CHEMKIN
CHEMKIN™, a software suite used worldwide in the microelectronics, combustion, and chemical processing industries, is one of the most successful and enduring products to come out of Sandia National Laboratories. CHEMKIN is a set of flexible and powerful tools for incorporating complex chemical kinetics into simulations of reacting flow. Using CHEMKIN, researchers are able to investigate thousands of reaction combinations to develop a comprehensive understanding of a particular process, which might involve multiple chemical species, concentration ranges, and gas temperatures. Since its origins nearly 30 years ago, CHEMKIN has enabled significant strides in the modeling of complex chemical processes, such as combustion. It has become the standard for anyone involved in chemistry modeling and chemically reacting flow modeling. It has also become an important educational tool in chemical engineering, mechanical engineering and chemistry curricula.
Keywords for this software
References in zbMATH (referenced in 199 articles )
Showing results 1 to 20 of 199.
Sorted by year (- Dietrich, Felix; Kooshkbaghi, Mahdi; Bollt, Erik M.; Kevrekidis, Ioannis G.: Manifold learning for organizing unstructured sets of process observations (2020)
- Owen, L. D.; Gao, X.; Guzik, S. M.: Techniques for improving monotonicity in a fourth-order finite-volume algorithm solving shocks and detonations (2020)
- Yang, Tianpeng; Wang, Jiangfeng; Yang, Liming; Shu, Chang: Development of multi-component generalized sphere function based gas-kinetic flux solver for simulation of compressible viscous reacting flows (2020)
- You, Jiaping; Yang, Yue: Modelling of the turbulent burning velocity based on Lagrangian statistics of propagating surfaces (2020)
- Lacaze, Guilhem; Schmitt, Thomas; Ruiz, Anthony; Oefelein, Joseph C.: Comparison of energy-, pressure- and enthalpy-based approaches for modeling supercritical flows (2019)
- Irfan, Muhammad; Muradoglu, Metin: A front tracking method for particle-resolved simulation of evaporation and combustion of a fuel droplet (2018)
- Jeon, Min-Kyu; Kim, Nam Il: Fuel pyrolysis and its effects on soot formation in non-premixed laminar jet flames of methane, propane, and DME (2018)
- Kim, Yu Jeong; Lee, Bok Jik; Im, Hong G.: Dynamics of lean premixed flames stabilized on a meso-scale bluff-body in an unconfined flow field (2018)
- Musa, Omer; Chen, Xiong; Zhou, Chang-sheng; Li, Ying-kun; Liao, Wen-He: Investigations on the influence of swirl intensity on solid-fuel ramjet engine (2018)
- Xie, Qing; Xiao, Zhixiang; Ren, Zhuyin: A spectral radius scaling semi-implicit iterative time stepping method for reactive flow simulations with detailed chemistry (2018)
- Bryan W. Weber, Kyle E. Niemeyer: ChemKED: a human- and machine-readable data standard for chemical kinetics experiments (2017) arXiv
- Fooladgar, Ehsan; Chan, C. K.; Nogenmyr, Karl-Johan: An accelerated computation of combustion with finite-rate chemistry using LES and an open source library for in-situ-adaptive tabulation (2017)
- Kang, Xin; Gollan, Rowan J.; Jacobs, Peter A.; Veeraragavan, Ananthanarayanan: On the influence of modelling choices on combustion in narrow channels (2017)
- Smirnov, N. N.; Nikitin, V. F.; Stamov, L. I.; Nerchenko, V. A.; Tyrenkova, V. V.: Numerical simulations of gaseous detonation propagation using different supercomputing architechtures (2017)
- Carpio, Jaime; Prieto, Juan Luis; Vera, Marcos: A local anisotropic adaptive algorithm for the solution of low-Mach transient combustion problems (2016)
- Furfaro, Damien; Saurel, Richard: Modeling droplet phase change in the presence of a multi-component gas mixture (2016)
- MacArt, Jonathan F.; Mueller, Michael E.: Semi-implicit iterative methods for low Mach number turbulent reacting flows: operator splitting versus approximate factorization (2016)
- Motheau, E.; Abraham, J.: A high-order numerical algorithm for DNS of low-Mach-number reactive flows with detailed chemistry and quasi-spectral accuracy (2016)
- Yonkee, Nathan; Sutherland, James C.: PoKiTT: exposing task and data parallelism on heterogeneous architectures for detailed chemical kinetics, transport, and thermodynamics calculations (2016)
- Zhang, Y. F.; Vicquelin, R.: Controlling bulk Reynolds number and bulk temperature in channel flow simulations (2016)