Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 7th July 2022, 15:39:12 CEST

 
 
Session Overview
Session
Session W1.9 (Online Track): Ensuring high quality building simulations/BIM
Time:
Wednesday, 01/Sept/2021:
10:30 - 12:00

Session Chair: Heba Hassan, Beni Suef University
Location: Virtual Meeting Room 3

External Resource: Click here to join the Zoom Meeting
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Presentations
10:30 - 10:48

Automatic generation of second level space boundary geometry from IFC models

Eric Fichter, Veronika Richter, Jérôme Frisch, Christoph van Treeck

Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

Building Information Modeling (BIM) describes a method of networked planning, execution and management of buildings using software. All relevant building data are digitally modelled, combined and recorded. To ensure a holistic planning process, it is advisable to use building models for process planning simulations. In case of an OpenBIM approach, the models can be transferred as IFC files [1]. In simulation practices, however, the models are often of poor quality. This is due to immature export functions and incomplete enrichment. In context of thermal simulations, this includes the lack of second level space boundaries within IFC models, which are necessary for simulation in EnergyPlus [2]. The consequence is a time-consuming manual rework for the simulation expert. An automated enrichment using software that is robust against geometric modelling or export errors and that does not rely on perfect meta-information would be beneficial. Therefore, the goal of this paper is to present a tool that enriches IFC files with correct second level space boundaries. The algorithm will be explained and then applied to an example building. For verification, the enriched IFC model will be simulated using EnergyPlus. The results will be compared with a manually generated simulation model.

Scientific Innovation and Relevance

(max 200 words)

In the last two decades, multiple algorithms and programs for the generation of second level space boundaries were presented and documented in literature [3, 4, 5, 6]. However, most of them are not actively supported anymore, are based on older IFC versions (for example IFC 2x3) or are not publicly accessible. Moreover, all the mentioned algorithms used closed-source libraries. In contrast, the tool presented in this paper is based on widely used and well maintained open-source libraries. Furthermore, no meta information, e.g. the definition of spaces and their relation to building elements, is needed. Nevertheless, if meta information is provided, it could also be used. By avoiding Boolean operations between volumes, the algorithm is robust against modeling errors, such as gaps and non-physical superposition of volumes. Beside the generation of the space boundaries, a watertight and simplified surface geometry is created, in which the faces of the building elements are split according to the boundaries. Moreover, the spaces are generated as well.

Preliminary Results and Conclusions

(max 200 words)

The generated space boundaries are exported to IFC. If necessary, the simplified and corrected geometries can also be exported as boundary representation in a geometry file format. The proposed method significantly reduces the manual effort for model generation and contributes to the derivation of simulation models from BIM data. Therefore, it improves the OpenBIM work process along with the design and optimization of building energy systems. In addition to the use in building energy performance simulation, an application in the pre-processing of geometry for Computational Fluid Dynamics (CFD) simulations is conceivable. The algorithm and the applications will be presented in the paper.

Main References

(max 200 words)

[1] ISO 16739-1:2018, Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries — Part 1: Data schema

[2] EnergyPlus Development Team, 2020. EnergyPlus engineering reference: The reference to EnergyPlus calculations. EnergyPlus Version 9.0. US Department of Energy.

[3] van Treeck, C., Rank, E. Dimensional reduction of 3D building models using graph theory and its application in building energy simulation. Engineering with Computers 23, 109–122 (2007).

[4] Rose, C.M., Bazjanac, V. An algorithm to generate space boundaries for building energy simulation. Engineering with Computers 31, 271–280 (2015).

[5] Lilis, Georgios & Giannakis, Georgios & Rovas, Dimitrios. (2016). Automatic generation of second-level space boundary topology from IFC geometry inputs. Automation in Construction. 76.

[6] Jones, Nathaniel & McCrone, C.J. & Walter, B.J. & Pratt, K.B. & Greenberg, D.P. (2013). Automated translation and thermal zoning of digital building models for energy analysis. Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association. 202-209.



