Data Underlying the MSc Thesis: An Advanced Tool for Evaluating the Probability of Failure of Existing Tailings Dams

The frequent occurrence of catastrophic tailings dam failures underscores the urgent need to improve safety practices and minimise associated risks. This study introduces an advanced tool to evaluate the total Probability of Failure (PoF) of existing tailings dams systematically and effectively, supporting the rational prioritisation of mitigation efforts and minimising risk within the ALARP principle.<br>The tool utilises a semi-quantitative approach, combining observation frequency and expert judgment. A baseline PoF for each dam construction method and failure category is established using a database of 450 tailings dam incidents and accidents developed in this study. This baseline PoF is subsequently modified based on site-specific factors influencing failure prevalence. A total of 255 key contributing factors are identified based on a fault tree analysis, the Global Industry Standard on Tailings Management (GISTM), and experts in the field. The factors encompass site conditions, design elements, and the Level of Practice (LoP), which address all major credible failure modes and mechanisms. The factors are linked to the failure categories they influence and assigned relative weights through the analytical hierarchy processing method for each dam construction method and failure category. Subsequently, the weights are multiplied by modifiers to account for the effects of site-specific conditions (favourable: 0.2, neutral: 1, adverse: 5, and unknown: 2). Within the tool, users can choose fulfilment conditions for each factor from drop-down menus and the selected inputs are connected to the modifiers. The adjusted weights are multiplied by the baseline PoF of each failure category, given the dam construction method. The summation of these products yields the total PoF of the investigated dam.<br>The results provide preliminary insight into factors significantly affecting the total PoF for the dam under investigation, aiding in evaluating whether the PoF reduction justifies costs. It facilitates preliminary, rational prioritisation of mitigation measures in accordance with the ALARP principle, contributing to ongoing efforts to improve tailings dam safety.<br>To validate the tool’s capabilities, two case studies with available data are analysed: the Aznalcóllar failure to examine the ability to identify high-risk factors and a recently improved dam to evaluate if the mitigation efforts are adequately reflected. The studies demonstrate the tool’s potential but also reveal uncertainties, inaccuracies, and limitations. These stem from discrepancies in the baseline PoF, weightings, modifiers, and unaccounted factors. Therefore, caution is warranted in the tool’s utilisation. Recommendations include various improvements and further verification and validation across a broader range of case studies. Value can be added by incorporating additional components and adapting the tool for new dams. <br><em>Notes: </em><em>The tool is developed as part of the Master Thesis: 'An Advanced Tool for Evaluating the Probability of Failure of Existing Tailings Dams', wherein comprehensive details about the development are provided. </em><em>I welcome discussions on the tool. Feel free to reach out if you have any points to discuss. </em><em>Please be aware of the tool's limitations when using it. </em>

尾矿坝灾难性失效事件时有发生，凸显了完善安全管控实践、降低关联风险的迫切需求。本研究提出一款先进工具，可系统且高效地评估现有尾矿坝的总失效概率（Probability of Failure, PoF），助力合理排序减灾工作优先级，并依据合理可行尽量低（As Low As Reasonably Practicable, ALARP）原则最小化风险。
该工具采用半定量方法，融合观测频次与专家判断。本研究构建包含450起尾矿坝事故案例的数据库，以此为基础确立了针对各类坝体施工方法与失效类别的基准失效概率。后续将结合影响失效发生的场地特定因素对基准失效概率进行修正。基于故障树分析（Fault Tree Analysis）、全球尾矿管理行业标准（Global Industry Standard on Tailings Management, GISTM）以及领域专家意见，本研究共识别出255项关键影响因素，涵盖场地条件、设计要素与实践水平（Level of Practice, LoP），可覆盖所有主要可信失效模式与失效机理。各因素与其所影响的失效类别建立关联，并针对每种坝体施工方法与失效类别，通过层次分析法（Analytical Hierarchy Process, AHP）赋予各因素相对权重。随后将权重乘以修正系数，以量化场地特定条件的影响：有利工况取0.2、中性工况取1、不利工况取5、工况未知取2。工具支持用户通过下拉菜单选择各因素的满足状态，所选输入项将与修正系数建立关联。将调整后的权重乘以对应坝体施工方法下各失效类别的基准失效概率，将所有乘积求和后，即可得到待评估尾矿坝的总失效概率。
该研究结果可初步揭示对待评估尾矿坝总失效概率产生显著影响的因素，辅助评估失效概率降低措施的成本合理性，可助力依据ALARP原则合理排序初步减灾措施优先级，为持续提升尾矿坝安全管控水平的工作提供支撑。
为验证该工具的性能，本研究选取两个具备公开数据的案例开展分析：一是阿兹纳科洛尔尾矿坝溃坝事故，用以检验工具识别高风险因素的能力；二是一处近期完成减灾升级的尾矿坝，用于评估工具能否充分反映减灾措施的实施效果。案例分析既展现了该工具的应用潜力，也暴露了其不确定性、偏差与局限性。这些问题源于基准失效概率、权重赋值、修正系数存在差异，以及部分未纳入考量的影响因素。因此，使用该工具时需保持谨慎。研究建议对工具开展多维度改进，并通过覆盖更广范围的案例研究进一步开展验证与校核。此外，可通过增设功能模块、适配新建尾矿坝的评估场景来提升工具的应用价值。
*注：
本工具为硕士学位论文《现有尾矿坝失效概率评估先进工具》的研究成果，论文中详细记载了工具的开发全流程。
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