Even though the developed method can obtain objective scores regarding different factors, some limitations affect the factors individually or in a group. The following limitations should be overcome:
The currently proposed method needs to be applied using BIM technology due to the
data and implementation requirements, designers who are not provided with BIM authoring tools may find difficult to obtain the same results.
The Geometric Entropy Characterization method implemented in the research can
only score planar shapes, curved shapes or irregular shapes are not in the research scope. Further metrics for curved and irregular shapes may open the evaluation to most of the different type of design currently available and also to other building systems.
The method is primarily applied to buildings only. This research does not involve
other types of constructions such as bridges, dams, tunnels, and so forth. However, is believed that an adjustment on the factors metrics may influence positively on scoring those types of particular structures. The proposed method should be only used to compare constructions of the same type.
The Implementation used in this research creates a slow performance, especially if
the building has many elements. It is recommended to use another type of implementation methods such as Revit API or other BIM authoring tool. A translation of this method could be the first step to enhance optimal performance.
The method only takes in count the construction core systems and finishing. The
proposed method does not take in count other construction systems, such as MEP systems or any special systems that can be used in a building. Further research is open to obtain the correct buildability index, system max scores and involved stakeholders for those types of elements.
The Geometric complexity scores are obtained independently from the construction
methods, allowing the use of this score to compare buildings from different places.
On the other hand, the construction complexity scores are restricted to the construction method defined in a specific area, not allowing the comparison of building from different places. A generic buildability index values, systems max score and stakeholders involved can open the possibilities of the application of this complexities to not restrained area
8 Conclusion
This research proposes a method to calculate the geometric complexity and the construction complexity of a BIM model, directly from the authoring tool. The model itself is the closest representation of the construction product which is the building. The factors that affect the product complexity can be taken as main factors that may affect the building complexity. From those factors two types of answers can be characterized: how hard is to describe the building is characterized by using the geometric entropy score, the number of elements in a building and the shapes variety on the building. On the other hand, the construction complexity represents how hard is to create this building can be characterized by the buildability, size, and multidisciplinarity factors. The factors metrics were taken and adapted from other studies that prove their veracity. The factors were tested in different models, and the results supported their goal independently. The factors score in a group gave an idea of the geometric and construction complexity from the point of view where a design can affect the construction directly, or it can affect the construction indirectly by affecting the visualization or the communication in the people involved in the construction. During the test, four buildings were tested. These buildings were specially designed or selected to represent a controlled testing environment. The subjectivity was removed by the obvious complexity differences between the buildings.
The result showed the building 1, which had the purpose to have a low geometric and construction complexity; scored (4.5,0,1), (10.82,2.07,20),(7.56,0,4) for its foundation, shell, and interior geometric complexity respectively. The same building 1 sample obtained a score of (24.1,24,139) for its construction complexity. On the other hand the building 4, which was the one with obvious high geometric and construction complexity scored (0,0,76),(17.04,2.39,989),(16.67,2.66,699) for its foundation, shell, and interior geometric complexity respectively. The same building scored (24.1,40,2515) for its
construction complexity. The result obtained from these complexities calculations may imply to be the first step on help the designer to objectively compare different designs and have an idea of the effect that design can have on the visualization of 2D views in plans, and from this objective score, decide the best method for visualization depending on the design. The results also help the designer to understand the communication and construction issues that a specific design may provoke. In conclusion, this research proposes a way to objectively score the geometric and construction complexity directly from the BIM model authoring tool. These scores aims to allow the model designer obtain an objective way to understand and compare BIM models and from the results know that the model in study may imply a different type of visualization method due to its geometric complexity, or it may imply new design assessments due to its construction complexity.
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