Model Independent Chemical Module. MICM can be used to configure and solve atmospheric chemistry systems.
Copyright (C) 2018-2024 National Center for Atmospheric Research
Note MICM 3.x.x is part of a refactor and may include breaking changes across minor revision numbers and partially implemented features
To build and install MICM locally, you must have CMake installed on your machine.
Open a terminal window, navigate to a folder where you would like the MICM files to exist, and run the following commands:
git clone https://github.com/NCAR/micm.git
cd micm
mkdir build
cd build
ccmake ..
sudo make install -j 8
To run the tests:
make test
If you would later like to uninstall MICM, you can run
sudo make uninstall
from the build/
directory.
There are multiple options for running micm. You can use json to configure a solver, llvm to JIT-compile solvers on CPUs or cuda-based solvers to solve chemistry on GPUs. Please read our docs to learn how to enable these options.
You must have Docker Desktop installed and running. With Docker Desktop running, open a terminal window. To build the latest MICM release, run the following command to start the MICM container:
docker run -it ghcr.io/ncar/micm:release bash
To build the latest pre-release version of MICM, instead run:
git clone https://github.com/NCAR/micm.git
cd micm
docker build -t micm -f docker/Dockerfile .
docker run -it micm bash
Inside the container, you can run the MICM tests from the /build/
folder:
cd /build/
make test
A simple driver for MICM is built with the library and can be used to solve a chemical system for given initial conditions over one time step.
Just pass the driver the path to the folder containing a valid JSON mechanism configuration and the path to a CSV file holding the initial conditions.
Several example mechanisms and sets of conditions can be found in the
/examples/configs/
folder.
You can use them like this:
micm examples/configs/chapman examples/configs/chapman/initial_conditions.csv
The output should be:
time, O, O1D, O2, O3
0, 0.00e+00, 0.00e+00, 7.50e-01, 8.10e-06
60, 2.57e-12, 3.49e-22, 7.50e-01, 8.10e-06
The following example solves the fictitious chemical system:
foo --k1--> 0.8 bar + 0.2 baz
foo + bar --k2--> baz
The k1
and k2
rate constants are for Arrhenius reactions. See the MICM documentation for details on the types of reactions available in MICM and how to configure them.
To solve this system save the following code in a file named foo_chem.cpp
:
#include <iomanip>
#include <iostream>
#include <micm/process/arrhenius_rate_constant.hpp>
#include <micm/solver/rosenbrock.hpp>
using namespace micm;
int main(const int argc, const char *argv[])
{
auto foo = Species{ "Foo" };
auto bar = Species{ "Bar" };
auto baz = Species{ "Baz" };
Phase gas_phase{ std::vector<Species>{ foo, bar, baz } };
System chemical_system{ SystemParameters{ .gas_phase_ = gas_phase } };
Process r1 = Process::create()
.reactants({ foo })
.products({ Yield(bar, 0.8), Yield(baz, 0.2) })
.rate_constant(ArrheniusRateConstant({ .A_ = 1.0e-3 }))
.phase(gas_phase);
Process r2 = Process::create()
.reactants({ foo, bar })
.products({ Yield(baz, 1) })
.rate_constant(ArrheniusRateConstant({ .A_ = 1.0e-5, .C_ = 110.0 }))
.phase(gas_phase);
std::vector<Process> reactions{ r1, r2 };
RosenbrockSolver<> solver{ chemical_system, reactions, RosenbrockSolverParameters::three_stage_rosenbrock_parameters() };
State state = solver.GetState();
state.conditions_[0].temperature_ = 287.45; // K
state.conditions_[0].pressure_ = 101319.9; // Pa
state.SetConcentration(foo, 20.0); // mol m-3
state.PrintHeader();
for (int i = 0; i < 10; ++i)
{
auto result = solver.Solve(500.0, state);
state.variables_ = result.result_;
state.PrintState(i*500);
}
return 0;
}
To build and run the example using GNU (assuming the default install location):
g++ -o foo_chem foo_chem.cpp -I/usr/local/micm-3.3.1/include -std=c++20
./foo_chem
Output:
time, Bar, Baz, Foo
0, 5.90e+00, 1.91e+00, 1.18e+01
500, 9.05e+00, 3.32e+00, 6.79e+00
1000, 1.07e+01, 4.21e+00, 3.83e+00
1500, 1.17e+01, 4.74e+00, 2.14e+00
2000, 1.22e+01, 5.04e+00, 1.19e+00
2500, 1.24e+01, 5.21e+00, 6.58e-01
3000, 1.26e+01, 5.31e+00, 3.64e-01
3500, 1.27e+01, 5.36e+00, 2.01e-01
4000, 1.27e+01, 5.39e+00, 1.11e-01
4500, 1.28e+01, 5.41e+00, 6.13e-02
MICM is part of the MUSICA project and can be cited by reference to the MUSICA vision paper. The BibTeX entry below can be used to generate a citation for this.
@Article { acom.software.musica-vision,
author = "Gabriele G. Pfister and Sebastian D. Eastham and Avelino F. Arellano and Bernard Aumont and Kelley C. Barsanti and Mary C. Barth and Andrew Conley and Nicholas A. Davis and Louisa K. Emmons and Jerome D. Fast and Arlene M. Fiore and Benjamin Gaubert and Steve Goldhaber and Claire Granier and Georg A. Grell and Marc Guevara and Daven K. Henze and Alma Hodzic and Xiaohong Liu and Daniel R. Marsh and John J. Orlando and John M. C. Plane and Lorenzo M. Polvani and Karen H. Rosenlof and Allison L. Steiner and Daniel J. Jacob and Guy P. Brasseur",
title = "The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA)",
journal = "Bulletin of the American Meteorological Society",
year = "2020",
publisher = "American Meteorological Society",
address = "Boston MA, USA",
volume = "101",
number = "10",
doi = "10.1175/BAMS-D-19-0331.1",
pages= "E1743 - E1760",
url = "https://journals.ametsoc.org/view/journals/bams/101/10/bamsD190331.xml"
}
We welcome contributions and feedback from anyone, everything from updating the content or appearance of the documentation to new and cutting edge science.
-
- Anyone interested in scientific collaboration which would add new software functionality should read the MUSICA software development plan.
-
- Please read this through to you understand the expectations with how to interact with this project.
-
- Before submiitting a PR, please thouroughly read this to you understand our expectations. We reserve the right to reject any PR not meeting our guidelines.
Please see the MICM documentation for detailed installation and usage instructions.
Copyright (C) 2018-2024 National Center for Atmospheric Research