TAILINGS LIQUEFACTION AND DAM STABILITY: ADVANCES IN DIAGNOSIS, MONITORING, STANDARDS AND MITIGATION – A CRITICAL REVIEW
DOI:
https://doi.org/10.61164/erfqjg05Palabras clave:
Tailings Liquefaction; Static and Cyclic Instability; State Parameter (Ψ); CPTu/SCPTu Diagnostics; TSF Monitoring and Governance; Numerical Modelling and RunouResumen
This review synthesizes advances from 2020 to 2025 in the understanding, diagnosis, modelling and governance of tailings liquefaction, drawing on a PRISMA-based assessment of scientific literature, case histories, technical guidelines and regulatory frameworks. Recent findings clarify the distinct roles of critical state and steady-state concepts in interpreting the behaviour of sandy, silty and structured tailings, while new evidence highlights the importance of depositional fabric, partial drainage and anisotropy in governing undrained softening and liquefaction susceptibility. Progress in CPTu/SCPTu interpretation, shear-wave velocity–based correlations and multi-parameter diagnostic frameworks has strengthened field evaluation but remains limited by heterogeneous stratigraphy and incomplete calibration across tailings typologies. Multi-source monitoring approaches—integrating InSAR, piezometry, geodetic instrumentation and operational data—have improved the detection of precursors and the interpretation of hydraulic and mechanical triggers. Hybrid numerical workflows combining FEM and MPM have advanced the modelling of triggering, strain softening and runout, although significant uncertainties persist regarding residual strength and softening laws. Regulatory developments, including GISTM (2020), ICOLD Bulletin 194 (2022) and Brazil’s ANM Resolution 95/2022, have shifted industry expectations toward life-cycle, evidence-based risk management. Collectively, the literature reveals substantial conceptual and technological progress but also persistent gaps in data integration, partially drained behaviour, decharacterization criteria and portfolio-scale governance, underscoring the need for more robust, adaptive and mechanistic approaches to TSF stability.
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Referencias
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