Abstract
Natural ventilation is often used as a passive technology to reduce building energy consumption. To leverage the rule-based natural ventilation control to more advanced control at multiple spatial scales, mathematical modeling is needed to calculate the real-time ventilation rate, indoor air temperatures, and velocities at high spatial resolution. This study aims to develop a real-time mathematical modeling framework based on computational fluid dynamics (CFD). The real-time concept is implemented by using real-time sensor data, e.g., wall surface temperatures as boundary conditions, while data assimilation is employed to implement real-time self-calibration. The proof of concept is demonstrated by a case study using synthetic data. The results show that the modeling framework can adequately predict real-time ventilation rates and indoor air temperatures. The data assimilation method can nudge the simulated air velocities toward the observed values to continuously calibrate the model. The real-time CFD modeling framework will be further tested by the real-time sensor data once building construction is fully completed.
Highlights
Building energy consumption consists of a large share of total global energy use
The innovation of the concept of real-time computational fluid dynamics (CFD) lies in two critical components: the real-time boundary conditions provided by sensors and real-time self-calibration through data assimilation of measured air velocities
This paper develops a real-time modeling framework to provide ventilation rates, indoor air temperatures, velocities at high spatial resolutions
Summary
Building energy consumption consists of a large share of total global energy use. Major reductions in fossil fuel use urgently challenge architects and engineers to improve overall building energy use and efficiency [1]. The state-of-art rule-based strategy fails tofails control natural ventilation at multiple for the zone. The state-of-art rule-based strategy to control natural ventilation at spatial scales, e.g., from occupant zone to the whole building, due to the limited number and location multiple spatial scales, e.g., from occupant zone to the whole building, due to the limited number of sensors [5,6]. The air speed can be monitored in a room, is replace natural ventilation rate to supplement the feedback parameters. The occupied might outside provide the misleading to windows ventilation rate, The air speedzone measured occupiedfeedback zone might provideoperation. MisleadingNatural feedback to windows local air temperature, and velocity at a higher and spatial resolution are needed leverage the operation.
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