Kinetics parameter optimization of hydrocarbon fuels via neural ordinary differential equations
Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating
complex combustion phenomena. In this study, a neural ordinary differential equation …
complex combustion phenomena. In this study, a neural ordinary differential equation …
Automatic validation and analysis of predictive models by means of big data and data science
Validation is an essential procedure in the development of a predictive model in several
engineering fields. In addition, recent data analysis techniques and the increasing …
engineering fields. In addition, recent data analysis techniques and the increasing …
Bayesian calibration of a methane-air global scheme and uncertainty propagation to flame-vortex interactions
Simplified chemistry models are commonly used in reactive computational fluid dynamics
(CFD) simulations to alleviate the computational cost. Uncertainties associated with the …
(CFD) simulations to alleviate the computational cost. Uncertainties associated with the …
Uncertainty quantification and data consistency analysis for the development of hydrogen and syngas oxidation model
The exponential growth of contemporary chemical kinetics data coupled with the potential
inherent high uncertainty poses significant challenges for developing chemical kinetic …
inherent high uncertainty poses significant challenges for developing chemical kinetic …
Hybrid Algorithm for Development of Reduced Skeletal Kinetic Mechanisms with Specific Species Targeting
AB Zarch, K Mazaheri, M Khademorezaeian - ACS omega, 2024 - ACS Publications
A novel algorithm is introduced to reduce the number of detailed kinetic mechanisms. The
algorithm uniquely employs a classification of species and a defined parameter that …
algorithm uniquely employs a classification of species and a defined parameter that …
Does a reduced model reproduce the uncertainty of the original full-size model?
The present study addresses the title question by taking a detailed mechanism of a concrete
combustion system, syngas ignition, deriving from it three reduced models with different …
combustion system, syngas ignition, deriving from it three reduced models with different …
A shock-tube and modeling study of syngas ignition delay times in rich CO2 environment at elevated pressures
W Li, C Zou, H Yao - Combustion and Flame, 2023 - Elsevier
Oxy-fuel combustion techniques are crucial for fossil fuel power plants with substantially
reduced greenhouse gas emission. The chemical effect of CO 2 as a reactant/product or a …
reduced greenhouse gas emission. The chemical effect of CO 2 as a reactant/product or a …
Bayesian Inference and Experimental Design of Combustion Kinetic Models
H Chen - 2024 - dspace.mit.edu
In combustion kinetic model calibration, researchers usually use experimental data to
reduce the uncertainty of kinetic parameters, and Bayesian inference is the most common …
reduce the uncertainty of kinetic parameters, and Bayesian inference is the most common …
[图书][B] Quantifying the agreement between computational models and experimental data under uncertainty
AS Hegde - 2020 - search.proquest.com
Bound-to-bound data collaboration (abbreviated B2BDC) is a deterministic optimization-
based approach for uncertainty quantification. The framework combines models and data …
based approach for uncertainty quantification. The framework combines models and data …
[PDF][PDF] A Complete Bibliography of Publications in SIAM slash ASA Journal on Uncertainty Quantification
NHF Beebe - 2024 - 155.101.98.136
CHKP19, DMS23, Dia23, DY21, EFF+23, ESS15, EDA23, GP18, GBC+14, GGS23, GG24,
GP24, GK19, HS21, HSAY20, HQS21, HN17, Hos17, HKZ18a, HKZ18b, KLLU19, KBS13 …
GP24, GK19, HS21, HSAY20, HQS21, HN17, Hos17, HKZ18a, HKZ18b, KLLU19, KBS13 …