Frequency domain regression method to predict thermal behavior of brick wall of existing buildings

被引:13
|
作者
Sassine, Emilio [1 ,2 ,3 ]
Younsi, Zohir [1 ,2 ]
Cherif, Yassine [2 ,3 ]
Antczak, Emmanuel [2 ,3 ]
机构
[1] FUPL, HEI, LGCgE EA 4515, 13 Rue Toul, F-59000 Lille, France
[2] Univ Artois, LGCgE EA 4515, Technoparc Futura, F-62400 Bethune, France
[3] Univ Lille Nord France, LGCgE EA 4515, F-59000 Lille, France
关键词
Frequency-domain regression method; Old buildings; CTF model; Dynamic simulation; Brick wall insulation; OPTIMUM INSULATION THICKNESS; EXTERNAL WALLS; MODEL; PERFORMANCE; TEMPERATURE; CONDUCTION;
D O I
10.1016/j.applthermaleng.2016.11.134
中图分类号
O414.1 [热力学];
学科分类号
摘要
The prediction of the thermal behavior of the envelope of old buildings (built before 1948), subjected to various boundary conditions, is very useful for the implementation of an effective thermal renovation strategy. For this purpose, the present work aims at studying the transient thermal behavior of a brick wall and determinate the optimum insulation thickness by using a theoretical model based on the Frequency-Domain Regression (FDR) model. The brick wall of 34 cm thick (main characteristics of Northern European old buildings) has been used in this work. The numerical results agree well with experimental results obtained on a specially developed experimental setup. Subsequently, the model has been used to investigate the effects of the insulation thickness on the energy requirement and total cost. Simulation results indicated that thermal insulation is able to enhance the thermal behavior of massive wall, and that insulation thickness has influence on the profile of heat flux. The optimum insulation thicknesses for internal insulation vary between 55 and 12.4 cm, vary between 4.9 and 8.4 cm for external insulation depending on the fuel types. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:24 / 35
页数:12
相关论文
共 50 条
  • [41] An improvement to frequency-domain regression method for calculating conduction transfer functions of building walls
    Xu, Xinhua
    Wang, Shengwei
    Chen, Youming
    APPLIED THERMAL ENGINEERING, 2008, 28 (07) : 661 - 667
  • [42] On the ~ 7 year periodic signal in length of day from a frequency domain stepwise regression method
    Can-Can Hsu
    Peng-Shuo Duan
    Xue-Qing Xu
    Yong-Hong Zhou
    Cheng-Li Huang
    Journal of Geodesy, 2021, 95
  • [43] Transient heat flow calculation for multilayer constructions using a frequency-domain regression method
    Wang, SW
    Chen, YM
    BUILDING AND ENVIRONMENT, 2003, 38 (01) : 45 - 61
  • [44] The evaluation of the thermal behaviour of a mortar based brick masonry wall coated with TiO2 nanoparticles: An experimental assessment towards energy efficient buildings
    Carneiro, Joaquim O.
    Vasconcelos, Graca
    Azevedo, Sofia
    Jesus, Carlos
    Palha, Carlos
    Gomes, Nuno
    Teixeira, Vasco
    ENERGY AND BUILDINGS, 2014, 81 : 1 - 8
  • [45] A frequency-domain method to predict hydroelastic responses of a pontoon-separated floating bridge
    Wei W.
    Song C.-H.
    Fu S.-X.
    Ren T.-X.
    Chuan Bo Li Xue/Journal of Ship Mechanics, 2020, 24 (10): : 1302 - 1314
  • [46] Seismic behavior of asymmetric RC wall buildings: Principles and new deformation-based design method
    Sommer, A
    Bachmann, H
    EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, 2005, 34 (02): : 101 - 124
  • [47] Space charge and resistive wall impedance computation in the frequency domain using the finite element method
    Niedermayer, Uwe
    Boine-Frankenheim, Oliver
    De Gersem, Herbert
    PHYSICAL REVIEW SPECIAL TOPICS-ACCELERATORS AND BEAMS, 2015, 18 (03):
  • [48] A NEW SIMPLIFIED METHOD FOR EVALUATING THE THERMAL-BEHAVIOR OF DIRECT GAIN PASSIVE SOLAR BUILDINGS
    OLIVEIRA, AC
    FERNANDES, ED
    SOLAR ENERGY, 1992, 48 (04) : 227 - 233
  • [49] A COMPUTER ORIENTED METHOD FOR THE ANALYSIS OF NON STEADY-STATE THERMAL-BEHAVIOR OF BUILDINGS
    BARBARO, S
    GIACONIA, C
    ORIOLI, A
    BUILDING AND ENVIRONMENT, 1988, 23 (01) : 19 - 24
  • [50] A Regression Method Based on Noninvasive Clinical Data to Predict the Mechanical Behavior of Ascending Aorta Aneurysmal Tissue
    Auricchio, Ferdinando
    Ferrara, Anna
    Lanzarone, Ettore
    Morganti, Simone
    Totaro, Pasquale
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2017, 64 (11) : 2607 - 2617