Dynamic3D¶
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<thermal solver="Dynamic3D">¶ Corresponding Python class:
thermal.dynamic.Dynamic3D.Attributes: - name (required) – Solver name.
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<geometry>¶ Geometry for use by this solver.
Attributes: - ref (required) – Name of a Cartesian3D geometry defined in the
<geometry>section.
- ref (required) – Name of a Cartesian3D geometry defined in the
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<mesh>¶ Rectangular3D mesh used by this solver.
Attributes: - ref (required) – Name of a Rectangular3D mesh defined in the
<grids>section.
- ref (required) – Name of a Rectangular3D mesh defined in the
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<temperature>¶ Temperature boundary conditions. See subsection Boundary conditions.
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<loop>¶ Configuration of the time-evolution loop.
Attributes: - inittemp – Initial temperature used for the first computation. (float (K), default 300 K)
- timestep – Single-iteration time step. (float (ns), default 0.1 ns)
- rebuildfreq – Number of iterations until the whole matrix is rebuilt. The larger this number is, the more efficient computations are, however it may be less accurate is material parameters strongly depend on temperature. If this parameter is set to zero, matrix is never rebuilt. (int, default 0)
- logfreq – Number of iterations until the computations progress is reported. (int, default 500)
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<matrix>¶ Matrix solver configuration.
Attributes: - algorithm – Algorithm used for solving set of linear positive-definite equations. (
cholesky,gauss, oriterative, default isiterative) - methodparam – Mid-step parameter for implicit finite-difference time discretization. Defaults to ½, which results in the Crank-Nicholson method. 0 makes the method explicit, while 1 results in backward Euler method. (float, default 0.5)
- lumping – This attribute determines whether the mass matrix is lumped or non-lumped (consistent). (bool, default is
yes)
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<iterative>¶ Parameters for iterative matrix solver. PLaSK uses NSPCG package for performing iterations. Please refer to its documentation for explanation of most of the settings.
Attributes: - maxit – Maximum number of iterations. (int, default 1000)
- maxerr – Maximum iteration error. (float, default 1e-6)
- noconv – Desired behavior if the iterative solver does not converge. (
error,warning, orcontinue, default iswarning) - accelerator – Accelerator used for iterative matrix solver. (
cg,si,sor,srcg,srsi,basic,me,cgnr,lsqr,odir,omin,ores,iom,gmres,usymlq,usymqr,landir,lanmin,lanres,cgcr, orbcgs, default iscg) - preconditioner – Preconditioner used for iterative matrix solver. (
rich,jac,ljac,ljacx,sor,ssor,ic,mic,lsp,neu,lsor,lssor,llsp,lneu,bic,bicx,mbic, ormbicx, default isic) - nfact – This number initializes the frequency of partial factorizations. It specifies the number of linear system evaluations between factorizations. The default value is 1, which means that a factorization is performed at every iteration. (int, default 10)
- ndeg – Degree of the polynomial to be used for the polynomial preconditioners. (int, default 1)
- lvfill – Level of fill-in for incomplete Cholesky preconditioners. Increasing this value will result in more accurate factorizations at the expense of increased memory usage and factorization time. (int, default 0)
- ltrunc – Truncation bandwidth to be used when approximating the inverses of matrices with dense banded matrices. An increase in this value means a more accurate factorization at the expense of increased storage. (int, default 0)
- omega – Relaxation parameter. (float, default 1.0)
- nsave – The number of old vectors to be saved for the truncated acceleration methods. (int, default 5)
- nrestart – The number of iterations between restarts for the restarted acceleration methods. (int, default 100000)
Preconditioner choices:¶ richRichardson’s method jacJacobi method ljacLine Jacobi method ljacxLine Jacobi method (approx. inverse) sorSuccessive Overrelaxation ssorSymmetric SOR (can be used only with SOR accelerator) icIncomplete Cholesky (default) micModified Incomplete Cholesky lspLeast Squares Polynomial neuNeumann Polynomial lsorLine SOR lssorLine SSOR llspLine Least Squares Polynomial lneuLine Neumann Polynomial bicBlock Incomplete Cholesky (ver. 1) bicxBlock Incomplete Cholesky (ver. 2) mbicModified Block Incomplete Cholesky (ver. 1) mbicxModified Block Incomplete Cholesky (ver. 2) Accelerator choices:¶ cgConjugate Gradient acceleration (default) siChebyshev acceleration or Semi-Iteration sorSuccessive Overrelaxation (can use only SOR preconditioner) srcgSymmetric Successive Overrelaxation Conjugate Gradient Algorithm (can use only SSOR preconditioner) srsiSymmetric Successive Overrelaxation Semi-Iteration Algorithm (can use only SSOR preconditioner) basicBasic Iterative Method meMinimal Error Algorithm cgnrConjugate Gradient applied to the Normal Equations lsqrLeast Squares Algorithm odirORTHODIR, a truncated/restarted method useful for nonsymmetric systems of equations ominORTHOMIN, a common truncated/restarted method used for nonsymmetric systems oresORTHORES, another truncated/restarted method for nonsymmetric systems iomIncomplete Orthogonalization Method gmresGeneralized Minimal Residual Method usymlqUnsymmetric LQ usymqrUnsymmetric QR landirLanczos/ORTHODIR lanminLanczos/ORTHOMIN or Biconjugate Gradient Method lanresLanczos/ORTHORES or “two-sided” Lanczos Method cgcrConstrained Generalized Conjugate Residual Method bcgsBiconjugate Gradient Squared Method
- algorithm – Algorithm used for solving set of linear positive-definite equations. (
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