Performance assessment of a ductless personalized ventilation system using a validated CFD model

Abstract

The aim of this study is twofold: to validate a computational fluid dynamics (CFD) model, and then to use the validated model to evaluate the performance of a ductless personalized ventilation (DPV) system. To validate the numerical model, a series of measurements was conducted in a climate chamber equipped with a thermal manikin. Various turbulence models, settings, and options were tested; simulation results were compared to the measured data to determine the turbulence model and solver settings that achieve the best agreement between the measured and simulated values. Subsequently, the validated CFD model was then used to evaluate the thermal environment and indoor air quality in a room equipped with a ductless personalized ventilation system combined with displacement ventilation. Results from the numerical model were then used to quantify thermal sensation and comfort using UC Berkeley thermal comfort model.

Simulating the human body's microclimate using automatic coupling of CFD and an advanced thermoregulation model

“…As a result of its comprehensive components, the UCB model has received much attention . It was used by many researchers to evaluate thermal comfort due to its comprehensive method of calculation …”

A Review of CFD Analysis Methods for Personalized Ventilation (PV) in Indoor Built Environments

“…Similarly, the results of SKE and RNG are in good agreement with experimental data, while performance of the k-ω group models does not agree well with experiments in forced and mixed convection cases [135]. Another study validated a conventional round nozzle delivering fresh air directly to an occupant's face using STK, RKE, and RNG [118]. RKE achieved the best results based on the air temperature, ventilation effectiveness index, and air velocity between the PV outlet and the occupant's face.…”

“…Note that several PV types included in relatively few articles are not presented in this figure and can be found in the references. These less popular PV types include ductless personalized ventilation (DPV) [118], local exhaust ventilation for offices (LEVO) [111,112], movable slot diffuser plate (MSDP) [82], natural personalized ventilation (NPV) [83], robotic personal air conditioning (RPAC) [107], targeted personalized ventilation (TPV) [122], and wide-cover personalized ventilation (WCPV) [101]. [29,37], (c) CMPV [88,89] and DMPV [120], (d) DF and CF [103,104].…”

“…Honeycomb and hexahedral grids were used for the majority of PV studies in Star CCM+ [39,115]. The total grid number reached 5.77 million and 6.5 million, representing 0.27 million grids and 0.20 million grids per cubic meter, respectively, in two recent studies [118,120]. However, two early studies used only 1.81 million and 1.75 million grids, resulting in 0.12 million/m 3 and 0.11 million/m 3 , respectively [36,69].…”

“…Regarding thermal comfort involving air temperature, radiant temperature, air velocity, humidity, clothes insulation, and activity, it is recommended to consider all six factors for human response, e.g., by using an integrated thermal comfort model. A recent advanced thermal comfort (ATC) model [196][197][198] is widely accepted for assessing segmental/overall body thermal comfort and sensation using CFD simulation for PV studies [98,118]. A thermal comfort scale from −4 (very uncomfortable) to +4 (very comfortable), and thermal sensation scale from −4 (very cold) to +4 (very hot) are utilized.…”