INTEGRATING BIM, CFD AND AR FOR THERMALASSESSMENT OF INDOOR GREENERY

KAZUKI YOKOI1, TOMOHIRO FUKUDA2,NOBUYOSHI YABUKI3 and ALI MOTAMEDI41,2,3,4Osaka University, Japan1yokoi@it.see.eng.osaka-u.ac.jp 2,3,4{fukuda|yabuki|motamedi}@see.eng.osaka-u.ac.jp

Abstract. The renovation projects to improve the thermal environmentare gaining importance because of energy saving effects and occupants’health considerations. However, the indoor thermal design is not usu-ally performed in a very efficient manner by owners and designers be-cause the architectural design data including the indoor thermal designis not centrally managed among all professional designers. Addition-ally, the visualizations of the CFD simulation results are difficult for thestakeholders to understand. On the other hand, greenery has been intro-duced to buildings as a method for adjusting the thermal condition. Theresearch goal presented in this paper is to investigate a cooperative ar-chitectural design process for the thermal environment by developing asystem in which BIM, CFD, and AR are integrated to provide interactivevisualizations. Case studies are performed to verify the developed sys-tem and to assess the thermal effects of multiple indoor greenery designoptions.

Keywords. Interdisciplinary Computational Design; Indoor Ther-mal Environment; Computational Fluid Dynamics (CFD); Aug-mented Reality (AR); Indoor Greenery.

1. IntroductionThe renovation projects in the field of the architecture are gaining im-portance asthey can replace costly construction projects of new build-ings. Recently, renova-tion projects to improve the thermal environment are more frequent due to energysaving (Marszal et al. 2011) and occu-pants’ health considerations (Laschewskiand Jendritzky 2002). For ex-ample, the difference of one degree centigradearound thirty-five de-grees centigrade seriously affects the possibility of the heat-stroke. How-ever, the indoor thermal environment for new or renovated projectsare not still satisfactory for some owners. This is partly because the indoor ther-mal design is not usually performed in a very efficient manner be-tween owners,landscape designers, and thermal designers.

P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows and Glitches, Proceedings of the22nd International Conference of the Association for Computer-Aided Architectural Design Research in Asia(CAADRIA) 2017, 85-95. © 2017, The Association for Computer-Aided Architectural Design Research inAsia (CAADRIA), Hong Kong.

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One reason for the inefficiency issue is that architectural design process is usu-ally divided into multiple processes, such as landscape design, facility design, andstructure design. Accordingly, the architectural design data is not centrally man-aged among all professional designers. In addition, the difficulty to execute majordesign changes disturbs an efficient discussion. Recently, the Integrated ProjectDelivery (IPD) has been promoted as a new design process concept (Ghassemi andGerber 2011). IPD is a concept for optimizing the architectural design process inwhich stakeholders, such as owners or designers, cooperate from the beginning tothe end of the design project. Using Building Information Modelling (BIM) is es-sential for realizing IPD. BIM is a standard information model that hosts life-cycledata of the facility and will be utilized for the various simulations relating to thearchitectures such as the earthquake simulations. Hence, all the life-cycle data isrequired to be integrated with the BIM (Hiyama et al. 2013). However, Compu-tational Fluid Dynamics (CFD) software applications, which are widely used as atool to perform advanced thermal environment analysis (Hartog et al. 2000), arenot integrated with the BIM. Especially, BIM models of architectural spaces arenot utilized as the object domain in the CFD simulation (Lee and Song 2010).

Another reason for the collaboration inefficiency issue is that the visualiza-tion results generated by CFD software applications are not easy to interpret fornone-professionals. The CFD results are usually heavy numerical data and it isdifficult to comprehend them in relation with the 3D space, which affects the ef-ficiency of discussions related to the thermal design. The results are generallyvisualized in 3D by the analysis software applications. These applications cananalyse the CFD results in detail; however, they cannot visualize the models ofthe simulation objects realistically due to unrealistic lighting simulation or back-ground scenes. Additionally, scenes can only be visualized in a third-person view.In order to solve these problems, the visualization of CFD results using a VirtualReality (VR) authoring software application has been investigated by Hosokawa etal. (2016). Their research visualizes the CFD results in a photorealistic 3D spacein a first-person view, and studies both thermal and landscape design. However,a VR environment created by Computer Graphics (CG) models are used for theirstudy, which is disconnected from the real world and does not allow users to expe-rience the real feelings of the environment. On the other hand, Augmented Reality(AR), which is a technology to augment the real world with digital information andmedia, such as 3D models and graphics, can replace VR to provide a more naturalfeeling of the environment for users. This technology has an advantage of beingused in the real scene, such as existing rooms. Hence, CFD visualization using ARtechnology can be efficiently utilized for examining the outcomes of renovationprojects (Yokoi et al. 2016).

