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Review of reduced order models for heat and moisture transfer in building physics with emphasis in PGD approaches. (English) Zbl 1375.80006
Summary: This paper presents a review of the use of model reduction techniques for building physics applications. The use of separated representations, the so called Proper Generalised Decomposition (PGD), is particularly investigated. This technique can be applied for efficient building physics modelling at different levels: the wall and multizone models, the whole-building (coupled envelope and air volumes) simulation and their practical applications. The PGD can be formulated as a space-time representation to provide fast and accurate solutions of 2- and 3-dimensional problems at the wall or the whole-building level. Furthermore, the PGD solution allows to treat efficiently parametric problems of practical building applications.
MSC:
80A20 Heat and mass transfer, heat flow (MSC2010)
Software:
FEMLAB; Simulink; ESP-r; IBPT; WUFI
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[1] B. LBNL. The Home of DOE-2 based Building Energy Use and Cost Analysis Software. http://doe2.com/DOE2/index.html
[2] W. National Institute of Building Sciences. Building loads analysis and system thermodynamics. https://www.wbdg.org/tools/blast.php · Zbl 1157.80368
[3] G. ESRU. Modelling tool for building performance simulation. http://www.esru.strath.ac.uk/Programs/ESP-r.htm · Zbl 1391.76099
[4] Peuportier B (2013) Livre blanc sur les recherches en energtique des batiments. Mines Paris Les Presses Paristech. ISBN 9782356710512
[5] Woloszyn, M; Rode, C, Tools for performance simulation of heat, air and moisture conditions of whole buildings, Build Simul, 1, 5, (2008)
[6] Paris. International Energy Agency. http://www.iea.org/publications/
[7] Chinesta F, Keunings R, Leygue A (2013) The proper generalized decomposition for advanced numerical simulations: a primer. Springer International Publishing AG, New York · Zbl 1287.65001
[8] Berger J (2014) Contribution to hygrothermal modelling of buildings: application of model reduction techniques (in french). Ph.D. thesis, University of Savoie, Chambery
[9] Künzel HM, Kiessl J (1995) Simultaneous heat and moisture transport in building components: one- and two-dimensional calculation using simple parameters. IRB Verlag, Stuttgart
[10] Tariku, F; Kumaran, K; Fazio, P, Transient model for coupled heat, air and moisture transfer through multilayered porous media, Int J Heat Mass Transf, 53, 3035, (2010) · Zbl 1194.80070
[11] Steeman, HJ; Belleghem, M; Janssens, A; Paepe, M, Coupled simulation of heat and moisture transport in air and porous materials for the assessment of moisture related damage, Build Environ, 44, 2176, (2009)
[12] Li, Q; Rao, J; Fazio, P, Development of HAM tool for building envelope analysis, Build Environ, 44, 1065, (2009)
[13] Rouchier, S; Woloszyn, M; Foray, G; Roux, J, Influence of concrete fracture on the rain infiltration and thermal performance of building facades, Int J Heat Mass Transf, 61, 340, (2013)
[14] Mendes, N; Philippi, PC, A method for predicting heat and moisture transfer through multilayered walls based on temperature and moisture content gradients, Int J Heat Mass Transf, 48, 37, (2005) · Zbl 1099.76535
[15] Santos, GH; Mendes, N, Combined simulation of central HVAC systems with a whole-building hygrothermal model, Energy Build, 40, 276, (2008)
[16] Santos, GH; Mendes, N, Heat, air and moisture transfer through hollow porous blocks, Int J Heat Mass Transf, 52, 2390, (2009) · Zbl 1158.80317
