Investigation on high-dimensional uncertainty quantification and reliability analysis of aero-engine

[1]  Cheng Yang,et al.  An interval perturbation method for singular value decomposition (SVD) with unknown-but-bounded (UBB) parameters , 2023, J. Comput. Appl. Math..

[2]  Liming Song,et al.  Uncertainty quantification and sensitivity analysis of aerothermal performance for the turbine blade squealer tip , 2022, International Journal of Thermal Sciences.

[3]  Z. Wen,et al.  Film cooling of showerhead holes from the twisted leading edge of a gas turbine blade: Complex mainstream characteristics and reasonable angle arrangement , 2021, Aerospace Science and Technology.

[4]  Zhuo Wang,et al.  Reliability assessment and lifetime prediction of TBCs on gas turbine blades considering thermal mismatch and interfacial oxidation , 2021 .

[5]  Zhangli Hu,et al.  A maximum cost-performance sampling strategy for multi-fidelity PC-Kriging , 2021, Structural and Multidisciplinary Optimization.

[6]  Jiaqi Luo,et al.  Robust design optimization considering inlet flow angle variations of a turbine cascade , 2021 .

[7]  Charbel Farhat,et al.  Active Manifold and Model-Order Reduction to Accelerate Multidisciplinary Analysis and Optimization , 2021, AIAA Journal.

[8]  Xiaochuan Tian,et al.  An asymptotically compatible probabilistic collocation method for randomly heterogeneous nonlocal problems , 2021, J. Comput. Phys..

[9]  H. Moon,et al.  Wake effects on heat transfer from a turbine blade tip with different configurations and its corresponding shroud , 2021, International Communications in Heat and Mass Transfer.

[10]  Jia Geng,et al.  Uncertainties in gas-path diagnosis of gas turbines: Representation and impact analysis , 2021 .

[11]  Y. Xuan,et al.  The effects of tip gap variation on transonic turbine blade tip leakage flow based on VLES approach , 2021 .

[12]  Elias Tsoutsanis,et al.  A sequential model-based approach for gas turbine performance diagnostics , 2021 .

[13]  Q. Fei,et al.  An efficient wave based method for the mid-frequency transverse vibration analysis of a thermal beam with interval uncertainties , 2021 .

[14]  Yu Zhang,et al.  Deep Recurrent Entropy Adaptive Model for System Reliability Monitoring , 2021, IEEE Transactions on Industrial Informatics.

[15]  Ning-Cong Xiao,et al.  A new reliability method for small failure probability problems by combining the adaptive importance sampling and surrogate models , 2020 .

[16]  Sunday N. Ozonuwe,et al.  Application of the Two-parameter Weibull Distribution Method to Assess the Reliability of Gas Turbine Compressors , 2020 .

[17]  Cheng-Wei Fei,et al.  Moving extremum surrogate modeling strategy for dynamic reliability estimation of turbine blisk with multi-physics fields , 2020 .

[18]  Ahmed Hafaifa,et al.  Gas turbine reliability modelling based on a bath shaped rate failure function: modified Weibull distribution validation , 2020, Life Cycle Reliability and Safety Engineering.

[19]  Dalu Cao,et al.  A Study on Aeroengine Conceptual Design Considering Multi-Mission Performance Reliability , 2020 .

[20]  Xinqian Zheng,et al.  Review of Geometric Uncertainty Quantification in Gas Turbines , 2020 .

[21]  Kin Huat Low,et al.  Three-dimensional (3D) Monte-Carlo modeling for UAS collision risk management in restricted airport airspace , 2020 .

[22]  A. A. Abiodun,et al.  The Maxwell–Weibull Distribution in Modeling Lifetime Datasets , 2020, Annals of Data Science.

[23]  Aytac Altan,et al.  Model predictive control of three-axis gimbal system mounted on UAV for real-time target tracking under external disturbances , 2020 .

[24]  Shazaib Ahsan,et al.  Reliability analysis of gas turbine engine by means of bathtub‐shaped failure rate distribution , 2020 .

[25]  Umit Kutluay,et al.  Generation of surrogate-based aerodynamic model of an UCAV configuration using an adaptive co-Kriging method , 2019 .

