Research Papers

An Inverse Parameter Estimation Method for Building Thermal Analysis

[+] Author and Article Information
A. Moftakhari

School of Mechanical Engineering,
K. N. Toosi University of Technology,
Tehran 19697 64499, Iran
e-mail: ardeshir_2010@yahoo.com

C. Aghanajafi

School of Mechanical Engineering,
K. N. Toosi University of Technology,
Tehran 19697 64499, Iran

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received April 27, 2015; final manuscript received December 23, 2015; published online February 1, 2016. Assoc. Editor: Jorge E. Gonzalez.

J. Sol. Energy Eng 138(2), 021004 (Feb 01, 2016) (11 pages) Paper No: SOL-15-1110; doi: 10.1115/1.4032476 History: Received April 27, 2015; Revised December 23, 2015

The aim of this study is to introduce a new solution methodology for thermal parameter estimation in building engineering science. By defining a good numerical modeling, inverse algorithm provides us a chance to enhance design conditions in building thermal analysis. The definition of mathematical governing equations and a good solution method to solve them direct the analysis procedure to find temperature distribution using dynamic coding in the computational field. In fact, inverse algorithm utilizes known data resulted from numerical modeling in order to determine the unknown value of important thermal design properties in building problems. The results obtained from implementation of such algorithms demonstrate the accuracy and precision of this new thermal analysis methodology with those of real data resulted from experiments in building problems.

Copyright © 2016 by ASME
Your Session has timed out. Please sign back in to continue.


