Computing for Structural Fatigue

Predicting how repeated thermal and mechanical cycling accumulates damage in components until cracks initiate and grow.

Why cycling matters

A component can survive a load applied once yet fail after that same load is applied many times. Fatigue is the accumulation of microscopic damage under cyclic loading, leading eventually to crack initiation and growth. In a fusion plant, thermal cycles from startup and shutdown, pulsed operation, and vibration all impose cyclic loads, so fatigue life is a first-order design constraint.

What drives fatigue here

• Thermal cycling: expansion and contraction as the plant heats and cools
• Pressure and flow-induced loads that vary in time
• Electromagnetic loads that change with operating state
• Irradiation, which alters the material's fatigue resistance over life

How life is estimated

Two complementary approaches are used. Stress-life methods relate the cyclic stress amplitude to the number of cycles to failure, using curves measured for the material. Fracture-mechanics methods track a specific crack, predicting how fast it grows per cycle until it reaches a critical size. Together they bound both when cracks start and how long a detected crack can be tolerated.

def cycles_to_failure(stress_amp, A, m):
    # power-law stress-life form: higher stress, fewer cycles
    return A * (stress_amp ** -m)

The irradiation twist

Neutron damage changes fatigue behavior, often reducing ductility and altering crack growth, so fatigue life must be assessed for the irradiated material, not the pristine one. This couples fatigue analysis to degradation modeling, and it means fatigue margins can shrink over a component's life as damage accumulates.

Kronos framing

Structural fatigue analysis sets inspection intervals and component life for the Hyperion breeder's magnets, vessel, and internals, drawing loads from thermal-hydraulics and electromagnetic analysis. It is design-stage work ahead of construction in the second quarter of 2027, and it feeds predictive maintenance planning.