Journal Articles

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https://hdl.handle.net/20.500.14170/301

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Browsing Journal Articles by Author "Abdulnasser Nabil Abdullah"
  • Publication
    Correction model for metal oxide sensor drift caused by ambient temperature and humidity
    ( 2022)
    Abdulnasser Nabil Abdullah
    ;
    Kamarulzaman Kamarudin
    ;
    Latifah Munirah Kamarudin
    ;
    Abdul Hamid Adom
    ;
    Syed Muhammad Mamduh Syed Zakaria
    ;
    Zaffry Hadi Mohd Juffry
    ;
    Victor Hernandez Bennetts
    For decades, Metal oxide (MOX) gas sensors have been commercially available and used in various applications such as the Smart City, gas monitoring, and safety due to advantages such as high sensitivity, a high detection range, fast reaction time, and cost-effectiveness. However, several factors affect the sensing ability of MOX gas sensors. This article presents the results of a study on the cross-sensitivity of MOX gas sensors toward ambient temperature and humidity. A gas sensor array consisting of temperature and humidity sensors and four different MOX gas sensors (MiCS-5524, GM-402B, GM-502B, and MiCS-6814) was developed. The sensors were subjected to various relative gas concentrations, temperatures (from 16 °C to 30 °C), and humidity levels (from 75% to 45%), representing a typical indoor environment. The results proved that the gas sensor responses were significantly affected by the temperature and humidity. The increased temperature and humidity levels led to a decreased response for all sensors, except for MiCS-6814, which showed the opposite response. Hence, this work proposed regression models for each sensor, which can correct the gas sensor response drift caused by the ambient temperature and humidity variations. The models were validated, and the standard deviations of the corrected sensor response were found to be 1.66 kΩ, 13.17 kΩ, 29.67 kΩ, and 0.12 kΩ, respectively. These values are much smaller compared to the raw sensor response (i.e., 18.22, 24.33 kΩ, 95.18 kΩ, and 2.99 kΩ), indicating that the model provided a more stable output and minimised the drift. Overall, the results also proved that the models can be used for MOX gas sensors employed in the training process, as well as for other sets of gas sensors.
      1  11
  • Publication
    Correction Model for Metal Oxide Sensor Drift Caused by Ambient Temperature and Humidity
    ( 2022-05-01)
    Abdulnasser Nabil Abdullah
    ;
    Kamarulzaman Kamarudin
    ;
    Latifah Munirah Kamarudin
    ;
    Abdul Hamid Adom
    ;
    Syed Muhammad Mamduh Syed Zakaria
    ;
    Zaffry Hadi Mohd Juffry
    ;
    Bennetts V.H.
    For decades, Metal oxide (MOX) gas sensors have been commercially available and used in various applications such as the Smart City, gas monitoring, and safety due to advantages such as high sensitivity, a high detection range, fast reaction time, and cost-effectiveness. However, several factors affect the sensing ability of MOX gas sensors. This article presents the results of a study on the cross-sensitivity of MOX gas sensors toward ambient temperature and humidity. A gas sensor array consisting of temperature and humidity sensors and four different MOX gas sensors (MiCS-5524, GM-402B, GM-502B, and MiCS-6814) was developed. The sensors were subjected to various relative gas concentrations, temperatures (from 16◦C to 30◦C), and humidity levels (from 75% to 45%), representing a typical indoor environment. The results proved that the gas sensor responses were significantly affected by the temperature and humidity. The increased temperature and humidity levels led to a decreased response for all sensors, except for MiCS-6814, which showed the opposite response. Hence, this work proposed regression models for each sensor, which can correct the gas sensor response drift caused by the ambient temperature and humidity variations. The models were validated, and the standard deviations of the corrected sensor response were found to be 1.66 kΩ, 13.17 kΩ, 29.67 kΩ, and 0.12 kΩ, respectively. These values are much smaller compared to the raw sensor response (i.e., 18.22, 24.33 kΩ, 95.18 kΩ, and 2.99 kΩ), indicating that the model provided a more stable output and minimised the drift. Overall, the results also proved that the models can be used for MOX gas sensors employed in the training process, as well as for other sets of gas sensors.
      3  18
  • Publication
    Correction model for metal oxide sensor drift caused by ambient temperature and humidity
    ( 2022)
    Abdulnasser Nabil Abdullah
    ;
    Kamarulzaman Kamarudin
    ;
    Latifah Munirah Kamarudin
    ;
    Abdul Hamid Adom
    ;
    Syed Muhammad Mamduh Syed Zakaria
    ;
    Zaffry Hadi Mohd Juffry
    ;
    Victor Hernandez Bennetts
    For decades, Metal oxide (MOX) gas sensors have been commercially available and used in various applications such as the Smart City, gas monitoring, and safety due to advantages such as high sensitivity, a high detection range, fast reaction time, and cost-effectiveness. However, several factors affect the sensing ability of MOX gas sensors. This article presents the results of a study on the cross-sensitivity of MOX gas sensors toward ambient temperature and humidity. A gas sensor array consisting of temperature and humidity sensors and four different MOX gas sensors (MiCS-5524, GM-402B, GM-502B, and MiCS-6814) was developed. The sensors were subjected to various relative gas concentrations, temperatures (from 16 °C to 30 °C), and humidity levels (from 75% to 45%), representing a typical indoor environment. The results proved that the gas sensor responses were significantly affected by the temperature and humidity. The increased temperature and humidity levels led to a decreased response for all sensors, except for MiCS-6814, which showed the opposite response. Hence, this work proposed regression models for each sensor, which can correct the gas sensor response drift caused by the ambient temperature and humidity variations. The models were validated, and the standard deviations of the corrected sensor response were found to be 1.66 kΩ, 13.17 kΩ, 29.67 kΩ, and 0.12 kΩ, respectively. These values are much smaller compared to the raw sensor response (i.e., 18.22, 24.33 kΩ, 95.18 kΩ, and 2.99 kΩ), indicating that the model provided a more stable output and minimised the drift. Overall, the results also proved that the models can be used for MOX gas sensors employed in the training process, as well as for other sets of gas sensors.
      11  12
  • Publication
    Theoretical and numerical study on the effect of ambient temperature towards gas dispersion in indoor environment using CFD approach
    (Semarak Ilmu Publishing, 2023)
    Zaffry Hadi Mohd Juffry
    ;
    Kamarulzaman Kamarudin
    ;
    Abdul Hamid Adom
    ;
    Muhammad Fahmi Miskon
    ;
    Abdulnasser Nabil Abdullah
    The usage of harmful chemical gas and natural gas has been increasing rapidly which increase the risk of gas leakage incident to occur especially in the indoor environment. It is important to learn the gas dispersal behavior in order to mitigate the casualty caused by gas leakage. In addition, one of the factors that contribute to the dispersion of gas is temperature. This paper focuses to study the role of ambient temperature toward gas dispersion in an indoor environment by looking at the theoretical and numerical knowledge of gas diffusion's relationship with temperature. Computational Fluid Dynamics (CFD) has been utilized to simulate gas dispersion at different ambient temperature levels in an indoor environment. This study released ethanol vapor to simulate gas dispersion at 5°C, 25°C, and 40°C of ambient temperature to observe the way gas distribute in the indoor environment. Both results from the theoretical calculation and simulation were compared. The result indicates that the gas diffusivity has an increment of 3.5% for every 5°C increment of the temperature. This causes the gas to diffuse rapidly in the warm air compared to the cool air. This paper also finds out that when the initial ambient temperature which is 5°C, was increased to 25°C and 40°C it causes the spread distance of the gas increased by 13.75% and 32.50% respectively.
      2  12