Daylight Performance Simulations and 3D Modeling in
BIM and non-BIM Tools
Interoperability and accuracy – an experience aiming to a more integrated
and interdisciplinary approach
Marina Stavrakantonaki Brussels, Belgium
marina.stavrak@gmail.com
Abstract. The fusion between building assessment and design can lead to better informed design decisions. Performance oriented design is better supported through the use of interoperable file formats for data exchange between BIM and non-BIM tools. At the same time, the parameters that influence the calculation during a performative assessment are no longer a purely engineering problem, since 3D modeling is of primary importance in defining the numerical output. The role of the designer along with the selection of the tools becomes all more relevant in this direction. A framework is presented hereby, which can be used for the selection between different BIM tools for daylight assessment. An insight is also given on the major parameters that can affect the outcome and on the obstacles that were experienced in four case-studies in relation to data exchange and information flow.
Keywords. Performance simulations; parameters; interoperability; daylight.
INTRODUCTION
During the last years, there is an increasing demand for the integration of BPS (Building Performance Simulation) tools in the early design phase (Attia et al., 2012). The interoperability of BIM (Building Infor-mation Modeling) and non-BIM tools influences the workflow within the design team, while the building practice is progressively oriented to a more interdis-ciplinary approach (Augenbroe, 1992). The hereby presented study initiated as an internal research for the consultants of the company DGMR in the Netherlands, with the task to evaluate the three fol-lowing daylight performance simulation packages; Design Builder v.3.0.0.105, Ecotect 2011
v.5.60/Radi-ance and DIVA 2.0 as plug-in for Rhinoceros NURBS modeler, and to provide suggestions for future use. All of the examined tools can provide dynamic day-light simulations under given conditions. The prob-lems that consulting with the use of this software faces on a daily base, are related to incompatibility between the architectural 3D model and the simula-tion software, the long 3D modeling times and the error probability when complex geometries are in-volved. The aim is to acquire semantic information on the performance of the building over time, in a way that it can be integrated in the design process. The evaluation is based on the following criteria:
• Ability to simulate detailed and complex build-ing forms
• Accuracy
• Interoperability of Building Modeling (IBM). The above-mentioned criteria refer to two of the five major tools’ selection criteria as defined by Attia et al. (2012) and incorporate the three factors that are given in the ASHRAE handbook:
• Capability of the tool to deal with the project requirements.
• Complexity of input. • Quality of output.
Their selection for this study, reflects the problems with which engineering is confronted the most dur-ing collaboration with the architectural team for daylight assessments. At the present moment, it is common practice that the analytical model is de-rived from the architectural model after the extrac-tion of a significant amount of geometrical data. Effort and long working hours are dedicated to the restructuring of the architectural model before sim-ulating; and it is common that decorative elements need to be extracted, or the layering structure of the 3D model has to be redefined in order to pro-vide appropriately defined layers where material properties can be accurately assigned. At the same time, the ability of the software to simulate detailed or complex building forms is closely related to issues of processing power and computing robustness and becomes clear that the building geometry that is used for performance evaluations has a direct im-pact on the calculation output.
A better collaboration between the design and performance assessment team is therefore neces-sary; in such a case the architects need to be in-formed on the effect of their model to the calcula-tion process, so that they can structure it efficiently in order to facilitate, not only an accurate three-di-mensional representation of the building, but also a fast performative assessment that can provide feedback for better informed design decisions. Re-garding accuracy, in each of these tools, the output is the result of the connection of the imported or designed geometrical entities to a number of
data-bases. The process can be analyzed through the fol-lowing steps;
1. setting of the model
2. link of the model to the relevant for each case-study semantic information
3. calculation and presentation of the output. Each of these steps presents a different level of accessibility and control potential for the user, the later becoming considerably limited as we proceed from 1 to 3. A fully controlled process would opti-mally lead to more accurate results, since param-eters such as the geometry, material definitions or sky conditions would be fully editable, provided that the user is conscious of the influence of each param-eter on the calculation output. Radiance provides such a possibility through a number of file formats (i.e., .rad, .dat), without posing restrictions regard-ing the computed geometry. An example on how a variation of the parameters affects the results is pre-sented during this paper.