Valancius, K. , Motuziene, V. , and Paulauskaite, S. , 2015, “ Redeveloping Industrial Buildings for Residential Use: Energy and Thermal Comfort Aspects,” Energy for Sustainable Dev., 29, pp. 38–46. [CrossRef]
Han, G. , and Srebric, J. , 2015, “ Comparison of Survey and Numerical Sensitivity Analysis Results to Assess the Role of Life Cycle Analyses From Building Designers' Perspectives,” Energy Build., 108, pp. 463–469. [CrossRef]
Zhao, K. , Liu, X. , and Jiang, Y. , 2013, “ Application of Radiant Floor Cooling in a Large Open Space Building With High-Intensity Solar Radiation,” Energy Build., 66, pp. 246–257. [CrossRef]
Kirimtat, A. , Kundakci Koyunbaba, B. , Chatzikonstantinou, I. , and Sariyildiz, S. , 2016, “ Review of Simulation Modeling for Shading Devices in Buildings,” Renewable Sustainable Energy Rev., 53, pp. 23–49. [CrossRef]
Stephenson, D. G. , and Mitalas, G. P. , 1967, “ Cooling Load Calculations by Thermal Response Factor Method,” ASHRAE Trans., 73(1), pp. 509–515.
Andersen, K. K. , 2001, “ Stochastic Modeling of Energy Systems,” Ph.D. thesis, Department of Mathematical Modelling, The Technical University of Denmark, Lyngby, Denmark.
Hensen, R. , Auer, H. , and Biermay, P. , 1995, “ On System Simulation for Building Performance Evaluation,” Fourth IBPSA World Congress on Building Simulation, Madison, WI, Aug. 14–16, pp. 259–267.
Pedersen, C. O. , Fisher, D. E. , and Liesen, R. J. , 1997, “ Development of a Heat Balance Procedure for Calculating Cooling Loads,” ASHRAE Trans., 103(2), pp. 459–468.
Hadamard, J. , 1952, Sur les Problem aux Derivees Partielles et Leur Signification Physique, Vol. 13, University Princeton Press,, Princeton, NJ, pp. 49–52.
Beck, J. V. , 1970, “ Sensitivity Coefficients Utilized in Nonlinear Estimation With Small Parameters in a Heat Transfer Problem,” ASME J. Basic Eng., 92(2), pp. 215–222. [CrossRef]
Shenefelt, J. , Luck, R. , Taylor, R. P. , and Berry, J. T. , 2002, “ Model Reduction Solution for Inverse Heat Conduction Problems Employing Matrix Transfer,” Int. J. Heat Mass Transfer, 45(1), pp. 67–74. [CrossRef]
Tikhanov, A. N. , and Arsenin, V. Y. , 1977, Solution of Ill-Posed Problems, Winston, Washington, DC.
Fayazbakhsh, M. A. , Bagheri, F. , and Bahrami, M. , 2015, “ An Inverse Method for Calculation of Thermal Inertia and Heat Gain in Air Conditioning and Refrigeration Systems,” Appl. Energy, 138, pp. 496–504. [CrossRef]
Lei, L. , Wang, Sh. , and Zhang, T. , 2014, “ Inverse Determination of Wall Boundary Convective Heat Fluxes in Indoor Environments Based on CFD,” Energy Build., 73, pp. 130–136. [CrossRef]
Chaffar, K. , Chauchois, A. , Defer, D. , and Zalewski, L. , 2014, “ Thermal Characterization of Homogeneous Walls Using Inverse Method,” Energy Build., 78, pp. 248–255. [CrossRef]
Grieu, S. , Faugeroux, O. , Traoré, A. , Claudet, B. , and Bodnar, J. L. , 2011, “ Artificial Intelligence Tools and Inverse Methods for Estimating the Thermal Diffusivity of Building Materials,” Energy Build., 43, pp. 543–554. [CrossRef]
Hua, J. , Fan, H. , Wang, X. , and Zhang, Y. , 2015, “ A Novel Concept to Determine the Optimal Heating Mode of Residential Rooms Based on the Inverse Problem Method,” Build. Environ., 85, pp. 73–84. [CrossRef]
Reddy, T. A. , Deng, S. , and Claridge, D. E. , 1999, “ Development of an Inverse Method to Estimate Overall Building and Ventilation Parameters of Large Commercial Buildings,” ASME J. Sol. Energy Eng., 121(1), pp. 40–46. [CrossRef]
Fernández, E. , and Besuievsky, G. , 2012, “ Inverse Lighting Design for Interior Buildings Integrating Natural and Artificial Sources,” Comput. Graphics, 36(8), pp. 1096–1108. [CrossRef]
Ukrainczyk, N. , 2009, “ Thermal Diffusivity Estimation Using Numerical Inverse Solution for 1D Heat Conduction,” Int. J. Heat Mass Transfer, 52, pp. 5675–5681. [CrossRef]
Zhang, Y. , Shi, W. , Shang, R. , Cheng, R. , and Wang, X. , 2015, “ A New Approach, Based on the Inverse Problem and Variation Method, for Solving Building Energy and Environment Problems: Preliminary Study and Illustrative Examples,” Build. Environ., 91, pp. 204–218. [CrossRef]
Zhang, Y. , O'Neill, Z. , Dong, B. , and Augenbroe, G. , 2015, “ Comparisons of Inverse Modeling Approaches for Predicting Building Energy Performance,” Build. Environ., 86, pp. 177–190. [CrossRef]
Sangi, R. , Baranski, M. , Oltmanns, J. , Streblow, R. , and Müller, D. , 2016, “ Modeling and Simulation of the Heating Circuit of a Multi-Functional Building,” Energy Build., 110, pp. 13–22. [CrossRef]
Harish, V. S. K. V. , and Kumar, A. , 2016, “ Reduced Order Modeling and Parameter Identification of a Building Energy System Model Through an Optimization Routine,” Appl. Energy, 162, pp. 1010–1023. [CrossRef]
Hui, S. C. M. , 1988, “ Simulation Based Design Tools for Energy Efficient Buildings in Hong Kong,” Hong Kong Papers Design Develop., 1, pp. 40–46.
Berdahl, P. , Martin, M. , and Sakkal, F. , 1983, “ Thermal Performance of Radiative Cooling Panels,” Int. J. Heat Mass Transfer, 26(6), pp. 871–880. [CrossRef]
De Carli, M. , Scarpa, M. , Tomasi, R. , and Zarrella, A. , 2012, “ A Numerical Model for Thermal Balance of Rooms Equipped With Radiant Systems,” Build. Environ., 57, pp. 126–144. [CrossRef]
Hui, S. C. M. , and Cheung, K. P. , 1998, “ Application of Building Energy Simulation to Air-Conditioning Design,” Mainland-Hong Kong HVAC Seminar '98, Beijing, China, Mar. 23–25, pp. 12–20.
Duda, P. , 2016, “ A General Method for Solving Transient Multidimensional Inverse Heat Transfer Problems,” Int. J. Heat Mass Transfer, 93, pp. 665–673. [CrossRef]
Ozisik, M. N. , and Orlande, H. R. B. , 2000, Inverse Heat Transfer Problems: Fundamentals and Applications, Taylor and Francis, New York.
Moftakhari, A. , Torabi, F. , and Aghanajafi, C. , 2016, “ A Novel Energy Simulation Approach for Thermal Design of Buildings Equipped With Radiative Panels Using Inverse Methodology,” Energy Buildings, 113, pp. 169–181. [CrossRef]
Kim, D. , Hong, S. , and Armando Duarte, C. , 2015, “ Generalized Finite Element Analysis Using the Preconditioned Conjugate Gradient Method,” Appl. Math. Modell., 39(19), pp. 5837–5848. [CrossRef]
Marquadt, M. , 1963, “ An Algorithm for Least Square Estimation of Nonlinear Parameters,” J. Sci. Appl. Math., 11(2), pp. 431–441.


Grahic Jump Location
Fig. 1

Radiation from the surface of a body

Grahic Jump Location
Fig. 2

The flow chart of solution algorithm

Grahic Jump Location
Fig. 3

The radiant systems inside a residential building

Grahic Jump Location
Fig. 4

Building load simulation with both code and software

Grahic Jump Location
Fig. 5

Conduction heat transfer relative sensitivity factor

Grahic Jump Location
Fig. 6

Interior convection heat transfer relative sensitivity factor

Grahic Jump Location
Fig. 7

Exterior convection heat transfer relative sensitivity factor



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In