface methodology based damage identification techniqueSmart Materials and Structures, 18
-
J. Hou, Ł. Jankowski, J. Ou (2015)
Frequency-Domain Substructure Isolation for Local Damage IdentificationAdvances in Structural Engineering, 18
-
D. Mukherjee, B. Rao, A. Prasad (2011)
Global sensitivity analysis of unreinforced masonry structure using high dimensional model representationEngineering Structures, 33
-
Genyuan Li, H. Rabitz (2006)
Ratio control variate method for efficiently determining high‐dimensional model representationsJournal of Computational Chemistry, 27
-
Ling Yu, Peng Xu (2011)
Structural health monitoring based on continuous ACO methodMicroelectron. Reliab., 51
-
(2010)
Application of particle swarm optimization and genetic algorithms to multiobjective damage identification inverse problems with modelling -
R. Perera, S. Fang, Antonio Ruiz (2010)
Application of particle swarm optimization and genetic algorithms to multiobjective damage identification inverse problems with modelling errorsMeccanica, 45
-
M. Cao, Wei Xu, W. Ostachowicz, Z. Su (2014)
Damage identification for beams in noisy conditions based on Teager energy operator-wavelet transform modal curvatureJournal of Sound and Vibration, 333
-
T. Mukhopadhyay, R. Chowdhury, A. Chakrabarti (2013)
Reliability analysis of response surface based damage identification method -
K. Deb (2001)
Multi-objective optimization using evolutionary algorithms -
Silvio Galanti, A. Jung (1997)
Low-Discrepancy Sequences, 5
-
S. Sandesh, K. Shankar (2010)
Application of a hybrid of particle swarm and genetic algorithm for structural damage detectionInverse Problems in Science and Engineering, 18
-
T. Ziehn, A. Tomlin (2008)
A global sensitivity study of sulfur chemistry in a premixed methane flame model using HDMRInternational Journal of Chemical Kinetics, 40
-
R. Chowdhury, B. Rao (2009)
Assessment of high dimensional model representation techniques for reliability analysisProbabilistic Engineering Mechanics, 24
-
Susmita Naskar, S. Bhalla (2016)
Metal-wire-based twin one-dimensional orthogonal array configuration of PZT patches for damage assessment of two-dimensional structuresJournal of Intelligent Material Systems and Structures, 27
-
Miles Miller, Xiao-Jiang Feng, Genyuan Li, H. Rabitz (2012)
Identifying Biological Network Structure, Predicting Network Behavior, and Classifying Network State With High Dimensional Model Representation (HDMR)PLoS ONE, 7
-
Y. Lei, A. Kiremidjian, K. Nair, J. Lynch, K. Law, T. Kenny, E. Carryer, A. Kottapalli (2003)
Statistical Damage Detection Using Time Series Analysis on a Structural Health Monitoring Benchmark Problem -
W. Fan, P. Qiao (2011)
Vibration-based Damage Identification Methods: A Review and Comparative Study:Structural Health Monitoring-an International Journal, 10
-
S. Dey, Susmita Naskar, T. Mukhopadhyay, U. Gohs, A. Spickenheuer, L. Bittrich, S. Sriramula, S. Adhikari, G. Heinrich (2016)
Uncertain natural frequency analysis of composite plates including effect of noise – A polynomial neural network approachComposite Structures, 143
-
X. Li, S. Law (2008)
Damage Identification of Structures Including System Uncertainties and Measurement NoiseAIAA Journal, 46
-
F. Gembicki (1974)
Vector optimization for control with performance and parameter sensitivity indices -
J. Halton (1960)
On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integralsNumerische Mathematik, 2
-
Genyuan Li, Jishan Hu, Sheng-Wei Wang, P. Georgopoulos, J. Schoendorf, H. Rabitz (2006)
Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions.The journal of physical chemistry. A, 110 7
-
S. Dey, T. Mukhopadhyay, S. Sahu, G. Li, H. Rabitz, S. Adhikari (2015)
Thermal uncertainty quantification in frequency responses of laminated composite platesComposites Part B-engineering, 80
-
S. Dey, T. Mukhopadhyay, H. Khodaparast, S. Adhikari (2016)
A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite ShellsPeriodica Polytechnica-civil Engineering, 60
-
A. Dash, D. Parhi (2014)
Analysis of an Intelligent Hybrid System for Fault Diagnosis in Cracked StructureArabian Journal for Science and Engineering, 39
-
Weilin Xiang, Dansheng Wang, Hong-ping Zhu (2014)
Damage Identification in a Plate Structure Based on Strain Statistical MomentAdvances in Structural Engineering, 17
-
H. Faure (1992)
Good permutations for extreme discrepancyJournal of Number Theory, 42
-
H. Taboada, Fatema Baheranwala, D. Coit, N. Wattanapongsakorn (2007)
Practical solutions for multi-objective optimization: An application to system reliability design problemsReliab. Eng. Syst. Saf., 92
-
S. Dey, T. Mukhopadhyay, S. Adhikari (2015)
Stochastic free vibration analysis of angle-ply composite plates – A RS-HDMR approachComposite Structures, 122
-
Genyuan Li, Sheng-Wei Wang, H. Rabitz (2002)
Practical Approaches To Construct RS-HDMR Component FunctionsJournal of Physical Chemistry A, 106
-
I. Sobol (1967)
On the distribution of points in a cube and the approximate evaluation of integralsUssr Computational Mathematics and Mathematical Physics, 7
-
A. Furukawa, H. Otsuka, J. Kiyono (2006)
Structural Damage Detection Method Using Uncertain Frequency Response FunctionsComputer‐Aided Civil and Infrastructure Engineering, 21
- Publisher
- SAGE
- Copyright
- © The Author(s) 2016
- ISSN
- 1369-4332
- eISSN
- 2048-4011
- DOI
- 10.1177/1369433216630370
- Publisher site
- See Article on Publisher Site
Abstract
Structural damage identification and quantification of damage using non-destructive methods are important aspects for any civil, mechanical and aerospace engineering structures. In this study, a novel damage identification algorithm has been developed using random sampling-high dimensional model representation approach. A global sensitivity analysis based on random sampling-high dimensional model representation is adopted for important parameter screening purpose. Three different structures (spring mass damper system, simply supported beam and fibre-reinforced polymer composite bridge deck) have been used for various single and multiple damage conditions to validate the proposed algorithm. The performance of this method is found to be quite satisfactory in the realm of damage detection in structures. The random sampling-high dimensional model representation-based approach for meta-model formation is particularly useful in damage identification as it works well when large numbers of input parameters are involved. In this study, two different optimization methods have been used and their relative capability to identify damage has been discussed. Performance of this damage identification algorithm under the influence of noise has also been addressed in this article.
Journal
Advances in Structural Engineering – SAGE
Published: Jun 1, 2016