Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model
Rotary regenerative oxidiser (r-RTO), an effective VOCs treatment equipment, needs to be operated for a long time under actual working conditions, resulting in excessive temperatures on the outer wall of the r-RTO furnace, which causes production accidents. In order to avoid production accidents, th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X22005573 |
| _version_ | 1811344068216619008 |
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| author | Bo Sun Tong Zhao Lu Li Zhilong Wang Pengzhao Sun Cong Peng |
| author_facet | Bo Sun Tong Zhao Lu Li Zhilong Wang Pengzhao Sun Cong Peng |
| author_sort | Bo Sun |
| collection | DOAJ |
| description | Rotary regenerative oxidiser (r-RTO), an effective VOCs treatment equipment, needs to be operated for a long time under actual working conditions, resulting in excessive temperatures on the outer wall of the r-RTO furnace, which causes production accidents. In order to avoid production accidents, the heat transfer process of airflow inside r-RTO regenerator should be clarified. Computational Fluid Dynamics (CFD) method is applied to analyse the temperature and pressure distribution in r-RTO regenerator. The temperature distribution of regenerator is analysed in order to find the main thermal dissipation path based on thermal-fluid coupling method. In temperature distribution, the outlet temperature Toutlet is decreased with the increase of regenerator height h. However, Toutlet is increased with the increase of gas flow rate vgas pore size Dp, respectively. In pressure distribution, the pressure drop Pdrop is increased with the increase of h and vgas. However, Pdrop is decreased with the increase of Dp. The results of the temperature distribution analysis are shown that the main pathway for thermal dissipation is along the partition dividers to insulation material where thermal dissipated through the insulation material. Quadratic regression method is used to design multivariate simulation experiments. Genetic algorithm is used to find optimal operating parameters. In addition, partition divider material and thermal insulation thickness are used as optimization parameters to optimize the thermal insulation construction. The present study reveals that thermal-fluid coupling method and quadratic regression method are satisfactory for the optimization of regenerator operating parameters and thermal insulation construction for r-RTO regenerator. |
| first_indexed | 2024-04-13T19:41:20Z |
| format | Article |
| id | doaj.art-8575d8e385134b8a9de929b5d253eb36 |
| institution | Directory Open Access Journal |
| issn | 2214-157X |
| language | English |
| last_indexed | 2024-04-13T19:41:20Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj.art-8575d8e385134b8a9de929b5d253eb362022-12-22T02:32:52ZengElsevierCase Studies in Thermal Engineering2214-157X2022-09-0137102314Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression modelBo Sun0Tong Zhao1Lu Li2Zhilong Wang3Pengzhao Sun4Cong Peng5School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an, Shaanxi, China; Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba University, Chiba-shi, JapanSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an, Shaanxi, China; Corresponding author.School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an, Shaanxi, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an, Shaanxi, ChinaXi'an Yurcent Environmental Technology Co., Ltd, Xi'an, Shaanxi, ChinaXi'an Yurcent Environmental Technology Co., Ltd, Xi'an, Shaanxi, ChinaRotary regenerative oxidiser (r-RTO), an effective VOCs treatment equipment, needs to be operated for a long time under actual working conditions, resulting in excessive temperatures on the outer wall of the r-RTO furnace, which causes production accidents. In order to avoid production accidents, the heat transfer process of airflow inside r-RTO regenerator should be clarified. Computational Fluid Dynamics (CFD) method is applied to analyse the temperature and pressure distribution in r-RTO regenerator. The temperature distribution of regenerator is analysed in order to find the main thermal dissipation path based on thermal-fluid coupling method. In temperature distribution, the outlet temperature Toutlet is decreased with the increase of regenerator height h. However, Toutlet is increased with the increase of gas flow rate vgas pore size Dp, respectively. In pressure distribution, the pressure drop Pdrop is increased with the increase of h and vgas. However, Pdrop is decreased with the increase of Dp. The results of the temperature distribution analysis are shown that the main pathway for thermal dissipation is along the partition dividers to insulation material where thermal dissipated through the insulation material. Quadratic regression method is used to design multivariate simulation experiments. Genetic algorithm is used to find optimal operating parameters. In addition, partition divider material and thermal insulation thickness are used as optimization parameters to optimize the thermal insulation construction. The present study reveals that thermal-fluid coupling method and quadratic regression method are satisfactory for the optimization of regenerator operating parameters and thermal insulation construction for r-RTO regenerator.http://www.sciencedirect.com/science/article/pii/S2214157X22005573Rotary regenerative thermal oxidizer (r-RTO)RegeneratorThermal dissipationQuadratic regression modelThermal-fluid coupling method |
| spellingShingle | Bo Sun Tong Zhao Lu Li Zhilong Wang Pengzhao Sun Cong Peng Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model Case Studies in Thermal Engineering Rotary regenerative thermal oxidizer (r-RTO) Regenerator Thermal dissipation Quadratic regression model Thermal-fluid coupling method |
| title | Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model |
| title_full | Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model |
| title_fullStr | Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model |
| title_full_unstemmed | Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model |
| title_short | Optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer (r-RTO) based on thermal-fluid coupling method and quadratic regression model |
| title_sort | optimization of regenerator operating parameters and thermal insulation construction for rotary regenerative thermal oxidizer r rto based on thermal fluid coupling method and quadratic regression model |
| topic | Rotary regenerative thermal oxidizer (r-RTO) Regenerator Thermal dissipation Quadratic regression model Thermal-fluid coupling method |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X22005573 |
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