Ideally, data exchange would happen automati-cally in both directions, so that every alteration in the 3D model can change the simulation output and vice-versa (Kensek and Sumedha, 2008). In such a case better building performances can be achieved through a seamless back and forth process. Interop-erability can be defined as the possibility of informa-tion exchange through interoperable file formats that allow for the use of the exchanged information Its importance lies on the possibility to diminish the time lost due to the exchange of data between the BIM or non-BIM modeler and the BIM tool.
In building practice, performance assessment is often carried out separately from the architectural design. The engineering team, is in many cases de-tached from the design of the building, while the architect uses assessments only as external informa-tion when compliance with regulainforma-tions is strictly re-quired. A better merging of the groups can be facili-tated with a better collaboration of the software, so that both teams can refer to the same core models through interoperable file formats.
This study traces the flexibility of the examined software in importing and modeling 3D geometry
and the range of deviations that can be expected during the calculation of the analytical model, and specifies the information that is being lost during the process. The Drawing Exchange Format (DXF) is hereby used as the basic means of design informa-tion transfer.
METHODOLOGY
For the needs of the present research three case-studies were used on the grounds of the following methodology; a base model was prepared and sim-ulated in Design Builder v.3.0.0.105. This model was exported in .dxf format and recalculated in DIVA 2.0 and Ecotect 2011 v.5.60. Rhinoceros 3D-CAD mod-eler was used as a complimentary tool in order to model the missing export data. All the three pack-ages were linked to Radiance and provided output based on the climate data of Energy- Plus _IWEC weather data files. The following input data were given for each one of the packages. The settings re-flect the effort to use equal input data. Identical in-put is not possible at the moment due to differences in the software settings (Table 1).
The three case-studies refer to two on-going
projects and to a simplified setting:
• Case study 1: a complex geometry (Figure 1). • Case study 2: a purely orthogonal geometry
(Figure 2).
• Case study 3: a simplified setting of a typical of-fice space (Figure 3).
The common feature between the geometries is the linear form. They refer to two on-going projects and one simplified setting that is often met in everyday practice.
The simulation was oriented to one-variable approach in order to facilitate the comparison be-tween the tools. With regard to precision, the fol-lowing settings were used: ambient bounces (ab) = 2, ambient accuracy (aa) = 0.1, ambient resolution (ar) = 300, ambient divisions (ad) = 1000, ambient super-samples (as) as default. For the needs of this study, the Daylight Factor was chosen as the main calculation measurement; the prediction of the Daylight Factor under a CIE overcast sky condition is at the moment the dominant approach in evalu-ating daylight, despite the fact that it provides only a rough estimation of the yearly indoor conditions (Tregenza, 1980). Yet, it is in broad use by the Euro-Basic input, model 1 to 3
Design Builder v.3.0.0.
NLD_Amsterdam. 062400_IWEC weather file CIE overcast sky
double glazing with airgap LTA 0.7 concrete ceiling, brick walls, wooden floor Grid : 0.1m-0.2m Calc. plane: 0.7m Ecotect 2011 v.5.60 NLD_Amsterdam. 062400_IWEC weather file CIE overcast sky
LTA 0.7 ceiling ref. 80%,
brick walls ref. 50%, wooden floor ref. 20%
Grid size: 40x32x32cm Calc. plane: 0.7m
DIVA 2.0 NLD_Amsterdam.
062400_IWEC weather file CIE overcast sky
double glazing low-e
generic ceiling ref. 80%, generic wall ref. 50%, generic floor ref. 20%
Grid-nodes’ density 500x800 Calc. plane: 0.7m
Table 1
Basic input data models 1 to 3.
Figure 1
Case study 1 as modeled and imported in the three tools; from left to right, in Design Builder, in Ecotect and DIVA.
pean building regulations and most assessment rat-ing systems includrat-ing BREEAM, in order to provide benchmark values for indoor daylight quality. The specification of daylight quality for the presented case-studies lies beyond the interest of this study. The aim is to evaluate the three packages on the se-lected criteria and to provide a general framework that can optimally facilitate the selection between the numerous daylight performance calculation tools that are at disposal as open-source or commer-cial software packages.
