Abstract
One of the great challenges in the architecture, engineering, and construction (AEC) industry is data communication and its development in modelling techniques. The development of 5G techniques, with the Internet of things (IoT), artificial intelligence (AI), amongst others, is developing significant advances for staging of data integration in the so-called digital twins (DTs). Undoubtedly, the DTs intend to synchronize the real physical data with a digital world that experiences successive changes that occur throughout the life cycle of the system. In this context, this work experiments with a horizontal integration methodology to evaluate the U-value of a window frame from structure from motion (SfM) photogrammetry data, as part of a digital twin. The “in situ” evaluation of the thermal transmittance of a common aluminium window frame that is being used in existing buildings in the 1960s and that reached constructions of the 1980s is addressed. The experimental results apply simulation analysis using two-dimensional software. Thermal transmittance measurement equipment was used through a thermal flow meter plate, and the variations in thermal behaviour were analyzed according to the geometry of the frame. The results show different Uf-value data between the simulation and the in situ measurement with a dispersion variability of 1.5 W/m2K between the models. The essence and originality of the experimentation lie in the integration of horizontal aggregates (HA) as a basis in the simulation, measurement, and reverse engineering processes to an energy model of the DT system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
CMNUCC, Acuerdo de París, COP21. 21930 (2015) 40. http://unfccc.int/resource/docs/2015/cop21/spa/l09s.pdf
Pérez-Lombard L, Ortiz J, Pout C (2008) A review on buildings energy consumption information. Energ Build 40:394–398. https://doi.org/10.1016/j.enbuild.2007.03.007
Bienvenido-Huertas D, Rubio-Bellido C, Pérez-Fargallo A, Pulido-Arcas JA (2020) Energy saving potential in current and future world built environments based on the adaptive comfort approach. J Clean Prod 249. https://doi.org/10.1016/j.jclepro.2019.119306
Sánchez-García D, Bienvenido-Huertas D, Pulido-Arcas JA, Rubio-Bellido C (2020) Analysis of energy consumption in different European cities: the adaptive comfort control implemented model (ACCIM) considering representative concentration pathways (RCP) scenarios. Appl Sci 10:1–24. https://doi.org/10.3390/app10041513
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C (2020) Analysing natural ventilation to reduce the cooling energy consumption and the fuel poverty of social dwellings in coastal zones. Appl Energ 279. https://doi.org/10.1016/j.apenergy.2020.115845
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C (2021) Adaptive setpoint temperatures to reduce the risk of energy poverty? A local case study in Seville. Energ Build 110571. https://doi.org/10.1016/j.enbuild.2020.110571
Pérez-Fargallo A, Bienvenido-Huertas D, Rubio-Bellido C, Trebilcock M (2020) Energy poverty risk mapping methodology considering the user’s thermal adaptability: the case of Chile, Energy. Sustain Dev 58:63–77. https://doi.org/10.1016/j.esd.2020.07.009
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C, Pulido-Arcas JA (2020) Analysing the inequitable energy framework for the implementation of nearly zero energy buildings (nZEB) in Spain. J Build Eng. https://doi.org/10.1016/j.jobe.2020.102011
