Dimensionality reduction for surrogate model construction for global sensitivity analysis: Comparison between active subspace and local sensitivity analysis

Lin, Keli; Zhou, Zijun; Law, Chung K.; Yang, Bin

doi:10.1016/j.combustflame.2021.111501

Cited by 17 publications

(4 citation statements)

References 63 publications

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“…Local sensitivity coefficient is defined by S i = x i y ∂ y ∂ x i where x i is the i th input parameter and y is the model output. Global sensitivity indices are computed by active subspace-based surrogate model (ASSM) . The inputs of ASSM (rate coefficients) are first merged to new features whose dimension is much lower than the inputs.…”

Section: Methodsmentioning

confidence: 99%

“…Global sensitivity indices are computed by active subspacebased surrogate model (ASSM). 44 The inputs of ASSM (rate coefficients) are first merged to new features whose dimension is much lower than the inputs. For the four conditions in this work, 45 active parameters are selected as active parameters, and their uncertainties are considered in the following model optimization process.…”

Section: Model Analysis Methodmentioning

confidence: 99%

“…One of the advantages of the ASSM is that all parameters can be investigated during the global sensitivity analysis. Details for ASSM are available in ref . According to the results of sensitivity analyses, parameters whose global sensitivity index or the absolute value of the local sensitivity coefficient is larger than 0.01 are regarded as active parameters.…”

Section: Methodsmentioning

confidence: 99%

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Improving the Predictive Accuracy for Ketene in Diacetyl Laminar Premixed Flames: Experiment and Model Analysis

et al. 2022

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Ketene is an important species in core mechanisms for the combustion of hydrocarbon and oxygenated fuels, but direct experiments with ketene are challenging to conduct due to its high reactivity. Diacetyl can be used as a precursor of ketene, and abundant ketene is present in premixed flames of diacetyl. However, predictions of ketene in diacetyl flames with previous models have significant uncertainties. The study of Sun et al. [SunW.WangJ.HuangC.HansenN.YangB. Sun, W. Wang, J. Huang, C. Hansen, N. Yang, B. Combust. Flame20192051121] shows that the flame structure measurements should be performed under certain conditions to improve the predictive accuracy of ketene in diacetyl flames. In this work, the structures of three laminar premixed flames of diacetyl under atmospheric pressure in a range of equivalence ratios are examined with flame-sampling molecular-beam mass spectrometry (MBMS). With the new experimental data and the data available in literature, Bayesian analysis is performed to optimize the kinetic model. The obtained optimized model is compared with the original one, and the results show that the optimized model agrees better with the experimental data than the original one. The uncertainties of the rate coefficients of some key reactions are constrained with these experimental data, which eventually leads to smaller modeling uncertainties for ketene concentrations under studied conditions.

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Section: Methodsmentioning

confidence: 99%

Section: Model Analysis Methodmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Improving the Predictive Accuracy for Ketene in Diacetyl Laminar Premixed Flames: Experiment and Model Analysis

et al. 2022

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“…Hence, The developments of steady equations promote to identify the main parameters influencing the state variables, making sensitivity analysis easier to conduct. In this study, the local sensitivity analysis (LSA) method is used since the analytic expression of the output variable was known (Lin et al, 2021). The LSA can be seen as a particular case of the OAT approach.…”

Section: Production Of Biomass and Co-products (I) Concentration Of Xpmentioning

confidence: 99%

Steady state modeling of autotrophic membrane bioreactor – a new approach to quantify biomass

Gasmi¹,

Heran²,

Elboughdiri³

et al. 2023

AGJSR

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PurposeThe main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.Design/methodology/approachModeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.FindingsThe developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.Originality/valueThese results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

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Radial basis function-assisted adaptive differential evolution using cooperative dual-phase sampling for high-dimensional expensive optimization problems

Shi

et al. 2022

Struct Multidisc Optim

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Dimensionality reduction for surrogate model construction for global sensitivity analysis: Comparison between active subspace and local sensitivity analysis

Cited by 17 publications

References 63 publications

Improving the Predictive Accuracy for Ketene in Diacetyl Laminar Premixed Flames: Experiment and Model Analysis

Improving the Predictive Accuracy for Ketene in Diacetyl Laminar Premixed Flames: Experiment and Model Analysis

Steady state modeling of autotrophic membrane bioreactor – a new approach to quantify biomass

Radial basis function-assisted adaptive differential evolution using cooperative dual-phase sampling for high-dimensional expensive optimization problems

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