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Chan-cheng Chen - One of the best experts on this subject based on the ideXlab platform.

  • Autoignition Temperature Data for Isopropyl Chloride, Butyl Chloride, Isobutyl Chloride, Pentyl Chloride, Pentyl Bromide, Chlorocyclohexane, and Benzoyl Chloride
    Industrial & Engineering Chemistry Research, 2013
    Co-Authors: Chen-peng Chen, Chan-cheng Chen, Tsung-han Han
    Abstract:

    Autoignition temperature (AIT) is indispensable information for safe handling and operation of Flammable Material. Typical applications of AIT in industry include classification of explosion-proof electric equipment and assessment of risk for potential leakage of hazardous chemical. Despite of its significance, in different data compilations, the discrepancies in reported AIT are appreciable, and an emergent need exists for investigating AIT of chemical substances through experimental approach before this information may be reliably attempted for industrial application. In this study the AITs of seven halogenated compounds were measured in compliance with the ASTM E659 test method. The AIT and ignition delay time determined from experiment for isopropyl chloride, butyl chloride, isobutyl chloride, pentyl chloride, pentyl bromide, chlorocyclohexane, and benzoyl chloride were (493.1 ± 9.9) °C/259.5 s, (244.0 ± 4.9) °C/35.9 s, (438.8 ± 8.8) °C/7.2 s, (252.0 ± 5.1) °C/58.0 s, (245.0 ± 4.9) °C/103.8 s, (255.8 ...

  • 2012 International Symposium on Safety Science and Technology A model for predicting the auto-ignition temperature using quantitative structure property relationship approach
    2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

  • A Model for Predicting the Auto-ignition Temperature using Quantitative Structure Property Relationship Approach
    Procedia Engineering, 2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    Abstract While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

Horng-jang Liaw - One of the best experts on this subject based on the ideXlab platform.

  • 2012 International Symposium on Safety Science and Technology A model for predicting the auto-ignition temperature using quantitative structure property relationship approach
    2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

  • A Model for Predicting the Auto-ignition Temperature using Quantitative Structure Property Relationship Approach
    Procedia Engineering, 2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    Abstract While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

Serge Bourbigot - One of the best experts on this subject based on the ideXlab platform.

  • Fire behavior of simulated low voltage intumescent cables with and without electric current
    Journal of Fire Sciences, 2017
    Co-Authors: Johan Sarazin, Pierre Bachelet, Serge Bourbigot
    Abstract:

    Many circumstances can lead to an electrical fire. It is then helpful to reproduce those circumstances in laboratory conditions to duplicate fire scenarios in order to increase knowledge and to develop safer and flame-retarded Materials and electrical systems. Our approach was to develop specific bench scale tests. The mass loss cone calorimeter coupled with Fourier transform infrared was used to mimic a fire scenario on simulated low voltage cable (flame-retarded polymer molded around copper wire) and to characterize the gas phase. The electric current creates an additional heating condition (Joule effect) which can modify the decomposition of the Flammable Material (e.g. the cable jacket made in thermoplastic), and so its fire behavior in case of fire. It is the reason why we performed the experiments mimicking different fire scenarios with and without electric current. Specific test was also developed to investigate the flame spread and the delamination of the polymer around the wire. The bench scale t...

  • Fire behavior of simulated low voltage intumescent cables with and without electric current
    Journal of Fire Sciences, 2017
    Co-Authors: Johan Sarazin, Pierre Bachelet, Serge Bourbigot
    Abstract:

    Many circumstances can lead to an electrical fire. It is then helpful to reproduce those circumstances in laboratory conditions to duplicate fire scenarios in order to increase knowledge and to develop safer and flame-retarded Materials and electrical systems. Our approach was to develop specific bench scale tests. The mass loss cone calorimeter coupled with Fourier transform infrared was used to mimic a fire scenario on simulated low voltage cable (flame-retarded polymer molded around copper wire) and to characterize the gas phase. The electric current creates an additional heating condition (Joule effect) which can modify the decomposition of the Flammable Material (e.g. the cable jacket made in thermoplastic), and so its fire behavior in case of fire. It is the reason why we performed the experiments mimicking different fire scenarios with and without electric current. Specific test was also developed to investigate the flame spread and the delamination of the polymer around the wire. The bench scale tests presented in this article were applied on intumescent polymers (ethylene-vinyl acetate containing commercial intumescent additive). The results were discussed with a special emphasis on the influence of electric current on the fire behavior.

