The team was faced with the task of modeling a large volume of elements within a strictly defined timeline. The specifics of the modeling included the following:

  1. Concrete structure;
  2. Steel structure;
  3. Pipelines and equipment;
  4. Surrounding landscape.

The low requested level of detail (LOD) allowed us to align the project seamlessly, without needing to scrutinize the smallest details. With this modeling approach, we achieved a high volume of modeling within narrow timeframes.

Scope of work: Low LOD Scan-to-BIM modeling of the structural and MEP components of the plant.

Input: Point cloud of a fragment of the Oil and Gas Plant.

Output: 3D Model at LOD 200; Sections illustrating the “Model vs Point Cloud” conditions throughout the building.

Subservices: Scan to BIM
Industry: Industrial
Object type: Oil and Gas
Area: 4450 m² / 47900 ft²
Tools used: Autodesk Revit, Autodesk ReCap, Cintoo
Project stages
1. Receiving input
2. Analysis of the input: Evaluating the provided data; Requesting supplementary information; Selecting the optimal team structure.
3. Modeling of the concrete structure
4. Modeling of the metal structure
5. Modeling of MEP and equipment
6. Modeling of the surrounding landscape
7. Project support

Overall description

The modeling of as-built conditions of industrial plants, saturated with various kinds of equipment and systems, has its work-specific challenges. The number of elements and tiny details can be substantial, and it’s essential to define the required LOD (level of detail) in the initial stages of a project. This will eliminate excessive work, which can take a tremendous amount of time due to the project’s scope.

The other challenges are related to the density of the elements, which complicates obtaining a high-quality survey from the project site. With these multitudes of elements, it’s impossible to get access with a scanner to each zone of the scanned area. Therefore, the modeling team must apply its analytical abilities to fill the blank spaces with little evidence of the element’s presence.

Point cloud vs Model
Challenges on the project

There were a couple of reasons why some of the elements had not enough points data to fully identify them. These reasons are:

  • Distance between scanner and elements. The scanned elements’ height is significant and with the scanner installed on the bottom level some of the structural elements, pipes, etc. were poorly scanned taking into account the distancing;
  • The density of the elements and their layering complexifies the access of the laser to elements that are hidden behind the other elements;
  • Lack of density of scanner locations – many elements were surveyed only from one side.

Solution: Elements with bad visual identification were modeled taking into account secondary features such as structure regularity and patterns, the resemblance of the visible parts of the cloud with existing options of steel profiles, etc.

Also, the issues connected with the quality of the point cloud were transferred to the surveying company so they could be analyzed and eliminated in the following projects.

Scope of work

The model was required to contain all the identifiable:

  • Structural elements such as precast concrete and steel structures at a low level of detail. Therefore, all detailed connections were omitted from this model;
  • Piping (with d>3″ only) and all significant equipment as generic masses;
  • Additional elements providing access, such as ladders, stairs, ramps, catwalk flooring, etc.;
  • The landscape around the modeled area, representing all existing sloping for the water drainage system.

As a result, we developed a model containing approximately 16,650 elements with 2″ accuracy.

Point cloud vs Model
Precise as-built model based on the point cloud
Further usage of the model for plant maintenance
Possibility of coordinating the existing structures with newly designed systems
Tools used
Autodesk Revit
Autodesk ReCap
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