Indoor greenery has been used in the buildings as a renovation meth-od of thethermal environment (Bregon et al. 2012). It is often used for providing a stress-relief environment because of the effect of the green colour; however, its effect onadjusting the thermal environment has been verified (Asaumi et al. 1994).

The research goal presented in this paper is to investigate a cooperative archi-tectural design process of the thermal environment for realizing the IPD. A systemin which BIM, CFD, and AR are integrated is developed to provide interactive

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visualizations. In our proposed system, easy-to-comprehend visualization of CFDresults augment the real scenes to provide users with information about thermal ef-fects of their renovation design options. Case studies to assess the effect of indoorgreenery on the thermal environment are performed. This paper focuses on theeffect of the indoor greenery and the solar radiation on the thermal environment.

2. MethodologyIn our proposed system, BIM, CFD and AR are integrated. It consists of five steps;creating the BIMmodel, mesh generation, boundary conditions setting, simulationusing CFD, and visualization using AR technology. At first, BIM model of thearchitectures is created based on the design drawings using a BIM authoring soft-ware application. Next, the volume mesh is created based on the created modelusing mesh generation software applications. Boundary conditions are set manu-ally based on the information of the model such as the heat flux of the wall andthe amount of air-flow from the air-conditioner. In the simulation step, non-steadysate fluid simulation is executed based on the defined boundary conditions usinga CFD software application. The simulation results are visualized using AR tech-nology in the visualization step. The CGmodel of the simulation results augmentsthe scenes of the real in-door environment in the AR environment. Details of eachstep are described in the following subsections.

2.1. CREATING BIM MODEL & MESH GENERATION

BIM model is created based on the design drawings using a BIM authoring soft-ware application such as Autodesk Revit Architecture. Based on the createdmodel,the volume mesh is created using mesh software such as blockMesh and snappy-HexMesh. First, the model is split to structured grids. Next, the grids are split inmore detail around the objects, such as an air-conditioner.

2.2. BOUNDARY CONDITION SETTING & SIMULATION USING CFD

Boundary conditions are set manually based on the information of the model, suchas the heat flux of the wall and the amount of air-flow from the air-conditioner. Aradiation model is implemented to the solar model including the solar primary heatfluxes, the reflective fluxes on walls, and the diffusive sky radiative fluxes. Thesky diffusive radiations for horizontal and vertical walls are calculated accordingto the Fair Weather Conditions Method from the ASHRAE Handbook (ASHRAE2009). The information related to the solar direction such as Greenwich MeanTime (GMT), start date, start time, longitude, latitude, and the radiative proper-ties such as emissivity, absorptivity, and transmissivity of the architectural com-ponents are set manually.

Thermal conditions of the indoor environment are simulated using a CFD soft-ware application such as OpenFOAM (an open-source CFD software toolbox).The thermal simulation is performed on the assumption that the fluid is non-steadystate and turbulence flow. The CFD solver calculates the heat transmission usinga coupled analysis of solid heat conduction and fluid heat transfer and solid-fluidheat transmission. Each region of solid and fluid are allocated from the grids cre-

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ated in the mesh generation step. After executing the simulation, a post-processingactivity using a visualization software application, such as Paraview, is performedto check the results.

2.3. VISUALIZATION USING AR

Simulation results are visualized using the AR technology. The AR registrationmethods are vision-basedmethod (such asmarker-based ormarker-less-based) andlocation-based method. The display types are Head Mounted Display (HMD) andhand-held display. In this research, marker-based method with HMD is used be-cause of its ease of use in indoor space, and a higher degree of provided immersion.The system visualizes arrows of the air-flow and heat-maps of the temperature onthe scenes of the real indoor environment. The results are shown using cross-sections such as XY plane, YZ plane, and ZX plane. The 2D visualization planesare moved using an input device such as a gamepad controller.

3. 3. Case StudyThe system data flow is shown in figure 1. The BIM model was created usingAutodesk Revit Architecture 2016. The model is exported as IFC file, and im-ported to SketchUp 2016 and then exported as STL format. The volume mesh wasgenerated using blockMesh software and snappyHexMesh software. The CFDsimulation was executed using Open-FOAM (ver.1606+). The simulation resultsare exported as VTK file format, and imported to the Game Engine (i.e., Unity(Ver.5.3.2.f)). In the visualization using AR technology, CG models are visual-ized using Unity plugged-in Ovrvision Pro SDK. The Oculus Rift DevelopmentKit 2 (DK2), an HMD equipped Ovrvision Pro, a USB 3.0 VR stereo cam-era arealso used. The Oculus Rift DK2 is a video see-through typed HMD, and can securea wide angle. The system was operated using Logicool f710 game pad controller.

