weac.analysis.criteria_evaluator module

CriteriaEvaluator facade — public entry for fracture-criteria evaluations.

Envelope, coupled-criterion, and steady-state logic live in sibling modules; this class holds CriteriaConfig and delegates.

class weac.analysis.criteria_evaluator.CoupledCriterionHistory(skier_weights=<factory>, crack_lengths=<factory>, incr_energies=<factory>, sigma_maxs=<factory>, tau_maxs=<factory>, g_deltas=<factory>, dist_maxs=<factory>, dist_mins=<factory>)[source]

Bases: object

Stores the history of the coupled criterion evaluation.

Attributes:

skier_weightslist[float]

Skier weights evaluated during the iteration.

crack_lengthslist[float]

Crack lengths evaluated during the iteration.

incr_energieslist[np.ndarray]

Incremental energy release rates for each evaluated state.

sigma_maxslist[float]

Maximum normal stress values in kPa for each evaluated state. After iteration 1, values reuse the iteration-1 sample (uncracked rasterize is skipped; see main-loop stress bookkeeping).

tau_maxslist[float]

Maximum shear stress values in kPa for each evaluated state. After iteration 1, values reuse the iteration-1 sample.

g_deltaslist[float]

Fracture toughness envelope values for each evaluated state.

dist_maxslist[float]

Maximum distances to the stress envelope for each evaluated state. After iteration 1, values reuse the iteration-1 sample.

dist_minslist[float]

Minimum distances to the stress envelope for each evaluated state. After iteration 1, values reuse the iteration-1 sample.

skier_weights: list[float]
crack_lengths: list[float]
incr_energies: list[ndarray]
sigma_maxs: list[float]
tau_maxs: list[float]
g_deltas: list[float]
dist_maxs: list[float]
dist_mins: list[float]
__init__(skier_weights=<factory>, crack_lengths=<factory>, incr_energies=<factory>, sigma_maxs=<factory>, tau_maxs=<factory>, g_deltas=<factory>, dist_maxs=<factory>, dist_mins=<factory>)
Parameters:

  • skier_weights (list[float])

  • crack_lengths (list[float])

  • incr_energies (list[ndarray])

  • sigma_maxs (list[float])

  • tau_maxs (list[float])

  • g_deltas (list[float])

  • dist_maxs (list[float])

  • dist_mins (list[float])

Return type:

None

Parameters:

  • skier_weights (list[float])

  • crack_lengths (list[float])

  • incr_energies (list[ndarray])

  • sigma_maxs (list[float])

  • tau_maxs (list[float])

  • g_deltas (list[float])

  • dist_maxs (list[float])

  • dist_mins (list[float])

class weac.analysis.criteria_evaluator.CoupledCriterionResult(converged, message, self_collapse, pure_stress_criteria, critical_skier_weight, initial_critical_skier_weight, crack_length, g_delta, dist_ERR_envelope, iterations, history, final_system, max_dist_stress, min_dist_stress)[source]

Bases: object

Holds the results of the coupled criterion evaluation.

Attributes:

convergedbool

Whether the algorithm converged.

messagestr

The message of the evaluation.

self_collapsebool

Whether the system collapsed.

pure_stress_criteriabool

Whether the pure stress criteria is satisfied.

critical_skier_weightfloat

The critical skier weight.

initial_critical_skier_weightfloat

The initial critical skier weight.

crack_lengthfloat

The crack length.

g_deltafloat

The g_delta value.

dist_ERR_envelopefloat

The distance to the ERR envelope.

iterationsint

The number of iterations.

historyCoupledCriterionHistory

The history of the evaluation.

final_systemSystemModel

The final system model.

max_dist_stressfloat

Maximum distance to the stress envelope for the returned final_system geometry.

min_dist_stressfloat

Minimum distance to the stress envelope for the returned final_system geometry.

converged: bool
message: str
self_collapse: bool
pure_stress_criteria: bool
critical_skier_weight: float
initial_critical_skier_weight: float
crack_length: float
g_delta: float
dist_ERR_envelope: float
iterations: int
history: CoupledCriterionHistory | None
final_system: SystemModel
max_dist_stress: float
min_dist_stress: float
__init__(converged, message, self_collapse, pure_stress_criteria, critical_skier_weight, initial_critical_skier_weight, crack_length, g_delta, dist_ERR_envelope, iterations, history, final_system, max_dist_stress, min_dist_stress)
Parameters:

