CICT phased generator for arbitrary multi-scale quantification uncertainty effective modeling

The needs to assess resilient and antifragile performances for complex systems and to answer tighter regulatory processes (security, safety, environmental control, and health impacts, etc.) have led to the emergence of a new industrial simulation challenge to take uncertainties into account when dealing with complex numerical simulation frameworks. Current uncertainty quantification (UQ) approaches aim to include uncertainty in mathematical models and quantify its effect on output of interest used in decision making. For observing and determining single molecule transport characteristics or for detecting a minute change in resistance or capacitance at biostrucuture nanoscale, we need stronger research modeling and computational tools. To get stronger solution to advanced problems, like resonant nanoparticle, nanophotonic, optifluidics structure modeling, etc., we have to look for convenient arbitrary multi-scaling (AMS) BU (bottom-up) point-of-view (POV) (from discrete to continuum view ≡ BU POV) to start from first, and NOT the other way around! We present a simple example on multiscale quantification uncertainty modeling by unfolding the full information content hardwired into Rational OpeRational (OR) representation (nano-microscale discrete representation) and relating it to a continuum framework (meso-macroscale) with no information dissipation. This paper is a relevant contribute to show how CICT and GSI can offer stronger and more effective AMS quantification uncertainty solution to complex system modeling.