[17] Janssen, H, Simulation efficiency and accuracy of different moisture transfer potentials, J Build Perform Simul, (2014)
[18] Bauklimatik Dresden B (2011) Simulation program for the calculation of coupled heat, moisture, air, pollutant, and salt transport. http://www.bauklimatik-dresden.de/delphin/index.php?aLa=en
[19] Fraunhofer IBP (2005) Wufi http://www.hoki.ibp.fhg.de/wufi/wufi_frame_e.html · Zbl 1359.76219
[20] Lelievre, D; Colinart, T; Glouannec, P, Hygrothermal behavior of bio-based building materials including hysteresis effects: experimental and numerical analyses, Energy Build, 84, 617, (2014)
[21] At Oumziane Y, Bart M, Moissette S, Lanos C, Prtot S, Collet F (2011) Hygrothermal behaviour of a hemp concrete wall: influence of sorption modelling. In 9th Nordic Symposium on building Physics (Finland)
[22] Rode, PFC, Prediction of moisture transfer in building constructions, Build Environ, 27, 387, (1992)
[23] Carmeliet J, Wit M, Janssen H. Hysteresis and moisture buffering of wood. In Proceedings of the 7th Symposium on Building Physics in the Nordic Countries, pp 55-62
[24] Kwiatkowski, J; Woloszyn, M; Roux, J, Modelling of hysteresis influence on mass transfer in building materials, Build Environ, 44, 633, (2008)
[25] Crausse, P; Laurent, J; Perrin, B, Influence des phnomnes d’hystrsis sur LES proprits hydriques de matriaux poreux: comparaison de deux modles de simulation du comportement thermohydrique de parois de btiment, Revue Gnrale de Thermique, 35, 95, (1996)
[26] Kalagasidis, AS; Weitzmann, P; Nielsen, T; Peuhkuri, R; Hagentoft, CE; Rode, C, The international building physics toolbox in simulink, Energy Build, 39, 665, (2007)
[27] Tran, A; Maalouf, C; Mendona, KC; Mai, H; Wurtz, E, Study of moisture transfer in a double-layered wall with imperfect thermal and hydraulic contact resistances, J Build Perform Simul, 2, 251, (2009)
[28] Labat, M; Woloszyn, M; Garnier, G; Roux, J, Dynamic coupling between vapour and heat transfer in wall assemblies: analysis of measurements achieved under real climate, Build Environ, 87, 129, (2015)
[29] Janssen, H; Blocken, B; Carmeliet, J, Conservative modelling of the moisture and heat transfer in building components under atmospheric excitation, Int J Heat Mass Transf, 50, 1128, (2007) · Zbl 1124.80332
[30] Kunzel, HM; Kiessl, K, Calculation of heat and moisture transfer in exposed building components, Int J Heat Mass Transf, 40, 159, (1996)
[31] Hens, H; Carmeliet, J, Performance prediction for masonry walls with EIFS using calculation procedures and laboratory testing, J Build Phys, 25, 167, (2002)
[32] Belleudy, C; Woloszyn, M; Chhay, M; Cosnier, M, A 2D model for coupled heat, air, and moisture transfer through porous media in contact with air channels, Int J Heat Mass Transf, 95, 453, (2016)
[33] Mendes, N; Philippi, P; Lamberts, R, A new mathematical method to solve highly coupled equations of heat and mass transfer in porous media, Int J Heat Mass Transf, 45, 509, (2002) · Zbl 1106.76464
[34] Mendes, N; Philippi, PC, Multitridiagonal-matrix algorithm for coupled heat transfer in porous media: stability analysis and computational performance, J Porous Media, 7, 129-211, (2004) · Zbl 1074.76580
[35] Santos, GH; Mendes, N, Multidimensional effects of ground heat transfer on the dynamics of building thermal performance, ASHRAE Trans, 110, 345, (2004)
[36] Santos, GH; Mendes, N, Simultaneous heat and moisture transfer in soils combined with building simulation, Energy Build, 38, 303, (2006)
