Effects of operation parameters on performances of stratum ventilation for heating mode

Zhang, Sheng; Lin, Zhang; Ai, Zhengtao; Wang, Fenghao; Cheng, Yong; Huan, Chao

doi:10.1016/j.buildenv.2018.11.001

Cited by 79 publications

(33 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The PMV predicts the thermal sensation according to the difference between the actual heat flow from the body in a given environment and that required for the thermal neutrality 8 . It requires the inputs of four environmental parameters (indoor air temperature, mean radiant temperature, indoor air velocity, and relative humidity) and two occupant‐related parameters (metabolic rate and clothing insulation) 28,29 . These inputs have important effects on thermal comfort but have not been fully considered by the adaptive approach 5 .…”

Section: Introductionmentioning

confidence: 99%

Adaptive‐rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient

Zhang

2020

Indoor Air

Self Cite

View full text Add to dashboard Cite

Thermal adaptations, as feedbacks of occupants to physical stimuli, extend thermal comfort zone thereby reducing building energy consumption effectively. The rational approach models thermal comfort from the perspective of the body's heat balance, but is limited in explaining the thermal adaptations. The adaptive approach of modeling thermal comfort can fully account for the thermal adaptations, but ignores the body's heat balance. To improve thermal comfort prediction, this study proposes an adaptive‐rational thermal comfort model, that is, an adaptive predicted mean vote with a variable adaptive coefficient (termed as arPMV). By linearly linking the negative feedback effects of the thermal adaptations to the ambient temperature according to the adaptive approach, the variable adaptive coefficient is linearly related to the reciprocal of the ambient temperature with two constants. The variable adaptive coefficient is determined by explicitly quantifying the two constants as the functions of the predicted mean vote, thermal sensation vote, and ambient temperature. The proposed arPMV is validated for naturally ventilated, air‐conditioned, and mixed‐mode buildings, with the mean absolute error and the robustness of the thermal sensation prediction reduced by 24.8%‐83.5% and improved by 49.7%‐83.4%, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Adaptive‐rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient

Zhang

2020

Indoor Air

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, previous studies have mainly been focused on stratum ventilation for cooling, with little attention on stratum ventilation for heating [19]. In addition, stratum ventilation has potential for application to heating because of its high supply air velocity and its layout of return outlet(s), which makes it capable of avoiding short-circuiting [19,20]. However, owing to the effects of upward thermal buoyancy, the airflow pattern of stratum ventilation for heating is distinct from that of stratum ventilation for cooling [19].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, stratum ventilation has potential for application to heating because of its high supply air velocity and its layout of return outlet(s), which makes it capable of avoiding short-circuiting [19,20]. However, owing to the effects of upward thermal buoyancy, the airflow pattern of stratum ventilation for heating is distinct from that of stratum ventilation for cooling [19]. The proper operation of stratum ventilation for heating is more complicated than that for cooling.…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria performance optimization for operation of stratum ventilation under heating mode

Zhang

Lin

et al. 2019

Applied Energy

Self Cite

View full text Add to dashboard Cite

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

show abstract

“…A small thermal deviation denotes a more comfortable thermal environment. Energy efficiency is indicated by the heat removal efficiencies of the subzones (Equations 4 and 5) [10]. The heat removal efficiency is a widely used ventilation efficiency indicator, and a larger heat removal efficiency indicates a higher energy efficiency [10].…”

Section: Introductionmentioning

confidence: 99%

“…Energy efficiency is indicated by the heat removal efficiencies of the subzones (Equations 4 and 5) [10]. The heat removal efficiency is a widely used ventilation efficiency indicator, and a larger heat removal efficiency indicates a higher energy efficiency [10]. The heat removal efficiencies of the subzones can also be modelled by the supply air parameters and exit air temperature (i.e., gi in Figure 1), because the air temperatures of the subzones are functions of the supply air parameters and exit air temperature [7,8].…”

Section: Introductionmentioning

confidence: 99%

Subzone Control of Air Distribution to Improve Thermal Comfort and Energy Efficiency

Zhang¹,

Cheng

Shao

et al. 2019

E3S Web Conf.

Self Cite

View full text Add to dashboard Cite

The conventional method for air distribution (e.g., mixing ventilation and stratum ventilation) controls the averaged thermal condition in the occupied zone to satisfy the averaged thermal preference of a group of occupants. However, since the thermal environment cannot be absolutely uniform, the microclimates of occupants can be distinct from the averaged thermal condition of the occupied zone. Moreover, the thermal preferences of occupants are well recognized to be diversified beyond the averaged value. Thus, the conventional method is unable to ensure thermal comfort and risks energy wastage because of overcooling. The method proposed by this study divides the occupied zone into several subzones, and determines the supply air parameters to optimize the overall performance regarding thermal comfort and energy efficiency of the subzones using the multi-criteria decision-making technique. Thermal comfort is indicated by the thermal deviation of the achieved thermal conditions of the subzones from the respective thermal preferences, and energy efficiency is indicated by the heat removal efficiencies of the subzones. Case studies based on experiments of stratum ventilation have demonstrated the effectiveness of the method proposed. Results show that the method proposed achieves thermal comfort for each subzone, and improves the overall performance by 2.1% to 31.0%.

show abstract

Effects of operation parameters on performances of stratum ventilation for heating mode

Cited by 79 publications

References 47 publications

Adaptive‐rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient

Adaptive‐rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient

Multi-criteria performance optimization for operation of stratum ventilation under heating mode

Subzone Control of Air Distribution to Improve Thermal Comfort and Energy Efficiency

Contact Info

Product

Resources

About