Research Article
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Year 2021, Volume 8, Issue 4, 279 - 285, 31.12.2021
https://doi.org/10.17350/HJSE19030000240

Abstract

References

  • Prugh, R.W. Life‐safety concerns in chemical plants. Process Safety Progress. 35(1) (2016) 18-25.
  • Cox, B.L., Carpenter, A.R., Ogle, R.A. Lessons learned from case studies of hazardous waste/chemical reactivity incidents. Process Safety Progress. 33(4) (2014) 395-98.
  • Morrison, D.T., Stern, M., Osorio‐Amado, C.H. Waste solvents to trash haulers: lessons learned from hazardous waste accidents. Process safety progress. 37(3) (2018) 427-41.
  • Ness, A., Gibson, R. Handling chemicals in small containers. Process safety progress. 24(4) (2005) 299-302.
  • Alexeev, S., Smirnov, V., Barbin, N., Alexeeva, D.Y. Evolution of the classification of flammable and combustible liquids in Russia. Process safety progress.37(2) (2018) 230-36.
  • DaCunha, S., Gerbaud, V., Shcherbakova, N., Liaw, H.J. Classification for ternary flash point mixtures diagrams regarding miscible flammable compounds. Fluid Phase Equilibria. 466 (2018) 110-23.
  • Stefanidou, M., Athanaselis, S., Spiliopoulou, C. Health impacts of fire smoke inhalation. Inhalation toxicology. 20(8) (2008) 761-66.
  • Purser, D.A., McAllister, J.L. Assessment of hazards to occupants from smoke, toxic gases, and heat. SFPE handbook of fire protection engineering. Springer; 2016. p. 2308-428.
  • Yuan, S., Zhang, Z., Sun, Y., Kwon, JS-I., Mashuga, C.V. Liquid flammability ratings predicted by machine learning considering aerosolization. Journal of hazardous materials. 386 (2020) 121640.
  • Yuan, W., Lv, W., Wang, H., Ma, Li, S. H. Performance prediction of suspension freeze crystallization for the treatment of liquid hazardous wastes via machine learning methods, Journal of Cleaner Production, (2021) 129629.
  • Yuan, Ji, C., Jiao, S., Huffman, Z., El-Halwagi, M., Wang, M.M., Q., Predicting flammability-leading properties for liquid aerosol safety via machine learning, Process Safety and Environmental Protection, 148 (2021) 1357-1366.
  • Jiao, Z., Ji, C., Yuan, S., Zhang, Z., Wang, Q. Development of machine learning based prediction models for hazardous properties of chemical mixtures, Journal of Loss Prevention in the Process Industries, 67 (2020) 104226.
  • Zhang, Z., Yuan, S., Yu, M., Mannan, M.S., Wang, Q., A hazard index for chemical logistic warehouses with modified flammability rating by machine learning methods, ACS Chemical Health & Safety, 27 (2020) 190-197.
  • Mahmodi, K., Mostafaei, M., Mirzaee-Ghaleh, E. Detection and classification of diesel-biodiesel blends by LDA, QDA and SVM approaches using an electronic nose. Fuel. 258 (2019) 116114.
  • Ji, C., Jiao, Z., Yuan, S., El-Halwagi, M.M., Wang, Q., Development of novel combustion risk index for flammable liquids based on unsupervised clustering algorithms, Journal of Loss Prevention in the Process Industries, 70 (2021) 104422
  • Li, Z., Haigh, A., Soutis, C., Gibson, A., Sloan, R. Microwaves sensor for wind turbine blade inspection. Applied Composite Materials. 24(2) (2017) 495-512.
  • Borisov, V., Karpenko, A. Using of the Michelson microwave interferometer for the measurement of permittivity of thin-layer materials. Russian journal of nondestructive testing. 37(8) (2001) 597-99.
  • Yurchenko, A.V., Novikov, A., Kitaeva, M.V. A resonator microwave sensor for measuring the parameters of Solar-quality silicon. Russian Journal of Nondestructive Testing. 48(2) (2012) 109-14.
  • Mathur, P., Thakur, A., Kurup, D.G. An artificial neural network-based non-destructive microwave technique for monitoring fluoride contamination in water. Journal of Electromagnetic Waves and Applications. 34(5) (2020) 612-22.
  • Turgul, V., Kale, I. Permittivity extraction of glucose solutions through artificial neural networks and non-invasive microwave glucose sensing. Sensors and Actuators A: Physical. 277 (2018) 65-72.
  • Sulaiman, N., Srisatit, S. Development of x-ray imaging technique for liquid screening at airport. AIP Conference Proceedings: AIP Publishing LLC; 2016. p. 030006.
  • Orachorn, P., Chankow, N., Srisatit, S. An Alternative Method for Screening Liquid in Bottles at Airports Using Low Energy X-ray Transmission Technique. Radiation environment and medicine: covering a broad scope of topics relevant to environmental and medical radiation research. 8(2) (2019) 77-84.
  • Chen, H., Hu, Z., Wang, P., Xu, W., Hou Y. Application of spectral droplet analysis method in flammable liquids identification. Paper presented at 2019 International Conference on Optical Instruments and Technology: Optical Sensors and Applications: International Society for Optics and Photonics, pp. 1143609, 2020.
  • Sun, L. Liquid dangerous goods detection based on electronic nose odor recognition technology. Paper presented at International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications: International Society for Optics and Photonics, pp. 890721, 2013.