Further on, a fourth model was chosen as a separate case study. Its geometry combines circular openings on a circular wall and is part of a project currently under development (Figure 4). The model could not be created in Design Builder and the ge-ometry was imported in Rhinoceros and Ecotect as an .obj file format, which was provided by the archi-tectural team. Importing an appropriate model for daylight calculation via gbXML or connection with SketchUp in Design Builder proved also problemat-ic. As a result, calculation output could be obtained
only in Ecotect and DIVA (Figure 5). This last model was further used to monitor the effect of the input parameters, regarding the architectural form as one of them. The tests were performed in DIVA 2.0 and provided an insight on the deviations that should be expected with the change of specific variables. The most important of the variables that were tested and the resulting output under CIE overcast sky for the same IWEC weather file are listed in Table 2.
The above listed results are some of the tests that were carried out in order to specify the influ-ence of the precision settings, the grid density and material properties on the output. Hereby we set as Low precision: ab (ambient bounces) = 2, ad (ambi-ent divisions) = 1000, as (ambi(ambi-ent super-samples) = 20, ar (ambient resolution) = 300, aa (ambient accu-racy) = 0.1, geometric density =70. High precision: ab (ambient bounces) = 3, ad (ambient divisions) = 2048, as (ambient super-samples) = 20, ar (ambient resolution) = 512, aa (ambient accuracy) = 0.2, geo-metric density =70.
Figure 2
Case study 2 as modeled and imported in the three tools; from left to right, in Design Builder, Ecotect and DIVA.
Figure 3
Case study 3 as modeled in the three tools; from left to right, in Design Builder, Ecotect, and DIVA.
RESULTS
The tests prove that the default precision settings should be considered with skepticism; the minimum
number of ambient bounces that could give pre-cise results was 3, whereas a very high precision (4 to 6 ambient bounces) did not considerably change Tests model 4
Test nr. Material ref. (%) Precision Mean D.F(%)
Test 1 Ceiling 0.9, int.wall 0.9, floor 0.5, int/ext. glass tr.0.9
Low, Grid point dist. = 0.1m 1.08 Test 2 Test 3 Test 4 Test 5 Test 6 Test 7
Ceiling 0.9, int.wall 0.9, floor 0.5, int/ext. glass tr.0.9
Ceiling 0.9, int.wall0.9, floor 0.5, int/ext. glass tr.0.9
Ceiling 0.9, int.wall 0.9, floor 0.5, int. glass tr.0.65, ext. glass tr. 0.9
Ceiling 0.9, int.wall 0.8, floor 0.2, int/ext. glass tr.0.9
Ceiling 0.9, int.wall 0.8, floor 0.2, int. glass tr.0.8, ext. glass tr.0.9
Ceiling 0.8, int.wall 0.8, floor0.4, int.glass tr.0.8, ext. glass tr.0.9
High, Grid point dist. = 0.05m High, Grid point dist. = 0.1m High, Grid point dist. = 0.1m High, Grid point dist. = 0.1m High, Grid point dist.= 0.1m High, Grid point dist.= 0.1m 1.80 1.78 0.70 1.59 0.98 1.07 Table 2 Tests on model 4. Figure 4
Model 4 in Rhinoceros inter-face: model setup.
Figure 5
Case study4 as calculated in Ecotect (left) and DIVA (right).
the output. The grid density is important, yet a me-dium density with a point-to-point distance = 0.1m is enough to provide a reliable output. For double density (point-to-point distance = 0.05m) the effect on the results was at the range of 1.11%, meaning that for models consisted of a large number of sur-faces, an extremely dense grid can be safely avoid-ed. The most important material settings are ranked in the following line from the most to the least im-portant: visible transmittance of glazing, reflectivity of the walls, reflectivity of the floor, reflectivity of ceiling.
Tables 3 and 4 present the output from the four case studies as simulated in the three software pack-ages. The differences in the output are indicative of the deviations that can result from the different abil-ity of the software to simulate detailed and complex
building forms as well as the differences in preci-sion, even when the input settings appear identical. Moreover, the information that we can obtain with one and only simulation from each program, varies significantly (Table 3). The analysis of the results of test-model 4 have already provided a ranked list on the deviations that we should expect when altera-tions in the input parameters occur.
