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Reality Modeling for Utility Infrastructure

By Peter Fitzgibbon - 10th March 2017 - 13:33

A recently-published White Paper from Bentley Systems outlines a method of creating 3D reality models that provides a real-world context for infrastructure designers, builders and operators

Reality modeling as it applies to electric and gas utility infrastructure has, until recently, largely depended upon LiDAR (Light Detection and Ranging) technology that includes mapping, geospatial and site analysis and the design, operation, and maintenance of critical assets such as substations, networks and transmission towers and lines. Now, software is coming to the fore that transforms photographs into detailed, comprehensive 3D models of all that infrastructure data -- and do it in a less labor-intensive, cheaper, and more efficient manner.

Photography for timeless asset control

Photography for timeless asset control Using high-fidelity 3D-imaging software, such as Bentley’s ContextCapture, real-world imagery from existing on-the-ground conditions can be turned into precise 3D reality models with highly impressive detail from standard digital photographs. It’s a technology breakthrough that makes it possible to automate the production of models much faster than before and can easily be used within CAD, BIM and GIS workflows and published to the Web without using a lot of expensive hardware.

What’s more, the versatility of the software is such that it accommodates a broad spectrum of cameras, from smartphones and tablets to highly specialized airborne or terrestrial multi-directional acquisition systems, and any desired image format. Because so many people have access to and are experienced with using cameras, the potential pool of people who can participate in the reality capture process can be greatly expanded, making reality capture much more ubiquitous.

While laser scanning techniques are still attractive because they’re versatile and very accurate, they’re also very costly and time-consuming to use and can only be operated by experts. Reality modeling allows any user the opportunity to take pictures of the infrastructure landscape with a digital camera, whether it’s hand-held or mounted on an unmanned aerial vehicle –i.e., a drone. From there, the imagery goes through photogrammetric processing to create a 3D mesh, with high-quality texture mapping, that’s as accurate and realistic as the original photo.

The most exciting implication of this process is that the scalable 3D model – portraying anything from small objects to broad-scale infrastructure networks – can be enhanced with more images and revised data. This allows utility personnel to survey the asset throughout its lifecycle, from initial design to current conditions, and apply that changing data to maintain up-to-date data on the equipment’s condition along the way. It expands the scope of project management beyond controlling the asset on the basis of what it was in the past or what it may be in the future to what it is right now. Continuously up-to-date reality becomes the context within which electric and gas utilities can design, build and operate their infrastructure projects.

Aside from being something that requires no specialized skills or training to operate, the technology produces a form that geometrically resembles an engineering model, which provides a real-world context for infrastructure designers, builders and operators. Previously, laser scanning was the requisite technology for engineering workflows, but that’s no longer the exclusive case.

Tools with multiple mapping properties

The new tools that have been rolled out along the IT continuum also are depicting sharper, more multi-faceted 3D pictures of any critical points within the infrastructure network. These can provide the backbone of information throughout the lifecycle and then turn these 3D digital engineering models into valuable assets.

Advanced point-cloud data processing enables the extraction of geometric features from point clouds, such as break, paint and cylinder center lines, surfaces, planes, and cylinders. Point-cloud visual-ization software is available and uses many different shading options that make it easier to interpret visual imagery. Layer-based editing and data segmentation properties let you manipulate the point cloud to show isolated parts of it or the big picture, and processing functionality can maximize point-cloud density and clarity.

Now, it’s also possible to produce and display very large digital terrain models that show the terrain from multiple perspectives. The view might emphasize elevation, slope, aspect angle, contours or even shadows.

You can even make highest-quality movies or animations of a given infrastructure site with the help of intuitive, time-based, fly-through and animation capabilities.

Design and maintenance for system integrity and protection

The latest reality modeling solutions are providing benefits all along the utility infrastructure value chain. Intelligent design applied to physical and electrical components of the substation is cutting down on design time and errors that would have to be corrected during the construction phase. The ability to visualize a substation in 3D improves design accuracy and makes it possible to spot potential safety risks early on (e.g., physical clearance issues). The design scope is immense, encompassing everything from single-line diagrams to minutely detailed 3D general layouts.