Bienvenido-Huertas D, Marín-García D, Carretero-Ayuso MJ, Rodríguez-Jiménez CE (2021) Climate classification for new and restored buildings in Andalusia: analysing the current regulation and a new approach based on k-means. J Build Eng 43:102829. https://doi.org/10.1016/j.jobe.2021.102829
Bienvenido-Huertas D, Oliveira M, Rubio-Bellido C, Marín D (2019) A comparative analysis of the international regulation of thermal properties in building envelope. Sustainability 11:5574. https://doi.org/10.3390/su11205574
Bienvenido-Huertas D (2021) Do unemployment benefits and economic aids to pay electricity bills remove the energy poverty risk of Spanish family units during lockdown? A study of COVID-19-induced lockdown. Energ Policy 150. https://doi.org/10.1016/j.enpol.2020.112117
Bienvenido-Huertas D (2021) Influence of the type of thermostat on the energy saving obtained with adaptive setpoint temperatures: analysis in the current and future scenario. Energ Build 244:111024. https://doi.org/10.1016/j.enbuild.2021.111024
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C, Oliveira MJ (2020) Influence of adaptive energy saving techniques on office buildings located in cities of the Iberian Peninsula. Sustain Cities Soc 53:101944. https://doi.org/10.1016/j.scs.2019.101944
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C, Pulido-Arcas JA (2021) Applying the mixed-mode with an adaptive approach to reduce the energy poverty in social dwellings: the case of Spain. Energy 237. https://doi.org/10.1016/j.energy.2021.121636
Bienvenido-Huertas D, Sánchez-García D, Pérez-Fargallo A, Rubio-Bellido C (2020) Optimization of energy saving with adaptive setpoint temperatures by calculating the prevailing mean outdoor air temperature. Build Environ 170. https://doi.org/10.1016/j.buildenv.2019.106612
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C, Marín-García D (2021) Potential of applying adaptive strategies in buildings to reduce the severity of fuel poverty according to the climate zone and climate change: the case of Andalusia. Sustain Cities Soc 73. https://doi.org/10.1016/j.scs.2021.103088
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C (2020) Comparison of energy conservation measures considering adaptive thermal comfort and climate change in existing Mediterranean dwellings. Energy 190. https://doi.org/10.1016/j.energy.2019.116448
Bienvenido-Huertas D (2020) Analysis of the relationship of the improvement of façades and thermal bridges of Spanish building stock with the mitigation of its energy and environmental impact. Energies 13. https://doi.org/10.3390/en13174499
Gastines M, Pattini A (2019) Propiedades energéticas de tecnologías de ventanas en Argentina. Rev. Hábitat Rev. Sustentable. 9:47–57
E.I. 10077-2 (2003) Thermal performance of windows, doors and shutters—calculation of thermal transmittance—numerical method for frames
Rosen R, Boschert S, Sohr A (2018) Next generation digital twin. Atp Mag 60:86–96. https://doi.org/10.17560/ATP.V60I10.2371
Al-Sehrawy R, Kumar B (2020) Digital twins in architecture, engineering, construction and operations. A brief review and analysis. Lect Notes Civ Eng 98:924–939. https://doi.org/10.1007/978-3-030-51295-8_64
Grieves M, Vickers J (2017) Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary perspectives on complex systems, pp 85–113. https://doi.org/10.1007/978-3-319-38756-7_4
Tao F, Sui F, Liu A, Qi Q, Zhang M, Song B, Guo Z, Lu SC-Y, Nee AYC (2018) Digital twin-driven product design framework. 57:3935–3953. https://doi.org/10.1080/00207543.2018.1443229
Angjeliu G, Coronelli D, Cardani G (2020) Development of the simulation model for Digital Twin applications in historical masonry buildings: the integration between numerical and experimental reality. Comput Struct 238:106282. https://doi.org/10.1016/J.COMPSTRUC.2020.106282
