Fatigue Risk Management Systems (FRMS) increasingly rely on Biomathematical Models to quantify performance risk and inform operational decisions. These models translate physiology—sleep homeostasis, circadian rhythmicity, and sleep inertia—into actionable metrics such as predicted effectiveness or likelihood of lapses. When implemented correctly, model outputs strengthen rostering, dispatch decisions, and investigation of fatigue-related events while maintaining regulatory […]
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