Beyond resilience: engineering antifragility and hazard mitigation in safety–critical systems using a stress–strain model

Abstract

Traditional resilience engineering struggles with modern safety–critical systems operating under extreme uncertainty. Antifragility, the ability to gain from systemic stressors and near-misses, remains a philosophical ideal, lacking a rigorous, quantitative framework for engineering. The Systemic Stress–Strain Model (SSM) is a quantitative framework that operationalizes antifragility by analogy to material science. The central thesis defines antifragility as a measurable increase in a system’s yield strength triggered by changes in the information stream. SSM defines system stress in complex socio-technical systems through distributed external or internal load and system strain as the system’s response. The SSM was validated via agent-based simulation, where an adaptive "information stream" enabled improved behavior, and an empirical application to the Houston flood case study, using NOAA data to map precipitation (stress) against causalities (strain). Simulations demonstrated that the antifragile configuration achieved a "snap-back" in performance and a strain reduction of up to 46% under high stress in the simulation. The Houston case study provided empirical evidence of improved system behavior, as post-Harvey (2019) interventions led to lower strain at stress levels comparable to pre-intervention floods (2015–2016). This SSM transforms antifragility into a testable, engineerable property, justifying investment in the adaptive "information stream" mechanisms required to build antifragile safety management systems that strengthen operational hazards and systemic shocks.