References
- Benavides-Serrano, A. J., W. Legg, R. Vazquez-Roman, M. S. Mannan, and C. D. Laird. 2014. A stochastic programming approach for the optimal placement of gas detectors: Unavailability and voting strategies. Industrial & Engineering Chemistry Research 53 (13):5355–65. doi: https://doi.org/10.1021/ie401369v.
- Benavides-Serrano, A. J., M. S. Mannan, and C. D. Laird. 2015. A quantitative assessment on the placement practices of gas detectors in the process industries. Journal of Loss Prevention in the Process Industries 35:339–51. doi: https://doi.org/10.1016/j.jlp.2014.09.010.
- Cen, K., T. Yao, Q. Wang, and S. Xiong. 2018. A risk-based methodology for the optimal placement of hazardous gas detectors. Chinese Journal of Chemical Engineering 26 (5):1078–86. doi: https://doi.org/10.1016/j.cjche.2017.10.031.
- Cheng, F. M., A. B. Zhang, T. Wang, Y. Chen, Z. C. Chang, and T. J. Ge. 2020. Research based on double coverage rate and reliability of gas detector layout optimization. Journal of Loss Prevention in the Process Industries 68:104285. doi: https://doi.org/10.1016/j.jlp.2020.104285.
- DeFriend, S., M. Dejmek, L. Porter, B. Deshotels, and B. Natvig. 2008. A risk-based approach to flammable gas detector spacing. Journal of Hazardous Materials 159 (1):142–51. doi: https://doi.org/10.1016/j.jhazmat.2007.07.123.
- Fang, K. 1994. Uniform design and uniform design table. Beijing, China: Science Press.
- Gomes, C., M. Claeys-Bruno, and M. Sergent. 2018. Space-filling designs for mixtures. Chemometrics and Intelligent Laboratory Systems 174:111–27. doi: https://doi.org/10.1016/j.chemolab.2018.01.013.
- Hansen, O. R., and D. M. Johnson. 2015. Improved far-field blast predictions from fast deflagrations, DDTs and detonations of vapour clouds using FLACS CFD. Journal of Loss Prevention in the Process Industries 35:293–316. doi: https://doi.org/10.1016/j.jlp.2014.11.005.
- He, X. D., W. X. Gou, Y. S. Liu, and Z. Z. Gao. 2015. A practical method of nonprobabilistic reliability and parameter sensitivity analysis based on space-filling design. Mathematical Problems in Engineering 2015:1–12. doi: https://doi.org/10.1155/2015/561202.
- Klise, K. A., B. L. Nicholson, C. D. Laird, A. P. Ravikumar, and A. R. Brandt. 2020. Sensor placement optimization software applied to site-scale methane-emissions monitoring. Journal of Environmental Engineering 146 (7):04020054. doi: https://doi.org/10.1061/(ASCE)EE.1943-7870.0001737.
- Legg, S. W., A. J. Benavides-Serrano, J. D. Siirola, J. P. Watson, S. G. Davis, A. Bratteteig, and C. D. Laird. 2012. A stochastic programming approach for gas detector placement using CFD-based dispersion simulations. Computers & Chemical Engineering 47:194–201. doi: https://doi.org/10.1016/j.compchemeng.2012.05.010.
- Legg, S. W., C. Wang, A. J. Benavides-Serrano, and C. D. Laird. 2013. Optimal gas detector placement under uncertainty considering conditional-value-at-risk. Journal of Loss Prevention in the Process Industries 26 (3):410–7. doi: https://doi.org/10.1016/j.jlp.2012.06.006.
- Li, R., D. K. Lin, and Y. Chen. 2004. Uniform design: Design, analysis and applications. International Journal of Materials and Product Technology 20 (1/2/3):101–14. doi: https://doi.org/10.1504/IJMPT.2004.003915.
- Li, X., G. Chen, R. Zhang, H. Zhu, and C. Xu. 2019. Simulation and assessment of gas dispersion above sea from a subsea release: A CFD-based approach. International Journal of Naval Architecture and Ocean Engineering 11 (1):353–63. doi: https://doi.org/10.1016/j.ijnaoe.2018.07.002.
- Li-Mei, X. U., and J. L. Lin. 2012. Construction of uniform design table based on improved simulated annealing algorithm. Computer Engineering 38:180–1.
- Liu, A., J. Huang, Z. Li, J. Chen, X. Huang, K. Chen, and W. b. Xu. 2018. Numerical simulation and experiment on the law of urban natural gas leakage and diffusion for different building layouts. Journal of Natural Gas Science and Engineering 54:1–10. doi: https://doi.org/10.1016/j.jngse.2018.03.006.
- Liu, C., Y. Li, L. Fang, J. Han, and M. Xu. 2017. Leakage monitoring research and design for natural gas pipelines based on dynamic pressure waves. Journal of Process Control 50:66–76. doi: https://doi.org/10.1016/j.jprocont.2016.12.003.
- Liu, C., Y. Li, L. Meng, W. Wang, F. Zhao, and J. Fu. 2015. Computational fluid dynamic simulation of pressure perturbations generation for gas pipelines leakage. Computers & Fluids 119:213–23. doi: https://doi.org/10.1016/j.compfluid.2015.06.023.
- Lu, H., K. Huang, L. Fu, Z. Zhang, S. Wu, Y. Lyu, and X. Zhang. 2018. Study on leakage and ventilation scheme of gas pipeline in tunnel. Journal of Natural Gas Science and Engineering 53:347–58. doi: https://doi.org/10.1016/j.jngse.2018.03.019.
