Optimal Experimental Design for the Assessment of Thermophysical Properties in Existing Building Walls

Abstract

The estimation of wall thermal properties through an inverse problem procedure enables to increase the reliability of the model predictions for building energy efficiency. Nevertheless, it requires defining an experimental campaign to obtain in situ observations for existing buildings. The quality of the estimated parameter strongly depends on the quality of the experimental data used for the parameter identification. In other words, there is a close relation between the experiment design and the precision of the retrieved parameters. The design of experiments enables to search for the optimal measurement plan. It ensures the highest precision of the parameter to be estimated. For in situ measurement in buildings, the design of experiments seeks to answer the following questions: How many sensors do we need? What is the sensor position in the wall? The optimal experiment design methodology enables us to answer those questions. The unknown parameter is the thermal conductivity of wall façade model considering two-dimensional heat transfer induced by time and space varying boundary conditions.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

The authors acknowledge the DSG 2021 project TOPS for the financial support.

Notes on contributors

Suelen Gasparin

Suelen Gasparin received her Ph.D. degree in Mechanical Engineer and Applied Mathematics from the Grenoble Alpes University, France and Pontifical Catholic University of Paraná, Brazil. After a postdoctoral fellow at the La Rochelle University, France, she is now a full researcher at the French Ministry of Environment, Cerema. She works on numerical methods for predicting heat and moisture transfer through porous building materials, based on advanced techniques such as Spectral model reduction approaches. Her objective is to develop fast and accurate models to represent the physical phenomena occurring in the porous building walls and their interactions with the ambient air.

Julien Berger

Julien Berger received his PhD in 2014 from the Grenoble Alpes University, France. He is now a Tenured Associate Scientist at the French National Centre for Scientific Research. He contributes to the numerical methods applied for heat and moisture transfer in porous material. The proposed numerical model is based on innovative approach such as model reduction methods. They are employed for the computing the prediction of the physical phenomena for comparison with experimental observation to evaluate the overall model reliability. Models can also be employed in the framework of inverse problems to determine the diffusion material properties using in situ measurement.

Giampaolo D’Alessandro

Giampaolo D’Alessandro received his M.S. and Ph.D. degree in Mechanical Engineering from University of L’Aquila, Italy, in 2014 and 2019, respectively. He has been a post-Doc student in the Department of Industrial and Information Engineering and Economics at University of L’Aquila, Italy, since 2019. His research activity is in the fields of heat conduction problems, parameter estimation, and mass diffusion.

Filippo de Monte

Filippo de Monte is a Professor of Mechanical Engineering at University of L’Aquila, Italy. He served as a full-time Visiting Ph.D. student at the Department of Engineering, University of Cambridge, UK, in 1992, and a seasonal Visiting Associate Professor at the Department of Mechanical Engineering, Michigan State University, USA, in 2007 up to 2014. He is a Member of American Society of Mechanical Engineers (ASME) and holds editorial positions at the Journal of Verification, Validation and Uncertainty Quantification (ASME) and Heat Transfer Engineering. He is coeditor of the Elsevier/Academic Press 1st Edition book: Modeling of Mass Transport Processes in Biological Media (August 2022), and coauthor of the Wiley 2nd Edition book: Inverse Heat Conduction: Ill-Posed Problems (Spring 2023), by Woodbury, Najafi, de Monte and Beck. His research interests include heat and mass transport by diffusion with applications to porous media, inverse heat transfer analysis, thermal properties estimation, refrigerating machines and Stirling thermal cycle. He is also ranked in the Top 2% of the world’s scientists list compiled by Stanford University, 2020–2022.

Dariusz Ucinski

Dariusz Ucinski was born in 1965. He received his MSc degree in electrical engineering from the Higher College of Engineering in Zielona Góra, Poland, in 1989, and his PhD and DSc degrees in automatic control and robotics from the Wrocław University of Science and Technology, Poland, in 1992 and 2000, respectively. In 2007 he was conferred the full professorial title, the highest scientific degree in Poland. He is currently a professor at the University of Zielona Góra, Poland. His research interests are in the area of measurement optimization for distributed parameter systems. He authored the book entitled Optimal Measurement Methods for Distributed Parameter System Identification (CRC Press, 2005). Other areas of his expertise include optimum experimental design, algorithmic optimal control, parallel computing, data analysis and machine learning.