Chair of Computational Modeling and Simulation
TUM Department of Civil, Geo and Environmental Engineering
Technical University of Munich

Development of a multi-LOD data model representing buildings at different phases

Team Members: Jimmy Abualdenien, André Borrmann

Funding: Deutsche Forschungsgemeinschaft (DFG), grant FOR 2363

Partners: rub uni KU logo Uni Duisburg

Running period: 03.2017-01.2020

Project description

The design of a building is a complex process in which the solution is developed in an iterative manner in order to fulfill objectives and boundary conditions of multiple designs and engineering disciplines involved. If the Building Information Modeling (BIM) methodology is applied, the planning process starts with a coarse model, which is gradually developed into a more and more detailed model. These refinement steps are described as levels of development (LOD) and form the analogon to the different scales in engineering drawings.


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.

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’s 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.

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’s 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:

  • Define component types’ LOD requirements
  • Model information uncertainty
  • Represent a building model on multiple stages
  • Describe the relationships between LODs
  • Check the consistency between LODs


Figure 1. Separation of geometry and semantics on different LODs of an external wall

The multi-LOD meta-model aims to maintain a clear separation between the building components’ 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.

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’s assigned value in case of uncertainty. The level of precision in assigning the attribute’s 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.

Figure 2. Example of assigning geometric-semantic attributes and fuzziness of an external wall

Figure 2 provides geometric and semantic attributes of an External Wall component type for LODs 120 to 300. The surface dimensions exist starting from LOD 120 with a permissible fuzziness range of ±10 cm, while no fuzziness is permitted afterward. Additionally, the information describing wall thickness and opening position are available starting from LOD 200 with ±10 cm of fuzziness and then reduced to ±5 cm on LOD 300. Considering a different type of fuzziness, the information about material can be available from LOD 200, where at this level; it is defined by specifying the material group, such as Ceramic, whereas afterward on LOD 300 the exact material value, like Brick, should be assigned.


Figure 3. Multi-LOD meta-model (UML diagram)

The multi-LOD meta-model design provides means for defining a project-specific data-model, incorporating formal LOD definitions for individual component types. It introduces two layers: data-model level defines the component types as well as their geometric and semantic requirements for each LOD. The instance level represents the building model by instantiating multiple instances of the component types defined on the data-model level.

The multi-LOD meta-model offers a high-level interface that provides a consistent way for defining and querying LODs in term of their semantic and geometric requirements. As the LOD requirements take into account the permissible fuzziness, the known uncertainties are explicitly modelled, which delivers great advantages in assessing and verifying the model consistency in the early design stages. The meta-model introduces two layers, data-model level and instance level. This offers a high degree of flexibility in defining per-project LOD requirements and facilitates formal checking of their validity, such as requiring specific information for Embodied Energy calculations, Building Performance simulations, or Structural analysis.

The main project is divided into 5 subprojects:

  • Development of a multi-LOD data model representing buildings at different phases (this part)
  • Methods for modeling design variants based on digital building models
  • Visual exploration for assessing design variants
  • System-based simulation of energy flow in buildings
  • Intelligent substitution models for structural design

An up-to-date information can be found on the project's main page.


▪  Abualdenien, J.; Borrmann, A.:
A meta-model approach for formal specification and consistent management of multi-LOD building models
Advanced Engineering Informatics 40 (1474-0346), pp. 135-153, 2019
DOI: 10.1016/j.aei.2019.04.003

doi pdf bibtex mediatum
▪  Abualdenien, J.; Borrmann,A.:
Multi-LOD model for describing uncertainty and checking requirements in different design stages
In: eWork and eBusiness in Architecture, Engineering and Construction: Proceedings of the 11th European Conference on Product and Process Modelling (ECPPM 2018), Copenhagen, Denmark, 2018

pdf bibtex mediatum
▪  Abualdenien, J.; Borrmann, A.:
A multi-LOD model representing fuzziness and uncertainty of building information models in different design stages
In: Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018), Ghent, Belgium, 2018

pdf bibtex mediatum

© 2019 CMS TUM | Technische Universität München