![](\"https:\/\/www.cms.bgu.tum.de\/images\/research\/multiLOD\/for_2363.png\")
<\/p>\nLeitung: Prof. Dr.-Ing. Andr\u00e9 Borrmann, TU M\u00fcnchen<\/p>\n
The design of a building is a collaborative process between multiple disciplines. Using Building Information Modeling (BIM), a model evolves throughout multiple refinement stages to satisfy various design and engineering requirements. Such refinement of geometric and semantic information is described as levels of development (LOD). So far, there is no method to explicitly define an LOD\u2019s requirements nor any specification of its uncertainty. Furthermore, despite the insufficient information available in early design stages, a BIM model appears precise and certain. This can lead to false assumptions and model evaluations, for example, in the case of energy efficiency calculations or structural analysis. <\/p>\n
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To allow the use of simulation and analysis software for assessing building design options in early design phases, it is required to explicitly describe the fuzziness involved with the information provided. However, so far, there are no capabilities to unambiguously define a BIM LOD including a specification of its fuzziness. In contrary, a BIM model appears to be precise and without any uncertainty at any stage in the design process. This can lead to false assumptions and therefore wrong model evaluations. Due to the increasing application and high potential of semantic BIM models for subsequent simulations and analyses, the implementation of a multi-LOD model seems essential for the future of digital planning and is thus the topic of this research project.<\/p>\n
The efforts and costs required to make changes in a building model in the early stages are relatively lower than in the subsequent stages. However, the lack of adequate information impedes taking informed decisions. Hence, it is crucial to maintain the individual component\u2019s LOD requirements. Especially in the process of designing a building, the components are associated with diverse levels of development within the same phase, such as load-bearing components can be described with a higher LOD than the interior fittings in the early design stages.<\/p>\n
To our knowledge, there is no approach for formally defining and maintaining multiple levels of development throughout the design stages. Neither is there a formal definition of a building component\u2019s level of development nor is there an explicit description of the fuzziness of its geometric and semantic information. Therefore, the multi-LOD meta-model is proposed in order to:<\/p>\n
<\/br> The multi-LOD meta-model aims to maintain a clear separation between the building components\u2019 semantic and geometric requirements. In terms of geometry representation of a building component, it is refined along with increasing the level of development. For example, as demonstrated in Figure 1 at LOD 100, an external wall is presented as a centerline, since in the next LODs additional information is available, such as a thickness and material, it is possible to render the wall solid model in its 3D shape and dimensions. This kind of hierarchical development of a centerline towards a solid model defines the dependencies between the geometric representations on the different levels of development. Accordingly, the relationships between the semantic requirements are determined, which supports checking the consistency between the multiple LODs.<\/p>\n With incrementing the LOD, additional attributes become available, for example, the construction type and material information can be determined starting from LOD 200. In some cases, it is uncertain whether a specific attribute is available or can be estimated from a specific LOD. Thus, the multi-LOD model provides the ability to specify whether an attribute is mandatory or optional as well as offering a level of precision in specifying the attribute\u2019s assigned value in case of uncertainty. The level of precision in assigning the attribute\u2019s value is related to its type; it might be achieved by specifying an abstract value, such as a classification, or a fuzziness range. With that said it is possible to model and analyze the known uncertainties of the building model at the early design stages where uncertainty is at its highest. <\/p>\n
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