Part 3: The Power of Parametric Modeling

The ability to make the best decisions depends first having complete and accurate data — including geological, geotechnical, design, engineering, market and regulatory data — and then being able to:

• measure the impact and effectiveness of one decision or set of decisions against another, and
• refine or change those decisions as required, as new information comes available or circumstances change.

The first article of this series looked at how you could use virtual twinning to visualise your systems as a collection of tiered virtual twins, each with its own data sources, processes, and areas of knowledge. Through a virtual connection, the tiers are linked so that they work together to respond to problems that arise along the value chain. In the second article, I talked about how properly consolidating, controlling, and managing your data will help you get ready to take full advantage of that data within a virtual twin experience.

Here, we look at the power of parametric modeling to use your cleaned and consolidated data to run comprehensive virtual scenarios — not just within each tier but between all your tiered virtual twins — to stress-test designs and engineering principles.

Parametric modeling fundamentals

Parametric modeling can be divided into two main types:

• propagation-based systems, in which algorithms result in final shapes that are unknown based on initial parametric inputs, and
• constraint systems, in which final constraints are set and algorithms are used to define fundamentals (structures, material use, etc.) that satisfy these constraints

Both types of parametric modeling have been used for years in other industries, such as civil construction, aviation, and manufacturing, as a replacement for traditional 2D CAD-based design.

In the mining industry today, however, it is not uncommon for mines to continue to use traditional CAD-based design, which does work, but there are drawbacks. For example, traditional CAD-based design is slow, because it requires a designer to modify the entire shape of a design in response to a change. This slowness can mean that a designer is able to produce just one or maybe two design options by deadline, with no time left for engineers to evaluate the integrity of the design.

Parametric modeling, on the other hand, is a tool for CAD-based design that removes or significantly reduces the amount of manual digitization a designer is required to do and, through the power of associativity, the need for the designer to edit the whole design every time they want to modify a single design parameter.

Associativity coupled with parametric modeling preserves the link between reference data — such as terrains and geology or resource models — and existing infrastructure models. This in turn makes it possible to update designs automatically every time there is new input data because, while the input data may have changed, the parameters of the design may not.

The result: designs are ready for review days or even weeks faster than current practice allows.

Other benefits

Parametric modeling also provides the opportunity for the designer to create a nearly limitless number of potential designs, and quickly make an equally infinite number of refinements to reflect changing data, all without losing previous design work and all while remaining — through the use of user-guided principles — in full control. The designer can ensure safety, too, by incorporating geotechnical and safety rules through defined parameters.

Once the design is ready for review, key stakeholders can then view and comment on the design and track the history of design decisions, so traceability, auditability, and knowledge retention are built-in.

Parametric modeling in action

A underground mine design example

To develop an underground mine, your mine designer first generates optimal stope shapes to target. Next, the designer needs to evaluate different access designs and mining methods to deplete these stopes.

Using a parametric design tool, the designer associates:

• the stopes to the target access design to rapidly re-evaluate the design to be modeled should the stopes be modified, and
• each tunnel and access design into a network that can propagate changes should the dimensions or location of a preceding tunnel be changed.

Then, the designer:

• builds a library of templates for each part of the development network, such as drifts, ramps, accesses, or raises, as well as the geometrical parameters associated with each, including profile, slope, spacing, and size
• tests the templates — for example, by varying tunnel heights, altering the radius of a ramp, or changing a gradient — to ensure they are working
• establishes rules and logic that will enable the templates to both automatically update the entire design and ensure the end-product is operationally feasible
• defines safety and operational principles to ensure a robust and practical design can be achieved, and
• tests and validates the performance of the parametric design.

A surface mine design example

Let's look at an example where the mine designer has two primary targets: multiple ramp options for battery- or trolley-assisted haul fleets, and waste storage facility capacity requirements based on the material extracted. Parametric mine design capabilities are provided today with the Role; Surface Mine Designer

Using a parametric design tool to evaluate multiple ramp options, the designer:

• defines multiple entry and exit points
• inputs and preserves ramp dimensions based on specific fleet requirements, such as minimum ramp width, and operational factors, such as a maximum ramp slope and specificities around supporting infrastructure, truck turning radius, and safety considerations
• evaluates tradeoffs between set or prioritized parameters for each option, and
• ensures full associativity between the ramp and the pit design so that, once the parameter of the ramp is modified, the pit design is adjusted accordingly complying to predefined geotechnical and safety rules.

Using a parametric design tool to evaluate waste storage facility capacity requirements, the designer is able to create an associated link — a bond — between pit design and waste facility design that:

• creates a base footprint for a waste facility as a baseline area for storage permitted in close proximity to the pit
• generates benches and ramps in the waste facility based on a target volume of material expected from the pit
• satisfies all pre-defined safety parameters inside the available footprint, and
• removes any guess work or trial and error in evaluating waste storage options.

Next in this series

The final article in the Re-imagining the Way We Work series will discuss the next leap in creating the best mine designs possible: combined and iterative parametric modeling and simulation, known as MODSIM.

About the author

@AJ - GEOVIA R&D Portfolio Management Director

Anthony is an experienced Product Management Director with a demonstrated history of working in the natural resources software industry. He has worked as a consultant using and teaching the use of software applications as well as providing guidance on the development of software applications for the last 10 years. Skills developed during this time are largely focused towards geological modelling, resource evaluation, mine planning and product management. 

Related Posts: