Evaluación del riesgo potencial de estallidos de roca en minería subterránea mediante la integración de Análisis de árbol de fallas (FTA), Análisis de Árbol de Eventos (ETA) y el algoritmo Fu-ETO.
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Date
2026
Journal Title
Journal ISSN
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Publisher
Universidad de Concepción
Abstract
Los estallidos de roca constituyen uno de los principales riesgos geomecánicos en minería subterránea profunda, debido a la liberación súbita y violenta de energía acumulada en el macizo rocoso. La ocurrencia de este fenómeno responde a la interacción compleja entre condiciones geomecánicas, estructurales y operacionales, lo que dificulta su análisis mediante enfoques deterministas y limita la disponibilidad de datos cuantitativos, los cuales suelen ser confidenciales a nivel industrial. En este contexto, el presente trabajo desarrolla un modelo probabilístico de evaluación de riesgo de estallidos de roca, basado en la integración del análisis de árbol de fallas (FTA) y el análisis de árbol de eventos (ETA) bajo un marco de lógica difusa, incorporando el juicio experto como fuente principal de información. El objetivo es identificar los mecanismos causales críticos del fenómeno, cuantificar su probabilidad de ocurrencia y evaluar escenarios de consecuencia asociados a la sismicidad inducida. El FTA se estructura considerando el estallido de roca como evento superior (EB), descompuesto en eventos intermedios (𝐴𝑛) asociados a acumulación crítica de energía, sismicidad inducida y condiciones locales que permiten la expulsión del macizo. A partir de esta estructura se identifican conjuntos mínimos de corte (CMC), permitiendo reconocer los escenarios críticos de falla. Las probabilidades de los eventos básicos (𝑃𝐸𝐵) se estiman mediante evaluaciones lingüísticas de expertos, transformadas en números difusos trapezoidales y agregadas utilizando la técnica para el orden de preferencia por similitud con la solución ideal (TOPSIS), con ponderación de expertos mediante el método de la entropía. La desfuzzificación se realiza mediante el método del Centroide (CoA) y las posibilidades obtenidas se convierten en probabilidades siguiendo el enfoque de Onisawa. Con base en los resultados del FTA, se desarrolla un ETA utilizando la sismicidad inducida como evento iniciador (EI), por tratarse del mecanismo más observable y operacionalmente medible. El ETA permite evaluar distintos escenarios de respuesta del sistema de soporte y control operacional, asignando probabilidades a cada trayectoria y cuantificando las consecuencias esperadas. El análisis revela que el riesgo máximo ocurre al coincidir sismicidad crítica con soporte insuficiente, subrayando la importancia del diseño dinámico. El modelo FTA–ETA se valida como una herramienta probabilística consistente para la gestión de estallidos de roca. Esta metodología facilita la toma de decisiones estratégicas en entornos de minería subterránea profunda.
Rockbursts constitute one of the main geomechanical risks in deep underground mining, due to the sudden and violent release of energy accumulated in the rock mass. The occurrence of this phenomenon results from the complex interaction between geomechanical, structural, and operational conditions, which makes its analysis difficult using deterministic approaches and limits the availability of quantitative data, which is often confidential at the industry level. In this context, this work develops a probabilistic model for assessing the risk of rockbursts, based on the integration of fault tree analysis (FTA) and event tree analysis (ETA) within a fuzzy logic framework, incorporating expert judgment as the primary source of information. The objective is to identify the critical causal mechanisms of the phenomenon, quantify its probability of occurrence, and evaluate consequence scenarios associated with induced seismicity. The FTA is structured by considering rock bursting as the top event (TE), decomposed into intermediate events (𝐴𝑛) associated with critical energy accumulation, induced seismicity, and local conditions that allow for the expulsion of the rock mass. From this structure, minimum shear sets (SMS) are identified, allowing for the recognition of critical failure scenarios. The probabilities of the basic events (𝑃𝐸𝐵) are estimated through expert linguistic evaluations, transformed into trapezoidal fuzzy numbers, and aggregated using the technique for ordering preference by similarity to the ideal solution (TOPSIS), with expert weighting using the entropy method. Defuzzification is performed using the Centroid (CoA) method, and the resulting probabilities are converted into probabilities following the Onisawa approach. Based on the FTA results, an ETA is developed using induced seismicity as the initiating event (EI), as it is the most observable and operationally measurable mechanism. The ETA allows for the evaluation of different response scenarios for the operational control and support system, assigning probabilities to each trajectory and quantifying the expected consequences. The analysis reveals that the maximum risk occurs when critical seismicity coincides with insufficient support, underscoring the importance of dynamic design. The FTA-ETA model is validated as a consistent probabilistic tool for rockburst management. This methodology facilitates strategic decision-making in deep underground mining environments.
Rockbursts constitute one of the main geomechanical risks in deep underground mining, due to the sudden and violent release of energy accumulated in the rock mass. The occurrence of this phenomenon results from the complex interaction between geomechanical, structural, and operational conditions, which makes its analysis difficult using deterministic approaches and limits the availability of quantitative data, which is often confidential at the industry level. In this context, this work develops a probabilistic model for assessing the risk of rockbursts, based on the integration of fault tree analysis (FTA) and event tree analysis (ETA) within a fuzzy logic framework, incorporating expert judgment as the primary source of information. The objective is to identify the critical causal mechanisms of the phenomenon, quantify its probability of occurrence, and evaluate consequence scenarios associated with induced seismicity. The FTA is structured by considering rock bursting as the top event (TE), decomposed into intermediate events (𝐴𝑛) associated with critical energy accumulation, induced seismicity, and local conditions that allow for the expulsion of the rock mass. From this structure, minimum shear sets (SMS) are identified, allowing for the recognition of critical failure scenarios. The probabilities of the basic events (𝑃𝐸𝐵) are estimated through expert linguistic evaluations, transformed into trapezoidal fuzzy numbers, and aggregated using the technique for ordering preference by similarity to the ideal solution (TOPSIS), with expert weighting using the entropy method. Defuzzification is performed using the Centroid (CoA) method, and the resulting probabilities are converted into probabilities following the Onisawa approach. Based on the FTA results, an ETA is developed using induced seismicity as the initiating event (EI), as it is the most observable and operationally measurable mechanism. The ETA allows for the evaluation of different response scenarios for the operational control and support system, assigning probabilities to each trajectory and quantifying the expected consequences. The analysis reveals that the maximum risk occurs when critical seismicity coincides with insufficient support, underscoring the importance of dynamic design. The FTA-ETA model is validated as a consistent probabilistic tool for rockburst management. This methodology facilitates strategic decision-making in deep underground mining environments.
Description
Tesis presentada para optar al título de Ingeniero/a Civil en Minas.
Keywords
Minería subterránea, Sismicidad inducida, Entropía