Tailings & Mine Waste 2026

Assessment of Material Anisotropy in the Modelling of a Tailings Storage Facility

Presented by: Juan Escobar on Monday, November 9 at 4:35 PM as part of the Session 1.3A - Design & Deposition - Material & Hydraulic Properties for Design

This study investigates the influence of anisotropic soil behavior on the static and dynamic response of a downstream-raised copper Tailings storage facility (TSF). Two advanced constitutive models, available in the Imperial College Finite Element Program (ICFEP), are employed in these analyses: the Bounding Surface Plasticity model (BSPM), an isotropic state parameter-based constitutive framework serving as base case; and the MIT-S1 model, which incorporates inherent and induced anisotropy. Both models are calibrated using laboratory and in-situ tailings data.

Two-dimensional plane strain hydro-mechanically coupled analyses were performed to simulate the construction and operational stages of the facility. The results show that both models predict stable dam behavior; however, notable differences arise in predicted deformation patterns within the tailings impoundment. The MIT-S1 model produces larger settlements and a more pronounced plastic response compared with the BSPM formulation, reflecting anisotropic strength mobilization and stress rotation effects.

The seismic response is further evaluated using one-dimensional column analyses. The BSPM successfully captures key aspects of liquefaction behavior, including pore pressure buildup, propagation, and post-seismic settlement. In contrast, the MIT-S1 model shows limited ability to reproduce these mechanisms, indicating the need for further development to represent liquefaction processes.

Lifecycle Risks and Governance Failures Rooted in Early Bias in Tailings Management System Selection

Presented by Dr. Nelson Amoah on Wednesday, November 11th at 10:50 AM as part of the Session 3.2B GISTM & Governance Learning from Failures

Cowritten by Danielle O’Toole and Johan Boshoff (Gold Fields Limited)

Tailings management system selection, encompassing tailings dewatering technology, containment approach, and operational methodology, represents one of the earliest and most consequential decisions in mine development. These decisions carry enduring implications for safety, environmental performance, cost, operational continuity, and social licence across the entire lifecycle of a facility. Despite their significance, selection processes are frequently undertaken with insufficient structural rigour. Selection frameworks often allow multiple entry points for cognitive and institutional bias, resulting in default outcomes that favour familiar or precedent-based systems. While such approaches may appear risk-averse in the short term, they inadequately address long-term consequences, uncertainty, and evolving risk contexts.

This paper will argue that adverse outcomes in tailings management are frequently rooted in early-stage system selection decisions made during concept and pre-feasibility phases, rather than arising solely from downstream design, construction, or operational deficiencies. It will examine how technology-led decision pathways, with an early focus on familiar technologies that constrain problem definition and limit optionality, can drive premature convergence on a preferred solution. The paper will further analyse how other interacting factors reinforce selection bias and advance decisions ahead of information maturity and consequence-based lifecycle evaluation. It will also consider how foundational assumptions established early in project development can persist unchallenged as projects transition into optimisation-focused phases.

Using a lifecycle and consequence-based risk lens aligned with the Global Industry Standard on Tailings Management (GISTM), the paper will trace the governance and risk implications of early selection bias from concept through operation, closure, and post-closure stewardship. It will propose a structured, problem-led decision framework designed to preserve optionality until commitment is supported by adequate information maturity and consequence-based evaluation. Practical governance strategies will be outlined to assist in identifying and mitigating selection bias, supporting GISTM’s objective of advancing tailings management toward transparent, risk-informed, and lifecycle-based decision-making.