ORE2_Tailings Dam Probability of Failure Analysis

ORE2_Tailings Dam Probability of Failure Analysis is the next step in the ORE2_Tailings deployment for a tailings dam.

Last week we looked at the causality analysis and the general data structure  enabling the methodology to work.

Data for Tailings Dam probability analysis

Ancillary water management structures such as weirs, penstock and related tunnel, diversion ditches are described and evaluated including water balance and its “near-misses”. The presence of pipelines at the crest is also part of the potential hazardous elements for the dam, in case of a burst.

As described in prior publications there are approximately thirty “diagnostic nodes” that are used to describe the structure:

• Oboni F., Oboni C. Tailings dams quantitative risk prioritization, Tailings and Mine Waste 2019, Vancouver, BC, November 17 to 20, 2019
• Oboni F., Oboni C. (2020) Dam Stability Failures. In: Tailings Dam Management for the Twenty-First Century. Springer, Cham, https://doi.org/10.1007/978-3-030-19447-5_11, ISBN978-3-030-19446-8
• Oboni, C. Oboni, R. Morin, Innovation in Dams Screening Level Risk Assessment,  ICOLD 2019, Ottawa, June 2019

ORE2_Tailings Dam Probability of Failure Analysis

ORE2_Tailings evaluates the probabilities of failure of the dam the various causalities and the (stability) engineering analyses performed by the designer/ engineer of record, i.e.:

• ESA Effective Stress Analysis,
• USA Undrained Strength Analysis and finally
• pseudo-static.

ORE2_Tailings expands from the “failure-modes” reasoning (how the dam fails) to the “causes” (why the dam fails). That is done by including the contribution of the causality factors and other diagnostic points, the uncertainties as discussed above and in prior blogposts on the subject.

If the dam is inactive statistics help correcting the probabilities.

ORE2_Tailings also considers the effect of water management ancillary structures.

Their global effect is evaluated as a probability of water mismanagement what would likely result in a overtopping or damages at the spillway (with their obvious nefarious effect on the dam).

This allows then to produce two scenarios:

1. the global probability of failure of the dam as is,
2. the global probability of failure of the dam if the water management structures were “perfect”.

Finally, as needed, the analyst can add special cases, such, for example a static liquefaction scenario.

Benchmarking

The historic (world-wide, 100 years) performance and recent catastrophic failures evaluations allow to systematically benchmark the probability of failure of considered dams. The benchmarks are the green, light blue and dark blue lines in the graph displaying the results (see the “Results” section below).

Let’s focus the attention on the historic benchmarks (World decade around 1979 and 1999). Their interval contains another, smaller one, named “Taguchi (UBC, 2014)”. This interval corresponds to the findings of the study of Mr. Taguchi considering fault trees around failure modes. It is easy to explain the gap between Taguchi’s values and the historic values. It is the gap between a theoretical analysis and “real-life” where human effects, management, normalization of deviance or “fixes” and repairs intervene.

Note that this explains both top and bottom gap. At the top, “real life” is worse than the theoretical “perfect” vision.  At the bottom gap human intervention, good sense, fast actions, oftentimes save situations that are theoretically compromised.

Results

The graph below shows the results for a real-life dam we have recently analyzed.

As it can be seen from the graph below, as it stands today, the dam is slightly above the world portfolio . Indeed,  it is more hazardous for all cases but liquefaction, where the situation is rather critical.

The orange dotted line shows the chances of overtopping failure (combined surface water mismanagement) across the graph. We also notice that bettering of the water management would have very positive impacts on the dam, pushing the probabilities below the historic benchmarks for all cases but liquefaction.

The global probability of failure of the structure is not the probability of each scenario but the result of their combination. Indeed, the structure can fail for any of the causes, resulting in one of the studied scenarios (causes generating failure modes).

The last graph shows this combination, again with the benchmarks “as is” (left) or with “perfect water management” structures (right).

Here again it is easy to note that the vulnerability of the system to liquefaction is an issue that cannot be ignored on a dam which is already rather vulnerable for a mix of reasons. 

Closing remarks

ORE2_Tailings Dam Probability of Failure Analysis is the second step in the ORE2_Tailings deployment.

The third step is the evaluation of potential consequences.

Finally ORE2_Tailings allows an evaluation of the risk generated by the tailings dam and a rational and sensible prioritization of a dam portfolio. Simplistic scales or ratings of consequences as proposed by many cannot indeed be used to prioritize portfolios. They will mislead their users. They will neither support rational mitigative efforts at large scale nor produce a meaningful tailings dam residual risk assessment.

Tagged with: Failure Analysis, tailings dam probability of failure

Category: Consequences, ORE2_Tailings, Probabilities, Risk analysis, Risk management