[26]  Z. Zou,et al.  Uncertainty analysis of impact of geometric variations on turbine blade performance , 2019, Energy.

[27]  Lei Wang,et al.  REIF: A novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis , 2019, Reliab. Eng. Syst. Saf..

[28]  Z. Tao,et al.  An investigation for the turbine blade film cooling performance on the suction side tip region under rotating condition , 2019, Applied Thermal Engineering.

[29]  Giacomo Bruno Azzurro Persico,et al.  Impact of geometric, operational, and model uncertainties on the non-ideal flow through a supersonic ORC turbine cascade , 2019, Energy.

[30]  Yan Shi,et al.  A reliability analysis method based on analytical expressions of the first four moments of the surrogate model of the performance function , 2018, Mechanical Systems and Signal Processing.

[31]  Shuying Zhai,et al.  H -adaptive RBF-FD method for the high-dimensional convection-diffusion equation , 2017 .

[32]  Kun He,et al.  Investigations into heat transfer and film cooling effect on a squealer-winglet blade tip , 2017 .

[33]  Jong-Keun Park,et al.  A Multi-Energy System Expansion Planning Method Using a Linearized Load-Energy Curve: A Case Study in South Korea , 2017 .

[34]  Guillermo Paniagua,et al.  Performance Robustness of Turbine Squealer Tip Designs Due to Manufacturing and Engine Operation , 2017 .

[35]  Christopher C. Pain,et al.  Non‐intrusive reduced‐order modeling for multiphase porous media flows using Smolyak sparse grids , 2017 .

[36]  J. Wiart,et al.  Polynomial-Chaos-based Kriging , 2015, 1502.03939.

[37]  Francesco Montomoli,et al.  Uncertainty Quantification: A Stochastic Method for Heat Transfer Prediction Using LES , 2013 .

[38]  Francesco Montomoli,et al.  Uncertainty quantification and film cooling , 2013 .

[39]  K. Ohmi,et al.  An ant colony optimization based stereoscopic particle pairing algorithm for three-dimensional particle tracking velocimetry , 2011 .

[40]  Hao Yu,et al.  Levenberg—Marquardt Training , 2011 .

[41]  Nathan Mendes,et al.  Identification of temperature and moisture content fields using a combined neural network and clustering method approach , 2009 .

[42]  Maoyu Zheng,et al.  Development of a numerical model for the simulation of vertical U-tube ground heat exchangers , 2009 .

[43]  Abhinav Saxena,et al.  Damage propagation modeling for aircraft engine run-to-failure simulation , 2008, 2008 International Conference on Prognostics and Health Management.

[44]  N. Bloom.  The Impact of Uncertainty Shocks , 2007 .

[45]  P. Masson,et al.  Estimation of the parameters of a Gaussian heat source by the Levenberg–Marquardt method: Application to the electron beam welding , 2007 .

[46]  Je-Chin Han,et al.  Heat Transfer Coefficients and Film Cooling Effectiveness on the Squealer Tip of a Gas Turbine Blade , 2003 .

[47]  J. Huang,et al.  Curse of dimensionality and particle filters , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[48]  Je-Chin Han,et al.  Heat-Transfer Coefficients of a Turbine Blade-Tip and Near-Tip Regions , 2002 .

[49]  Dongbin Xiu,et al.  The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations , 2002, SIAM J. Sci. Comput..

[50]  Ronald Scott Bunker,et al.  Heat Transfer and Flow on the First Stage Blade Tip of a Power Generation Gas Turbine: Part 1 — Experimental Results , 1999 .

[51]  E. Zaretsky,et al.  Probabilistic analysis of aircraft gas turbine disk life and reliability , 1997 .

[52]  N. Wiener.  The Homogeneous Chaos , 1938 .

[53]  Giray Ökten,et al.  Randomized quasi-Monte Carlo methods in global sensitivity analysis , 2021, Reliab. Eng. Syst. Saf..

[54]  Seunggyu Lee,et al.  Monte Carlo simulation using support vector machine and kernel density for failure probability estimation , 2021, Reliab. Eng. Syst. Saf..

[55]  Ahmed Hafaifa,et al.  Gas turbine reliability model based on tangent hyperbolic reliability function , 2015 .

[56]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.