Figure 1. System Flow.

3.1. EXPERIMENT CONDITIONS

The validation experiments were performed in on the assumption of an office roomin Osaka, Japan (North latitude: 34.822°, East longitude: 135.521°), with the fol-lowing dimensions: 6.5 m (depth) × 4.3 m (width) × 2.6 m (ceiling height) asshown in figure 2. The test conditions are set at 14:00PM in January 27th in thewinter and August 19th in the summer in Japan (GMT: 9). Solar direction is de-termined by the location, date, and time. The turbulence model was referred tok-epsilon turbulence model in which eddy viscosity coefficient is calculated usingturbulent energy and turbulent disappearance rate. In this experiment, the windowis facing south and receives the solar radiation. An AR marker (0.72 m (height) ×

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0.72 m (width)) was set on the table in the centre of the room as shown in figure 1.A user wore an HMD and was placed near the entrance in order to have the markerin his field of view.

Figure 2. Experiment room: Floor plan (left), Actual photo (right).

A ceiling mounted air-conditioner with four cassettes is used. The boundaryconditions of the architectural components were set including conditions relatedto the solar radiation such as emissivity, absorptivity and transmissivity (table 1).The boundary conditions of the air-conditioning unit including flow rate, velocity,and temperature were set based on values that are shown in table 2.

Table 1. Boundary Conditions (Architectural Components).

Table 2. Boundary Conditions (Air-conditioner).

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3.2. EXPERIMENT CASES

The experiments with the air-conditioner were performed in winter and summerwith the following settings: (a) no greenery (b) wall side with greenery (c) windowside with greenery (d) wall side & window side with greenery. Additionally, theexperiments without the air-conditioner were performed in winter and summer: (e)no greenery (f) wall side & window side with greenery. The boundary conditionsof each component with greenery are shown in table 3.

Table 3. Boundary Conditions (Components with Greenery).

3.3. RESULTS

The simulation results of temperatures in the cases with the air-conditioner areshown in table 4 (in winter) and table 5 (in summer). The average temperature forthe case (d) was higher than the case (a) in winter, and the case (d) was lower thanthe case (a) in summer.

Table 4. Simulation Results (cases with the air-conditioner in winter).

Table 5. Simulation Results (cases with the air-conditioner in summer).

The simulation results of temperatures in cases without the air-conditioner areshown in table 6. The average temperatures of the case (f) were higher than thecase (e) in both winter and summer. In the summer, the case (f) were 0.983 °Chigher than the case (e).

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Table 6. Simulation Results (cases without the air-conditioner).

The visualization results of cases with the air-conditioner in winter are shownin figure 3. The arrows of air-flow and heat-maps of temperatures were overlaidon real world scenes, and the greenery model was overlaid along the actual wallor window. The colours of heat-maps were distributed from blue to red, and thecolours near the air-conditioner were almost red. The directions of the arrows werealmost downward due to the blow from the air-conditioner.

3.4. DISCUSSIONS

For the case (a) in winter, simulation results were compared with the actual tem-perature values. The actual temperatures were measured in 36 points in the room(depth: 1.60 m, 3.85 m, 6.1 m × width: 1.1 m, 2.1 m, 3.1 m × ceiling height: 0.3 m,0.9m, 1.5m, 2.1 m). The average of the actual temperatures was 23.65 °C, whichwas 1.2 °C higher than the simulation result. Considering case studies with the air-conditioner, the temperature of cases with greenery was higher than cases withoutgreen-ery in the winter, and vice versa in the summer. The reason is that the green-ery supressed escaping of heat outside the room from the air-conditioner, that is,the warm air from the air-conditioner was saved in winter and the cool air fromthe air-conditioner was saved in summer. Considering the case studies withoutthe air-conditioner, the tempera-tures of cases with the greenery were higher thanthe cases without the greenery in both winter and summer. The actual survey byAsaumi et al. (1994) shows that the indoor greenery increases indoor temperature.This is because the effect of the greenery affects the heating up of the greenerysurface rather than solar shading. Although the solar radiation directly reachedto the floor and walls through the window in the cases with no greenery, the heattransmission coefficient of these surfaces were lower, and hence the amount of thesensible heat from these surfaces did not greatly affect the indoor air. The differ-ences of the temperatures between cases with greenery and cases without greenerywere not significant. The reason is that simulations in this study did not considerthe transpiration of the greenery due to the limitations of the simulation softwareapplication.

The accuracy of the AR registration was verified by comparing the actual posi-tion of objects with the location of the augmented 3D model. The horizontal andthe vertical errors were calculated in 10 different photographs. The results showthat the maximum error was 18.14 pixels and the minimum error was 12.64 pixels,and the average of the horizontal errors and the vertical errors were 6.78 pixels and13.80 pixels, respectively. One of the reasons for the error is the image-capturingproblem of the camera. The camera on the HMD was always slightly moving, orwas not stable because of the vibration. Additionally, the lighting condition andthe distance from the marker may affect the accuracy.