- McNay, J., and R. Hilditch. 2017. Evaluation of computational fluid dynamics (CFD) vs. target gas cloud for indoor gas detection design. Journal of Loss Prevention in the Process Industries 50:75–9. doi: https://doi.org/10.1016/j.jlp.2017.08.018.
- Meribout, M. 2021. Gas leak-detection and measurement systems: Prospects and future trends. IEEE Transactions on Instrumentation and Measurement 70:1–13. doi: https://doi.org/10.1109/TIM.2021.3096596.
- Meribout, M., L. Khezzar, A. Azzi, and N. Ghendour. 2020. Leak detection systems in oil and gas fields: Present trends and future prospects. Flow Measurement and Instrumentation 75:101772. doi: https://doi.org/10.1016/j.flowmeasinst.2020.101772.
- Rad, A., D. Rashtchian, and N. Badri. 2017. A risk-based methodology for optimum placement of flammable gas detectors within open process plants. Process Safety and Environmental Protection 105:175–83. doi: https://doi.org/10.1016/j.psep.2016.10.012.
- Rad, A., D. Rashtchian, and M. H. Eghbal Ahmadi. 2018. Optimum placement of gas detectors considering voting strategy with different detection set points. Journal of Loss Prevention in the Process Industries 55:53–60. doi: https://doi.org/10.1016/j.jlp.2018.05.002.
- Vazquez-Roman, R., C. Diaz-Ovalle, E. Quiroz-Perez, and M. S. Mannan. 2016. A CFD-based approach for gas detectors allocation. Journal of Loss Prevention in the Process Industries 44:633–41. doi: https://doi.org/10.1016/j.jlp.2016.03.004.
- Wang, K., T. Chen, S. T. Kwa, Y. F. Ma, and R. Lau. 2014. Meta-modelling for fast analysis of CFD-simulated vapour cloud dispersion processes. Computers & Chemical Engineering 69:89–97. doi: https://doi.org/10.1016/j.compchemeng.2014.07.003.
- Wang, K., J. Yang, Y. L. Peng, Q. Q. Wu, and C. L. Hu. 2020. Multiobjective optimization of sensor placement for precipitation station monitoring network design. Journal of Hydrologic Engineering 25 (9):04020039. doi: https://doi.org/10.1061/(ASCE)HE.1943-5584.0001954.
- Wang, T., Z. Luo, H. Wen, F. Cheng, J. Deng, J. Zhao, Z. Guo, J. Lin, K. Kang, and W. Wang. 2017. Effects of flammable gases on the explosion characteristics of CH4 in air. Journal of Loss Prevention in the Process Industries 49:183–90. doi: https://doi.org/10.1016/j.jlp.2017.06.018.
- Wu, J. S., Z. Liu, S. Q. Yuan, J. T. Cai, and X. F. Hu. 2020. Source term estimation of natural gas leakage in utility tunnel by combining CFD and Bayesian inference method. Journal of Loss Prevention in the Process Industries 68:104328. doi: https://doi.org/10.1016/j.jip.2020.104328.
- Xiao, Q., H. Yan, Y. Wei, Y. Wang, F. Zeng, and X. Zheng. 2012. Optimization of H2O2 dosage in microwave-H2O2 process for sludge pretreatment with uniform design method. Journal of Environmental Sciences 24 (12):2060–7. doi: https://doi.org/10.1016/S1001-0742(11)60998-4.
- Xinhong, L., C. Guoming, Z. Renren, Z. Hongwei, and F. Jianmin. 2018. Simulation and assessment of underwater gas release and dispersion from subsea gas pipelines leak. Process Safety and Environmental Protection 119:46–57. doi: https://doi.org/10.1016/j.psep.2018.07.015.
- Yang, J., J. Zhang, S. Mei, L. Di, and F. Zhao. 2017. Numerical simulation of sudden gas pipeline leakage in urban block. Energy Procedia 105:4921–6. doi: https://doi.org/10.1016/j.egypro.2017.03.1049.
- Yuan, R., D. K. J. Lin, and M.-Q. Liu. 2017. Nearly column-orthogonal designs based on leave-one-out good lattice point sets. Journal of Statistical Planning and Inference 185:29–40. doi: https://doi.org/10.1016/j.jspi.2017.01.002.
- Yuan, S. Q., J. S. Wu, X. L. Zhang, and W. Y. Liu. 2019. EnKF-based estimation of natural gas release and dispersion in an underground tunnel. Journal of Loss Prevention in the Process Industries 62:103931. doi: https://doi.org/10.1016/j.jlp.2019.103931.
- Zhang, B., and G. Chen. 2011. Sensitivity analysis on computational fluid dynamics modeling of gas dispersion. Science & Technology Review 29:57–61.
- Zhang, B., Y. Liu, and S. Qiao. 2019. A quantitative individual risk assessment method in process facilities with toxic gas release hazards: A combined scenario set and CFD approach. Process Safety Progress 38 (1):52–60. doi: https://doi.org/10.1002/prs.11979.
- Zhang, H. R., L. S. Pera, Y. J. Zhao, and C. V. Sanchez. 2015. Researches and applications on geostatistical simulation and laboratory modeling of mine ventilation network and gas drainage zone. Process Safety and Environmental Protection 94:55–64. doi: https://doi.org/10.1016/j.psep.2014.10.003.
- Zhang, Y., J. Wang, X. Bian, X. Huang, and L. Qi. 2017. A continuous gas leakage localization method based on an improved beamforming algorithm. Measurement 106:143–51. doi: https://doi.org/10.1016/j.measurement.2017.04.030.