[37] Dos Santos, GH; Mendes, N, Unsteady combined heat and moisture transfer in unsaturated porous soils, J Porous Media, 8, 493, (2005)
[38] Akinyemi, OD; Mendes, N; Jonsson, M; Meissner, J; Linhares, S, Effects of psychrometrics conditions on the drying of a porous soil, J Build Phys, 31, 73, (2007)
[39] Santos, GH; Mendes, N; Philippi, PC, A building corner model for hygrothermal performance and mould growth risk analyses, Int J Heat Mass Transf, 52, 4862, (2009) · Zbl 1176.80057
[40] Santos, GH; Mendes, N, Hygrothermal bridge effects on the performance of buildings, Int Commun Heat Mass Transf, 53, 133, (2014)
[41] Coelho, LDS; Freire, RZ; Santos, GH; Mendes, N, Identification of temperature and moisture content fields using a combined neural network and clustering method approach, Int Commun Heat Mass Transf, 36, 304, (2009)
[42] Santos, GH; Mendes, N, Combined heat, air and moisture (HAM) transfer model for porous building materials, J Build Phys, 32, 203, (2009)
[43] Santos, GH; Mendes, N, Numerical analysis of passive cooling using a porous sandy roof, Appl Therm Eng, 51, 25, (2013)
[44] Yahia, AA; Barrio, EPD, Thermal systems modelling via singular value decomposition: direct and modular approach, Appl Math Model, 23, 447, (1999) · Zbl 0935.80002
[45] Dauvergne, J; Barrio, EPD, A spectral method for low-dimensional description of melting/solidification within shape-stabilized phase-change materials, Numer Heat Transf Part B Fundam, 56, 142, (2009)
[46] Dauvergne, J; Barrio, EP, Toward a simulation-free pod approach for low-dimensional description of phase-change problems, Int J Therm Sci, 49, 1369, (2010)
[47] Petit, D; Hachette, R; Veyret, D, A modal identification method to reduce a high order model: application to heat conduction modelling, Int J Model Simul, 17, 242, (1994)
[48] Girault, M; Derouineau, S; Salat, J; Petit, D, Model reduction for natural convection by identification method (in French), Comptes Rendus de Mecaniques, 332, 811, (2004)
[49] Girault, M; Petit, D, Identification methods in nonlinear heat conduction. part I: model reduction, Int J Heat Mass Transf, 48, 105, (2005) · Zbl 1098.80003
[50] Neveu, A; El-Khoury, K; Flament, B, Simulation de la conduction non linaire en rgime variable: dcomposition sur LES modes de branche, Int J Therm Sci, 38, 289, (1999)
[51] Videcoq, E; Quemener, O; Lazard, M; Neveu, A, Heat source identification and on-line temperature control by a branch eigenmodes reduced model, Int J Heat Mass Transf, 51, 4743, (2008) · Zbl 1154.80369
[52] Videcoq, E; Neveu, A; Quemener, O; Girault, M; Petit, D, Comparison of two nonlinear model reduction techniques: the modal identification method and the branch eigenmodes reduction method, Numer Heat Transfer Part B Fundam, 49, 537, (2006)
[53] Barrio, EP; Raji, S; Duquesne, M; Sempey, A, Reduced models for coupled heat and moisture transfer simulation in wood walls, JP J Heat Mass Transf, 10, 1, (2014)
[54] Berger J, Tasca-Guernouti S, Woloszyn M, Buhe C (2013) On the integration of hygrothermal bridges into whole building and HAM modeling. International Conference on Building Performance Simulation, IBPSA
[55] Berger J, Guernouti S, Woloszyn M (2016) Evaluating model reduction methods for heat and mass transfer in porous materials: Proper Orthogonal Decomposition and Proper Generalised Decomposition. International Communication in heat and Mass Transfer submitted on 02 April 2016
