2014
DOI: 10.1093/mnras/stu114
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KROME - a package to embed chemistry in astrophysical simulations

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Cited by 240 publications
(291 citation statements)
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References 101 publications
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“…It leads to a significant temperature reduction in regions of relatively high H 2 mass fraction. Finally, the overall characteristics of chemothermal evolution obtained with NIRVANA agree well with the behavior observed in Grassi et al (2014) 9 .…”
Section: Nsupporting
confidence: 79%
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“…It leads to a significant temperature reduction in regions of relatively high H 2 mass fraction. Finally, the overall characteristics of chemothermal evolution obtained with NIRVANA agree well with the behavior observed in Grassi et al (2014) 9 .…”
Section: Nsupporting
confidence: 79%
“…adopted accompanied by all the thermal processes summarized in Table B.1. The chemistry model is that used in Grassi et al (2014) who performed the same Riemann problem to check their implementation of KROME in conjunction with the astrophysics codes RAMSES (Teyssier 2002) and FLASH (Fryxell et al 2000). The initial conditions are set up on a computational domain x = [0, 1 pc] discretized by 1000 equidistant grid cells.…”
Section: One-dimensional Riemann Problemmentioning
confidence: 99%
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“…It contains a wide variety of physics modules, making it suitable for many different astrophysical applications. We use a modified version of ENZO 2.3, replacing the chemistry implementation by a customized build of the KROME chemistry package (Grassi et al 2014), as discussed in the following subsections. The hydrodynamical equations are solved using the MUSCL scheme, which is a second-order accurate extension of Godunov's method.…”
Section: Numerical Methodology and Simulation Setupmentioning
confidence: 99%
“…As we mentioned above, this may not be the case on a dust-grain surface under particular conditions; hence, using the rate-equation approach to describe interstellar surface chemistry can lead to large errors when compared with results using more realistic stochastic techniques. The main reason why modelers persist with such a method is the convenience, stability, and the rather fast numerical performance of the pure chemical kinetics codes, even for reaction networks which consist of thousands of reactions involving hundreds of molecules (e.g., Dalgarno and Black 1976;Leung et al 1984;D'Hendecourt et al 1985;Brown and Charnley 1990;Hasegawa et al 1992;Bergin et al 1995;Millar et al 1997;Aikawa et al 1996;Willacy et al 1998;Semenov et al 2010;Agúndez and Wakelam 2013;Albertsson et al 2013;McElroy et al 2013;Grassi et al 2014). As an indication, rate equations require CPU time of ∼1-60 seconds.…”
Section: Outline Of a Generic Gas-grain Codementioning
confidence: 99%