Prognostics Design for Structural Health Management
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Juan Chiachio | Manuel Chiachio | Kai Goebel | Shankar Sankararaman | Abhinav Saxena | K. Goebel | A. Saxena | J. Chiachío | M. Chiachío | S. Sankararaman
[1] Shankar Sankararaman,et al. Significance, interpretation, and quantification of uncertainty in prognostics and remaining useful life prediction , 2015 .
[2] K. Goebel,et al. Bayesian model selection and parameter estimation for fatigue damage progression models in composites , 2015 .
[3] Kai Goebel,et al. Uncertainty Quantification in Remaining Useful Life Prediction Using First-Order Reliability Methods , 2014, IEEE Trans. Reliab..
[4] K. Goebel,et al. Analytical algorithms to quantify the uncertainty in remaining useful life prediction , 2013, 2013 IEEE Aerospace Conference.
[5] Bhaskar Saha,et al. Requirements Flowdown for Prognostics and Health Management , 2012, Infotech@Aerospace.
[6] Aditi Chattopadhyay,et al. Condition Based Structural Health Monitoring and Prognosis of Composite Structures under Uniaxial and Biaxial Loading , 2010 .
[7] Sankalita Saha,et al. Requirements Specification for Prognostics Performance - An Overview , 2010 .
[8] Zhonghua Han,et al. Efficient Uncertainty Quantification using Gradient-Enhanced Kriging , 2009 .
[9] George Vachtsevanos,et al. Methodologies for uncertainty management in prognostics , 2009, 2009 IEEE Aerospace conference.
[10] Habib N. Najm,et al. Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics , 2009 .
[11] G. Kacprzynski,et al. Advances in uncertainty representation and management for particle filtering applied to prognostics , 2008, 2008 International Conference on Prognostics and Health Management.
[12] B. Saha,et al. Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques , 2008, 2008 IEEE Aerospace Conference.
[13] Jeong-Beom Ihn,et al. A Potential Link from Damage Diagnostics to Health Prognostics of Composites through Built-in Sensors , 2007 .
[14] Simon J. Godsill,et al. An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo , 2007, Proceedings of the IEEE.
[15] Charles R Farrar,et al. Damage prognosis: the future of structural health monitoring , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[16] Janis Varna,et al. Constitutive Relationships for Laminates with Ply Cracks in In-plane Loading , 2005 .
[17] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[18] James R. Van Zandt. A more robust unscented transform , 2001 .
[19] J. Beck,et al. Estimation of Small Failure Probabilities in High Dimensions by Subset Simulation , 2001 .
[20] Nando de Freitas,et al. Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.
[21] Michael A. West,et al. Combined Parameter and State Estimation in Simulation-Based Filtering , 2001, Sequential Monte Carlo Methods in Practice.
[22] Stephen J. Engel,et al. Prognostics, the real issues involved with predicting life remaining , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).
[23] Roberts Joffe,et al. Analytical modeling of stiffness reduction in symmetric and balanced laminates due to cracks in 90° layers , 1999 .
[24] Hisashi Tanizaki,et al. Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations , 1998 .
[25] R. Caflisch. Monte Carlo and quasi-Monte Carlo methods , 1998, Acta Numerica.
[26] Wei-Liem Loh. On Latin hypercube sampling , 1996 .
[27] Jun S. Liu,et al. Sequential Imputations and Bayesian Missing Data Problems , 1994 .
[28] Y.-T. Wu,et al. COMPUTATIONAL METHODS FOR EFFICIENT STRUCTURAL RELIABILITY AND RELIABILITY SENSITIVITY ANALYSIS , 1993 .
[29] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[30] Peter Gudmundson,et al. An analytic model for thermoelastic properties of composite laminates containing transverse matrix cracks , 1993 .
[31] John A. Nairn,et al. The initiation and growth of delaminations induced by matrix microcracks in laminated composites , 1992 .
[32] C. Cornell,et al. Adaptive Importance Sampling , 1990 .
[33] Donald L. Iglehart,et al. Importance sampling for stochastic simulations , 1989 .
[34] Lars Tvedt,et al. Second Order Reliability by an Exact Integral , 1989 .
[35] M. Hohenbichler,et al. Improvement Of Second‐Order Reliability Estimates by Importance Sampling , 1988 .
[36] C. Bucher. Adaptive sampling — an iterative fast Monte Carlo procedure , 1988 .
[37] A. Kiureghian,et al. Second-Order Reliability Approximations , 1987 .
[38] Zvi Hashin,et al. Analysis of cracked laminates: a variational approach , 1985 .
[39] K. Doliński,et al. First-order second-moment approximation in reliability of structural systems: Critical review and alternative approach , 1982 .
[40] R. Rackwitz,et al. First-order concepts in system reliability , 1982 .
[41] J. E. Bailey,et al. Multiple transverse fracture in 90° cross-ply laminates of a glass fibre-reinforced polyester , 1977 .
[42] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .
[43] M. Rosenblatt. Remarks on Some Nonparametric Estimates of a Density Function , 1956 .