Paper Info
Title
Computationally Efficient Atmospheric Chemical Kinetic Modeling by Means of High Dimensional Model Representation (HDMR)
Abstract
This paper presents an application of the efficient High Dimensional Model Representation (HDMR) method for relievingthe computational burden of chemical kinetic calculations in air quality models. An efficient HDMR for these types of calculations is based on expressing a kinetic output variable (e.g., a chemical species concentration at a given reaction time) as an expansion of correlated functions consisting of the kinetic input variables (e.g., initial chemical species concentrations). The application of the HDMR method to atmospheric chemistry presented here focuses on a photochemical box model study of complex alkane/NOx/O3 photochemistry. It is shown that the HDMR calculations of multi-species time-concentration profiles can maintain accuracy comparable to the box-model simulations over reasonably wide ranges of initial chemical conditions. Furthermore, the HDMR expansion is about 400 times faster than the original box-model for performing ten thousand Monte Carlo uncertainty propagation runs, while producing very similar probability distributions of model outputs.
Year
DOI
Venue
2001
10.1007/3-540-45346-6_34
LSSC
Keywords
Field
DocType
kinetic modeling,high dimensional model representation,computationally efficient atmospheric chemical,correlation function,reaction time,chemical kinetics,atmospheric chemistry,monte carlo,kinetics,uncertainty propagation,probability distribution
Discrete mathematics,Monte Carlo method,Propagation of uncertainty,Biological system,Chemical species,Simulation,Computer science,Probability distribution,High-dimensional model representation,Atmospheric chemistry,Kinetic energy
Conference
Volume
ISSN
ISBN
2179
0302-9743
3-540-43043-1
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
S. W. Wang100.34
P. G. Georgopoulos200.34
G. Li362.18
H. Rabitz4161.54