Gardado en:
| Autor Principal: | |
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| Formato: | Recurso digital |
| Idioma: | inglés |
| Publicado: |
Zenodo
2026
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| Subjects: | |
| Acceso en liña: | https://doi.org/10.5281/zenodo.19520116 |
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Table of Contents:
- <p>This paper presents a synthetic validation of the Universal Risk Cascade Theory (URCT) applied to agentic nuclear systems. Rather than modeling a specific plant, the study introduces an abstract dynamic framework capturing the interaction of physical, informational, and coordination-based risk components.</p> <p>A discrete-time simulation environment is constructed to represent coupled processes including physical degradation, AI-driven decision layers, persistent memory drift, and multi-agent coordination dynamics. Within this framework, human arbitration (HAP) and shared-state coordination architecture (MASP) are operationalized as control mechanisms.</p> <p>The central result demonstrates that persistent memory drift and coordination divergence, when considered independently, may remain within subcritical regimes. However, their interaction produces a supercritical composite cascade, leading to rapid regime transition and instability. This effect emerges consistently across multiple synthetic scenarios and Monte Carlo stress tests.</p> <p>The findings suggest that future nuclear risk models must explicitly incorporate agentic memory dynamics and coordination structure, as their interaction constitutes a distinct and currently underexplored class of systemic risk.</p> <p>This work is interpretive and synthetic in nature and does not represent a plant-specific safety model. Its purpose is to provide a formal and reproducible framework for analyzing cascade behavior in hybrid human–AI nuclear systems.</p>