Browsing by Author "Salameh, Muna"

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    From Heritage to Sustainability: The Future of the Past in the Hot Arid Climate of the UAE
    (MDPI, 2023) Salameh, Muna; Touqan, Basim
    Achieving future energy objectives and promoting social, economic, and environmental sustainability can be inspired by heritage and historic structures, which make up a sizeable component of the existing building industry. Heritage architecture and urban sites are known for their capability of positive interaction with the climate to provide better thermal conditions, beside their capability of strengthening cultural identity and improving the economic sector for the related sites. Thus, the main purpose of this research is to highlight the positive sustainable effects (social, economic and environmental) for a proposal of conserving and reconstructing a vernacular heritage architecture site in the hot arid climate in the UAE. The research used a qualitative methodology based on multicriteria descriptive schemes beside ENVI-met software. The research’s findings presented the capability of the conserved heritage area to strengthen the social and cultural identity and improve the economic sector. Moreover, the results demonstrated that the conserved heritage district had a better microclimate and predicted mean vote for outdoor thermal comfort compared to the basic case heritage district prior to rehabilitation and another modern district. The conclusion promotes heritage conservation in hot arid climates and encourages the preservation of vernacular architecture and traditional sites to achieve the sustainable goals for creating sustainable cities that can mitigate climate change.
  • No Thumbnail Available
    Item
    HVAC multivariable system modelling and control
    (Sage journals, 2022) Touqan, Basim; Abdul-Ameer, Alaa; Salameh, Muna
    Heating, Ventilation and Air Conditioning (HVAC) is a multivariable process where any alteration with one system input affects most or all of the system’s outputs simultaneously. Owing to its comprehensiveness, a readily derived multivariable HVAC mathematical model is selected for this work, mainly a hybrid distributed-lumped parameters model. As the transfer function matrix was not established in the selected HVAC model, it was exclusively developed in this study, using the time domain graphical responses of the chosen model. Based on the developed transfer function matrix, a conceptual two-step approach was followed to control HVAC model performance. The first was decoupling the interactions that affect all the system outputs, and the second was designing proper PID controllers for each decoupled loop similar to those used for single input single output (SISO) systems. A direct Nyquist Array (DNA) multivariable control strategy was used for this purpose and successfully decoupled the HVAC system into three separate (SISO) loops. Three PID controllers afterwards were applied for each decoupled loop. The results showed quite decoupled system outputs with a minor coupling percentage so that any change in a system input only affected the corresponding system output. The output responses are also underdamped with almost zero steady-state error confirming the effectiveness of the selected PID parameters. The values of steady-state responses are obtained in (10– 15) s compared with (200–600) s of open-loop response time. However, various overshoot percentages in the responses are encountered but are relatively small, with a short settling time, so they don’t affect the thermal comfort of the ventilated volume. System stability using the Nyquist criterion has also been examined and found to satisfy the criterion. The multivariable DNA control technique and the SISO closed-loop PID controllers have shown the capability to suppress external disturbances and restore the system to its original functional steady-state values.
  • No Thumbnail Available
    Item
    HVAC multivariable system modelling and control
    (2022) Touqan, Basim; Abdul-Ameer, Alaa; Salameh, Muna
    Heating, Ventilation and Air Conditioning (HVAC) is a multivariable process where any alteration with one system input affects most or all of the system’s outputs simultaneously. Owing to its comprehensiveness, a readily derived multivariable HVAC mathematical model is selected for this work, mainly a hybrid distributed-lumped parameters model. As the transfer function matrix was not established in the selected HVAC model, it was exclusively developed in this study, using the time domain graphical responses of the chosen model. Based on the developed transfer function matrix, a conceptual two-step approach was followed to control HVAC model performance. The first was decoupling the interactions that affect all the system outputs, and the second was designing proper PID controllers for each decoupled loop similar to those used for single input single output (SISO) systems. A direct Nyquist Array (DNA) multivariable control strategy was used for this purpose and successfully decoupled the HVAC system into three separate (SISO) loops. Three PID controllers afterwards were applied for each decoupled loop. The results showed quite decoupled system outputs with a minor coupling percentage so that any change in a system input only affected the corresponding system output. The output responses are also underdamped with almost zero steady-state error confirming the effectiveness of the selected PID parameters. The values of steady-state responses are obtained in (10– 15) s compared with (200–600) s of open-loop response time. However, various overshoot percentages in the responses are encountered but are relatively small, with a short settling time, so they don’t affect the thermal comfort of the ventilated volume. System stability using the Nyquist criterion has also been examined and found to satisfy the criterion. The multivariable DNA control technique and the SISO closed-loop PID controllers have shown the capability to suppress external disturbances and restore the system to its original functional steady-state values.