Some of the substation elements that these 3D tools can design include the grounding grid and lightning protection, wiring diagrams, schematics and panel layouts. Reality capture functionality can facilitate picking the best site, gauging subsurface soil condition impacts, and even estimating cost for earth moving operations. Support reactions gleaned from structural analysis models can be used to design foundations, while substation structures can be designed to meet code requirements and handle static and dynamic loads.

On the most macro level, it’s possible to design the entire site, including the substation pad, drainage and access roads.

To get the infrastructure design process rolling, reality modeling can build a base model of the project site by creating and pulling together aerial imagery, design terrain models, land use maps and transportation layouts. The infrastructure can be laid out and engineered in a common data environment to make project coordination simpler and more effective. What’s even more powerful is the ability to re-survey a site or set of assets – continuously. This has enabled a temporal series of management and monitoring opportunities previously not seen on this scale.

Where utility corridors can go and how well and how long they can operate depends, in no small part, on an accurate assessment of the presence and impact of surrounding elements. Reality modeling applications can acquire and analyze field data on vegetation (e.g., encroachment on corridor routes), terrain and existing infrastructure and evaluate the relationship among those factors. They can draw up horizontal and vertical geometries to meet corridor design needs.

Performance management solutions that reveal past and present real-world behavior are lending important support to the maintenance of safe and reliable infrastructure operations. By capturing and analyzing historical and real-time asset data in this way, utilities can develop the most optimal and dependable maintenance and inspection plans and, hence, minimize operating risks and unplanned downtime and increase efficiency. The advanced software offerings now available proactively monitor and more consistently predict what’s happening now, and what will happen, to equipment, pumps, piping systems and other associated infrastructure.

The realized goal of these new modeling capabilities is comprehensive system protection that maintains the mechanical integrity of static piping and pressurized vessels, minimizes deterioration-based containment loss, controls corrosion, analyzes root causes of potential failures and subsequently takes preventive measures, and preserves structural integrity.

Multiple incentives for reality capture technologies

These emerging technologies will likely be in continuous use in the coming years, inasmuch as a confluence of factors aging infrastructure, the growing popularity of natural gas for electricity generation, a lack of distribution networks in emerging markets and the need for more distribution efficiency, energy security and a reduction in greenhouse gas emissions – are fueling a booming investment in gas utilities infrastructure development. Because of these drivers, capital expenditures in global gas infrastructure were expected to top $41 billion in 2015.1

On the electric side, transmission network needs and growth opportunities are expected to build a transmission investment of $120-$160 billion in the decade ending in 2025. Much of the more immediate spending is going toward new construction or expansion – between 43 and 48 percent in the 2014-2017 period, which is roughly twice the percentage investment in the next largest category, advanced technologies.2 The need to replace and upgrade aging transmission assets is the main reason for the expenditure – which isn’t surprising, since most of the existing grid was built 30-50 years ago. There’s also the growth of smart grid infrastructure to consider, as spending for increased grid automation and demand response in this area reached $70 billion annually in 2014.3

Photography and LiDAR: comparing and combining

The rising popularity of advanced photogrammetry notwithstanding, LiDAR still has its place, and may remain in use thanks to its millimeter-scale measurement precision.

This kind of scanning is ideal for high-accuracy depictions of small to medium-scale assets, though it becomes unwieldy for very large-scale assets. In general, lasers have been preferable to photos for such high-definition scanning, and unlike photography, they can capture ground targets that are visually obscured by other objects. Airborne LiDAR also has had an advantage over photogrammetry in that it could filter out vegetation from point cloud models so that areas that would be hidden by trees, shrubbery and the like, can be clearly visualized. LiDAR also can capture data at night, which photogrammetry can’t do, and it’s suitable for collecting linear shaped data, which makes it very useful for linear corridor mapping and power line monitoring.4

