Reality Computing for Civil Infrastructure – Part 6

This post wraps up our exploration of Reality Computing for Civil Infrastructure by looking at how five different companies used Reality Computing on their projects.

 

Atkins

The reinforced concrete cantilevered piers supporting the elevated section of London’s M4 motorway are approximately 50 years old and require prioritized refurbishment. Atkins, part of the consortium managing the highway, is using Reality Computing to support this effort.

Piers supporting elevated sections of London’s M4 motorway are being
monitored and refurbished with the help of Reality Computing.
Image courtesy of Atkins.

The geometry of all the crossheads and the surrounding carriageway below the piers was laser scanned. Atkins created a 3D model from the point cloud data, which was used as a reference for its design of strengthening reinforcements. The model provided a geometrically accurate representation of the existing structure, enabling designs to be ‘built’ and tested in a virtual environment before construction.

Click here for more information about this project.

 

Cole Engineering

Cole Engineering used Reality Computing on a 40-kilometer water distribution project in southern Ontario. In the proposal stage, the firm used civil engineering software to combine a variety of publically available datasets and develop its pre-engineering design in the context of the surrounding neighborhoods. Those datasets included a digital model of the existing terrain from airborne LiDAR, aerial orthophotographs, and GIS data including property lines, right-of-way data, and utility locations.

Cole Engineering used mobile LiDAR data collection and mapping (performed by Tulloch Mapping Solutions)
to capture existing conditions during its design of a water distribution project in southern Ontario.
Image courtesy of Cole Engineering.

During detailed design, the firm commissioned a high-definition ground-based LiDAR survey replacing the airborne digital terrain model used during the proposal phase with a very precise terrain model. The survey data included documented survey codes that, when imported into its civil engineering software environment, enabled the application to automatically generate the appropriate 3D model objects such as trees, telephone poles, hydrants, and so forth.

Click here for more information about this project.

 

Great Lakes Geomatics

While planning the replacement of the northbound bridge deck for the I-275 bridges spanning the Lower Branch River Rouge, the Michigan Department of Transportation (MDOT) needed to efficiently and accurately locate all of the cylindrical piers supporting the bridge decks while avoiding lane closures.

Point cloud rendering shows bridge pier and deck details captured by laser scanning under an on-ramp.
Image courtesy of Great Lakes Geomatics.

The project team (which included Great Lake Geomatics) used laser scanners to capture point clouds of the piers, and then uploaded that information to their bridge design software to inform their design development. In addition, other survey points needed for design and construction were extracted from the laser scan after the initial survey, without having to return to the site. The point cloud was also used as an historical record, to verify exiting conditions prior to construction.

For more information on this project, click here.

 

Hüttenwerke Krupp Mannesmann

German steel company Hüttenwerke Krupp Mannesmann (HKM) implemented a 3D information system of the company’s 2.5-square-kilometer plant for planning and operations. Reality Computing helped HKM capture existing data of the facility using laser scanning and photogrammetry technology. Infrastructure design software was used to develop new 3D models for missing data or to supplement incomplete or inadequate infrastructure data.

HKM used Reality Computing to help capture existing data of its plant to support ongoing
operations and maintenance, and as a reference for the design of its coking plant expansion.
Image courtesy of Hüttenwerke Krupp Mannesmann.

Reality data representing existing conditions was also crucial for the design of an expansion to its existing coking plant. The company used a 3D medium-range laser scanner to capture above-ground pipe bridges, parts of the existing coking plant, as well as surrounding plants and buildings.

For more information, click here.

 

Sundt Construction

Sundt Construction used Reality Computing to help rebuild Cordes Junction, an outdated highway interchange in Arizona. The firm used intelligent, 3D models to support its construction sequencing and planning, and to automatically generate survey points for bridge construction.

Sundt Construction uses Reality Computing to support automated machine guidance operations.
Image courtesy of Sundt Construction.

Sundt also used the models to support automated machine guidance operations—loading the model directly into computerized monitors on heavy civil equipment. This saved time by eliminating the need for a survey crew to spend weeks ‘blue topping’ the road and helped the firm deliver the construction with minimal rework.

Click here to read a case study about this project.

 

Conclusion

Reality Computing is particularly suited to civil infrastructure projects due to the size and scope of projects and the inevitable physical disruption of the surrounding area.

Hardware and software advances have resulted in the ability to quickly and cost-effectively capture information about the physical world. This information is being used to support and inform decision-making during planning, design, construction, and eventually operations—minimizing environmental disruption and benefitting project design firms, contractors, and infrastructure ownerss.

 

This concludes our  Reality Computing for Civil Infrastructure blog series. Click here to download these posts, combined into a printable paper for easy viewing, printing, and distribution.