Wong JKW, Li H, Wang H, Huang T, Luo E, Li V (2013) Toward low-carbon construction processes: the visualisation of predicted emission via virtual prototyping technology. Autom Constr 33:72–78. https://doi.org/10.1016/J.AUTCON.2012.09.014
Götz CS, Karlsson P, Yitmen I (2020) Exploring applicability, interoperability and integrability of Blockchain-based digital twins for asset life cycle management. Smart Sustain Built Environ. https://doi.org/10.1108/SASBE-08-2020-0115/FULL/PDF
Macchi M, Roda I, Negri E, Fumagalli L (2018) Exploring the role of digital twin for asset lifecycle management. IFAC-PapersOnLine 51:790–795. https://doi.org/10.1016/J.IFACOL.2018.08.415
Moin S, Karim A, Safdar Z, Safdar K, Ahmed E, Imran M (2019) Securing IoTs in distributed blockchain: analysis, requirements and open issues. Futur Gener Comput Syst 100:325–343. https://doi.org/10.1016/J.FUTURE.2019.05.023
Wong JKW, Ge J, He SX (2018) Digitisation in facilities management: a literature review and future research directions. Autom Constr 92:312–326. https://doi.org/10.1016/J.AUTCON.2018.04.006
Teni M, Krstić H, Kosiński P (2019) Review and comparison of current experimental approaches for in-situ measurements of building walls thermal transmittance. Energ Build 203:109417. https://doi.org/10.1016/j.enbuild.2019.109417
Tejedor B, Casals M, Gangolells M (2018) Assessing the influence of operating conditions and thermophysical properties on the accuracy of in-situ measured U-values using quantitative internal infrared thermography. Energ Build 171:64–75. https://doi.org/10.1016/j.enbuild.2018.04.011
Tejedor B, Casals M, Gangolells M, Roca X (2017) Quantitative internal infrared thermography for determining in-situ thermal behaviour of façades. Energ Build 151:187–197. https://doi.org/10.1016/j.enbuild.2017.06.040
Bienvenido-Huertas D, Bermúdez J, Moyano J, Marín D (2019) Comparison of quantitative IRT to estimate U-value using different approximations of ECHTC in multi-leaf walls. Energ Build 184:99–113. https://doi.org/10.1016/j.enbuild.2018.11.028
Bienvenido-Huertas D, Bermúdez J, Moyano JJ, Marín D (2019) Influence of ICHTC correlations on the thermal characterization of façades using the quantitative internal infrared thermography method. Build Environ 149:512–525. https://doi.org/10.1016/j.buildenv.2018.12.056
Evangelisti L, Guattari C, Gori P, Bianchi F (2017) Heat transfer study of external convective and radiative coefficients for building applications. Energ Build 151:429–438. https://doi.org/10.1016/j.enbuild.2017.07.004
Evangelisti L, Guattari C, Asdrubali F (2018) Influence of heating systems on thermal transmittance evaluations: simulations, experimental measurements and data post-processing. Energ Build 168:180–190. https://doi.org/10.1016/j.enbuild.2018.03.032
Ficco G, Iannetta F, Ianniello E, D’Ambrosio Alfano FR, Dell’Isola M (2015) U-value in situ measurement for energy diagnosis of existing buildings. Energ Build 104:108–121. https://doi.org/10.1016/j.enbuild.2015.06.071
Bienvenido-Huertas D, Rubio-Bellido C, Pérez-Ordóñez JL, Oliveira MJ (2020) Automation and optimization of in-situ assessment of wall thermal transmittance using a Random Forest algorithm. Build Environ 168. https://doi.org/10.1016/j.buildenv.2019.106479
Bienvenido-Huertas D, Rubio-Bellido C, Solís-Guzmán J, Oliveira MJ (2020) Experimental characterisation of the periodic thermal properties of walls using artificial intelligence. Energy 203. https://doi.org/10.1016/j.energy.2020.117871
Lucchi E, Roberti F, Alexandra T (2018) Definition of an experimental procedure with the hot box method for the thermal performance evaluation of inhomogeneous walls. Energ Build 179:99–111. https://doi.org/10.1016/j.enbuild.2018.08.049
Lucchi E (2017) Thermal transmittance of historical brick masonries: a comparison among standard data, analytical calculation procedures, and in situ heat flow meter measurements. Energ Build 134:171–184. https://doi.org/10.1016/j.enbuild.2016.10.045
Malvoni M, Baglivo C, Congedo PM, Laforgia D (2016) CFD modeling to evaluate the thermal performances of window frames in accordance with the ISO 10077. Energy 111:430–438. https://doi.org/10.1016/j.energy.2016.06.002
Lechowska AA, Schnotale JA, Baldinelli G (2017) Window frame thermal transmittance improvements without frame geometry variations: an experimentally validated CFD analysis. Energ Build 145:188–199. https://doi.org/10.1016/j.enbuild.2017.04.002
Baldinelli G, Bianchi F (2014) Windows thermal resistance: infrared thermography aided comparative analysis among finite volumes simulations and experimental methods. Appl Energ 136:250–258. https://doi.org/10.1016/J.APENERGY.2014.09.021
International Organization for Standardization, ISO 9869-1:2014—Thermal insulation—Building elements—In situ measurement of thermal resistance and thermal transmittance. Part 1: Heat flow meter method, Geneva, Switzerland, 2014
Soares N, Martins C, Gonçalves M, Santos P, da Silva LS, Costa JJ (2019) Laboratory and in-situ non-destructive methods to evaluate the thermal transmittance and behavior of walls, windows, and construction elements with innovative materials: a review. Energ Build 182:88–110. https://doi.org/10.1016/j.enbuild.2018.10.021
Fokaides PA, Kalogirou SA (2011) Application of infrared thermography for the determination of the overall heat transfer coefficient (U-Value) in building envelopes. Appl Energ 88:4358–4365. https://doi.org/10.1016/j.apenergy.2011.05.014
B. Software, Psi-Therm GmbH (2020)
Osello A (2012) The future of drawing with BIM for engineers and architects-. Dario Flaccovio Ed. Srl.
Bienvenido-Huertas D, Moyano J, Rodríguez-Jiménez CE, Muñoz-Rubio A, Bermúdez Rodríguez FJ (2020) Quality control of the thermal properties of superstructures in accommodation spaces in naval constructions. Sustainability 12:4194. https://doi.org/10.3390/su12104194
Bienvenido-Huertas D, Pérez-Ordóñez JL, Moyano J, Seara-Paz S (2020) Towards an in-situ evaluation methodology of thermal resistance of basement walls in buildings. Energ Build 208:109643. https://doi.org/10.1016/j.enbuild.2019.109643
N.I.I. 10077-2 (2012) Thermal performance of windows, doors and shutters—Calculation of thermal transmittance—Part 2: Numerical
Asdrubali F, Baldinelli G, Bianchi F (2012) A quantitative methodology to evaluate thermal bridges in buildings. Appl Energ 97:365–373. https://doi.org/10.1016/j.apenergy.2011.12.054
O’Grady M, Lechowska AA, Harte AM (2017) Infrared thermography technique as an in-situ method of assessing the heat loss through thermal bridging. Energ Build 135:20–32. https://doi.org/10.1016/j.enbuild.2016.11.039
Scheuer C, Boot E, Carse N, Clardy A, Gallagher J, Heck S, Marron S, Martinez-Alvarez L, Masarykova D, Mcmillan P, Murphy F, Steel E, Van Ekdom H, Vecchione H (1978) Application of aerial infrared thermography to the measurement of building heat loss. Build Syst Des 75:24–26. https://doi.org/10.2/JQUERY.MIN.JS
Glaessgen EH, Stargel DS (2012) The digital twin paradigm for future NASA and U.S. Air force vehicles. Collect technical paper—AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference. https://doi.org/10.2514/6.2012-1818.