While the global LiDAR market has been projected to grow annually by more than 15 percent from 2013 to 2018, and projected to reach $551.3 million in 2018, corridor mapping, particularly for transmission lines, is the LiDAR application expected to show the highest annual growth rates during that period.5

Photogrammetric 3D reconstruction, however, can be used on any scale asset, is much less labor-intensive for data acquisition, and delivers more visually understandable photo-realism than laser scanning (making it preferable for visualization). It also shows textures more sharply and clearly, can map all types of ground features accurately, including structures, and can capture break points and mass lines. Unlike lasers, technology improvements tend to be software-based and don’t require physical equipment upgrades.6 Beyond that, photogrammetry produces a point cloud considerably faster than a laser. Photogrammetry can also produce orthophotos – i.e., aerial photos corrected to provide accurate measurement of features and distances – and gives an absolutely true picture of water flows, which is problematic for lasers.7 On the most mundane level – cost – photogrammetry fits more comfortably into tight project budgets, given the huge amount of detail contained in LiDAR datasets. Photo-based modeling really saves money in the preliminary planning and design phase, where its efficiency can greatly accelerate the workflow and even lower construction costs. In short, photography for reality modeling now creates economies of scale through the speed and ease of site data capture and the automation of the modeling process.8

âEnhanced accessibility

Maybe even more importantly, the reality models produced from photogrammetric reconstruction are so much lighter and more portable than point clouds, that they can be much more easily shared and accessed throughout the extended enterprise, even using a simple Web browser. This enhanced accessibility, presents the opportunity for more stakeholders throughout the enterprise to leverage this valuable information to make better decisions, whether in the office, on-site, or in the field.

The larger point however, is that both LiDAR and 3D photogrammetry are in the palette of 3D reality capture technologies whose adoption by the utility infrastructure industry is accelerating. That’s partly because the private sector’s assumption of a growing share of construction and utility infrastructure investment has put a premium on productivity increases that can boost ROI – and that, in turn, translates into greater investments in technologies that model what’s actually happening throughout the AEC journey.

Actually, the way forward may see LiDAR and photography complement one another at times in an integrated technology approach. In recent years, many mobile mapping solutions have been linking up LiDAR scanners with multi-camera systems to simultaneously obtain calibrated image and point cloud data and maintain excellent quality and accuracy. In a sense, lasers and photography have taken cyclical turns in making their impact in reality modeling, in utility infrastructure and other applications: Lasers initially supplanted photography, then augmented their interpretation of 3D data with a more user-friendly process that used external cameras, and now, thanks to advances in digital photogrammetry, are inextricably joined with that technology in providing leading-edge 3D measurement and data collection resources. 9


  1. I&R: The Global Gas Utilities Infrastructure Market Report 2015, PR Newswire, 2015.
  2. Pfeifenberger, Johannes, Change, Judy, Tsoukalis, John, Investment Trends and Fundamentals in U.S. Transmission and Electricity Infrastructure, The Brattle Group, 2015.
  3. The Energy Cloud: Emerging Opportunities on the Decentralized Grid, Navigant, 2016.
  4. Marre, Fabrice, Photogrammetry or LiDAR?, Geoconnexion International Magazine, February 2014.
  5. Zeiss, Geoff, 3D in Construction: Building a New World, Geospatial World, March 2014.
  6. Leonova, Margarita, Laser Scanning vs. Photogrammetry, Lanmar Services, November 2014.
  7. Beasy, Christopher, LiDAR and Photogrammetry…How Do I Choose?, Eagle Mapping, 2007.
  8. Ball, Matt, Thanks to NASA, Photo-Based 3D Modeling Is About to Explode, Autodesk – Line/Shape/Space, October 2014.

Folwell, Peter, Laser Scanning vs. Image-Based Modeling, AEC Magazine, December 2015.

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March 2017

Read More: 3D / 4D Aerial Imaging GIS Construction Engineering Oil & Gas Utilities Security & Safety Mining Transport & Logistics

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