Automated Derivation of Building Envelope Thermal Performance Based on BIM for Building Energy Analysis

  • Authors

    • Chang-Young Park
    • Chang-Min Kim
    • Hyang-In Jang
    • Chang-Ho Choi
    2019-01-02
    https://doi.org/10.14419/ijet.v8i1.4.25127
  • Building Envelope, Building Information Modeling, Energy Analysis, Industrial Foundation Classes, Thermal Performance
  • Building envelope performance is an important factor used to calculate the energy loads required for heating and cooling buildings. Despite the large influence that building envelope thermal performance has over the energy consumption of buildings, thermal performance evaluations are often carried out using two-dimensional CAD drawings that require much time and effort. Recently, Building Information Modeling (BIM) has been used as a tool to enhance the efficiency of manually performed building information management practices. In addition, studies in the field of energy performance evaluations that have incorporated BIM have also been conducted. In this study, a method of automatically extracting information from BIM necessary for the derivation of building envelope performance was proposed. The first step of the proposed method was to classify parts that directly or indirectly made contact with the outdoor air. The second step was to classify the parts composing the envelope to appropriately reflect the standard used for the evaluation. Third, the thermal transmittance of each component composing the building envelope was calculated. Lastly, the area of each part was calculated. A case study was performed on a multi-residential unit to verify the accuracy of the proposed method. The verification results indicated that the proposed method was applicable in practice. Further research is planned to verify the performance of the proposed method with regard to its application to various standards and types of residential buildings.

     

  • References

    1. [1] EIA (2015), Annual Energy Outlook 2015, U.S. Energy Information Administration.

      [2] IEA (2013), Technology Roadmap: Energy Efficient Building Envelopes, International Energy Agency.

      [3] DOE (2012), Analysis of the Russia Market for Building Energy Efficiency, US department of Energy.

      [4] Berardi U (2017), A cross-country comparison of the building energy consumptions and their trends. Resources, Conservation and Recycling 123, 230-241.

      [5] IPCC (2014), Climate Change 2014: Mitigation of Climate Change, Chapter 9: Buildings, Intergovernmental Panel on Climate Change.

      [6] Straube JF & Burnett EFP (2005), Building science for building enclosures, Building science press.

      [7] Granadeiro V, Duarte JP, Correia JR & Leal VMS (2013), Building envelope shape design in early stages of the design process: Integrating architectural design systems and energy simulation. Automation in Construction 32, 196-209.

      [8] Tran DJ, Behr RA & Parfitt, MK (2014), Global differences in building enclosures. Journal of Architectural Engineering 20, 04014001.

      [9] Azis SS, Sipan I, Sapri M, Jalil RA & Mohammad IS (2017), The Effect of green envelope components on green building value. Property Management 35, 181-201.

      [10] Sadineni SB, Madala S & Boehm RF (2011), Passive building energy savings: A review of building envelope components. Renewable and Sustainable Energy Reviews 15, 3617-3631.

      [11] Cho YK, Li H, Park JW & Zheng K (2015), A framework for cloud-based energy evaluation and management for sustainable decision support in the built environments. Procedia Engineering 118, 442-448.

      [12] Aktacir MA, Büyükalaca O & Yılmaz T (2010), A case study for influence of building thermal insulation on cooling load and air-conditioning system in the hot and humid regions. Applied Energy 87, 599-607.

      [13] Yu J, Tian L, Xu X & Wang J (2015), Evaluation on energy and thermal performance for office building envelope in different climate zones of China. Energy and Buildings 86, 626-639.

      [14] Feng G, Sha S, & Xu X (2016), Analysis of the building envelope influence to building energy consumption in the cold regions. Procedia Engineering 146, 244-250.

      [15] Kaynakli O (2012), A review of the economical and optimum thermal insulation thickness for building applications. Renewable and Sustainable Energy Reviews 16, 415-425.

      [16] Dupeyrat P, Ménézo C, & Fortuin S (2014), Study of the thermal and electrical performances of PVT solar hot water system. Energy and Buildings 68 (Part C), 751-755.

      [17] Echenagucia TM, Capozzoli A, Cascone Y & Sassone M (2015), The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis. Applied Energy 154, 577-591.

      [18] Huang Y & Niu J (2015), Application of super-insulating translucent silica aerogel glazing system on commercial building envelope of humid subtropical climates – Impact on space cooling load. Energy 83, 316-325.

      [19] ASHRAE (2005), ASHRAE Handbook of Fundamentals, ASHARE.

