Generating bridge geometric digital twins from point clouds

Abstract

The automation of digital twinning for existing bridges from point clouds remains unresolved. Previous research yielded methods that can generate surface primitives combined with rule-based classification to create labelled cuboids and cylinders. While these methods work well in synthetic datasets or simplified cases, they encounter huge challenges when dealing with real-world point clouds. The proposed framework employs bridge engineering knowledge that mimics the intelligence of human modellers to detect and model reinforced concrete bridge objects in imperfect point clouds. Experiments on ten bridge point clouds indicate the framework can achieve high and reliable performance of geometric digital twin generation of existing bridges. End-user requirements (EURs)Developing detailed EURs of DTs is outside the scope of this study. This section summarizes the fundamental information that a DT must contain. The end-users of DTs are inspectors, engineers, and the decision makers. The EURs define the information that will be required by the end-users from both their own internal team and from suppliers. The EURs should clearly articulate the information requirements and describe the expected information deliverables. However, the nature of the EURs depends on the complexity of the project, the experience, and the requirements of the end-users. Experienced end-users may develop detailed EURs, whilst others may only set out highlevel requirements, and basic rules. Broadly, a DT includes:EUR 1: Component-level digital representation.

Defining a Digital Strategy in a BIM Environment to Manage Existing Reinforced Concrete Bridges in the Context of Italian Regulation

“…As far as existing bridges are concerned, complete digitalization is necessary with the goal of supporting the management and maintenance of specific characteristics over time. This digital reconstruction can be put into action with automatic or semi-automatic methodologies that use survey data (e.g., point clouds) to generate models, for example, in IFC format, or for the automatic detection of the bridge elements and related damage information [21,59,[61][62][63][64]. In addition, between BIM and FEM, the adoption of an adequate parametric strategy allows one to manage highly complex projects and facilitates collaborations between different disciplines or technicians [65][66][67].…”

Digital Twin for Civil Engineering Systems: An Exploratory Review for Distributed Sensing Updating

“…Torques and rotation rates, temperatures of components and the state of the lubricating oil must also be tracked, together with environmental conditions (wind speed, wind direction, temperature, humidity and pressure)". Generally, the EURs of a Digital Twin define the information required by its end-users [18]-whether these are engineers, infrastructure managers, both, or others-or, that is, the expected output for the proper design/management of the asset in question.…”

“…Overall, the global Digital Twin market size was valued at USD 3.1 billion in 2020 and is projected to reach USD 48.2 billion by 2026 [17]. In regards to the construction industry, it is estimated that the integration of Digital Twins will allow for savings of 15-25% by 2025 [18].…”

“…In contrast to a traditional digital model (developed, for example, by means of Computer-Aided Design software), Digital Twins are not restricted to being just geometrically accurate digital replicas. Instead, as correctly stated in Lu and Brilakis [18], in a Digital Twin, the geometric and graphical data are enriched by semantic information, i.e., massive, cumulative, real-time, real-world data measurements. These data include, but are not restricted to, engineering data (movements, deformations, overheating), operational data, behavior descriptions, inspection reports, and maintenance history.…”

Open‐source terrestrial laser scanner for the virtualization of geometrical entities in AEC classrooms

“…The vast number of studies carried out regarding the use of laser scanning techniques has proven its effectiveness for monitoring assets during design, construction, and maintenance stages across multiple disciplines within AEC. Enabling its information in the BIM environment, providing added value to feed calculation models, inadvertently postulate the TLS as a geometrical digital twin (gDT) generator [50,34,27].…”