Sunday, January 24, 2016: 11:00 AM-12:30 PM
Cutting-Edge Technologies
Chair:
Atila Novoselac, Ph.D., University of Texas at Austin
Technical Committee: 04.10 Indoor Environmental Modeling
Computational fluid dynamics (CFD) is a powerful modeling tool, widely applied in HVAC design. However, it could be computationally expensive and complex, and new techniques and models are needed for application in standard design practice. The building modeling community has been developing methods that are fast and accurate enough to be used in early stage of the design or even in real time control systems. This seminar presents application of coarse grid CFD, fast fluid dynamics (FFD) and reduced order modeling (ROM) on real problems, such as air distribution in buildings and data centers. It considers speed improvement and accuracy.
1 Coarse Grid CFD for Fast Modeling of Indoor Environments: Why NOT?
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John Zhai, Ph.D., University of Colorado |
Large-scale CFD analysis requires extended time and computing resource, and in recent years reduced order modeling techniques are developed. Among many of these techniques, proper orthogonal decomposition (POD) stands out as a preferable method. POD allows the processing of large amounts of high-dimensional data with the aim of obtaining low-dimensional descriptions that capture much of the analyzed phenomena. Here, we discuss how POD is used to overcome the issues addressed from the traditional CFD method and show how POD can be used for data center analyses. Both CFD and POD methods are compared in terms of running time and accuracy.
2 Reduced Order Modeling of Airflow and Thermal Fields in a Data Center
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Cheng-Xian Lin, Ph.D., Florida International University |
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Long Phan, Florida International University |
It is challenging to properly control the ventilation in a complex built environment, such as a data center room and aircraft cabin. The ventilation effects depend on both an indoor airflow distribution and HVAC system. This presentation introduces a coupled simulation of three-dimensional indoor airflow and building HVAC system. The indoor airflow is simulated by a fast fluid dynamics program, while the HVAC and control system is modeled with a Modelica language. We will introduce the principle of the coupled simulation and demonstrate its usage for the ventilation control.
3 Faster and Simpler CFD for Data Center Applications
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James W. VanGilder, P.E., Schneider Electric |
Traditional CFD methods have proven useful, though slow and complex, for data center applications. Alternative, simpler technologies are becoming available which trade varying degrees of accuracy for speed and simplicity. Potential flow modeling (PFM) offers nearly real-time steady-state modeling for practical applications and is best suited for estimates early in the data center design cycle. The fast fluid dynamics (FFD) approach includes all of the physics of traditional CFD methods while being simpler to code and delivering an order of magnitude speed improvement for transient applications. This presentation discusses PFM and FFD in the context of data center applications.
4 A Fast Coupled Simulation of 3D Indoor Airflow Motion and HVAC System for Ventilation Control of Complex Environment
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Wangda Zuo, Ph.D., University of Miami |
Major CFD computational penalty is caused by high requirement on spatial mesh resolution and this presentation shows the theory and practical feasibility of using coarse-grid CFD. It utilizes numerical viscosity induced by coarse CFD grid, coupled with simplest turbulence model. Case studies show that a uniform coarse grid can be applied, along with a constant turbulence viscosity model, to reasonably predict general airflow patterns. Such predictions is not as precise as fine-grid CFDs, but the accuracy is acceptable for indoor environment study at an early stage of a project. The computing speed is about 100 times faster than fine-grid CFD.