Documentation for Release 2024.2
Dynamic Ventilation
This tutorial is automatically generated from TestDynamicVentilationTutorial.hpp at revision 0a2ab4e09adf. Note that the code is given in full at the bottom of the page.
An example showing how to simulate ventilation over a full breathing cycle.
In this tutorial we demonstrate the use of !DynamicVentilationProblem to simulate breathing over a single breathing cycle. Acini are represented by linear balloon models and the simulation is driven by an oscillating pleural pressure. Simulation results are written to a VTK unstructured grid file for visualisation.
NB. UMFPACK or KLU is required for this test to execute. The test has a reasonably long run time (~6 minutes on a quad core i7). Progress can be followed by watching the file $CHASTE_TEST_OUTPUT/TestDynamicVentilationTutorial/progress_status.txt
The usual headers are included
!DynamicVentilationProblem does most of the work in calculating a ventilation distribution.
A number of acinar models could be used. Here we include the simplest possible model: a linear elastic balloon.
Note that this tutorial only works with UMFPACK or KLU – we need to warn the user if it’s not installed.
!DynamicVentilationProblem uses the Petsc solver library. This setups up Petsc ready for use.
Acinar Unit Factory
!DynamicVentilationProblem couples a ventilation model on an airway tree to acinar dynamics models. The distal ends of the airway tree have an acinar model associated with them. These models are specified by subclassing !AbstractAcinarUnitFactory as shown here.
!DynamicVentilationProblem calls this method once for each terminal node. The user must create, configure and return an Acinar model. The created model is subsequently used in the ventilation simulation.
Here we use the simplest possible acinar model: a linear elastic balloon.
The acinar model can be configured in different ways. Here we simply set a constant spatially homogeneous compliance and a spatially homogeneous initial volume. However, things like gravitational gradients can easily be configured here by altering the compliance (or other parameters) based on the nodal location (obtained from pNode->rGetLocation()).
!DynamicVentilationProblems are driven by a change in Pleural pressure. !DynamicVentilationProblem calls this method to determine what the current pleural pressure is. Here we specify a spatially homogeneous oscillating pressure in the tidal breathing range.
Define the test
!DynamicVentilationProblem is not (yet) parallel.
IMPORTANT
See the note below about use of direct solvers. This tutorial cannot be run without a direct solver.
First we need to create an acinar unit factory object from the class we specified earlier. An acinar compliance is specified in Pa/m^3^. The given value is roughly equal to a lung compliance of 0.1 cmH2O/L (assuming there are 30000 acini).
We now create a !DynamicVentilationProblem object that does most of the work in simulating ventilation. The factory we just created is passed to the constructor along with the location of an airways mesh.
We assign a zero pressure boundary condition at the entrance to the trachea.
The mesh we are using is specified in millimetres rather than in metres.
The mesh we are using specifies airway radii on the edges rather than the nodes.
Tell the solver to use a more accurate Pedley based dynamic resistance scheme.
Here we tell the solver the time step size to use. The given value will typically result in a stable numerical scheme. However, users should assess the time step size required to achieve a suitable level of numerical convergence when setting up their own simulations.
Tell the solver where to write its output to. The solver will also write out a progress_status.txt file to this directory to allow the user to monitor progress. We specify output in VTK format for easy visualisation.
Tell the solver how often to write output. Here we ask for output every 5 time steps.
Specify when to end the simulation (in seconds) and solve. Note that after solving it is possible to set a new end time and solve again if needed.
For execution speed reasons we only simulate an inspiration. Try setting a later end time to see a full breathing cycle.
It is now possible to analyse the data produced by the ventilation simulation. Typically this will be done using the output written to disk and an external program. This simulation will output a file in $CHASTE_TEST_OUTPUT/TestDynamicVentilationTutorial/tidal_breathing.vtu for easy visualisation. For demonstration purposes we perform a simple check of the final lung volume here.
IMPORTANT: Using UMFPACK/KLU
Ventilation problems lead to very badly conditioned matrices. Iterative solvers such as GMRES can stall on these matrices. When running problems on large airway trees it is vital that to change the linear solver to a direct solver such as UMFPACK or KLU. UMFPACK and KLU are not pre-requisites for installing Chaste, hence this is not (currently) the default linear solver for ventilation problems.
‘‘UMFPACK or KLU should be considered pre-requisites for large ventilation problems’’
To use UMFPACK or KLU, you need to have PETSc installed with UMFPACK/KLU.
To switch on UMFPACK or KLU on within chaste, set “ccflags=’-DLUNG_USE_UMFPACK’” or
“ccflags=’-DLUNG_USE_KLU’” in your local.py or
open the file lung/src/ventilation/MatrixVentilationProblem.hpp
and uncomment the line
#define LUNG_USE_UMFPACK near the top of the file.