Extended Thesis Abstract
Digital Enhancement for Early Stage Building Information Modelling (BIM) Clash Detection
Through discussions and research of contemporary clash and error detection methods, this research explores the nature of procedures used within the architecture, engineering and construction (AEC) industry. Throughout both design and documentation, the objectives of these tools are to spot potential faults by performing clash detection of BIM information take off and to investigate the quality of your BIM files by automating the design process, to analyse and present to the clients of relevant problems quickly and easily to avoid expensive reworking by knowing your BIM model comply with the constraints. According to researchers, BIM-based clash detection are becoming more crucial and plays a major role in the design process to design production (Jung-Ho S 2012). Previously, the traditional method to identify clashes was via manual overlay 2D drawings on a light table to visually see clashes which was inefficient and time consuming. The early 3d graphics integrated later allows the user for a better visual clash detection analysis but was still not 100%accurate and still time consuming (Wang, J 2013). There are three clash classes in the clash detection BIM model, first is the hard clash, secondly is the soft clash/clearance clash and lastly is the 4D/ workflow clash. The differences between these three are the level of detail (LOD) of the BIM model. The hard clash detection is the geometry base detection commonly between the two main architectural or structural elements that’s in the shared space which intersect each other. The soft clash/Clearance clash are geometries requires to be within the tolerance to comply with constraints. The 4D/Workflow clash detection is to solve the clash delivery prediction timeline or schedule related information (ACD 2017). This research will mainly be focusing on the two clash classes of the hard and soft clash.
For the final design to be clash-free, efficient collaboration is crucial. Yet, current state of design practices is too dependent on the clash detection tool to coordinate and solve problems later in the design stage because current design practices often solely held meetings and general “design coordination” to identify and solve clashes to deliver a clash-free 3D BIM model (Akponeware, A and Adamu, Z, 2017). Therefore, these information addresses the aspect and the opportunity to the question on, is there a better system to filter the differences between the REAL and the NOT REAL clash? to redefine the design process to achieve better coordination. This paper is to discuss on the current state of the art in architectural design positions on complexity and CAAD, and how complexity can be dealt with, from architect’s perspectives and how miscommunication and conflict may cause clashes to occur (Chougui, Ali 2006).
In a constantly changing environment, nothing its perfect, precise and accurate, this is because one attempts to represent a perfect design in an imperfect world through various software, where parties are still working independently. For these reasons, there’s always going to be clashes and hidden errors in every project.
This research paper will underpin some of the key focal points and the foundations of how clashes occurred and may occur, is it a miscommunication factor, the complexity of the design or is it the shift of attention from the design process to design product etc. to digitally enhance the construction methods (Chougui, Ali 2006). This paper proposes an enhanced workflow that streamlines the process of clash detection, yielding an increase in both precision and computational efficiency methodology to be employed and carried out in collaboration with Aurecon through case studies and surveys of existing clash detection process in the AEC industry. Rule-based algorithm clash detection like Solibri Model and geometry-based such as Autodesk Navisworks Manager (Guangbin, W 2011) against the proposed clash detection methodology which attempt to rationalise the collision of multiple inputs with minimal effect. This methodology will be run on Autodesk Revit and Dynamo to support collaboration between parties, which can potentially be reducing cost and the amount of labouring hours reworking on the project. This will be done through a rule-based algorithm as constraints to determine the geometry compliance of positive (true) and negative (false) return values are added into the data structure will be mandatory during the design phase (Schwabea, M 2016). Rules-based algorithm will be base of geometry clash classification on two classes as mentioned earlier of the hard clash and soft clash to optimise the design decision and to prioritise and investigate he differences between the REAL and the NOT REAL clash. The differences between the real and not real clash is generally base on the result or the clash report, for example as shown on Fig.1, a scenario where there are 10 rafters running along the roof and there happened to be a pipe hitting the underside of each rafters, the end clash detection report compile with a list of 10 clashes, in reality, there’s only 1 real clash.
Fig.1 (AEC DevBlog, 2013) (Autodesk Navisworks Clash Report Interface)
The outcome is to provide a user friendly and intuitive interface, capable of providing the user with more efficient methods of clash visualisation, elimination and possessed comparable predictive capabilities, and at times, an increased accuracy to strengthen the design process coordination for efficient construction review. Surveys will be conducted through user testing and their experience to determine if the proposed methodology as mention above had any value addition to their existing workflow. Expected result aims to provide the feasibility of clash detection and avoidance to improve current coordination issues to minimise labouring hours and with a more intuitive experience compared to the daunting change of software.
For future testing, our approach aims to support any implicit and parametric geometric representation that supports both solid and curve geometry intersection. At some point of practical testing, some of the approaches would cross path between the accuracy and computational efficiency to accommodates the requirements.
Integrating the proposed clash detection methodology in the design process has proven to minimise and eliminate clashes and increase BIM coordination (clash detection) efficiency at Aurecon. Clash detection is not something new to the built environment, the advancement of technology available has allow designers and architects explore more than just three dimensional. To understand clash detection, one must first experience the behaviour of the building as an event through elements and characteristics to influence the way the building is conceived, to truly achieve clash-free 3D BIM models.
· Akponeware, A and Adamu, Z, 2017, Clash Detection or Clash Avoidance? An Investigation into Coordination Problems in 3D BIM
· Association of Construction and Development ACD, 2017, Clash Detection in BIM Modeling, visit 18//17, http://www.associationofconstructionanddevelopment.org/articles/view.php?article_id=10780
· Chougui, Ali (2006), THE DIGITAL DESIGN PROCESS: Reflections on architectural design positions on complexity and CAAD, pp. 273–288.
· Guangbin W, Wei, L and Xuru, D, 2011, Exploring the High-efficiency Clash Detection between Architecture and Structure.
· Jung-Ho. S, Baek-Rae. L, Ju-Hyung. K, Jae-Jun. K, 2012, Collaborative Process to Facilitate BIM-based Clash Detection Tasks for Enhancing Constructability, 299–314.
· Schwabea, M, Königa, M and Teizerb, J (2016), BIM Applications of Rule-based Checking in Construction Site Layout Planning Tasks, Germany.
· AEC DevBlog 2013, What’s New in Autodesk Navisworks Family of software 2014 — Part4, visit 17/09/1, http://adndevblog.typepad.com/aec/2013/04/whats-new-in-autodesk-navisworks-family-of-software-2014-part4.html