Latent Risk Geometry Classification (LRGC) A Causal Taxonomy of Hidden Failure Geometries in Infrastructure and Complex Systems
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866902026637541376 |
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| author | Mitchell , Thomas S. |
| author_facet | Mitchell , Thomas S. |
| contents | <p>Latent Risk Geometry Classification (LRGC) introduces a constrained causal taxonomy for hidden failure behavior in infrastructure and complex systems. Rather than treating resilience loss as a single universal phenomenon, the framework separates latent-risk dynamics into four non-interchangeable geometries: Corridor Fragility, Hidden Scarring, Visible Lock-In, and Symmetry-Protected Binary Failure. These geometries arise from four dominant causal terms: topology (T), delayed degradation memory (M), synchronization (S), and reinforcement/pruning (R).<br>The branch was developed through frozen observables, frozen thresholds, null-controlled mechanism tests, synthetic falsification, and real-world infrastructure interrogation. Key findings include: synchronization actively suppresses heterogeneity formation; bottleneck topology injects inherited fragility at time zero; reinforcement alone cannot generate lock-in without active pruning; and rerouting alone cannot generate Hidden Scarring without delayed degradation memory.<br>Real-world validation includes ERCOT WESTEX transmission corridors, IEEE 118-bus benchmark comparison, EAGLE-I outage data, and Con Edison utility-scale reliability analysis. The work demonstrates that latent failure geometry is scale-dependent and that some mechanisms do not merely generate geometries — they suppress the emergence of others.<br>This paper does not propose a universal resilience law. It presents a falsifiable, mechanism-separated taxonomy for identifying and distinguishing latent-risk geometries in real systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20361754 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Latent Risk Geometry Classification (LRGC) A Causal Taxonomy of Hidden Failure Geometries in Infrastructure and Complex Systems Mitchell , Thomas S. latent risk geometry, resilience, infrastructure fragility, hidden scarring, corridor fragility, synchronization failure, complex systems, network topology, degradation memory, infrastructure resilience, cascading failure, outage dynamics, power grid resilience, ERCOT, EAGLE-I, Con Edison, system recoverability, heterogeneity formation, failure geometry, complex network dynamics <p>Latent Risk Geometry Classification (LRGC) introduces a constrained causal taxonomy for hidden failure behavior in infrastructure and complex systems. Rather than treating resilience loss as a single universal phenomenon, the framework separates latent-risk dynamics into four non-interchangeable geometries: Corridor Fragility, Hidden Scarring, Visible Lock-In, and Symmetry-Protected Binary Failure. These geometries arise from four dominant causal terms: topology (T), delayed degradation memory (M), synchronization (S), and reinforcement/pruning (R).<br>The branch was developed through frozen observables, frozen thresholds, null-controlled mechanism tests, synthetic falsification, and real-world infrastructure interrogation. Key findings include: synchronization actively suppresses heterogeneity formation; bottleneck topology injects inherited fragility at time zero; reinforcement alone cannot generate lock-in without active pruning; and rerouting alone cannot generate Hidden Scarring without delayed degradation memory.<br>Real-world validation includes ERCOT WESTEX transmission corridors, IEEE 118-bus benchmark comparison, EAGLE-I outage data, and Con Edison utility-scale reliability analysis. The work demonstrates that latent failure geometry is scale-dependent and that some mechanisms do not merely generate geometries — they suppress the emergence of others.<br>This paper does not propose a universal resilience law. It presents a falsifiable, mechanism-separated taxonomy for identifying and distinguishing latent-risk geometries in real systems.</p> |
| title | Latent Risk Geometry Classification (LRGC) A Causal Taxonomy of Hidden Failure Geometries in Infrastructure and Complex Systems |
| topic | latent risk geometry, resilience, infrastructure fragility, hidden scarring, corridor fragility, synchronization failure, complex systems, network topology, degradation memory, infrastructure resilience, cascading failure, outage dynamics, power grid resilience, ERCOT, EAGLE-I, Con Edison, system recoverability, heterogeneity formation, failure geometry, complex network dynamics |
| url | https://doi.org/10.5281/zenodo.20361754 |