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Figure 3. Visualization Results: Air-flows (left), Temperatures (right).

4. Conclusions and Future WorkThis research developed a system in which BIM, CFD, and AR are integrated toassist a cooperative architectural design process of the thermal environment. TheBIM model was utilized together with the CFD simulation considering the solarradiation. The results of the CFD simulations were visualized with arrows andheat-maps using the AR technology. Case studies were performed for the renova-tion projects with indoor greenery, and the simulation results were compared withcases with no greenery. The thermal results and the greenery model augmentedthe scenes of the actual room when using the prototype system.

This system contributed to facilitating the cooperative architectural design pro-cess especially between owners, landscape designers and thermal designers. In-

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tegrating BIM and CFD helps realizing IPD. Additionally, integrating CFD andAR provided users, such as owners and landscape designers, with a more naturalfeeling of the thermal environment. The case studies showed that both landscapedesign study and thermal design study could be performed at the same time.

As future work, more detailed settings, such as the transpiration of greenery,should be performed for more accurate CFD simulation. Additionally, it is ex-pected to simulate and visualize other factors such as air quality or sound insula-tion for more extensive renovation studies. The case studies should be performedin larger spaces and for other scenarios such as demolition of a wall. Using marker-less AR, such as location-based method or method that uses natural feature points,will be required to realize a walk-through for users in larger spaces.

AcknowledgementThis research has been partly supported by the research grant of Nohmura Founda-tion for Membrane Structure’s Technology and JSPS KAKENHI Grant Number26-04368.

ReferencesAsaumi, H., Nishina, H., Kei, T., Masui, Y. and Hashimoto, Y.: 1994, Effects of Foliage Plants

on Thermal Environment and Comfort Inside Room – Experiment Analysis in Winter -,Architectural Institute of Japan Planning, Environment and Engineering, 39-46.

ASHRAE, : 2009, ASHRAE Handbook - Fundamentals (I-P Edition), American Society ofHeating, Refrigerating and Air-Conditioning Engineers, Inc..

Bregon, N. F., Urrestarazu, M. and Valera, D. L.: 2012, Effects of a Vertical Greenery Systemon Selected Thermal and Sound Mitigation Parame-ters for Indoor Building Walls, Journalof Food Agriculture and Environment, 10 (3), 1025-1027.

Gerber, B. B. and Kensek, K.: 2010, Building information modelling in architecture, engineer-ing, and construction: emerging re-search directions and trends, Journal of ProfessionalIssues in Engineering Education and Practice, 136(3), 139-147.

Ghassemi, R. and Gerber, B.B.: 2011, ransitioning to integrated project delivery: potentialbarriers and lessons learned, Lean Construction Journal, 119, 32-52.

Hartog, J. P., Koutamanis, A. and Luscuere, P. G.: 2000, Possibilities and limitations of CFDsimulation for indoor climate analysis, 5th Design and Decision Support System in Archi-tecture and Urban Planning – Part One: Architecture Proceedings, 152-167.

Hiyama, K., Diao, Y., Kato, S. and Koganei, M.: 2013, Impact Analysis of BIM Spread onMechanical Design Process Impact Analysis of BIM Spread on Mechanical Design Pro-cess Based on Consciousness Survey among Japanese Mechanical Engineers, InternationalJournal of High-Rise Buildings, 2(2), 97-104..

Hosokawa, M., Fukuda, T., Yabuki, N., Michikawa, T. and Motamedi, A.: 2016, IntegratingCFD and VR for indoor thermal design feedback, The 21st International Conference onComputer-Aided Architectural Design Research in Asia, 663-672.

Laschewski, G. and Jendritzky, G.: 2002, Effects of the thermal environment on human health:An investigation of 30 years of daily mortality data from SW Germany, Climate Research,21(1), 91-103.

Lee, S. and Song, D.: 2010, Prediction and Evaluation Method of Wind Environment in theEarly Design Stage Using BIM-Based CFD Simulation, IOP Conference Series: MaterialsScience and Engineering, 10(1), 1-10.

Marszal, A. J., Heiselberg, P., Bourrelle, J. S., Musall, E., Voss, K., Sartori, I. and Napolitano,A.: 2011, Zero Energy Building – A review of definitions and calculation methodologies,Energy and Buildings, 43(4), 971-979.

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Yokoi, K., Fukuda, T., Yabuki, N. andMotamedi, A.: 2016, Integrating CFD and AR for indoorthermal design feedback, Proceedings of the 11th International Symposium on ArchitecturalInterchanges in Asia, 111-114.