TLMM v5.6 — Unified Closed-Loop Viability Stabilization: Adaptive Viability Control under Structured Uncertainty

TLMM v5.6 presents a unified conceptual framework for adaptive viability stabilization under structured uncertainty. This release introduces an integrated closed-loop architecture combining: • structured uncertainty budgeting,• topology-aware monitoring via persistent homology,• multi-mode viability reconstruction,• momentum-stabilized adaptive trigger dynamics,• recovery landscape analysis,• Pareto-optimal intervention trade-offs,• predictive horizon preservation,• digital twin synchronization and re-alignment,• federated adaptive twin coordination,• long-horizon benchmarking,• adaptive viability landscapes,• and methodological roadmap evolution. The framework is designed as a conceptual systems architecture for resilient adaptive viability management in uncertain, multi-scale environments. The repository contains:• the complete 13-figure conceptual atlas,• a full PDF framework document,• and illustrative Python demonstration code. All figures, simulations, trajectories, benchmarks, and numerical values are synthetic and intended solely for conceptual and methodological demonstration. No empirical, clinical, engineering deployment, or operational claims are made. Author:Koji OkinoIndependent Researcher — SD Lab ORCID:https://orcid.org/0009-0003-9273-9813

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-23
DOI
https://doi.org/10.5281/zenodo.20351568
Primary Topic
Traffic control and management
Type
preprint
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preprint

TLMM v5.6 — Unified Closed-Loop Viability Stabilization: Adaptive Viability Control under Structured Uncertainty

Koji Okino
Zenodo (CERN European Organization for Nuclear Research)
Traffic control and management
preprint

TLMM v5.6 — Unified Closed-Loop Viability Stabilization: Adaptive Viability Control under Structured Uncertainty

Koji Okino
preprint en

Abstract

TLMM v5.6 presents a unified conceptual framework for adaptive viability stabilization under structured uncertainty. This release introduces an integrated closed-loop architecture combining: • structured uncertainty budgeting,• topology-aware monitoring via persistent homology,• multi-mode viability reconstruction,• momentum-stabilized adaptive trigger dynamics,• recovery landscape analysis,• Pareto-optimal intervention trade-offs,• predictive horizon preservation,• digital twin synchronization and re-alignment,• federated adaptive twin coordination,• long-horizon benchmarking,• adaptive viability landscapes,• and methodological roadmap evolution. The framework is designed as a conceptual systems architecture for resilient adaptive viability management in uncertain, multi-scale environments. The repository contains:• the complete 13-figure conceptual atlas,• a full PDF framework document,• and illustrative Python demonstration code. All figures, simulations, trajectories, benchmarks, and numerical values are synthetic and intended solely for conceptual and methodological demonstration. No empirical, clinical, engineering deployment, or operational claims are made. Author:Koji OkinoIndependent Researcher — SD Lab ORCID:https://orcid.org/0009-0003-9273-9813

Zenodo (CERN European Organization for Nuclear Research)
United States Department of Labor (US)
Traffic control and management
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TLMM v5.6 — Unified Closed-Loop Viability Stabilization: Adaptive Viability Control under Structured Uncertainty — Koji Okino · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS