Modélisation et validation expérimentale d'un modèle vibroacoustique d'un silencieux d'une motoneige

Ce mémoire traite la modélisation et la validation expérimentale du bruit d’un silencieux de motoneige. La première phase du projet consiste à modéliser numériquement le système d’échappement avec les méthodes numériques suivantes : éléments finis et éléments finis de frontière, afin d’évaluer ses performances acoustiques : perte par transmission, bruit de bouche et bruit de paroi. Une deuxième phase du projet consiste à valider expérimentalement les performances acoustiques calculées numériquement. La dernière phase du projet se consacrera à une étude paramétrique expérimentale d’un silencieux sur banc moteur. En conclusion, les résultats des modèles numériques mis en œuvre concordent bien avec les résultats expérimentaux. Cependant, les aspects non linéaires rencontrés à la dernière phase du projet n’ont pas été étudiés davantage.

A framework for analyzing system intelligence of the building control system : a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.