May 2020 www. .com

UNDERGROUND MINING

Risk-based design offers more than safety factorSRK’s William Joughin on dealing with uncertainty and risk in rock engineering design

Safety risk model and acceptance criteria

Managing risk in underground mines would benefit from risk-based

design, an approach which presents advantages over the commonly used ‘factor of safety’ method. SRK says it has developed an approach to underground geotechnical design that strikes a balance between cost and risk, while remaining aligned with the move towards zero harm.

Speaking recently at a number of international and local conferences related to rock mechanics, SRK Consulting chairman and principal mining geotechnical engineer William Joughin argued for a risk-based approach to rock engineering design in underground mines – taking into account the natural variability in the rock mass conditions and geotechnical uncertainty. These uncertainties include measurement errors, insufficient data, sampling bias, stress state uncertainty and model uncertainty.

“Uncertainty is reduced with more and better-quality data, but this takes time and money,” said Joughin. “Model uncertainty will

always be present due to the need to simplify the real world into mathematical equations and simulations. More complex models have further input parameters and require a deeper understanding of the mechanics involved.”

He highlighted that these models reduce uncertainty only if they are correctly applied and the uncertainties in the data used to determine the input parameters have been sufficiently reduced.

“There always will be some level of uncertainty involved as engineering decisions need to be made at the time that they are required, and with the data available,” he said.

DATA AND JUDGEMENTIn the early stages of a mining project, the available data is always limited. It requires experience and good engineering judgement to anticipate the range of ground conditions and potential consequences. As more and better data is gathered, the decisions become less subjective.

“In recent years, pillar failures at

Everest, Ngezi and Lily mines have had disastrous consequences, and it is important to learn from these incidents,” he said. “Poor decisions can be made when the full range of rock mass conditions have not yet

The graph represents the probability of having one or more fatalities per year in a part of a mine. The curves represent the societal risk for a range of design probabilities of failure.

These are calculated using the personnel exposure models taking the possible excavation damage into consideration. Exposure mitigation will move the curves downward. Improving the support and mining layout will reduce the probability of fail-ure calculated using probabilistic analysis techniques.

The design probability of failure should be selected to ensure that the societal risk curves fall within the ALARP region, while always striving toward negligible risk. ALARP boundaries can be determined using basic principles, which have been developed for large dams, nuclear facilities and roads - taking the scale of the analysis into consideration.

Note that this analysis is for a part of a mechanised mine where personnel exposure is low and there is a very low proba-bility that more than five people will be exposed in the same place at the same time. For a conventional mine where large groups of people are exposed, the societal risk curves will be flatter and usually higher up, unless excellent exposure mitiga-tion is in place.

Using risk evaluation models that take both safety and economic risk

into consideration, acceptable probabilities of failure can be

determined for rock engineering design

May 2020www. .com

UNDERGROUND MINING

been properly quantified, and this uncertainty has not been appropriately considered.”

He noted that some degree of subjective engineering judgement is always necessary to make good decisions, which take the natural variability and uncertainty into consideration.

With the deterministic methods that are conventionally applied in rock engineering, designs are usually evaluated by determining a factor of safety. The natural variability and uncertainty are represented by a distribution of values and therefore a single value will not be representative of the range of potential conditions that are likely to be encountered.

“Often, mean values are used for the rock mass input parameters, with a factor of safety of 1.5 or 2.0 catering for the inherent uncertainty and variability,” said Joughin. “However, if the uncertainty and variability are high, then the design may not be adequate; conversely, the design may be overly conservative and expensive if the variability is low.”

To take all of this variability and uncertainty into consideration, he said, it is necessary to conduct a probabilistic analysis, using techniques such as Monte-Carlo simulations. The outcome is then represented as a probability of failure, which could manifest as damage to excavations, excessive ground movement or rockfalls.

MANAGING RISK, NOT FAILUREHe said the reasons for the limited application of a probabilistic approach to date included the additional effort required, insufficient tools to conduct such analysis on a mine site, and the lack of prescribed ‘acceptable probabilities of failure’, which serve as design acceptance criteria.

According to Joughin, the probability of rock failure, on its own, has little meaning within the mining context – as the important factor that needs to be managed is not failure, but risk.

“In mining, failure with limited adverse consequence is preferable to unnecessary stability at a high cost,” he said. “The risk evaluation process therefore requires some practical understanding of the potential consequences of failure.”

This is why a risk-based design approach is preferable, where the acceptance criteria are defined in terms of both safety and risk – and therefore include probabilistic assessment and risk evaluation components.

“In a risk-based approach, it is necessary to examine a mining layout and evaluate the potential consequences of stress damage and rockfalls,” he said.

These could include injuries and economic consequences, such as the cost of repairing or replacing equipment, rehabilitating damaged excavations or production losses when access through damaged excavations is prevented.

SAFETY ACCEPTANCE CRITERIAPersonnel exposure models have been developed to assess the potential for injuries, which enables exposure mitigation measures to be evaluated.

The safety acceptance criteria draw on individual and societal risk guidelines originally developed for the civil engineering industry – and used specifically in the construction of large dams, nuclear facilities and roads.

The late Oskar Steffen – one of the founders of SRK Consulting – was able to apply this concept to slope stability in open-pit mines. As a result, the approach now appears in guidelines for large open-pit design. Joughin has taken this a step further, applying it to the underground mining environment.

“This approach is compatible with the mission toward zero harm,” he said. “The safety guidelines work on the principle that the risk should be as low as reasonably practicable (ALARP) and one should always strive towards negligible risk.”

He emphasised that in the real world, a probability of failure of zero is impossible, due to the inherent uncertainty and variability, but it can be so low that injuries are extremely unlikely to occur. Ignoring the uncertainty and natural variability may result in a calculated probability of failure of zero, but this is not a true representation of the potential risk.

RISK ACCEPTANCE CRITERIADamage costs and production losses can be assessed with input from the planning team. Models have been

developed to determine the potential economic losses, which depend on the extent of damage or size of rockfall.

Economic acceptance criteria are based on corporate risk matrices, where the potential monetary losses are presented on one axis and expected frequency of occurrence on the other.

“The risk model is presented on a risk matrix, where the criteria have been defined by corporate executives,” he said.

“Potential incidents with catastrophic economic consequences must have an extremely low expected frequency, while those with minor to moderate economic consequences can have higher expected frequencies – but still within accepted limits. The risk model takes the full range of potential incidents into consideration.”

Joughin’s work in this field was conducted with SRK colleagues and other global experts, as part of a research project on Ground Support Systems Optimisation – lead by the Australian Centre for Geomechanics (ACG).

This article first appeared on miningmagazine.com

The graph represents a typical corporate risk matrix with curves representing the cumulative annual fre-quency of damage losses for a range of design prob-abilities of failure.

This example represents a critical excavation, which can have a major impact on production if damage occurs and operations are interrupted during repairs.

In less critical parts of the mine, the curves will be shifted to the left, because the impact on production will be less significant. Improving mine layouts and support will reduce the probability of failure, but this is likely to increase capital or operating costs.

The selected design probability of failure should meet the corporate risk management expectations.

Economic risk model and acceptance criteria