Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection

被引:244
|
作者
Reagan, MT [1 ]
Najm, HN
Ghanem, RG
Knio, OM
机构
[1] Sandia Natl Labs, Livermore, CA 94551 USA
[2] Johns Hopkins Univ, Baltimore, MD 21286 USA
关键词
uncertainity; flame; simulation; spectral; polynomial; chaos;
D O I
10.1016/S0010-2180(02)00503-5
中图分类号
O414.1 [热力学];
学科分类号
摘要
A spectral formalism has been developed for the "non-intrusive" analysis of parametric uncertainty in reacting-flow systems. In comparison to conventional Monte Carlo analysis, this method quantifies the extent, dependence, and propagation of uncertainty through the model system and allows the correlation of uncertainties in specific parameters to the resulting uncertainty in detailed flame structure. For the homogeneous ignition chemistry of a hydrogen oxidation mechanism in supercritical water, spectral projection enhances existing Monte Carlo methods, adding detailed sensitivity information to uncertainty analysis and relating uncertainty propagation to reaction chemistry. For 1 -D premixed flame calculations, the method quantifies the effect of each uncertain parameter on total uncertainty and flame structure, and localizes the effects of specific parameters within the flame itself. In both 0-D and 1-D examples, it is clear that known empirical uncertainties in model parameters may result in large uncertainties in the final output. This has important consequences for the development and evaluation of combustion models. This spectral formalism may be extended to multidimensional systems and can be used to develop more efficient "intrusive" reformulations of the governing equations to build uncertainty analysis directly into reacting flow simulations. (C) 2003 The Combustion Institute. All rights reserved.
引用
收藏
页码:545 / 555
页数:11
相关论文
共 50 条
  • [41] Prediction and reduction of runtime in non-intrusive forward UQ simulations
    Kuenzner, Florian
    Neckel, Tobias
    Bungartz, Hans-Joachim
    SN APPLIED SCIENCES, 2019, 1 (09):
  • [42] Prediction and reduction of runtime in non-intrusive forward UQ simulations
    Florian Künzner
    Tobias Neckel
    Hans-Joachim Bungartz
    SN Applied Sciences, 2019, 1
  • [43] Non-intrusive reduced-order modeling for uncertainty quantification of space-time-dependent parameterized problems
    Sun, Xiang
    Choi, Jung-Il
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2021, 87 : 50 - 64
  • [44] Non-Intrusive Microwave System for Multiphase Flow Metering
    Sheila-Vadde, Aparna C.
    Melapudi, Vikram
    Suma, M. N.
    Kumar, Manoj K. M.
    Ward, John
    2018 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC): DISCOVERING NEW HORIZONS IN INSTRUMENTATION AND MEASUREMENT, 2018, : 1801 - 1806
  • [45] Fluorescent particles for non-intrusive surface flow observations
    Tauro, F.
    Grimaldi, S.
    Porfiri, M.
    Petroselli, A.
    FOUR DECADES OF PROGRESS IN MONITORING AND MODELING OF PROCESSES IN THE SOIL-PLANT-ATMOSPHERE SYSTEM: APPLICATIONS AND CHALLENGES, 2013, 19 : 895 - 903
  • [46] Non-intrusive uncertainty quantification in the simulation of turbulent spray combustion using Polynomial Chaos Expansion: A case study
    Enderle, Benedict
    Rauch, Bastian
    Grimm, Felix
    Eckel, Georg
    Aigner, Manfred
    COMBUSTION AND FLAME, 2020, 213 : 26 - 38
  • [47] Uncertainty Quantification of CMOS Active Filter Circuits: A Non-Intrusive Computational Approach Based on Generalized Polynomial Chaos
    Duman, Mecit Emre
    Suvak, Onder
    IEEE ACCESS, 2020, 8 (08): : 189246 - 189261
  • [48] Non-Intrusive Load Monitoring of Buildings Using Spectral Clustering
    Ghaffar, Muzzamil
    Sheikh, Shakil R.
    Naseer, Noman
    Din, Zia Mohy Ud
    Rehman, Hafiz Zia Ur
    Naved, Muhammad
    SENSORS, 2022, 22 (11)
  • [49] Quantification of uncertainties in brain tissue conductivity in a heterogeneous model of deep brain stimulation using a non-intrusive projection approach
    Schmidt, Christian
    van Rienen, Ursula
    2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2012, : 4136 - 4139
  • [50] Nonlinear Propagation of Orbit Uncertainty Using Non-Intrusive Polynomial Chaos
    Jones, Brandon A.
    Doostan, Alireza
    Born, George H.
    JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2013, 36 (02) : 430 - 444