Trajectory Looping: Difference between revisions
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===Related methods and applications=== | ===Related methods and applications=== | ||
A conceptually equivalent approach has been published nearly in parallel: | A conceptually equivalent approach has been published nearly in parallel: | ||
* <span class="pmbm">Bednarek X</span>, <span class="pmbm">Martin S</span>, <span class="pmbm">Ndiaye A</span>, <span class="pmbm">Peres V</span>, <span class="pmbm">Bonnefoy O</span>. '''Extrapolation of DEM simulations to large time scale. Application to the mixing of powder in a conical screw mixer''', ''Chem Eng Sci'' <u>197</u>:223–234 (2019) [https://doi.org/10.1016/j.ces.2018.12.022 CrossRef] | * <span class="pmbm">Bednarek X</span>, <span class="pmbm">Martin S</span>, <span class="pmbm">Ndiaye A</span>, <span class="pmbm">Peres V</span>, <span class="pmbm">Bonnefoy O</span>. '''Extrapolation of DEM simulations to large time scale. Application to the mixing of powder in a conical screw mixer''', ''Chem Eng Sci'' <u>197</u>:223–234 (2019) [https://doi.org/10.1016/j.ces.2018.12.022 CrossRef] | ||
An interesting application of trajectory looping: | An interesting application of trajectory looping: | ||
* <span class="pmbm">Lichtenegger T</span> and <span class="pmbm">Miethlinger T</span>. '''On the connection between Lagrangian and Eulerian metrics for recurrent particulate flows''', ''Phys | * <span class="pmbm">Lichtenegger T</span> and <span class="pmbm">Miethlinger T</span>. '''On the connection between Lagrangian and Eulerian metrics for recurrent particulate flows''', ''Phys Fluids'' <u>32</u>:113308 (2020) [https://doi.org/10.1063/5.0025597 CrossRef] |
Revision as of 09:44, 17 November 2020
With trajectory looping one can use a single trajectory, generated
by a prior simulation of diffusive motions of molecules, to sample
chemical kinetic processes on time scales that are several orders
of magnitude longer than the duration of the diffusive trajectory.
A wyvern eating its own tail (public domain).
Reference
- Żuk PJ, Kochańczyk M, Lipniacki T. Sampling rare events in stochastic reaction–diffusion systems within trajectory looping, Physical Review E 98:022401 (2018) CrossRef | PDF-ms
Downloads
- Looper – an implementation of the method in C++
- Example input trajectory (~2.4 GB, parameters: N=500, φ=20%, ε=0.05, θ=100τB)
On the implementation
Trajectory looping can be implemented in two different but equivalent ways. One may first perform multiple joins of the base contacts trajectory and in this manner obtain a looped contacts trajectory of a desired length without considering chemical events. The looped contacts trajectory, consisting of the base contacts trajectory and index maps resulting from optimal assignments, provides a complete information necessary for a subsequent simulation of chemical trajectory (this way has been presented in Figure 1 in the article).
The second way consists in interweaving the simulation of chemical events with joins of the base contacts trajectory. This way can be more convenient for some applications because what is expanding in computer memory is the ultimate looped chemical trajectory, which is of direct interest, and not the intermediary looped contacts trajectory, whose desired length may be hard to guess. When using the second way, a stop condition can be defined depending on the chemical state of the system or based on the already collected chemical event statistics.
Looper has been written according to the second way.
Format of input trajectory
Looper reads in binary trajectories. They are expected to have a header consisting of:
- the number of molecules (4-byte signed integer),
- time step (double-precision real number),
- length of the edge of the cubical simulation box (positive value) or three (negative) values for lengths of non-cubical but cuboidal box (double-precision real number(s)).
The body of the trajectory file contains multiple frames. A single frame consists of:
- current step index (4-byte signed integer),
- current time (double-precision real number),
- an ordered series of molecule coordinates.
Molecule coordinates comprise six values (six double-precision real numbers), out of which three first describe absolute molecule position (x, y, z) and the remaining three are only placeholders intended to be used in future to describe molecule orientation. Currently, they are ignored (and thus can be simply, e.g., three zeros).
Modifying the source code
In order to change simulation parameters or define a new system of chemical reactions, one has to modify and recompile the source code of Looper.
Defining a reaction system
In file Chemistry.hpp there are already two systems of reactions: ChemistrySystem1
and ChemistrySystem2
, which correspond to the monostable and the bistable
reaction systems, respectively, analyzed in the article.
To define and use a new system of reactions, one has to create a class that
inherits from the StochasticChemistry
class. The subclass should set initial
conditions in its constructor and should provide a match_events()
method.
To provide a new system of reactions, please follow the conventions used to
implement ChemistrySystem1
and ChemistrySystem2
and associated enums for molecule species. The chemistry to be used in the simulator
is pointed in Settings.hpp with a type alias chemistry_t
.
Various settings
Simulation duration:
kTimeEnd
in Settings.hpp.
Chemical rates and time scaling:
kLambda
in Settings.hpp.
Contact diameter:
kSearchRadius
in Settings.hpp.
Skipping frames when writing out:
kWriteToChemStateFileEverySteps
in Settings.hpp
Building
Compiler. A decent and recent C++ compiler that supports C++14 standard is required. The code has been confirmed to compile successfully under Linux with GNU g++ 8.0 and Clang++ 6.0.
Toolchain. Compilation is managed by CMake. To build Looper under Linux, it should be
sufficient to enter the build directory and execute ./build_release.sh
.
Usage
Invoke simply as:
./Looper trajectory chemprefix
Multiple input trajectories.
More than one trajectory file can be read in and used. Multiple files should
be listed consecutively before the last invocation argument, e.g., as:
./Looper traj1.bin traj2.bin traj3.bin chemprefix
The order of the use of multiple trajectories is random. The trajectories should have the same number of molecules and the same time step.
Multiple simulations – seed.
If more than one simulation is to be performed (by setting appropriately
variable kNumOfReplicas
in file Settings.hpp), each simulation is seeded
sequentially starting from the value assigned to kSimulationSeedsBase
(file
Settings.hpp). This value can be overridden by setting the environmental
variable LOOPER_SEED_BASE
prior to Looper invocation.
Multiple simulations – multi-threading.
Multiple simulations of chemical kinetics that use the same base chemical
trajectory can run in parallel. During run-time, the software chooses the
number of threads based on both the kNumOfReplicas
(described above) and
hardware capabilities. If necessary, this behavior can be tweaked manually
using variable kNumOfThreads
(in file Settings.hpp).
Related methods and applications
A conceptually equivalent approach has been published nearly in parallel:
- Bednarek X, Martin S, Ndiaye A, Peres V, Bonnefoy O. Extrapolation of DEM simulations to large time scale. Application to the mixing of powder in a conical screw mixer, Chem Eng Sci 197:223–234 (2019) CrossRef
An interesting application of trajectory looping:
- Lichtenegger T and Miethlinger T. On the connection between Lagrangian and Eulerian metrics for recurrent particulate flows, Phys Fluids 32:113308 (2020) CrossRef