A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions

Year 2021, Volume 8, Issue 4, 279 - 285, 31.12.2021
https://doi.org/10.17350/HJSE19030000240

Abstract

Strong liquid explosives were obtained by mixing some chemical liquids and these explosives were used in many terrorist attacks in crowded places such as airports, railway stations and shopping malls. They were also used to cause sabotage to facilities that produce, store or use hazardous chemicals in their processes. For this reason, it is very important to take the necessary measures to prevent sabotage and terrorist attacks that may occur in such places in order to ensure public and environmental safety. In this study, a machine learning based liquid control system that can be used in airports, railway stations and shopping malls as well as in places with high fire probability is proposed. The difference of the proposed system from traditional liquid scanner systems is that it can detect the hazardous liquid concentration in the solutions as well as the detection of pure flammable liquids. Linear Discriminant Analysis and Quadratic Discriminant Analysis are used as classifiers and the performances of these techniques are compared. The results show that Quadratic Discriminant Analysis offers higher accuracy and lower error rates compared to Linear Discriminant Analysis.

References

  • Prugh, R.W. Life‐safety concerns in chemical plants. Process Safety Progress. 35(1) (2016) 18-25.
  • Cox, B.L., Carpenter, A.R., Ogle, R.A. Lessons learned from case studies of hazardous waste/chemical reactivity incidents. Process Safety Progress. 33(4) (2014) 395-98.
  • Morrison, D.T., Stern, M., Osorio‐Amado, C.H. Waste solvents to trash haulers: lessons learned from hazardous waste accidents. Process safety progress. 37(3) (2018) 427-41.
  • Ness, A., Gibson, R. Handling chemicals in small containers. Process safety progress. 24(4) (2005) 299-302.
  • Alexeev, S., Smirnov, V., Barbin, N., Alexeeva, D.Y. Evolution of the classification of flammable and combustible liquids in Russia. Process safety progress.37(2) (2018) 230-36.
  • DaCunha, S., Gerbaud, V., Shcherbakova, N., Liaw, H.J. Classification for ternary flash point mixtures diagrams regarding miscible flammable compounds. Fluid Phase Equilibria. 466 (2018) 110-23.
  • Stefanidou, M., Athanaselis, S., Spiliopoulou, C. Health impacts of fire smoke inhalation. Inhalation toxicology. 20(8) (2008) 761-66.
  • Purser, D.A., McAllister, J.L. Assessment of hazards to occupants from smoke, toxic gases, and heat. SFPE handbook of fire protection engineering. Springer; 2016. p. 2308-428.
  • Yuan, S., Zhang, Z., Sun, Y., Kwon, JS-I., Mashuga, C.V. Liquid flammability ratings predicted by machine learning considering aerosolization. Journal of hazardous materials. 386 (2020) 121640.
  • Yuan, W., Lv, W., Wang, H., Ma, Li, S. H. Performance prediction of suspension freeze crystallization for the treatment of liquid hazardous wastes via machine learning methods, Journal of Cleaner Production, (2021) 129629.
  • Yuan, Ji, C., Jiao, S., Huffman, Z., El-Halwagi, M., Wang, M.M., Q., Predicting flammability-leading properties for liquid aerosol safety via machine learning, Process Safety and Environmental Protection, 148 (2021) 1357-1366.
  • Jiao, Z., Ji, C., Yuan, S., Zhang, Z., Wang, Q. Development of machine learning based prediction models for hazardous properties of chemical mixtures, Journal of Loss Prevention in the Process Industries, 67 (2020) 104226.
  • Zhang, Z., Yuan, S., Yu, M., Mannan, M.S., Wang, Q., A hazard index for chemical logistic warehouses with modified flammability rating by machine learning methods, ACS Chemical Health & Safety, 27 (2020) 190-197.
  • Mahmodi, K., Mostafaei, M., Mirzaee-Ghaleh, E. Detection and classification of diesel-biodiesel blends by LDA, QDA and SVM approaches using an electronic nose. Fuel. 258 (2019) 116114.
  • Ji, C., Jiao, Z., Yuan, S., El-Halwagi, M.M., Wang, Q., Development of novel combustion risk index for flammable liquids based on unsupervised clustering algorithms, Journal of Loss Prevention in the Process Industries, 70 (2021) 104422
  • Li, Z., Haigh, A., Soutis, C., Gibson, A., Sloan, R. Microwaves sensor for wind turbine blade inspection. Applied Composite Materials. 24(2) (2017) 495-512.
  • Borisov, V., Karpenko, A. Using of the Michelson microwave interferometer for the measurement of permittivity of thin-layer materials. Russian journal of nondestructive testing. 37(8) (2001) 597-99.
  • Yurchenko, A.V., Novikov, A., Kitaeva, M.V. A resonator microwave sensor for measuring the parameters of Solar-quality silicon. Russian Journal of Nondestructive Testing. 48(2) (2012) 109-14.
  • Mathur, P., Thakur, A., Kurup, D.G. An artificial neural network-based non-destructive microwave technique for monitoring fluoride contamination in water. Journal of Electromagnetic Waves and Applications. 34(5) (2020) 612-22.
  • Turgul, V., Kale, I. Permittivity extraction of glucose solutions through artificial neural networks and non-invasive microwave glucose sensing. Sensors and Actuators A: Physical. 277 (2018) 65-72.
  • Sulaiman, N., Srisatit, S. Development of x-ray imaging technique for liquid screening at airport. AIP Conference Proceedings: AIP Publishing LLC; 2016. p. 030006.
  • Orachorn, P., Chankow, N., Srisatit, S. An Alternative Method for Screening Liquid in Bottles at Airports Using Low Energy X-ray Transmission Technique. Radiation environment and medicine: covering a broad scope of topics relevant to environmental and medical radiation research. 8(2) (2019) 77-84.
  • Chen, H., Hu, Z., Wang, P., Xu, W., Hou Y. Application of spectral droplet analysis method in flammable liquids identification. Paper presented at 2019 International Conference on Optical Instruments and Technology: Optical Sensors and Applications: International Society for Optics and Photonics, pp. 1143609, 2020.
  • Sun, L. Liquid dangerous goods detection based on electronic nose odor recognition technology. Paper presented at International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications: International Society for Optics and Photonics, pp. 890721, 2013.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Ebru EFEOĞLU
0000-0001-5444-6647
Türkiye