As seen in the results from model 1 (15.993 meshes), the setting on the principle of zones does not facilitate the acquisition of direct information on a specific floor. The averages obtained from the zones hereby do not provide clear input for the design team. At the same time, the differences be-tween Ecotect/Radiance and DIVA range bebe-tween 2 and 10%. In the second model (23.580 meshes) the deviations are bigger; The difference between Detailed output model 1 Floor area
Above threshold(%) Average DF (%) Min. DF (%) Min./Max. Illuminance (lux) Design Builder v.3.0.0.105 Ground Floor Zone1 Zone2 Second Floor Zone1 Zone2 - Ecotect 2011 / Radiance Ground Floor Second Floor - DIVA 2.0 Ground Floor Second Floor 61.350 83.245 58.898 48.911 graphically presented 62.8 50.7 3.916 2.86 4.339 3.248 5.385 4.366 5.5 3.91 0.016 0.5 0.116 0.2 graphically presented graphically presented 1.57/2291.96 50.35/964.46 11.62/1970.44 20.29/1825.88 Mean Illum. 309.6258 199.1255 217.5 158.13 Table 3
Detailed simulation output, model 1.
Output av. DF(%) Design Builder v.3.0.0.105 Ecotect 2011/ Radiance DIVA 2.0/ Rhinoceros Model 1 (15.993 meshes) Ground Floor Second Floor Model 2 (23.580 meshes) First Floor Second Floor Model 3 (136 meshes) Model 4 (74 meshes) Zone 1/2 3.916/2.86 Zone 1/2 4.339/3.248 2.194 2.112 6.378 Not obtained 5.385 4.366 2.2 2.34 7.66 0.95 5. 5 3.91 3.25 3.35 7.94 1.07 Table 4
Simulation output, average DF, model 1 to 4.
Design Builder and Ecotect are below 0,5% for the first floor, yet they are around 10% for the second floor. DIVA gave a daylight factor, by approx. 50% higher if compared to the other two programs. In order to explain the differences, a third simple cubi-cal space was prepared through the same process (136 meshes). The deviation in the output between Ecotect and DIVA was approx. 3,6%, while Design Builder presented by approx. 20% lower values. In the fourth case study we observe that Ecotect and DIVA show a deviation around 10%, whereas no re-sults were obtained in Design Builder due to mod-eling difficulties as already explained.
The deviations prove, that accuracy is relevant and highly related to program settings, while they are expected to rise when a significant amount of surfaces is computed. Identical settings for the pro-grams are not possible, whereas the 3D form should not be considered identical once imported in differ-ent packages.
In relation to interoperability, the workflow can be supported between BIM and non-BIM tools, yet it is important to control the information transfer while exporting a model; 3D geometry can be easily prepared within Design Builder for example, yet the exported .dxf files do not transfer material database information and are normally deprived of the glazed surfaces when imported in Rhinoceros or Ecotect. Additional modeling is then necessary, in order to correct the missing surfaces. An export in multiple files is sometimes advised, in order to facilitate a multi-layered imported model.
The main reason for which Design Builder was used as a base modeler was the fact that most of the energy calculations demand an apart modeling based on energy zones. In such a case, the daylight performance simulation of a building could be per-formed either on the architectural or the energy 3D model, since both are prepared by the team during the study. In many cases, such as the three first case studies, daylight simulations are possible in both models. Yet, there are cases that the demands of the 3D model exclude one of the two tools, as seen in case study 4.
We attempted to show that the architectural model is of major importance in defining the choice between the available software packages and fa-cilitating the flow of data from the design model to the calculation/analytical model and vice versa. The following criteria can be used as a guideline for the selection of the appropriate BIM tool for the calcula-tion of daylight:
• The type of geometry that the tool is expected to model and calculate; failure in modeling does not necessarily mean failure in perform-ing the simulation. In such a case, the data exchange formats that will be used to import the model are of primary importance. The user has to be informed on the amount of data that can be transferred through the supported file extensions.
• The expected precision in input/output; the choice of the tools should depend on the de-manded precision. In any case knowledge of the influence of the input variables on the re-sult is necessary.