      [20] Azari R (2014), Integrated energy and environmental life cycle assessment of office building envelopes. Energy and Buildings 82, 156-162.

      [21] Golparvar-Fard M, Peña-Mora F & Savarese S (2012), Automated progress monitoring using unordered daily construction photographs and based building information models. Journal of Computing in Civil Engineering 29, 04014025.

      [22] Kim C, Son H & Kim C (2013), Automated construction progress measurement using a 4D building information model and 3D data. Automation in Construction 31, 75-82.

      [23] Kim C, Son H & Kim C (2013), Fully automated registration of 3D data to a 3D CAD model for project progress monitoring. Automation in Construction 35, 587-594.

      [24] Han KK & Golparvar-Fard M (2015), Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs. Automation in Construction 53, 44-57.

      [25] Zhang S, Teizer J, Lee J, Eastman CM & Venugopal M (2013), Building information modeling (BIM) and safety: Automatic safety checking of construction models and schedules. Automation in Construction 29, 183-195.

      [26] Zhang S, Sulankivi K, Kiviniemi M, Romo I, Eastman CM & Teizer J (2015), BIM-based fall hazard identification and prevention in construction safety planning. Safety Science 72, 31-45.

      [27] Chen L & Luo H (2014), A BIM-based construction quality management model and its application. Automation in Construction 46, 64-73.

      [28] Zhiliang M, Zhenhua W, Wu S & Zhe L (2011), Application and extension of the IFC standard in construction cost estimating for tendering in China. Automation in Construction 20, 196-204.

      [29] Lee S, Kim K & Yu J (2014), BIM and ontology-based approach for building cost estimation. Automation in Construction 41, 96-105.

      [30] Ma Z & Liu Z (2014), BIM-based intelligent acquisition of construction information for cost estimation of building projects. Procedia Engineering 85, 358-367.

      [31] Choi J, Choi J & Kim I (2014), Development of BIM-based evacuation regulation checking system for high-rise and complex buildings. Automation in Construction 46, 38-49.

      [32] Fazio P, He HS, Hammad A & Horvat M (2007), based framework for evaluation total performance of building envelopes. Journal of Architectural Engineering 13, 44-53.

      [33] Kim H & Anderson K (2013), Energy modeling system using building information modeling open standards. Journal of Computing in Civil Engineering 27, 203-211.

      [34] Ahn K, Kim Y, Park C, Kim I & Lee K (2014), BIM interface for full vs. semi-automated building energy simulation. Energy and Buildings 68, 671-678.

      [35] Cheng JCP & Das M (2014), A BIM-based web service framework for green building energy simulation and code checking. Journal of Information Technology in Construction 19, 150-168.

      [36] Kim J, Shen Z, Kim I, Kim K, Stumpf A & Yu J (2016), BIM IFC information mapping to building energy analysis (BEA) model with manually extended material information. Automation in Construction 68, 183-193.

      [37] Jalaei F & Jrade A (2014), Integrating building information modeling (BIM) and energy analysis tools with green building certification system to conceptually design sustainable buildings. Journal of Information Technology in Construction 19, 494-519.

      [38] Abanda FH & Byers L (2016), An investigation of the impact of building orientation on energy consumption in a domestic building using emerging BIM (Building Information Modelling). Energy 97, 517-527.

      [39] Kim JB, Jeong W, Clayton MJ, Haberl JS & Yan W (2015) Developing a physical BIM library for building thermal energy simulation. Automation in Construction 50, 16-28.

      [40] Choi C, Kim C, Park C & Jang H (2018), IFC-BIM based framework for automated evaluation of building envelope thermal performance. International Journal of Energy, Information and Communications 9, 13-18.

      [41] Cemesova A, Hopfe CJ & Mcleod RS (2015), PassivBIM: Enhancing interoperability between BIM and low energy design software. Automation in Construction 57, 17-32.

      [42] Wu I & Hsieh S (2007), Transformation from IFC data model to GML data model: Methodology and tool development. Journal of the Chinese Institute of Engineers 30, 1085-1090.

      [43] Deng Y, Cheng JCP, & Anumba C (2016), Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison. Automation in Construction 67, 1-21.

  • Downloads

  • How to Cite

    Park, C.-Y., Kim, C.-M., Jang, H.-I., & Choi, C.-H. (2019). Automated Derivation of Building Envelope Thermal Performance Based on BIM for Building Energy Analysis. International Journal of Engineering & Technology, 8(1.4), 1-12. https://doi.org/10.14419/ijet.v8i1.4.25127