Vessel Properties as Predictors of System Transformation: A Cross-Scale Extension of the Containment Framework within DDET

This paper introduces a vessel-based framework for understanding system transformation under energetic stress across physical, biological, and cognitive scales. Rather than focusing on the nature of what systems contain, it redefines resilience, collapse, and adaptation through how containment is structured. Central to this approach is the containment ratio R, where ρ represents internal energetic density and γ the geometric or functional capacity of the vessel. As R approaches a threshold near 0.1, vessel properties including elasticity, absorption, resistance, and permeability redistribute in predictable patterns that determine the system’s ability to adapt or rupture. The model formalises transformation as a function of internal redistribution rather than external causation, offering testable predictions and cross-scale diagnostic potential. Applications span quantum mechanics, medicine, artificial intelligence, and aerospace engineering. By tracing how vessel properties shift under pressure and how containment shapes certainty, this framework offers a unified lens for understanding continuity, breakdown, and intelligent design across complex systems.