How to use reality data on rural highway projects
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Rural highway projects are a tremendous challenge for BIM and construction managers. The complexities (like long duration, wide areas, constant change, and hidden geotechnical conditions) make it extremely difficult to stay up on the current state of work, and ensure positive financial results.
You’ve heard that reality data can improve rural highway work, and you’d like to implement a reality capture process on your own project. But there’s too much information out there — how do you get started?
This guide will offer everything you need to know. Below you’ll find a quick reference from industry experts that explains:
!!! Important note !!!
Regarding questions of accuracy, please refer to local guidelines, official resources, and client agreements. Since accuracy requirements will depend on a variety of circumstances that vary according to region and project, we won’t offer any specific guidance on accuracy below.
Quick guide for data capturing recommendations
X = Recommended options, O = Optional, for higher quality.
Design phase
Design work begins at the early stages of the project, and continues throughout construction as the situation on site changes. Up-to-date reality data can offer a view of current conditions, which is crucial to keep the design process running smoothly.
?? Capture this data
?? What makes good data
Focus on getting all the data necessary for design work. Pay attention to:
Ground visibility
Coverage
?? How to use the data
Once captured, use the data to produce all the models and calculations necessary for the initial project design.
Generate baseline topographic models?
Calculate earthworks quantities/masses
Combine topographic models with geotechnical surveys
Planning Phase
Once the design models are complete, the project plans construction. In this phase, reality capture offers the data needed to analyze the site for surface conditions, material levels, and so on.?
?? Capture this data
?? What makes good data
Your reality captures should document any changes that have occurred between the design stage and construction planning. Pay attention to:
Recency
?? How to use the data
Update your project assets, including designs, estimates, client agreements, and more.
Reality Data in the Preparation, Removal, and Construction Phases
These construction phases are largely focused on moving large amounts of materials. Reality capture offers the data needed to track the volume of that material, where it goes, any costs associated with it, and more.
1. Preparation Phase
This portion of construction involves the removal of trees and topsoil and getting the site ready for work. Once the land is clear, reality data can be used to validate designs and plans.
?? Capture this data
?? What makes good data
Focus on capturing the “bare” site by focusing on:
Coverage
Recency
?? How to use the data
Use the data to revisit your original plans and estimates, and adjust as needed.
2. Soil, Mid-layer, and Sub-base Removal Phase
As you remove layers, reality capture offers a way to track the materials being moved, determine true volume, and improve cost accounting with real-world data.
?? Capture this data
?? What makes good data
Focus on capturing work as it is completed. Pay attention to:
?? How to use the data
?3. Construction Phase
As the project begins the actual construction work, more precise reality data—like point clouds captured by lidar—can offer detailed records for work as it is completed, as well as greater context about the terrain.
?? Capture this data
?? What makes good data
Focus on data that will help you evaluate the site’s readiness for construction, then record that construction as it happens. Pay attention to:
Most projects will not need to capture the entire work area in every capture—just the portions where a phase has been completed.
?? How to use the data
?Reality Data in the As-built Capture Phase
Once surfaces and overground structures are constructed, reality data acts as a high-quality record of the project’s complete state, and a reference for future maintenance and potential QA disputes.
?? Capture this data
?? What makes good data
Focus on gathering data that reflects the project as it was completed—as opposed to how it was originally designed.
Focus on:
?? How to use the data
Converted to the appropriate deliverables for project completion.
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