Fang-yi Tsai - One of the best experts on this subject based on the ideXlab platform.

  • 2012 International Symposium on Safety Science and Technology A model for predicting the auto-ignition temperature using quantitative structure property relationship approach
    2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

  • A Model for Predicting the Auto-ignition Temperature using Quantitative Structure Property Relationship Approach
    Procedia Engineering, 2012
    Co-Authors: Fang-yi Tsai, Chan-cheng Chen, Horng-jang Liaw
    Abstract:

    Abstract While Flammable Materials are operated in process industries, the electric equipments should be explosion-proof to reduce the possibility of a fire or an explosion. Auto-ignition temperature (AIT) of a Flammable Material is the primary characteristic in determining the specifications of these explosion-proof equipments. However, due to limitations on experiments, the AIT of a compound reported in different data compilations is very diverse, and the difference between different compilations was found to be higher than 300 K in many cases. Thus, an effective method to predict the AIT of Flammable Materials is indispensible in this regard. In this study, a model to predict the AIT of organic compounds is built by using the quantitative structure property relationship (QSPR) approach. This model is built from a set of 820 organic compounds, which are collected from the DIPPR database supported by American Institute of Chemical Engineer. This model is of four molecular descriptors: mean electrotopological state, the aromatic ratio, rotatable bond fraction, and atom-centered fragments. It is found that the R value of the proposed model is 0.900, the average error in percentage is of 6.0%, and the average absolute error is about 36.0 K. While comparing with other works in the literature, this model is built from the largest data set and gives satisfactory performance. As compared with the known experimental errors in measuring the AIT, the proposed model also offers a reasonable estimate of the AIT. Thus, the proposed model can estimate the AIT of a compound for which its AIT is as yet not readily available within a reasonable accuracy.

Johan Sarazin - One of the best experts on this subject based on the ideXlab platform.

  • Fire behavior of simulated low voltage intumescent cables with and without electric current
    Journal of Fire Sciences, 2017
    Co-Authors: Johan Sarazin, Pierre Bachelet, Serge Bourbigot
    Abstract:

    Many circumstances can lead to an electrical fire. It is then helpful to reproduce those circumstances in laboratory conditions to duplicate fire scenarios in order to increase knowledge and to develop safer and flame-retarded Materials and electrical systems. Our approach was to develop specific bench scale tests. The mass loss cone calorimeter coupled with Fourier transform infrared was used to mimic a fire scenario on simulated low voltage cable (flame-retarded polymer molded around copper wire) and to characterize the gas phase. The electric current creates an additional heating condition (Joule effect) which can modify the decomposition of the Flammable Material (e.g. the cable jacket made in thermoplastic), and so its fire behavior in case of fire. It is the reason why we performed the experiments mimicking different fire scenarios with and without electric current. Specific test was also developed to investigate the flame spread and the delamination of the polymer around the wire. The bench scale t...

  • Fire behavior of simulated low voltage intumescent cables with and without electric current
    Journal of Fire Sciences, 2017
    Co-Authors: Johan Sarazin, Pierre Bachelet, Serge Bourbigot
    Abstract:

    Many circumstances can lead to an electrical fire. It is then helpful to reproduce those circumstances in laboratory conditions to duplicate fire scenarios in order to increase knowledge and to develop safer and flame-retarded Materials and electrical systems. Our approach was to develop specific bench scale tests. The mass loss cone calorimeter coupled with Fourier transform infrared was used to mimic a fire scenario on simulated low voltage cable (flame-retarded polymer molded around copper wire) and to characterize the gas phase. The electric current creates an additional heating condition (Joule effect) which can modify the decomposition of the Flammable Material (e.g. the cable jacket made in thermoplastic), and so its fire behavior in case of fire. It is the reason why we performed the experiments mimicking different fire scenarios with and without electric current. Specific test was also developed to investigate the flame spread and the delamination of the polymer around the wire. The bench scale tests presented in this article were applied on intumescent polymers (ethylene-vinyl acetate containing commercial intumescent additive). The results were discussed with a special emphasis on the influence of electric current on the fire behavior.