Kang JS, Chung K, Hong EJ (2021) Multimedia knowledge-based bridge health monitoring using digital twin. Multimed Tools Appl 80:34609–34624. https://doi.org/10.1007/S11042-021-10649-X/FIGURES/11
Stanley R, Thurnell D (2014) The benefits of, and barriers to, implementation of 5D BIM for quantity surveying in New Zealand, Australas. J Constr Econ Build 14(1):105–117. https://doi.org/10.3316/INFORMIT.200817347855487
Kim JB, Jeong W, Clayton MJ, Haberl JS, Yan W (2015) Developing a physical BIM library for building thermal energy simulation. Autom Constr 50:16–28. https://doi.org/10.1016/J.AUTCON.2014.10.011
Cemesova A, Hopfe CJ, McLeod RS (2015) PassivBIM: enhancing interoperability between BIM and low energy design software. Autom Constr 57:17–32. https://doi.org/10.1016/J.AUTCON.2015.04.014
Zhang X, Shen J, Saini PK, Lovati M, Han M, Huang P, Huang Z (2021) Digital twin for accelerating sustainability in positive energy district: a review of simulation tools and applications. Front Sustain Cities 3:35. https://doi.org/10.3389/FRSC.2021.663269/BIBTEX
Khajavi SH, Motlagh NH, Jaribion A, Werner LC, Holmstrom J (2019) Digital twin: vision, benefits, boundaries, and creation for buildings. IEEE Access 7:147406–147419. https://doi.org/10.1109/ACCESS.2019.2946515
G. Digital(2022) GE Predix Platform | Industrial IoT Platform | GE Digital
Trebilcock M (2021) Proceso de Diseño Integrado: nuevos paradigmas en arquitectura sustentable. Arquitetura Rev 5:65–75. https://doi.org/10.4013/arq.2009.52.01
Ruikar K, Kotecha K, Sandbhor S, Thomas A (eds), Deng M, Menassa CC, Kamat VR (2021) From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry, ITcon Vol. 26, Special Issue Next Generation ICT—How distant is ubiquitous computing, pp 58–83, http://www.itcon.org/2021/5. https://doi.org/10.36680/J.ITCON.2021.005.
Bienvenido-Huertas D, Pulido-Arcas JA, Rubio-Bellido C, Pérez-Fargallo A (2020) Influence of future climate changes scenarios on the feasibility of the adaptive comfort model in Japan. Sustain Cities Soc 61:102303. https://doi.org/10.1016/j.scs.2020.102303
Bienvenido-Huertas D, Sánchez-García D, Rubio-Bellido C (2022) Influence of the RCP scenarios on the effectiveness of adaptive strategies in buildings around the world. Build Environ 208. https://doi.org/10.1016/j.buildenv.2021.108631
Bienvenido-Huertas D, Rubio-Bellido C, Marín-García D, Canivell J (2021) Influence of the Representative Concentration Pathways (RCP) scenarios on the bioclimatic design strategies of the built environment. Sustain Cities Soc 72:103042. https://doi.org/10.1016/j.scs.2021.103042
Bienvenido-Huertas D, Nieto-Julián JE, Moyano JJ, Macías-Bernal JM, Castro J (2019) Implementing artificial intelligence in H-BIM using the J48 algorithm to manage historic buildings. Int J Archit Herit 1–13.https://doi.org/10.1080/15583058.2019.1589602
Andriasyan M, Moyano J, Nieto-Julián JE, Antón D (2020) From point cloud data to building information modelling: an automatic parametric workflow for heritage. Rem Sens 12. https://doi.org/10.3390/rs12071094
Moyano J, Nieto-Julián JE, Antón D, Cabrera E, Bienvenido-Huertas D, Sánchez N (2020) Suitability study of structure-from-motion for the digitisation of architectural (Heritage) spaces to apply divergent photograph collection. Symmetry (Basel) 12:1–25. https://doi.org/10.3390/sym12121981
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Fernández-Alconchel, M., Nieto-Julián, J.E., Carretero-Ayuso, M.J., Moyano-Campos, J. (2022). Methodology for the Evaluation of an Energetic Model of Thermal Transmittance in a Window by Means of Horizontal Aggregation (HA) from Short-range Photogrammetry for Model Digital Twin. In: Bienvenido-Huertas, D., Moyano-Campos, J. (eds) New Technologies in Building and Construction. Lecture Notes in Civil Engineering, vol 258. Springer, Singapore. https://doi.org/10.1007/978-981-19-1894-0_4
Download citation
DOI: https://doi.org/10.1007/978-981-19-1894-0_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1893-3
Online ISBN: 978-981-19-1894-0
eBook Packages: EngineeringEngineering (R0)