Gürkan TUNA (Primary Author)
TRAKYA UNIVERSITY
0000-0002-6466-4696
Türkiye

Publication Date December 31, 2021
Application Date April 23, 2021
Acceptance Date December 4, 2021
Published in Issue Year 2021, Volume 8, Issue 4

Cite

Bibtex @research article { hjse926894, journal = {Hittite Journal of Science and Engineering}, issn = {}, eissn = {2148-4171}, address = {Hitit Üniversitesi Mühendislik Fakültesi Kuzey Kampüsü Çevre Yolu Bulvarı 19030 Çorum / TÜRKİYE}, publisher = {Hitit University}, year = {2021}, volume = {8}, pages = {279 - 285}, doi = {10.17350/HJSE19030000240}, title = {A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions}, key = {cite}, author = {Efeoğlu, Ebru and Tuna, Gürkan} }
APA Efeoğlu, E. & Tuna, G. (2021). A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions . Hittite Journal of Science and Engineering , 8 (4) , 279-285 . DOI: 10.17350/HJSE19030000240
MLA Efeoğlu, E. , Tuna, G. "A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions" . Hittite Journal of Science and Engineering 8 (2021 ): 279-285 <https://dergipark.org.tr/en/pub/hjse/issue/67751/926894>
Chicago Efeoğlu, E. , Tuna, G. "A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions". Hittite Journal of Science and Engineering 8 (2021 ): 279-285
RIS TY - JOUR T1 - A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions AU - Ebru Efeoğlu , Gürkan Tuna Y1 - 2021 PY - 2021 N1 - doi: 10.17350/HJSE19030000240 DO - 10.17350/HJSE19030000240 T2 - Hittite Journal of Science and Engineering JF - Journal JO - JOR SP - 279 EP - 285 VL - 8 IS - 4 SN - -2148-4171 M3 - doi: 10.17350/HJSE19030000240 UR - https://doi.org/10.17350/HJSE19030000240 Y2 - 2021 ER -
EndNote %0 Hittite Journal of Science and Engineering A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions %A Ebru Efeoğlu , Gürkan Tuna %T A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions %D 2021 %J Hittite Journal of Science and Engineering %P -2148-4171 %V 8 %N 4 %R doi: 10.17350/HJSE19030000240 %U 10.17350/HJSE19030000240
ISNAD Efeoğlu, Ebru , Tuna, Gürkan . "A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions". Hittite Journal of Science and Engineering 8 / 4 (December 2021): 279-285 . https://doi.org/10.17350/HJSE19030000240
AMA Efeoğlu E. , Tuna G. A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions. Hittite J Sci Eng. 2021; 8(4): 279-285.
Vancouver Efeoğlu E. , Tuna G. A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions. Hittite Journal of Science and Engineering. 2021; 8(4): 279-285.
IEEE E. Efeoğlu and G. Tuna , "A New Approach for Liquid Scanners to Determine Flammable Liquid Concentration in Solutions", Hittite Journal of Science and Engineering, vol. 8, no. 4, pp. 279-285, Dec. 2021, doi:10.17350/HJSE19030000240