cratepy.online.crom.asca

Adaptive Self-consistent Clustering Analysis (ASCA).

This module includes the implementation of the Adaptive Self-consistent Clustering Analysis (ASCA), a clustering-based reduced-order model proposed by Ferreira et. al (2022) [1]. Under infinitesimal strains, the Self-consistent Clustering Analysis (SCA) proposed by Liu et. al (2016) [2] is recovered in the absence of clustering adaptivity.

[1]

Ferreira, B.P., Andrade Pires, F.M. and Bessa, M.A. (2022). Adaptivity for clustering-based reduced-order modeling of localized history-dependent phenomena. Comp Methods Appl M, 393 (see here)

[2]

Liu, Z., Bessa, M., and Liu, W.K. (2016). Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials. Comp Methods Appl M, 396:319-341 (see here)

The finite strain extension compatible with multiplicative kinematics of both SCA and ASCA methods is also available as proposed by Ferreira (2022) [3] (see Sections 4.7-4.9). However, the development of an accurate self-consistent scheme compatible with such as a formulation is still under investigation (see Section 4.9).

[3]

Ferreira, B.P. (2022). Towards Data-driven Multi-scale Optimization of Thermoplastic Blends: Microstructural Generation, Constitutive Development and Clustering-based Reduced-Order Modeling. PhD Thesis, University of Porto (see here)

Besides the main class that implements the aforementioned methods, this module also includes a class associated with the reference (fictitious) homogeneous material, which arises in the formulation of the SCA and ASCA, and an interface to implement any self-consistent scheme, required to determine the properties of such a reference material.

Classes

ASCA

Adaptive Self-Consistent Clustering Analysis (ASCA).

ReferenceMaterialOptimizer(ABC)

Elastic reference material properties optimizer interface.

InfinitesimalRegressionSCS(ReferenceMaterialOptimizer)

Infinitesimal strains format regression-based self-consistent scheme.

Functions

abstractmethod(funcobj)	A decorator indicating abstract methods.
assemble_cit(strain_formulation, ...)	Assemble global cluster interaction matrix.

Classes

ABC()	Helper class that provides a standard way to create an ABC using inheritance.
ASCA(strain_formulation, problem_type[, ...])	Adaptive Self-Consistent Clustering Analysis (ASCA).
AdaptivityManager(strain_formulation, ...)	CRVE clustering adaptivity manager.
ClusteringAdaptivityOutput(adapt_file_path, ...)	Clustering adaptivity output.
EffTanOutput(file_path)	Output file: CRVE effective material consistent tangent modulus.
ElasticReferenceMaterial(strain_formulation, ...)	Elastic reference material.
HomResOutput(file_path)	Output file: Homogenized strain/stress results.
IncrementRewinder(rewind_inc, phase_clusters)	Rewind analysis to rewind state increment (initial instant).
InfinitesimalRegressionSCS(...[, is_symmetrized])	Infinitesimal strains format regression-based self-consistent scheme.
LoadingPath(strain_formulation, ...[, ...])	Loading incrementation flow.
RefMatOutput(file_path, strain_formulation, ...)	Output file: Homogeneous (fictitious) reference material data.
ReferenceMaterialOptimizer(...)	Elastic reference material properties optimizer interface.
RewindManager(rewind_state_criterion, ...[, ...])	Manage analysis rewind operations and evaluate analysis rewind criteria.
VTKOutput(type, version, byte_order, format, ...)	VTK output.
VoxelsOutput(voxout_file_path, ...)	Output file: Voxels material-related output.