Data required to run ORE2_Tailings
Nov 3rd, 2021
Now that the last eight blogposts (General ORE2 tailings workflow, ORE2 tailings technical explanations, first steps ORE2 tailings workflow , ORE2 tailings deployment steps , ORE2 tailings results, ORE2 tailings RIDM , ORE2 tailings tactical and strategic, ORE2 tailings conclusions) have shown the capabilities and results, let’s see the data required to run ORE2_Tailings quantitative risk assessments compliant with GISTM and ISO 31000.
A few words on ORE2_Tailings™ methodology
ORE2_Tailings™ is a subset of the “universal” ORE platform specific to Tailings dams, companion with ORE2_Dams and ORE2_Dykes.
- “symptoms” or diagnostic “points”/Diagnostic Nodes (DNxx) from dam inception to the day of the evaluation,
- data and information related to ancillary water management, pipelines, water balance and traffic at the crest and finally
- existing engineering analyses.
The DNxx can be grouped into KPIs (Key Performance Indicators)/or KRIs (Key Risk Indicators).
ORE2_Tailings™ mathematically combines the evaluations of the KPIs/KRIs to deliver a quantitative risk analysis, where consequences of a failure and probabilities generate the risk evaluation, including related uncertainties. Explicit consideration of uncertainties is indeed a fundamental step towards reasonable and defensible risk assessments.
ORE2_Tailings dam system and failure causality
ORE2_Tailings™ always considers the dams and their respective (or common in some cases) ancillary water management systems in addition to the dam body itself. Dam body and ancillary water systems constitute the “system”.
The KPIs/KRIs cover the life of the dam system from inception and converge on “families” of causality:
- investigation and material testing;
- construction and finally;
- operations and maintenance (including monitoring).
Causality analysis can be paramount in guiding mitigative decision-making.
The figure below conceptually displays the combination of the KPIs in the four aggregated causality families, the probability of failure, consequences and hence risk.
As one can see in the illustration above, the probability of failure resulting from the composition of the KPIs evolves all along the dam life while it maintains a certain level of uncertainties.
Key Risk Indicators/Key Performance Indicators used in ORE2_Tailings™
In this section we show the ORE2_Tailings™ KPIs/KRIs and the corresponding DNxx. DNxx the basic data required to run ORE2_Tailings™ and allow to:
The “normalization of deviance” and the uncertainties enter in the ORE2_Tailings™ probability of failure estimates as well as in the causality analysis.
This family includes general data on the system including of course year of construction.
- Dam country,
- Length (m),
- max height (m)
- section type and materials and finally
- Status: for instance active, inactive, closed
Additionally to the general data, this section describes the storage and of course its content.
- Main stored material: water, tailings,
- Supernatant pond surface m2,
- tailings surface m2,
- beaches: average beach length (m),
- Min beach (m)? Beach slopes? %
- Water volume Mm3 and finally
- tailings volume Mm3.
Ancillary water management
Ancillary water management is one of the two main macro-elements of the considered system. It is evaluated separately from the dam body itself as it may drive overtopping and as a matter of fact, other failure modes chains. For instance riverine erosion at the toe, collapse of bridges and other infrastructures capable of obstructing spillways, and malfunctioning of decants leading to internal erosion accidents.
- Water balance events descriptions in addition to near misses (year)? and return (years)?
- Weir, spillway age, design parameters and criteria (accidents? Near misses? When?).
- Description of status, maintenance, repairs.
- Obstructions? Bridges?
- Decant, gallery age design parameters and criteria including for instance accidents? Near misses? Dates?. Description of status, maintenance, repairs
- Diversion ditches age, design parameters and criteria in addition to accidents? Near misses and finally dates. Description of status, maintenance, repairs. Obstructions?
Investigations and geological model
Future failure of the dam may be seeded in poor investigations and insufficient understanding of the geological model. Indeed, these can be seen as congenital defects of the system.
- Boreholes density, depth with respect to structure height, sampling and testing results with description of tests, results, assumptions.
- Is the geological/geotechnical model satisfactory and well understood? For instance, is bedrock real bedrock?
- Are the geotechnical parameters used realistic? hydrological conditions realistic?.
- Seismic conditions? What acceleration, what return used in engineering analyses?
Project and construction
Future failure may also be the result of past oversight, lack of care in addition to incomplete analyses. As a result, ORE2_Tailingstm integrates the engineering analyses in the evaluation of the probability of failure.
- Level of analyses performed: ESA results? USA results? Residual strength results? Pseudo static results?
- Deformation analyses: results?
- Settlement analyses: results?
- Construction supervision? Documentation?
Liquefaction, piping and leaching
Due attention is given to liquefaction and residual strength considerations. Indeed the final result integrates these special conditions if the overall results.
- Are liquefiable materials present ? Where?
- Are liquefiable materials considered at peak or residual? and finally,
- What liquefaction triggers may be present?
Tailings lines and traffic
This is indeed an often neglected KRI, which can lead to unexpected/unwanted exposures. As a matter of fact these “minor” failure modes can be the initial trigger of cascading events which may, if they evolve unchecked, develop into serious failures. As a result these cannot be ignored or disregarded.
- Equipment at top: main tailings/spigotting line? in addition to detail of position, protection), traffic (details, protection), other?
- Traffic at top? For instance, detail of position, protection), traffic in addition to details, protection), other?
The KRIs cover all the sub-elements in place to prevent or control erosion as well as possible malfunctioning symptoms indicative of lack of care or deviance. As a result, the compilation of the DNxx across the full spectrum leads to quantifying the so called normalization of deviance.
- Berms/erosion control/
- Surficial drainage
- Internal drainage (vertical? horizontal?) parameters and finally,
- Was piping considered and checked? Any leaching, sources, water, humid zones?
As is status
This is another family of KRIs contributing to the “good quality” of the system while allowing to grasp the possible “normalization of deviance”.
- As built, alteration plans?
- Known errors and omissions?
- Divergence from plans?
- Unrepaired damages? Finally,
- History of issues, near misses?
Monitoring and inspections
- Monitoring devices: description, results, duration (piezometers, inclinometers, topographic, others…). Is the position of the instruments known and reported on cross sections? Are malfunctions reported?
- Deformations, movements.
- Inspections and past reports/observations and finally,
- Independent review? Details.
Closing remarks on data required to run ORE2_Tailings™
As a matter of fact, the data required to run ORE2_Tailings™ are the DNxx which can be derived from archival information and local visit if possible and necessary. The evaluation of the DNxx performed by the analyst allow to include uncertainties in the evaluation of the probability of failure of the dam system.
The evaluation of the DNxx requires an attentive study of the knowledge base, i.e. archival documentation, past inspections, monitoring reports, and finally, if available backward looking space observation, etc.
As a result, ORE2_Tailings™ analyses can be easily updated, as new information becomes available, by altering the values of the DNxx.
Tagged with: assessment, decision, management, operational, risk, Risk Assessment
Category: Consequences, ORE2_Tailings, Probabilities, Risk analysis, Risk management, Uncategorized