  • converged (bool)

  • message (str)

  • self_collapse (bool)

  • pure_stress_criteria (bool)

  • critical_skier_weight (float)

  • initial_critical_skier_weight (float)

  • crack_length (float)

  • g_delta (float)

  • dist_ERR_envelope (float)

  • iterations (int)

  • history (CoupledCriterionHistory | None)

  • final_system (SystemModel)

  • max_dist_stress (float)

  • min_dist_stress (float)

Return type:

None

Parameters:

  • converged (bool)

  • message (str)

  • self_collapse (bool)

  • pure_stress_criteria (bool)

  • critical_skier_weight (float)

  • initial_critical_skier_weight (float)

  • crack_length (float)

  • g_delta (float)

  • dist_ERR_envelope (float)

  • iterations (int)

  • history (CoupledCriterionHistory | None)

  • final_system (SystemModel)

  • max_dist_stress (float)

  • min_dist_stress (float)

class weac.analysis.criteria_evaluator.CriteriaEvaluator(criteria_config)[source]

Bases: object

Public facade for stability analysis of layered slabs on compliant elastic foundations.

Parameters:

criteria_config (CriteriaConfig)

__init__(criteria_config)[source]

Initialize the evaluator with criteria configuration.

Parameters:

criteria_config (CriteriaConfig) – Configuration for failure criteria.

criteria_config: CriteriaConfig
fracture_toughness_envelope(G_I, G_II, weak_layer)[source]

Evaluate the fracture toughness criterion for Mode I / Mode II ERRs.

The criterion is defined as:

g_delta = (|G_I| / G_Ic)^gn + (|G_II| / G_IIc)^gm

A value of 1 indicates the boundary of the fracture toughness envelope.

Parameters:

  • G_I (float | ndarray)

  • G_II (float | ndarray)

  • weak_layer (WeakLayer)

Return type:

float | ndarray

stress_envelope(sigma, tau, weak_layer, method=None)[source]

Evaluate the stress envelope for given stress components.

Weak Layer failure is defined as the stress envelope crossing 1.

Parameters:

  • sigma (float | ndarray)

  • tau (float | ndarray)

  • weak_layer (WeakLayer)

  • method (str | None)

Return type:

ndarray

evaluate_coupled_criterion(system, max_iterations=25, damping_ERR=0.0, tolerance_ERR=0.002, tolerance_stress=0.005, print_call_stats=False, _recursion_depth=0, _force_result=None)[source]

Evaluate the coupled criterion for anticrack nucleation.

Parameters:

  • system (SystemModel)

  • max_iterations (int)

  • damping_ERR (float)

  • tolerance_ERR (float)

  • tolerance_stress (float)

  • print_call_stats (bool)

  • _recursion_depth (int)

  • _force_result (FindMinimumForceResult | None)

Return type:

CoupledCriterionResult

evaluate_SteadyState(system, print_call_stats=False)[source]

Evaluate hybrid steady state from system.

Extracts layers, weak layer, and inclination φ from SystemModel. Returns a structured result with independent tensile and err blocks. Does not accept touchdown mode and does not force φ→0.

Per-leg elapsed_s / n_cut_samples are always recorded in result.diagnostics; set print_call_stats=True to print them.

Breaking change

Former flat-touchdown modes (TouchdownMode / mode=) and the old flat SteadyStateResult fields (touchdown_distance, top-level energy_release_rate, single maximal_stress_result) are no longer part of this API. Use result.tensile.critical_cut_length and result.err.energy_release_rate instead.

Parameters:
Return type:

SteadyStateResult

find_minimum_force(system, tolerance_stress=0.0005, print_call_stats=False)[source]

Find the minimum skier weight to surpass the stress failure envelope.

Parameters:

  • system (SystemModel)

  • tolerance_stress (float)

  • print_call_stats (bool)

Return type:

FindMinimumForceResult

find_minimum_crack_length(system, search_interval=None, target=1)[source]

Find the minimum crack length to surpass the ERR envelope.

Parameters:

  • system (SystemModel)

  • search_interval (tuple[float, float] | None)

  • target (float)

Return type:

tuple[float, list[Segment]]

check_crack_self_propagation(system, rm_skier_weight=False)[source]

Evaluate whether a crack will propagate without additional load.