10:48 - 11:06

Geometrical interoperability of 3D CityGML building models for urban energy use cases

Avichal Malhotra1, Yue Pan2, Jérôme Frisch1, Christoph van Treeck1

1Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany; 2Nesseler Grünzig Bau Gmbh, Germany

Aim and Approach

(max 200 words)

Geographical Information Systems (GIS) are often used as the foundation for urban scale thermal simulations. Virtual 3D city models, therefore, do serve as an important entity for analysing the thermal behaviour of buildings at an urban scale. However, the geometrical and semantic information for multiple buildings are openly available only for a relatively smaller number of countries, cities and districts. CityGML [1], a XML based modelling standard, is gaining popularity for city level information modelling and simulations. State- and city-wide 3D CityGML models are also available for countries like Germany, Austria and Switzerland [2]. However, the question about the geometrical interoperability of these models is still unanswered. Within the scope of this paper, the authors will present a CityGML Geometrical Transformation and Validation tool (CityGTV). This tool does facilitate the interoperability of 3D CityGML building models for countries where no or low quality data exists. Furthermore, the CityGTV will allow simulation scientists and urban planners to efficiently transform the building coordinates, validate the geometrical aspects of the buildings and further compute the district level energy performance of the buildings using environments such as Modelica, EnergyPlus, etc. With the tool, the altitude and orientations of individual buildings can also be transform.

Scientific Innovation and Relevance

(max 200 words)

For many of the developed and developing nations, the scarcity of CityGML datasets is quite high. These countries on the other hand have a large potential for energy conservation and green energy production. Facilitating coordinate transformations of the 3D models within different reference systems, the transformed CityGML datasets can be used for multiple use cases and scenarios. Moreover, as the semantic, geometric and sometimes monitoring data availability of the existing built-up buildings is higher, transformed virtual 3D models of these buildings can be used as references for future planning and development of an urban area. One possible use case would be to analyse the solar potential of a city quarter in equatorial regions using the transformed 3D models of buildings from temperate or polar areas. Though CityGML data models only contain the geometrical and semantic information, these could be extended using the CityGML Application Domain Extensions (ADEs) [3]. For the scenario-specific analysis, the building models can be enriched using tools such as CityGML Toolbox [4] and therefore, be simulated for the individual use cases. This tool will also help urban planners and the simulation community to increase the operability of CityGML data models for multiple applications and domains.

Preliminary Results and Conclusions

(max 200 words)

The CityGTV tool is currently being developed using python programming and PyQT [5] schema bindings. The user-friendly architecture and interface of the tool will allow users of different expertise levels to easily transform the building model(s) to their required reference systems. Within the tool the functionalities of geometrical validation and visualization are also foreseen by the authors. In future, the CityGTV tool will undergo an open source development process. The object oriented development methodology adapted by the authors will also facilitate the integration of CityGTV into different tool chains and simulation environments. The current implementation of the tool is being rigorously tested and further developed using open source datasets of large city quarters from cities such as Hamburg, Vienna, Berlin, etc. The transformed building models can be exported as new CityGML datasets which are in the user defined coordinate reference system.

Main References

(max 200 words)

[1] G. Gröger, T. Kolbe, C. Nagel und K. Häfele, „OGC City Geography Markup Language (CityGML) Encoding Standard,“ OGC, 2012.

[2] A. Malhotra, J. Bischof, J. Allan, J. O'Donnel, T. Schwengler, J. Benner und G. Schweiger, „A review on country specific data availability and acquisition techniques for city quarter information modelling for building energy analysis,“ in Forthcoming IBPSA BauSIM 2020, Graz, 2020.

[3] F. Biljecki, K. Kumar und C. Nagel, „CityGML Application Domain Extension (ADE): overview of developments,“ Open Geospatial Data, Software and Standards, 27 August 2018.

[4] J. Hütter, „KIT - IAI Homepage,“ 2018. [Online]. [Zugriff am 09 02 2020].

[5] PyQt, „PyQt Referencing Guide,“ 2012.



