Building Ventilation

Buildings use roughly 40% of the total energy used in the United States each year (approximately 40 quads of energy).  Each year the building sector spends about $400 billion to power commercial and residential buildings, which corresponds to about 70% of the electrical usage in the United States.

Due to these staggering numbers the US government has made energy conservation a high priority. Researchers, engineers, and designers push to develop and utilize more energy efficient technologies. Although saving energy and making the systems utilized in buildings more efficient is a priority, the comfort of the occupants that occupy these buildings should not be sacrifices. Simulations can be a powerful tool to help identify problematic regions of existing buildings, and aid in the design and optimization of the air distribution system in energy efficient newly constructed buildings.


High Performance Computing (HPC) for Building Ventilation Systems

StreamLinesSmallComputational Fluid Dynamics (CFD) simulations are an excellent tool to obtain spatially resolved thermal comfort metrics along with energy performance metrics.

Contributors

  • Anthony D. Fontanini
  • Songzhe Wu
  • Mirka Deza

 Computationally Driven Window Pane Design

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Computational Fluid Dynamics (CFD) simulations are an excellent tool to obtain spatially resolved thermal comfort metrics along with energy performance metrics.

 

 

 


Uncertainty Quantification

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When utilizing forward based energy simulations and network airflow models for prediction of thermal performance, a deterministic approach to modeling are used. The model parameters are determined to be a single value, which produces a single value or time series of the quantities of interest. However, some model parameters can fluctuate during the prediction period like occupancy, lighting, wind speed for natural ventilation, and internal heat sources. In cases like these, utilizing probabilistic methods for the network airflow model or the energy simulation provide better insight to the dynamics of the building. The results provide a variance of the quantities of interest, displays the best and worse case performance, and metrics of robustness for the building design.


 Variational Multiscale Implementation

interlockHouseSmallImplementing a Finite Element Method, and investigatign Variational Multi-Scale (VMS) Residual Based theory for Navier-Stoke with energy equation based on our own FEM library. The implementation was validated by a benchmark Rayleigh benard problem. Recently, I am working on further implementation for a more complex geometry (interlock house project).