[56] Beausoleil-Morrison, I; Kummert, M; Macdonald, F; Jost, R; McDowell, T; Ferguson, A, Demonstration of the new ESP-r and TRNSYS co-simulator for modelling solar buildings, Energy Procedia, 30, 505, (2012)
[57] Berger, J; Mazuroski, W; Guernouti, S; Mendes, N; Woloszyn, M, 2D whole-building hygrothermal simulation analysis based on a PGD reduced order model, Energy Build, (2015)
[58] Berger J, Guernouti S, Woloszyn M, Chinesta F (2015) Proper Generalised Decomposition for heat and moisture multizone modelling. Energy Build. doi:10.1016/j.enbuild.2015.07.021 http://www.sciencedirect.com/science/article/pii/S0360132396000455
[59] Hong, T; Jiang, Y, A new multizone model for the simulation of building thermal performance, Build Environ, 32, 123, (1997)
[60] Gouda M, Danaher S, Underwood C (2000) Low-order model for the simulation of a building and its system. Build Serv Eng Res Technol 21(3):199. doi:10.1177/014362440002100308 http://bse.sagepub.com/content/21/3/199.abstract
[61] Parker ST, Lorenzetti DM, Sohn MD (2014) Implementing state-space methods for multizone contaminant transport. Build Environ 71:131. doi:10.1016/j.buildenv.2013.09.021 http://www.sciencedirect.com/science/article/pii/S0360132313002850
[62] Parker S, Bowman V (2011) State-space methods for calculating concentration dynamics in multizone buildings. Build Environ 46(8):1567. doi:10.1016/j.buildenv.2011.01.016 http://www.sciencedirect.com/science/article/pii/S0360132311000266
[63] Goyal, S; Barooah, P, A method for model-reduction of non-linear thermal dynamics of multi-zone buildings, Energy Build, 47, 332, (2012)
[64] Liberge, E; Hamdouni, A, Reduced order modelling method via proper orthogonal decomposition (POD) for flow around an oscillating cylinder, J Fluids Struct, 26, 292, (2010)
[65] Ly, HV; Tran, HT, Modeling and control of physical processes using proper orthogonal decomposition, Math Comput Model, 33, 223, (2001) · Zbl 0966.93018
[66] Sempey, A; Inard, C; Ghiaus, C; Allery, C, Fast simulation of temperature distribution in air conditioned rooms by using proper orthogonal decomposition, Build Environ, 44, 280, (2009)
[67] Li, K; Su, H; Chu, J; Xu, C, A fast-POD model for simulation and control of indoor thermal environment of buildings, Build Environ, 60, 150, (2013)
[68] Hensen J. Modelling coupled heat and air flow: pingpong vs onions. In IEA Air infiltration and Ventilation Centre (1995-09), pp 253-262
[69] Ken Amissah O (2005) Indoor air Quality - combining air humidity with construction moisture. Indoor air quality - combining air humidity with construction moisture. Ph.D. thesis, University of Strathclyde
[70] Wills, A; Cruickshank, CA; Beausoleil-Morrison, I, Application of the ESP-r/TRNSYS co-simulator to study solar heating with a single-house scale seasonal storage, Energy Procedia, 30, 715, (2012)
[71] International Energy Agency (2013) Energy in Buildings and Communities Program, Annex 60. http://www.iea-annex60.org · Zbl 1124.80332
[72] Derome D (1999) Moisture occurrence in roof assemblies containing moisture storing insulation and its impact on the durability of building envelope. Ph.D. thesis, Concordia University, Montreal, Quebec, Canada
[73] Steeman, M; Janssens, A; Steeman, H; Belleghem, M; Paepe, M, On coupling 1D non-isothermal heat and mass transfer in porous materials with a multizone building energy simulation model, Build Environ, 45, 865, (2010) · Zbl 1157.80368
[74] Delcroix B, Kummert M, Daoud A, Miller M (2012) Conduction transfer functions in TRNSYS multizone building model : current implementation, limitations and possible improvements. SimBuild 2012, Madison, Wisconsin
