• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.313-322
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• 2022

The number of architects who adopt BIM(Building Information Modeling) as the design method are gradually increasing because of its productivity and efficiency. Climate Change and Global Warming lead to legislation of new energy regulations and strengthen existing ones. The current architectural design methods (2D CAD) take a lot of time and effort to verify energy codes and are hard to adjust according to the design changes. The purpose of this study is to show the effectiveness of the BIM in building envelop energy modeling of the housing project. In the process of design method change, We could contribute to increasing productivity and efficiency in building energy verification through BIM because the updated value could be calculated simultaneously without information omission or recalculation process. The procedure for the study is as follows. Using BIM of the Goldin at Essex Crosing Housing Project by Revit 2011 as a case model, this study analyze the criteria for energy plan to conform to the energy code in NYC. The result value from the setting of the Revit model is compared with the reference value required by the NYC Energy Code. Finally, the data from BIM are entered into COMckeck, the energy verification program provided by U.S. Department of Energy, to check whether the building envelope energy performance conforms to NYC Energy Code.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.561-569
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• 2014

In construction site, BIM is used in part of construct-ability review and design mistake checking. However, in a current domestic construction site, except public order project, most of work in private order project has been processing based on 2D work. As an expert resists to certain point in introduction of new technique, it may be shown in the introduction of BIM. For this, We need to analysis construct-ability of introducing BIM, work field of introducing and operational capability about present domestic construction engineers. Therefore, this study solves the problem of existing construct-ability analysis, and it visualizes the various information and objects for an effective job performance. Furthermore, construct-ability analysis by BIM that can use an intergrated management is theoretically examined and practical field-application priority among conclusions is proposed through a survey targeting on the hand-on worker. Therefore, this study suggests a factor supplying for a business-centric introduction plan and support condition.