arXiv subjects

Thierry Alex Mara

Publications and source records attributed to Thierry Alex Mara.

5 recordsLinked to original sources

arXiv2012

Black box modelling of HVAC system : improving the performances of neural networks

This paper deals with neural networks modelling of HVAC systems. In order to increase the neural networks performances, a method based on sensitivity analysis is applied. The same technique is also used to compute the relevance of each input. To avoid the prediction errors in dry coil conditions, a metamodel for each capacity is derived from the neural networks. The regression coefficients of the polynomial forms are identified through the use of spectral analysis. These methods based on sensitivity and spectral analysis lead to an optimized neural network model, as regard to its architecture and predictions.

cs.NE↗

arXiv2012

Elaboration of a new tool for weather data sequences generation

This paper deals about the presentation of a new software RUNEOLE used to provide weather data in buildings physics. RUNEOLE associates three modules leading to the description, the modelling and the generation of weather data. The first module is dedicated to the description of each climatic variable included in the database. Graphic representation is possible (with histograms for example). Mathematical tools used to compare statistical distributions, determine daily characteristic evolutions, find typical days, and the correlations between the different climatic variables have been elaborated in the second module. Artificial weather datafiles adapted to different simulation codes are available at the issue of the third module. This tool can then be used in HVAC system evaluation, or in the study of thermal comfort. The studied buildings can then be tested under different thermal, aeraulic, and radiative solicitations, leading to a best understanding of their behaviour for example in humid climates.

cs.CE↗

arXiv2012

Use of BESTEST procedure to improve a building thermal simulation program

Validation of building energy simulation programs is of major interest to both users and modellers. To achieve such a task, it is essential to apply a methodology based on a priori test and empirical validation. A priori test consists in verifying that models embedded in a program and their implementation are correct. this should be achieved before carrying out experiments. The aim of this report is to present results from the application of the BESTEST procedure to our code. We will emphasise the way it allows to find bugs in our program and also how it permits to qualify models of heat transfer by conduction

cs.CE↗

arXiv2012

Parametric sensitivity analysis of a test cell thermal model using spectral analysis

The paper deals with an empirical validation of a building thermal model. We put the emphasis on sensitivity analysis and on research of inputs/residual correlation to improve our model. In this article, we apply a sensitivity analysis technique in the frequency domain to point out the more important parameters of the model. Then, we compare measured and predicted data of indoor dry-air temperature. When the model is not accurate enough, recourse to time-frequency analysis is of great help to identify the inputs responsible for the major part of error. In our approach, two samples of experimental data are required. The first one is used to calibrate our model the second one to really validate the optimized model.

physics.data-an↗

arXiv2012

A Comparison between CODYRUN and TRNSYS, simulation models for thermal buildings behaviour

Simulation codes of thermal behaviour could significantly improve housing construction design. Among the existing software, CODYRUN and TRNSYS are calculations codes of different conceptions. CODYRUN is exclusively dedicated to housing thermal behaviour, whereas TRNSYS is more generally used on any thermal system. The purpose of this article is to compare these two instruments in two different conditions . We will first modelize a mono-zone test cell, and analyse the results by means of signal treatment methods. Then, we will modelize a real case of multi-zone housing, representative of housing in wet tropical climates. We could so evaluate influences of meteorological and building description data on model errors.

cs.CE↗