The existing Pattullo Bridge is already a key transportation link across Fraser River between the cities of New Westminster and Surrey, near Vancouver in British Columbia.
The bridge is due to be replaced by a wider 4-lane bridge that also includes new protected lanes for pedestrians and cyclists. The new bridge will provide more reliable, safer passage to all its users with minimized impact to the river itself.
This is a $1.377 billion project being delivered by the Transportation Investment Corporation, a provincial Crown corporation; with the bridge due to be completed and open to traffic in 2023.
A key design objective for the bridge is to reduce the impact on the Fraser River, both in terms of its hydrological systems and shipping activities. For example, the number of in-river piers supporting the bridge will be reduced from six to two, dramatically reducing the bridge’s footprint on the river below. Reducin
g these supporting structures brings obvious structural, hydraulic and, and seismic considerations.
Northwest Hydraulic Consultants (NHC) were contracted to build a physical 1:80 scale model of the existing Skytrain, Pattullo and CN Rail bridge pilings, on the riverbed so that hydraulic impacts could be tested and evaluated on the new bridge pilings, as well as the upgrades to the CN railway pilings for earthquake preparedness. Built within a warehouse and considered a robust tool available for assessing near-field changes to hydraulics and morphology, the physical model includes a scaled-down replica of the riverbed that is periodically flooded with different water levels and current speeds.
Rendering of the proposed Pattullo Bridge showing the reduced number of in-river pier supports
Underhill Geomatics appointed to provide laser scanned simulation data
One of Canada’s leading geomatics engineering and professional land surveying firms, Underhill Geomatics has been supporting NHC since 2016, providing laser scanned data for NHC’s simulations. When NHC’s physical model of the riverbed was first constructed, Underhill scanned the riverbed model, constructed to provide initial as-built reference data for subsequent simulations.
As NHC’s project has progressed, design modifications have been tested under different environmental conditions. After each test, the model is drained, and Underhill scans the simulated riverbed to provide digital 3D data for use in NHC’s computer-based analysis.
The 1:80 scale physical model of the riverbed
Replicating the physical model in the digital environment
Physical models are finite in their lifespan. The digital 3D representation captured by Underhill needed to be clean, complete, and precise. While survey-grade laser scanning systems were used to collect millions of measurement points across the survey of the model, as important in this project was a deep understanding of nuances and artifacts present in scanning data of this type, the nature of the environment that is being scanned and an understanding of how this data will be used by NHC in onward analysis routines.
Scanning a granular substrate that exhibits different levels of moisture post-draining can bring challenges to laser scanning:
- Errant ‘stray’ points (or noise) appeared (are we talking about what happened?) in point cloud data captured from these types of surfaces; noise, which if left in the point cloud has the potential to perpetuate error in any subsequent visual interpretation exercises by the engineers working with the data.
- Artificial upright pinning structures had been inserted into the physical model itself,
Both of which provided obstacles to the delivery of a clean surface model, needing to be removed before the model could be passed to the engineering team (especially since it was constructed to 1:80, so any error is magnified by the same proportions).
A laser scanning specialist from Underhill Geomatics aligns their high-definition laser scanning system to scan the next phase of the physical model
Optimized surface generation using a PointFuse workflow
At the beginning of this project, it was assumed that Underhill would deliver a cleaned point cloud data to NHC. This would be visually compared to the original reference dataset of the riverbed to assess the effect of the hydraulic phenomena that is being tested. However, due to the natural nature of the changing surfaces on the simulated riverbed in the physical model, visual comparisons between point cloud dataset can be problematic. There can also be inconsistencies in the extent that point clouds can be cleaned consistently, regardless of how experienced the technician is.
Ideally NHC needed to see the form of the riverbed as a series of surfaces within their CAD software environment (Autodesk’s Civil3D) and be able to perform spatial comparisons between the results of each simulation.
“At Underhill, we have a history in being early adopters of new technology. As a professional firm, one of our priorities is to bring experience and integrity to our projects”, comments Chris El-Araj, Managing Partner at Underhill Geomatics.
Underhill started using PointFuse in 2020 to provide an additional means to provide value to its reality capture clients; being able to provide modelled as-built data to customers who were struggling with point cloud data, but for whom the creation of full Revit models was not required.
The characteristics of PointFuse’s unique meshing algorithm includes subdividing a point cloud into a series of statistically best-fit surfaces, where unlike traditional meshing algorithms, spikes in the dataset are removed using statistically sound methods. Deviation from the original point cloud of each individual surface in the PointFuse mesh can be statistically assessed using tools within PointFuse prior to export, which gives assurance in the process.
With this knowledge, Underhill moved ahead with using PointFuse to convert the NHC project’s laser scanned point clouds into a series of 3D mesh surfaces. These surfaces were then easily imported into Civil3D for direct surface-to-surface comparison by the team. These PointFuse-generated surfaces are a more consistent product that is better suited for analysis in NHC’s software environment. In addition, since these surfaces were generated in approximately 50% of the time that it would otherwise take to deliver a cleaned point cloud, using a PointFuse workflow has enabled Underhill to deliver extra value to this project.
Mr. El-Araj continues “It was clear to us that including PointFuse software within our workflow provided an opportunity to appropriately use automation to bring reliability, consistency, and project efficiency to NHC’s simulations. Using PointFuse to produce surfaces that have been normalized for noise, and that can be imported directly into our client’s design software means that engineering decisions can be made without subjectivity being introduced by either our or our client’s interpretations”.
Continuous refinement and validation
With the bridge’s design now in final refinement stage, adoption of PointFuse as a consistent process to convert raw point cloud data into surfaces that can be seamlessly ingested by the project’s design and engineering software environments, means that any final tweaks to the bridge’s design can be assessed against any of the hydraulic situations simulated over the past 4 years.
As the bridge is currently undergoing design refinements, at the time of writing it is not possible to show the model, or the outputs from the meshing process in more detail. However, it has been fascinating to see effects each test has had on the evolution of the bridge’s design, and how using PointFuse’s meshing process has been used to provide accurate actionable data to NHC for their testing.