[75] Piot A, Abele C, Woloszyn M, Brau J (2008) Numerical Simulation Aided Design of an experimental protocol. In Proceedings of the 8th Symposium on Building Physics in the Nordic Countries, vol 2, Carsten Rode
[76] Santos, GH; Mendes, N, Simultaneous heat and moisture transfer in soils combined with building simulation, Energy Build, 38, 303, (2006)
[77] Holm A (2004) Predicting indoor temperature and humidity conditions including hygrothermal interactions with the building envelope. in American Society of Heating, Refrigerating and Air Conditioning Engineers. Transactions, pp 820-826
[78] Clarke, J, Moisture flow modelling within the ESP-r integrated building performance simulation system, J Build Perform Simul, 6, 385, (2013)
[79] Nakhi A (1995) Adaptative construction modelling within whole building dynamic simulation. Ph.D. thesis, University of Strathclyde, Glasgow
[80] Erriguible, A; Bernada, P; Couture, F; Roques, M, Simulation of convective drying of a porous medium with boundary conditions provided by CFD, Chem Eng Res Des, 84, 113, (2006)
[81] Mortensen, LH; Woloszyn, M; Rode, C; Peuhkuri, R, Investigation of microclimate by CFD modeling of moisture interactions between air and constructions, J Build Phys, 30, 279, (2007)
[82] Van Belleghem M, Steeman M, Willockx A, Janssens A, De Paepe M (2011-04) Benchmark experiments for moisture transfer modelling in air and porous materials. Build Environ 46(4):884. doi:10.1016/j.buildenv.2010.10.018
[83] van Schijndel (2003-02) AWM Modeling and solving building physics problems with FemLab. Build Environ 38(2):319. doi:10.1016/S0360-1323(02)00069-0
[84] Cornick A, Maref S, Mukhopadhyaya P, Dalgliesh A, Cornick S, Maref W, Mukhopadhyaya P. Hygrothermal Performance of Building Envelopes: Uses for 2D and 1D simulation
[85] Gao, Y; Roux, J; Zhao, L; Jiang, Y, Dynamical building simulation: a low order model for thermal bridges losses, Energy Build, 40, 2236, (2008)
[86] Barrio, EPD; Lefebvre, G; Behar, P; Bailly, N, Using model size reduction techniques for thermal control applications in buildings, Energy Build, 33, 1, (2000)
[87] Ladeveze, P, Sur une famille d’algorithmes en mcanique des structures, Comptes-rendus des seances de l’Academie des sciences. Srie 2, Mecanique-physique, chimie, sciences de l’univers, sciences de la terre, 300, 41, (1985) · Zbl 0597.73089
[88] Ammar, A; Mokdad, B; Chinesta, F; Keunings, R, A new family of solvers for some classes of multidimensional partial differential equations encountered in kinetic theory modelling of complex fluids: part II: transient simulation using space-time separated representations, J Non-Newton Fluid Mech, 144, 98, (2007) · Zbl 1196.76047
[89] Chinesta, F; Ammar, A; Cueto, E, Proper generalized decomposition of multiscale models, Int J Numer Methods Eng, 83, 1114, (2010) · Zbl 1197.76093
[90] Chinesta, F; Ladeveze, P; Cueto, E, A short review on model order reduction based on proper generalized decomposition, Arch Comput Methods Eng, 18, 395, (2011)
[91] Ammar A, Chinesta F (2008) Circumventing Curse of Dimensionality. In: Griebel M, Schweitzer MA (eds) The Solution of Highly Multidimensional Models Encountered in Quantum Mechanics Using Meshfree Finite Sums Decomposition, no. 65 in Lecture Notes in Computational Science and Engineering. in Meshfree Methods for Partial Differential Equations IV. Springer, Berlin Heidelberg, pp 1-17 · Zbl 1156.81365
[92] Nouy, A; Matre, OP, Generalized spectral decomposition for stochastic nonlinear problems, J Comput Phys, 228, 202, (2009) · Zbl 1157.65009
