## 5 Conclusions  
The Brazilian Iron Quadrangle region is home to numerous upstream tailing dams, making it necessary to assess the potential for liquefaction in these structures, a critical aspect for their management. This research evaluated the liquefaction susceptibility based on the estimation of \(\Psi\) values [36] in upstream Brazilian iron ore tailing dams, considering drainage analysis based on SCPTu tests. Field and laboratory tests were conducted in three upstream dams located within the Iron Quadrangle region of Brazil. The testing program included 531.26 m of SCPTu tests, 317 seismic tests, and characterization and triaxial tests performed on samples obtained from trenches and using a Shelby sampler. Our methodology can be delineated into three main components: First, we employed the classification methodology proposed by [PERSON], [PERSON] and [PERSON] [28; 29; 30] to distinctly differentiate between plastic and non-plastic tailings while simultaneously assessing drainage conditions. Second, three methodologies were employed to assess drainage conditions during the execution of SCPTu tests, involving the utilization of normalized tip resistance (Q\({}_{\text{m}}\)), pore pressure ratio (B\({}_{\text{q}}\)), and the normalized penetration velocity parameter (V). This analysis was complemented by adjusting the standard cone tip resistance obtained in CPTu tests (q\({}_{\text{t}}\)) to consider the influence of partial drainage conditions. Lastly, we examined liquefaction susceptibility employing the state parameter approach (\(\Psi\)) [36] derived from SCPTu tests. Our findings reveal the high susceptibility of the iron ore tailings from the Iron Quadrangle region to flow liquefaction. The state parameter approach [36] revealed that 94% of the samples exhibited vulnerability to liquefaction (e.g., presented \(\Psi>-0.05\)) [36]. Even after accounting for the correction of partially drained conditions, the analysis based on B\({}_{\text{q}}\) indicated that 96% of the tests still showed susceptibility to flow liquefaction, while the Q\({}_{\text{m}}\) analysis identified 98%, and the V analysis identified susceptibility of 99%. The results also indicate a significant level of heterogeneity in the studied tailings. Various parameters, such as specific gravity, material index (I\({}_{\text{c}}\)), and the proposed classification method, exhibited considerable variations. Additionally, the three distinct approaches used to assess drainage conditions demonstrated some degree of variability among each other, emphasizing the complexity of defining geotechnical analyses in terms of total and effective stress. This study also serves to validate the methodologies developed for classifying  
Figure 11: Estimation of state parameters for the iron ore tailings before and after q\({}_{\text{t}}\) correction according to B\({}_{\text{q}}\), Q\({}_{\text{m}}\) and V. P limit values are boundaries defined by in situ stresses generally experienced by soils [37]. and assessing liquefaction susceptibility in different soil types, with a particular focus on expanding the knowledge and database on iron ore tailings. By employing the state parameter (\(\Psi\)) derived from SCPTu tests, our research demonstrates a methodology for assessing the liquefaction potential of iron ore tailings, considering drainage effects. This approach allows for a more precise characterization of tailing materials, which is crucial for designing safer and more reliable tailing storage facilities. Our findings offer a comprehensive framework that can be applied to similar mining sites, aiding in the prevention and mitigation of catastrophic incidents associated with tailing dam failures. This study not only advances the field characterization of tailings but also contributes to the development of more effective design strategies and risk management practices in the mining industry.