STOCHASTIC MODELING OF ENERGY MIGRATION IN THE RING OF FIRE: INTEGRATING BIG DATA, EXPERIMENTAL PROTOTYPING, AND STRUCTURAL PATHOLOGY IN SOUTHERN MANABÍ, AS A FRAMEWORK FOR BUILDING EDUCATIONAL CAPACITIES

Abstract

DOI: https://doi.org/10.46296/yc.v10i19.0936

Abstract

This study presents a stochastic modeling approach to energy migration in the Ring of Fire, specifically applied to the southern zone of Manabí, Ecuador—a region characterized by high seismic activity and complex geodynamic behavior. The model integrates three interconnected components: (1) Big Data analytics for processing large-scale seismic and environmental datasets, (2) experimental prototyping for simulating energy release and ground motion patterns under controlled conditions, and (3) structural pathology diagnostics for identifying and characterizing vulnerabilities in the built environment. Beyond its geophysical and engineering applications, this research introduces a novel educational contribution. The stochastic model is conceived not as a closed predictive tool, but as a pedagogical platform for training students, technicians, and local decision-makers in the probabilistic understanding of seismic energy dynamics. By transforming uncertainty into a teachable concept, we propose a constructivist learning framework where geological variability and educational adaptability converge. The findings highlight that capacity building in high-risk territories require not only technological innovation but also the active co-construction of knowledge among scientists, educators, and communities. This work aims to bridge the gap between advanced geophysical modeling and accessible, participatory education, fostering resilience through informed decision-making and local empowerment.

Keywords: stochastic modeling, Manabí, energy, soil, construction.