[93] Dumon, A; Allery, C; Ammar, A, Proper general decomposition (PGD) for the resolution of Navier-Stokes equations, J Comput Phys, 230, 1387, (2011) · Zbl 1391.76099
[94] Berger, J; Chhay, M; Guernouti, S; Woloszyn, M, Proper generalised decomposition for solving coupled heat and moisture transfers, J Build Perform Simul, (2014)
[95] Pruliere, E; Chinesta, F; Ammar, A, On the deterministic solution of multidimensional parametric models using the proper generalized decomposition, Math Comput Simul, 81, 791, (2010) · Zbl 1207.65014
[96] Chinesta, F; Ammar, A; Leygue, A; Keunings, R, An overview of the proper generalized decomposition with applications in computational rheology, J Non-Newton Fluid Mech, 166, 578, (2011) · Zbl 1359.76219
[97] Gonzlez, D; Masson, F; Poulhaon, F; Leygue, A; Cueto, E; Chinesta, F, Proper generalized decomposition based dynamic data driven inverse identification, Math Comput Simul, 82, 1677, (2012)
[98] Neron, D; Ladeveze, P, Proper generalized decomposition for multiscale and multiphysics problems, Arch Comput Methods Eng, 17, 351, (2010) · Zbl 1269.74209
[99] Mendes, N; Barbosa, RM; Freire, RZ; Oliveira, RCLF, A simulation environment for performance analysis of HVAC systems, Build Simul, 1, 129, (2008)
[100] Bednar T, Hagentoft CE (2005) Analytical Solution for Moisture Buffering Effect Validation Exercises for Simulation Tools. Chalmers Publication Library (CPL), 7th Nordic Symposium on Building Physics, Reykjavik, Iceland
[101] Housez, P; Pont, U; Mahdavi, A, A comparison of projected and actual energy performance of buildings after thermal retrofit measures, J Build Phys, 38, 138, (2014)
[102] Wang, L; Greenberg, S; Fiegel, J; Rubalcava, A; Earni, S; Pang, X; Yin, R; Woodworth, S, Monitoring-based HVAC commissioning of an existing office building for energy efficiency, J Hernandez-Maldonado Appl Energy, 102, 1382, (2013)
[103] Henze, GP; Pavlak, GS; Florita, AR; Dodier, RH; Hirsch, A, An energy signal tool for decision support in building energy systems, Appl Energy, 138, 51, (2015)
[104] Viot, H; Sempey, A; Mora, L; Batsale, JC, Fast on-site measurement campaigns and simple building models identification for heating control, Energy Procedia, 78, 2015, (2015)
[105] Mahendra, S; Stphane, P; Frederic, W, Modeling for reactive building energy management, Energy Procedia, 83, 207, (2015)
[106] Mar, JD; Litovsky, E; Kleiman, J, Modeling and database development of conductive and apparent thermal conductivity of moist insulation materials, J Build Phys, 32, 9, (2008)
[107] Berger, J; Gasparin, S; Chhay, M; Mendes, N, Estimation of temperature-dependent thermal conductivity using proper generalised decomposition for building energy management, J Build Phys, (2016)
[108] Ozisik MN, Orlande HR (2000) Inverse heat transfer: fundamentals and applications. CRC Press, New York
[109] Orlande, HRB, Inverse problems in heat transfer: new trends on solution methodologies and applications, J Heat Transf, 134, 1, (2012)
[110] Orlande, HRB, Inverse heat transfer problems, Heat Transf Eng, 32, 715, (2011)
[111] Orlande, HRB; Colao, M; Dulikravich, G, Approximation of the likelihood function in the Bayesian technique for the solution of inverse problems, Inverse Probl Sci Eng, 16, 677, (2008) · Zbl 1154.65006
[112] Berger, J; Orlande, H; Mendes, N, Proper generalized decomposition model reduction in the Bayesian framework for solving inverse heat transfer problems, Inverse Probl Sci Eng, (2016) · Zbl 1362.80003
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.