Forward, tangent linear, and adjoint Runge-Kutta methods in KPP-2.2. This paper presents the new stiff solvers of the new version 2.2 of the Kinetic PreProcessor (KPP). Taking a set of chemical reactions and their rate coefficients as input, KPP generates Fortran90, Fortran77, Matlab, or C code for the temporal integration of the kinetic system. Efficiency is obtained by carefully exploiting the sparsity structures of the Jacobian and of the Hessian. A set of integration methods was added to the comprehensive suite of stiff numerical integrators. Moreover, KPP is now ready do be used to generate the tangent linear model, as well as the continuous and discrete adjoint models of the chemical system to do sensitivity analysis.
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References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Alexe, Mihai; Sandu, Adrian: Forward and adjoint sensitivity analysis with continuous explicit Runge-Kutta schemes (2009)
- Cheng, Haiyan; Sandu, Adrian: Efficient uncertainty quantification with the polynomial chaos method for stiff systems (2009)
- Carmichael, Gregory R.; Sandu, Adrian; Chai, Tianfeng; Daescu, Dacian N.; Constantinescu, Emil M.; Tang, Youhua: Predicting air quality: Improvements through advanced methods to integrate models and measurements (2008)
- Constantinescu, Emil M.; Sandu, Adrian; Carmichael, Gregory R.: Modeling atmospheric chemistry and transport with dynamic adaptive resolution (2008)
- Sandu, Adrian; Zhang, Lin: Discrete second order adjoints in atmospheric chemical transport modeling (2008)
- Miehe, Philipp; Sandu, Adrian: Forward, tangent linear, and adjoint Runge-Kutta methods in KPP-2.2 (2006)
- Sandu, Adrian: Targeted observations for atmospheric chemistry and transport models (2006)
- Sandu, Adrian; Daescu, Dacian N.; Carmichael, Gregory R.; Chai, Tianfeng: Adjoint sensitivity analysis of regional air quality models (2005)
- Carmichael, Gregory R.; Daescu, Dacian N.; Sandu, Adrian; Chai, Tianfeng: Computational aspects of chemical data assimilation into atmospheric models (2003)