Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

doi:10.1016/j.cjche.2017.07.022

Chin.J.Chem.Eng. ›› 2018, Vol. 26 ›› Issue (2): 356-363.DOI: 10.1016/j.cjche.2017.07.022

• Process Systems Engineering and Process Safety • Previous Articles Next Articles

Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

Denglong Ma¹, Wei Tan¹, Zaoxiao Zhang^2,3, Jun Hu⁴

1 School of Food Equipment Engineering and Science, Xi'an Jiaotong University, Xi'an 710049, China;
2 State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China;
3 School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an 710049, China;
4 School of Chemical Engineering, Northwest University, Xi'an 710069, China

Received:2017-05-02 Revised:2017-07-16 Online:2018-03-16 Published:2018-02-28
Contact: Denglong Ma
Supported by:
Supported by the National Natural Science Foundation of China (21676216), China Postdoctoral Science Foundation (2015M582667), Natural Science Basic Research Plan in Shaanxi Province of China (2016JQ5079), Key Research Project of Shaanxi Province (2015ZDXM-GY-115) and the Fundamental Research Funds for the Central Universities (xjj2017124).

Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

Denglong Ma¹, Wei Tan¹, Zaoxiao Zhang^2,3, Jun Hu⁴

1 School of Food Equipment Engineering and Science, Xi'an Jiaotong University, Xi'an 710049, China;
2 State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China;
3 School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an 710049, China;
4 School of Chemical Engineering, Northwest University, Xi'an 710069, China

通讯作者: Denglong Ma
基金资助:
Supported by the National Natural Science Foundation of China (21676216), China Postdoctoral Science Foundation (2015M582667), Natural Science Basic Research Plan in Shaanxi Province of China (2016JQ5079), Key Research Project of Shaanxi Province (2015ZDXM-GY-115) and the Fundamental Research Funds for the Central Universities (xjj2017124).

Abstract

Abstract: Source term identification is very important for the contaminant gas emission event. Thus, it is necessary to study the source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the source parameters. However, it is invalid for nonlinear inverse problem like gas emission process. 2-step nonlinear and linear PSO (partial swarm optimization)-Tikhonov regularization method proposed previously have estimated the emission source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularization and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO-Tikhonov regularization method. 1-step nonlinear method even performs better than other two methods in some cases, especially for source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO-Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO-Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas emission source term.

Key words: Parameter estimation, Parameter regularization method, Source identification, Inverse problem

摘要： Source term identification is very important for the contaminant gas emission event. Thus, it is necessary to study the source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the source parameters. However, it is invalid for nonlinear inverse problem like gas emission process. 2-step nonlinear and linear PSO (partial swarm optimization)-Tikhonov regularization method proposed previously have estimated the emission source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularization and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO-Tikhonov regularization method. 1-step nonlinear method even performs better than other two methods in some cases, especially for source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO-Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO-Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas emission source term.

关键词: Parameter estimation, Parameter regularization method, Source identification, Inverse problem

Denglong Ma, Wei Tan, Zaoxiao Zhang, Jun Hu. Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method[J]. Chin.J.Chem.Eng., 2018, 26(2): 356-363.

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Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

Gas emission source term estimation with 1-step nonlinear partial swarm optimization-Tikhonov regularization hybrid method

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