• The tolerance of the software in handling
different amounts of data; regarding geom-etry, the total number of surfaces that will be computed has to be taken into consideration. Abstraction is always necessary in order to fa-cilitate the time and precision of a daylight as-sessment.
CONCLUSIONS
A number of major drawbacks were experienced during the process, especially in relation to compu-tational effort when a significant number of surfaces was involved, regarding a higher probability for er-rors and longer calculation times. Early stage assess-ment tools, such as DIVA, can also prove less flexible during later stages of the design. The reason is the lack of detailed simulation output and the inability to set input values directly on the modeled surfaces.
The three software packages should be evaluat-ed differently with regard to the three criteria as set at the beginning of this study. In this frame, Design Builder and DIVA proved that we are not far from the
moment when one tool will be used both for the setting of the 3D model and its performative evalua-tion. Nonetheless, accuracy in the calculation output remains highly dependent on the model setting. For this reason, further examination of the consecutive calculation steps and the relevant files which are produced during simulation (i.e .rad, .tmp), are of great importance, and can explain some of the de-viations in the output. On the other hand, Ecotect presented lower flexibility with regard to geometry manipulation, even though it supports detailed ma-terial input.
Interoperability between BIM and non-BIM tools remains an issue especially for Design Builder with regard to 3D geometry input and processing, while DIVA/Rhinoceros was experienced as the most flex-ible during the process. Ecotect facilitated a rather one-sided approach (capable of importing 3D ge-ometries), and proved to be an analytical BIM tool which supports 3D input even when large amounts of surfaces are involved, without serious problems. In conclusion, interoperability as a seamless flow of information is partially supported, while the us-ability of the architectural model for performance evaluations is heavily dependent on a conscious modeling by the side of the designer, long before the geometry is exported for the calculation, in any interoperable file format.
The hereby presented experiences regarding modeling and simulating geometries of various sizes and complexity, prove that further steps need to be taken towards a better integration of 3D modeling capabilities in the engineering simulation software and vice-versa, especially with regard to the preci-sion of the input values and the operability of the 3D geometry in the BIM environment. The integration of Building Performance Simulation Techniques in the design process, can be facilitated by the selec-tion of a tool that will provide reliable feedback dur-ing the early but also the later design phase. Basic guidelines towards such a choice were given during this study, while addressing the issue of accuracy through four different case studies.
Furthermore, the role of the designer is central
in facilitating the collaboration of the team and pro-viding an efficient base model that will be bidirec-tionally used, therefore resulting to a better fusion between the disciplines. In this sense, an answer to the current interoperability problems can be given by a better coordinated design and assessment team, both having a global understanding of the process. Such a team will facilitate the flow of in-formation through the setting of the 3D models, in both BIM and non-BIM tools, when the complexity of the project or the limitations of file formats do not allow for one core model both for design and day-light assessment.
ACKNOWLEDGEMENTS
The study took place during a sixth month training period in the consultancy firm DGMR, The Hague. The office permitted for the use of the designs as were presented in case studies 1 and 2. Thanks are also due to Studiebureau Boydens in Brussels, that allowed for the use of design model 4, and inspired the study with comments and remarks regarding in-teroperability and simulation accuracy issues in the way that the office experiences them in everyday practice. The colleagues of both firms provided sup-port during this work, while the administration in both cases provided consensus for the publication of the models.
REFERENCES
Attia, S, Hensen, J, Beltránc, L and De Herde, A 2012, ‘Selec-tion criteria for building performance simula‘Selec-tion tools: contrasting architects’ and engineers’ needs’, Journal of
Building Performance Simulation, 5(3), pp. 155–169.
Augenbroe, G 1992, ‘Integrated Building Performance Eval-uation in the Early Design Stages’, Building and
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Kensek, KM and Sumedha, K 2008, ‘Sustainable Design Through Interoperability: BIM and Energy Analysis Pro-grams, a Case Study’, Cadernos de Pós-Graduação em
Arquitetura e Urbanismo, 8(1), pp. 42–58.
Tregenza, P 1980, ‘The daylight factor and actual illumi-nance ratios’, Lighting Research and Technology , 12(2), pp. 64–68.
