An Automated Layer Classification Method for Converting CAD Drawings to 3D BIM Models

Yin, Mengtian; Ye, Zihao; Tang, Llewellyn; Li, Shuhong

doi:10.1007/978-3-030-00220-6_9

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…In addition to exploring 3D and more immersive modalities, some researchers have looked at ways to leverage traditional 2D drawings, exploring ways to facilitate the process of drawing interpretation, such as using AR as a supplement to traditional drawings [8,22]. Other researchers have explored the conversion of 2D drawings into 3D models with varying levels of automation [23][24][25][26][27][28]. These works focus on the relationship between 2D and 3D documentation, but not necessarily on the impacts to the users or their learning.…”

Section: Bim and 2d In Constructionmentioning

confidence: 99%

Student Approaches and Performance in Element Sequencing Tasks Using 2D and Augmented Reality Formats

et al. 2022

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In civil and construction engineering education research, a focus has been on using 3D models to support students’ design comprehension. Despite this trend, the predominant mode of design communication in the industry relies on 2D plans and specifications, which typically supersede other modes of communication. Rather than focusing on the presentation of less common 3D content as an input to support students’ understanding of a design, this paper explores more common 2D inputs, but compares different visualization formats of student output in two educational interventions. In the first intervention, students document a construction sequence for wood-framed elements in a 2D worksheet format. In the second, students work with the same wood-framed design, but document their sequence through an augmented reality (AR) format where their physical interactions move full-scale virtual elements as if they were physically constructing the wood frame. Student approaches and performance were analyzed using qualitative attribute coding of video, audio, and written documentation of the student experience. Overall, results showed that the 2D worksheet format was simple to implement and was not mentally demanding to complete, but often corresponded with a lack of critical checks and a lack of mistake recognition from the students. The AR approach challenged students more in terms of cognitive load and completion rates but showed the potential for facilitating mistake recognition and self-remediation through visualization. These results suggest that when students are tasked with conceptualizing construction sequences from 2D documentation, the cognitive challenges associated with documenting a sequence in AR may support their recognition of their own mistakes in ways that may not be effectively supported through 2D documentation as an output for documenting and planning a construction sequence. The results presented in this paper provide insights on student tendencies, behaviors, and perceptions related to defining construction sequences from 2D documentation in order for educators to make informed decisions regarding the use of similar learning activities to prepare their students for understanding the 2D design documents used in industry.

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Section: Bim and 2d In Constructionmentioning

confidence: 99%

Student Approaches and Performance in Element Sequencing Tasks Using 2D and Augmented Reality Formats

et al. 2022

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“…Established procedures for modelling these buildings generally begin with importing CAD drawings into BIM software, providing a base 2D drawing on which the 3D model is developed manually (Barki et al 2015;Fadli et al, 2016). However, converting CAD to a 3D BIM model is restricted by the accuracy and automation level (Yin et al 2018). Besides, manually entering data into a BIM model of a large building is cumbersome; hence, it is essential to develop a framework for capturing and incorporating existing building data.…”

Section: Research Background and Knowledge Gapsmentioning

confidence: 99%

Untitled

2022

JER is an international, peer-reviewed journal that publishes f

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Building Information Modeling (BIM) is mainly used for the design and construction of new buildings.However, one of the main challenges facing BIM adoption for existing or old buildings constructed without consideration for their modeling is obtaining raw and accurate building data and converting it to the BIM model. Based on this challenge, this study develops a framework that uses different data capture techniques for existing buildings, then transforms this captured data into 3D BIM models through which it can improve its management processes as facilities during their service life. Specifically, 3D laser scanning techniques were used to capture indoor building data, while drones equipped with high-definition cameras (UAV) were used to capture outdoor building data such as geometric dimensions, material shapes, surfaces and various shapes. Then the captured data was converted into a high-resolution 3D model. This has been verified the accuracy of this engineering model by converting the two-dimensional engineering plans to threedimensional through the well-known engineering design tools. Moreover, the 3D model has been integrated with the Web Based Building Management System (BMS) platform. This research framework helps in developing engineering facility management processes and modern digital transformation processes that aim at speeding up facility management during their service period using modern technologies. This study aims to develop current knowledge in the construction industry and facility management by reviewing a comprehensive understanding of how to use modern technologies to obtain various information to develop BIM models for existing and non-modeled buildings in order to exploit and integrate them with advanced Journal of Engg. Research Online First Article 2 facility management systems and platforms, which constitutes a major progress in this field allowing to save a lot of effort and money in the future.

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Two-stage automatic structural design of steel frames based on parametric modeling and multi-objective optimization

Shan,

Zhou,

Liu

et al. 2024

Struct Multidisc Optim

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An Automated Layer Classification Method for Converting CAD Drawings to 3D BIM Models

Cited by 5 publications

References 9 publications

Student Approaches and Performance in Element Sequencing Tasks Using 2D and Augmented Reality Formats

Student Approaches and Performance in Element Sequencing Tasks Using 2D and Augmented Reality Formats

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Two-stage automatic structural design of steel frames based on parametric modeling and multi-objective optimization

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