A computational research of radiative-convective energy transport in large-scale enclosure with a heat-generating heater under normal room conditions has been conducted.The heater(underfloor heating system)is located ...A computational research of radiative-convective energy transport in large-scale enclosure with a heat-generating heater under normal room conditions has been conducted.The heater(underfloor heating system)is located at the bottom of the room.Employing the Boussinesq assumption,the control equations have been solved contemporaneously to receive both the velocity fields and temperature patterns.To generate the systems of linear equations using vorticity and stream function,the finite difference technique has been employed.The developed convective-radiative model has been validated through a comparison with several problems.The influence of heater size and location,internal surfaces emissivity from 0 to 1,Ostrogradsky number for a wide range from 0 to 5 on Nusselt numbers and both stream function and temperature distributions has been investigated.The results demonstrate that the influence of the thermal radiation on total heat transfer increases with surface emissivity of walls and heater surfaces.展开更多
Since the coronavirus disease 2019,the extended time indoors makes people more concerned about indoor air quality,while the increased ventilation in seeks of reducing infection probability has increased the energy usa...Since the coronavirus disease 2019,the extended time indoors makes people more concerned about indoor air quality,while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating,ventilation,and air-conditioning systems.In this study,to represent the dynamics of indoor temperature and air quality,a coupled grey-box model is developed.The model is identified and validated using a data-driven approach and real-time measured data of a campus office.To manage building energy usage and indoor air quality,a model predictive control strategy is proposed and developed.The simulation study demonstrated 18.92%energy saving while maintaining good indoor air quality at the testing site.Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones.The results showed 20%–40%energy saving in general while maintaining a predetermined indoor air quality setpoint.Although the infection risk is increased due to the reduced ventilation rate,it is still less than the suggested threshold(2%)in general.展开更多
基金supported by the Russian Science Foundation(No.19-79-00296).
文摘A computational research of radiative-convective energy transport in large-scale enclosure with a heat-generating heater under normal room conditions has been conducted.The heater(underfloor heating system)is located at the bottom of the room.Employing the Boussinesq assumption,the control equations have been solved contemporaneously to receive both the velocity fields and temperature patterns.To generate the systems of linear equations using vorticity and stream function,the finite difference technique has been employed.The developed convective-radiative model has been validated through a comparison with several problems.The influence of heater size and location,internal surfaces emissivity from 0 to 1,Ostrogradsky number for a wide range from 0 to 5 on Nusselt numbers and both stream function and temperature distributions has been investigated.The results demonstrate that the influence of the thermal radiation on total heat transfer increases with surface emissivity of walls and heater surfaces.
基金This research was jointly sponsored by Honeywell International Inc.and Syracuse University.
文摘Since the coronavirus disease 2019,the extended time indoors makes people more concerned about indoor air quality,while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating,ventilation,and air-conditioning systems.In this study,to represent the dynamics of indoor temperature and air quality,a coupled grey-box model is developed.The model is identified and validated using a data-driven approach and real-time measured data of a campus office.To manage building energy usage and indoor air quality,a model predictive control strategy is proposed and developed.The simulation study demonstrated 18.92%energy saving while maintaining good indoor air quality at the testing site.Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones.The results showed 20%–40%energy saving in general while maintaining a predetermined indoor air quality setpoint.Although the infection risk is increased due to the reduced ventilation rate,it is still less than the suggested threshold(2%)in general.