11:06 - 11:24

Interoperability between BIM and building energy modelling – a case study

Francesco Asdrubali1, Manuel Manzo2, Gianluca Grazieschi3

1University of Roma Tre, Italy; 2University of Roma Tre, Italy; 3University of Roma Tre, Italy

Aim and Approach

(max 200 words)

The paper aims to assess some interoperability issues between Building Energy Modelling (BIM) and dynamic Building Energy Modelling (BEM). The investigation is performed considering as a case study the design of a new residential complex composed of two terraced buildings located in the eastern belt of Rome. The two buildings are very similar and are designed following the most updated regulations about energy efficiency in Italy: they aim at the nearly zero energy standard. During their early design stage, the chosen case studies were modelled using Revit as a BIM platform. The BIM model was exported in Design Builder in order to perform a dynamic simulation of their energy consumptions in an optimization perspective.

Scientific Innovation and Relevance

(max 200 words)

Building Information Modelling is spreading in the recent years due to the legislations that impose it. Some energy simulation techniques have already been implemented in the BIM models since they can contain information about the thermo-physical properties of opaque and transparent surfaces. Moreover, some plug-ins can be added in BIM tools in order to perform energy analysis. However, in most cases, the energy modelling is simplified and stationary. In order to perform a dynamic energy simulation, it is appropriate to export the BIM model into a dynamic energy simulation software. This means that BIM and BEM tools should be interoperable. The interface between the two models still presents some limitations. Some research is needed to improve it and some potential software features for a better BIM to BEM interoperability are suggested.

Preliminary Results and Conclusions

(max 200 words)

The main difficulties and limitations in the interface between the two softwares are evaluated after the application to the case study. The creation of an accurate BIM-borne BEM model is quite time-consuming, laborious and subject to human made errors: the users are required to check the interoperability issues and, in some cases, to fix them manually.

After the description of the limitations found during the application, some suggestions are proposed in order to improve the interoperability between BIM and BEM models.

Main References

(max 200 words)

Léa Sattler, Samir Lamouri, Robert Pellerin, Thomas Maigne. Interoperability aims in Building Information Modeling exchanges: a literature review. IFAC-PapersOnLine, Volume 52, Issue 13, 2019, https://doi.org/10.1016/j.ifacol.2019.11.180.

Ehsan Kamel, Ali M. Memari. Review of BIM's application in energy simulation: Tools, issues, and solutions. Automation in Construction, Volume 97, 2019, Pages 164-180, https://doi.org/10.1016/j.autcon.2018.11.008.

Georgios Gourlis, Iva Kovacic, Building Information Modelling for analysis of energy efficient industrial buildings – A case study. Renewable and Sustainable Energy Reviews, Volume 68, Part 2, 2017, Pages 953-963, https://doi.org/10.1016/j.rser.2016.02.009.

Haily Fernald, Seungyeon Hong, Scott Bucking, William O’Brien. BIM to BEM translation workflows and their challenges: a case study using a detailed BIM model. Proceedings of eSim 2018, the 10ᵗʰ conference of IBPSA-Canada Montréal, QC, Canada, May 9-10, 2018.



11:24 - 11:42

Texture mapping and IFC material retrievement for virtual reality applications

Sebastian Duque Mahecha, Sergi Aguacil Moreno, Alexandre Dennis Stoll, Laurent Deschamps

Building2050 group, Ecole Polytechnique Fédérale de Lausanne (EPFL), Fribourg, Switzerland

Aim and Approach

(max 200 words)

Successful experiments have been carried out in order to enable interactive IoT device management through immersive environments supported by Virtual-Reality(VR) and Augmented Reality (AR)[1–7]. In these experiments, material texturing plays a key role in making the experience vivid and facilitating spatial orientation and object sight recognition. In parallel, Architecture, Engineering and Construction(AEC) professionals increasingly integrate into their practice Building Information Modelling(BIM) methodologies, notably relying on the IFC data model[8] as the open international standard [9,10]. According to these methodologies, digital models synthesising informed-3D elements function as central source of building data along the building lifecycle. In spite of the evident convenience of using such models for IoT device management, a review of current industry practice and scientific literature in achieving IFC-IoT integration shows that there is still a major difficulty in keeping together IFC parametric information and material textures. Therefore, this article analyses different workflows to manage IoT interactive environments capable of preserving, from the original model, the exported IFC geometric and parametric information, as well as the material-textures affected to the model's elements. More specifically, we describe an automated workflow IFC file > IFC verification definition correcting textures>Game Engine (Unity[11]), allowing the integration of material-textures to an IFC2.3 export.

