weac.analysis.criteria_evaluator module

This module provides the CriteriaEvaluator class, which is used to evaluate various fracture criteria based on the model results.

class weac.analysis.criteria_evaluator.CoupledCriterionHistory(skier_weights, crack_lengths, incr_energies, g_deltas, dist_maxs, dist_mins)[source]

Bases: object

Stores the history of the coupled criterion evaluation.

Parameters:

  • skier_weights (List[float])

  • crack_lengths (List[float])

  • incr_energies (List[ndarray])

  • g_deltas (List[float])

  • dist_maxs (List[float])

  • dist_mins (List[float])

skier_weights: List[float]
crack_lengths: List[float]
incr_energies: List[ndarray]
g_deltas: List[float]
dist_maxs: List[float]
dist_mins: List[float]
__init__(skier_weights, crack_lengths, incr_energies, g_deltas, dist_maxs, dist_mins)
Parameters:

  • skier_weights (List[float])

  • crack_lengths (List[float])

  • incr_energies (List[ndarray])

  • g_deltas (List[float])

  • dist_maxs (List[float])

  • dist_mins (List[float])

Return type:

None

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

The maximum distance to failure.

min_dist_stressfloat

The minimum distance to failure.

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.SSERRResult(converged, message, touchdown_distance, SSERR)[source]

Bases: object

Holds the results of the SSERR evaluation.

Attributes:

convergedbool

Whether the algorithm converged.

messagestr

The message of the evaluation.

touchdown_distancefloat

The touchdown distance.

SSERRfloat

The Steady-State Energy Release Rate calculated with the touchdown distance from G_I and G_II.

converged: bool
message: str
touchdown_distance: float
SSERR: float
__init__(converged, message, touchdown_distance, SSERR)
Parameters:

  • converged (bool)

  • message (str)

  • touchdown_distance (float)

  • SSERR (float)

Return type:

None

Parameters:

  • converged (bool)

  • message (str)

  • touchdown_distance (float)

  • SSERR (float)

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.CriteriaEvaluator(criteria_config)[source]

Bases: object

Provides methods for stability analysis of layered slabs on compliant elastic foundations, based on the logic from criterion_check.py.

Parameters:

criteria_config (CriteriaConfig)

__init__(criteria_config)[source]

Initializes the evaluator with global simulation and criteria configurations.

Parameters:

criteria_config (CriteriaConfig): The configuration for failure criteria.

Parameters:

criteria_config (CriteriaConfig)

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

Evaluates the fracture toughness criterion for a given combination of Mode I (G_I) and Mode II (G_II) energy release rates.

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 is reached.

Parameters:

G_Ifloat

Mode I energy release rate (ERR) in J/m².

G_IIfloat

Mode II energy release rate (ERR) in J/m².

weak_layerWeakLayer

The weak layer object containing G_Ic and G_IIc.

Returns:

g_deltafloat

Evaluation 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 (ndarray) – Normal stress components (kPa).

  • tau (ndarray) – Shear stress components (kPa).

  • weak_layer (WeakLayer) – The weak layer object, used to get density.

  • method (str, optional) – Method to use for the stress envelope. Defaults to None.

Returns:

stress_envelope – Stress envelope evaluation values in [0, inf]. Values > 1 indicate failure.

Return type:

ndarray

Notes

  • Mede’s envelopes (‘mede_s-RG1’, ‘mede_s-RG2’, ‘mede_s-FCDH’) are derived

    from the work of Mede et al. (2018), “Snow Failure Modes Under Mixed Loading,” published in Geophysical Research Letters.

  • Schöttner’s envelope (‘schottner’) is based on the preprint by Schöttner

    et al. (2025), “On the Compressive Strength of Weak Snow Layers of Depth Hoar”.

  • The ‘adam_unpublished’ envelope scales with weak layer density linearly

    (compared to density baseline) by a ‘scaling_factor’ (weak layer density / density baseline), unless modified by ‘order_of_magnitude’.

  • Mede’s criteria (‘mede_s-RG1’, ‘mede_s-RG2’, ‘mede_s-FCDH’) define

    failure based on a piecewise function of stress ranges.

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)[source]

Evaluates the coupled criterion for anticrack nucleation, finding the critical combination of skier weight and anticrack length.

Parameters:

system: SystemModel

The system model.

max_iterations: int

Max iterations for the solver. Defaults to 25.

damping_ERR: float

damping factor for the ERR criterion. Defaults to 0.0.

tolerance_ERR: float, optional

Tolerance for g_delta convergence. Defaults to 0.002.

tolerance_stress: float, optional

Tolerance for stress envelope convergence. Defaults to 0.005.

print_call_stats: bool

Whether to print the call statistics. Defaults to False.

_recursion_depth: int

The depth of the recursion. Defaults to 0.

returns:

results – An object containing the results of the analysis, including critical skier weight, crack length, and convergence details.

rtype:

CoupledCriterionResult

Parameters:

  • system (SystemModel)

  • max_iterations (int)

  • damping_ERR (float)

  • tolerance_ERR (float)

  • tolerance_stress (float)

  • print_call_stats (bool)

  • _recursion_depth (int)

Return type:

CoupledCriterionResult

evaluate_SSERR(system, vertical=False, print_call_stats=False)[source]

Evaluates the Touchdown Distance in the Steady State and the Steady State Energy Release Rate.

Parameters:

system: SystemModel

The system model.

vertical: bool, optional

Whether to evaluate the system in a vertical configuration. Defaults to False.

print_call_stats: bool, optional

Whether to print the call statistics. Defaults to False.

IMPORTANT: There is a bug in vertical = True, so always slope normal, i.e. vertical=False should be used.

Parameters:

  • system (SystemModel)

  • vertical (bool)

  • print_call_stats (bool)

Return type:

SSERRResult

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

Finds the minimum skier weight required to surpass the stress failure envelope.

This method iteratively adjusts the skier weight until the maximum distance to the stress envelope converges to 1, indicating the critical state.

Parameters:

system: SystemModel

The system model.

tolerance_stress: float, optional

Tolerance for the stress envelope. Defaults to 0.005.

print_call_stats: bool, optional

Whether to print the call statistics. Defaults to False.

Returns:

results: FindMinimumForceResult

An object containing the results of the analysis, including critical skier weight, and convergence details.

Parameters:

  • system (SystemModel)

  • tolerance_stress (float)

  • print_call_stats (bool)

Return type:

FindMinimumForceResult

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

Finds the minimum crack length required to surpass the energy release rate envelope.

Parameters:

system: SystemModel

The system model.

Returns:

minimum_crack_length: float

The minimum crack length required to surpass the energy release rate envelope [mm]

new_segments: List[Segment]

The updated list of segments

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]

Evaluates whether a crack will propagate without any additional load. This method determines if a pre-existing crack will propagate without any additional load.

Parameters:

system: SystemModel

returns:

  • g_delta_diff (float) – The evaluation of the fracture toughness envelope.

  • can_propagate (bool) – True if the criterion is met (g_delta_diff >= 1).

Parameters:
Return type:

tuple[float, bool]

find_crack_length_for_weight(system, skier_weight)[source]

Finds the resulting anticrack length and updated segment configurations for a given skier weight.

Parameters:

system: SystemModel

The system model.

skier_weight: float

The weight of the skier [kg]

returns:

  • new_crack_length (float) – The total length of the new cracked segments [mm]

  • new_segments (List[Segment]) – The updated list of segments

Parameters:
Return type:

tuple[float, List[Segment]]