Parameters:
Return type:

tuple[float, bool]

find_crack_length_for_weight(system, skier_weight)[source]

Find anticrack length and segments for a given skier weight.

Parameters:
Return type:

tuple[float, list[Segment]]

class weac.analysis.criteria_evaluator.FindMinimumForceResult(success, critical_skier_weight, new_segments, old_segments, iterations, max_dist_stress, min_dist_stress)[source]

Bases: object

Holds the results of the find_minimum_force evaluation.

Attributes:

successbool

Whether the algorithm converged.

critical_skier_weightfloat

The critical skier weight.

new_segmentslist[Segment]

The new segments.

old_segmentslist[Segment]

The old segments.

iterationsint

The number of iterations.

max_dist_stressfloat

The maximum distance to failure.

min_dist_stressfloat

The minimum distance to failure.

success: bool
critical_skier_weight: float
new_segments: list[Segment]
old_segments: list[Segment]
iterations: int | None
max_dist_stress: float
min_dist_stress: float
__init__(success, critical_skier_weight, new_segments, old_segments, iterations, max_dist_stress, min_dist_stress)
Parameters:

  • success (bool)

  • critical_skier_weight (float)

  • new_segments (list[Segment])

  • old_segments (list[Segment])

  • iterations (int | None)

  • max_dist_stress (float)

  • min_dist_stress (float)

Return type:

None

Parameters:

  • success (bool)

  • critical_skier_weight (float)

  • new_segments (list[Segment])

  • old_segments (list[Segment])

  • iterations (int | None)

  • max_dist_stress (float)

  • min_dist_stress (float)

class weac.analysis.criteria_evaluator.MaximalStressResult(principal_stress_kPa, Sxx_kPa, principal_stress_norm, Sxx_norm, max_principal_stress_norm, max_Sxx_norm, slab_tensile_criterion)[source]

Bases: object

Holds the results of the maximal stress evaluation.

Attributes:

principal_stress_kPa: np.ndarray

The principal stress in kPa.

Sxx_kPa: np.ndarray

The axial normal stress in kPa.

principal_stress_norm: np.ndarray

The normalized principal stress to the tensile strength of the layers.

Sxx_norm: np.ndarray

The normalized axial normal stress to the tensile strength of the layers.

max_principal_stress_norm: float

The normalized maximum principal stress to the tensile strength of the layers.

max_Sxx_norm: float

The normalized maximum axial normal stress to the tensile strength of the layers.

slab_tensile_criterion: float

The slab tensile criterion, i.e. the portion of the slab thickness that is prone to fail under tensile stresses in the steady state (between 0 and 1).

principal_stress_kPa: ndarray
Sxx_kPa: ndarray
principal_stress_norm: ndarray
Sxx_norm: ndarray
max_principal_stress_norm: float
max_Sxx_norm: float
slab_tensile_criterion: float
__init__(principal_stress_kPa, Sxx_kPa, principal_stress_norm, Sxx_norm, max_principal_stress_norm, max_Sxx_norm, slab_tensile_criterion)
Parameters:

  • principal_stress_kPa (ndarray)

  • Sxx_kPa (ndarray)

  • principal_stress_norm (ndarray)

  • Sxx_norm (ndarray)

  • max_principal_stress_norm (float)

  • max_Sxx_norm (float)

  • slab_tensile_criterion (float)

Return type:

None

Parameters:

  • principal_stress_kPa (ndarray)

  • Sxx_kPa (ndarray)

  • principal_stress_norm (ndarray)

  • Sxx_norm (ndarray)

  • max_principal_stress_norm (float)

  • max_Sxx_norm (float)

  • slab_tensile_criterion (float)

class weac.analysis.criteria_evaluator.SteadyStateResult(tensile, err, phi)[source]

Bases: object

Structured hybrid steady-state result with independent tensile / ERR legs.

Exposes core_scalars() / diagnostics for comparison harnesses (characteristic_length = tensile L_crit, energy_release_rate = ERR-leg winner).

Parameters:
tensile: SteadyStateTensileBlock
err: SteadyStateErrBlock
phi: float
property converged: bool
property message: str
property diagnostics: dict[str, Any]
core_scalars()[source]

JSON-friendly top-level scalars for comparison runners.

Return type:

dict[str, float | bool | str]

__init__(tensile, err, phi)
Parameters:
Return type:

None