Scientific Innovation and Relevance

(max 200 words)

To date, workflows available for immersive enabled IoT interactive environments allow retrieving either the material-texture information or the IFC parametric information. In general, using any game-engine software facilitates the transfer of texture information, but makes difficult retrieving the necessary IFC data to assure the IoT system connectivity. On the other hand, using IFC-compatible game-engine applications like Unity, which efficiently handle IFC data, pushes one to let go of texture information in spite the fact that, paradoxically, Unity's engine is particularly performant in terms of texture rendering. The reason for this, is that the current version IFC 4.2 does not suit a robust textures support, which may only be suited in the next major version, that is the IFC 5 [12]. In turn, most modelling software have hardly made it to IFC 2.3 certification [13]. Hence, stressing that under the circumstances it may take yet some years before modelling software providers can support texture information within an IFC based BIM methodology, this article describes an automated workflow to allow the updatable integration of material-textures into an IFC 2.3 export. In this way, it will be possible to work with material textures within a fully integrated BIM methodology.

Preliminary Results and Conclusions

(max 200 words)

Results of a first approach show that, after a relatively easy treatment in Blender+BlenderBIM [14,15], IFC parametric data can incorporate both material information and image-based texture definition. However, this procedure proved highly inefficient in relation to changes and updates in the original IFC exported-model. Thus, our second approach was to introduce our own script, in order to automate the procedure: a "transparent" step matching IFC entities and material-textures. Results are satisfactory in relation to the suppression and modification of elements. Currently we work on changes involving element addition. Reflecting on future applications it is important to highlight that textures, are more than a cosmetic artifice to produce impressive renderings. Being able to transfer material and texture information through workflows for different BIM usages is fundamental in achieving comprehensible immersive experiences, or getting results that are more precise in model-based simulations, such as light reflectance and solar irradiance studies. In the future, this method may as well indicate ways in which we will be able to exploit IFC's embedded material properties to retrieve physical material information as well as texture appearance from the model elements.

Main References

(max 200 words)

[1] G.White et al., Augmented reality in IoT, International Conference on Service-Oriented Computing. 11434,(2019)149–160.

[2] D.Jo, G.J.Kim, AR enabled IoT for a smart and interactive environment: A survey and future directions, Sensors 19,(2019).

[3] L.Müller et al., GuideMe: A mobile augmented reality system to display user manuals for home appliances, International Conference on Advances in Computer Entertainment Technology, 8253 (2013)152–167.

[4] K.M.Chang et al., An automated IoT visualization BIM platform for decision support in facilities management, Applied Sciences 8,(2018).

[5] SwissLivingChallenge, NeighborHub,(2017).

[6] S.Tang et al., Automation in Construction A review of building information modeling (BIM) and the internet of things ( IoT ) devices integration: Present status and future trends, Autom. Constr. 101 (2019)127–139.

[7] B.Dalton, M.Parfitt, Immersive Visualization of Building Information Models, Design Innovation Research Centre working paper 6(2013)1–20.

[8] BuildingSMART, Industry Foundation Classes-IFC,(2020).

[9] M.Poljanšek, Building Information Modelling (BIM) standardization,(2017).

[10] A.Kiviniemi et al., Review of the Development and Implementation of IFC compatible BIM Executive Summary, ERA Build(2008)1–2.

[11] UnityTechnologies, Unity platform,(2005). https://unity.com/.

[12] J.Ouellette, IFC-Problem about Elements with Texture, BuildingSMART forum, (2019). https://forums.buildingsmart.org/.

[13] BuildingSMART, IFC certified software,(2020). https://www.buildingsmart.org/.

[14] R.Ton, Blender Foundation,(2018).

[15] BlenderOrg, BlenderBIM - IfcOpenShell software library,(2019). https://blenderbim.org/.



11:42 - 12:00

Proposed integration of utilities in the Energy ADE 2.0

Maximilian Schildt, Christian Behm, Avichal Malhotra, Sebastian Weck-Ponten, Jérôme Frisch, Christoph van Treeck

Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

Energy Performance Simulations often require a large amount of data for building and district level simulations. This data highly depends on the quality, quantity as well as granularity of individual models and parameters. However, for efficiently storing, exchanging and reusing the information, a comprehensive data management system is very important. The management system should contain the relevant data from a district level to individual buildings in terms of geometry, HVAC components as well as network information in order to run energy performance simulations and operation optimization. Database management systems, such as 3D CityDB [1], do allow the storage of semantic data for 3D CityGML [2] building and virtual city models. Furthermore, for structuring the energy specific data, the use of the CityGML Energy Application Domain Extension [3] is foreseen. Currently, a comprehensive structuring of the energy systems data is missing in the Energy ADE 2.0 and therefore, the aim of this paper is to propose an approach to fill the gap for the management system. Moreover, the access to specific HVAC components within the data structure facilitates not only the analysis of energy demands but also the selection of components to cover the demand in a cost- or CO2-efficient manner.

Scientific Innovation and Relevance

(max 200 words)

Based on the investigations over the energy systems within a field test of a collaborative research project, a perspective blueprint for the decentralized energy system transformation is developed. Furthermore, within the scope of this paper, a decisive analysis will be carried out to determine the components of plant and building technologies that should be additionally mapped with its respective degrees of detail and their individual key performance indicators. The components to be mapped will be systematically structured and classified based on the Energy ADE schema into related categories such as energy sources, conversion and transmission. This paper will show an in-depth analysis to determine the coherence of the components that can be mapped using the existing ADEs [4]. For the missing components, however, a modular XML schema definition (XSD) will be developed based on the central dependencies between the established categories. This approach allows the simulations of CO2-emissions and footprints in districts that are linked to a central database. Moreover, this will serve as a basis for optimized choice, dimensioning and operation of energy systems and utilities at an urban scale.

Preliminary Results and Conclusions

(max 200 words)

Presently, the XML schema of Energy ADE has been extended using the classes necessary to map energy systems and utilities on district and building levels. The template of the extended classes has been linked to the 3DCityDB schema in an object-oriented database for implementation of the aforementioned research project. The approach is to attain a database that takes the utilities and energy systems fully into account and furthermore enables a tool-chain for energetic simulations and optimization scenarios. Comparing to Industry Foundation Classes (IFC) [5], CityGML and Energy ADE allow reduced order modelling and thereby reduce the amount of data needed to feed large datasets of buildings and districts into a simulation and optimization tool-chains. The current usage of CityGML Energy ADE and 3DCityDB is being investigated with the vision of reducing data redundancy while saving multi-criteria simulation results and optimization scenarios.

Main References

(max 200 words)

[1] Z. Yao, C. Nagel, F. Kunde, G. Hudra, P. Willkomm, A. Donaubauer, T. Adolphi and T. H. Kolbe, "3DCityDB – a 3D geodatabase solution for the management, analysis, and visualization of semantic 3D city models based on CityGML," Open Geospatial Data, Software and Standards, 2018.

[2] G. Gröger, T. Kolbe, C. Nagel and K. Häfele, "OGC City Geography Markup Language (CityGML) Encoding Standard," OGC, 2012.

[3] G. Agugiaro, J. Benner, P. Cipriano and R. Nouvel, "The Energy Application Domain Extension for CityGML: enhancing interoperability for urban energy simulations," Open Geospatial Data, Software and Standards, 5 March 2018.

[4] F. Biljecki, K. Kumar and C. Nagel, "CityGML Application Domain Extension (ADE): overview of developments," Open Geospatial Data, Software and Standards, 27 August 2018.

[5] buildingSMART, "IFC Specifications Database," 18 06 2020. [Online]. Available: https://technical.buildingsmart.org/standards/ifc/ifc-schema-specifications/. [Accessed 06 07 2020].