Simulation of Airflow Performance and Parameter Optimization of
Photoacoustic Cell Based on Orthogonal Test
CHENG Gang1, CAO Ya-nan1, TIAN Xing1, CAO Yuan2, LIU Kun2
1. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines (Anhui University of Science and Technology), Huainan 232001, China
2. Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Abstract:Photoacoustic spectroscopy gas detection technology is the most typical application of photoacoustic technology. Compared with other methods, photoacoustic gas detection technology has the advantages of a simple structure, wavelength free detector, zero background noise and low cost. This technology has been widely used in various fields. The photoacoustic cell is the core component of the photoacoustic spectrum gas detection system, and its performance greatly impacts the detection results. At present, the optimization of the photoacoustic cell is mainly carried out under static conditions, and there are few reports on the gas flow performance and dynamic time response in the photoacoustic cell cavity. Because the gas disturbance and system detection noise of the photoacoustic cell under dynamic detection conditions have a certain impact, the relevant parameters of the photoacoustic cell are further explored and optimized to improve the gas flow field distribution in the photoacoustic cell cavity. Dynamic pressure characteristics and gas concentration equilibrium time are of great significance to improve the gas detection performance of photoacoustic spectroscopy. Therefore, based on the traditional cylindrical photoacoustic cell, the steady-state and transient simulation models of the flow field in the photoacoustic cell cavity are established based on the three-dimensional flow field numerical simulation method, and the gas flow field distribution and gas concentration balance response law in the photoacoustic cell cavity are calculated. The results show that reducing the flow velocity in the photoacoustic cell and optimizing the transition structure in the photoacoustic cell will improve the dynamic pressure fluctuation caused by the flow and shorten the gas concentration regulation time in the cavity. Taking the five parameters of the transition corner between the buffer cavity and the resonator of the photoacoustic cell, the number of auxiliary holes, the radius of the auxiliary hole, the radius of the center circle of the auxiliary hole and the air inlet speed as factors, and taking the dynamic pressure value at the midpoint of the resonator axis and the gas concentration adjustment time as inspection indexes, the method of combining numerical simulation, orthogonal experimental design and entropy weight method is adopted, The primary and secondary order of the influence of the relevant parameters of the photoacoustic cell on the dynamic pressure value is obtained as follows: the radius of the auxiliary hole>the number of auxiliary holes>air inlet speed>transition fillet>the radius of the center circle of the auxiliary hole; The primary and secondary order of influence on the adjustment time is: inlet speed>auxiliary hole radius>number of auxiliary holes=auxiliary hole center circle radius>transition fillet. In order to balance the influence of indicators, this paper transforms the multi-objective parameter optimization problem into a single objective optimization problem. It objectively gives the weight of dynamic pressure value as 0.49 and the weight of adjustment time as 0.51 respectively. Within the range of parameters studied in this paper, the best combination of parameters is obtained: the circle at the transition between the buffer cavity and the resonator is 3.0 mm, the number of auxiliary holes is 8, the radius of auxiliary holes is 3.5 mm, the radius of the center circle of auxiliary holes is 22.5mm, the air inlet speed is 0.06 m·s-1, the dynamic pressure value at the midpoint of the axis of the optimized photoacoustic cell resonator is 9.4×10-4 Pa, and the gas concentration adjustment time in the cavity is 141 s. Compared with the indicators before the optimization of the photoacoustic cell, the dynamic pressure value is relatively reduced by 88.1%, and the adjustment time is relatively reduced by 17.5%. Both indicators have been optimized and improved, and the optimization effect is relatively ideal. The research methods and conclusions can provide important references for photoacoustic cell optimization design and expansion.
程 刚,曹亚南,田 兴,曹 渊,刘 锟. 基于正交试验的光声池气流性能模拟及参数优化[J]. 光谱学与光谱分析, 2023, 43(12): 3899-3905.
CHENG Gang, CAO Ya-nan, TIAN Xing, CAO Yuan, LIU Kun. Simulation of Airflow Performance and Parameter Optimization of
Photoacoustic Cell Based on Orthogonal Test. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3899-3905.
[1] Kost B, Baumann B, Germer M, et al. Applied Physics B, 2011, 102(1): 87.
[2] Haouari R, Rochus V, Lagae L, et al. Topology Optimization of an Acoustical Cell for Gaseous Photoacoustic Spectroscopy Using COMSOLD○R Multiphysics, Proceedings of the 2017 COMSOL Conference in Rotterdam, 2017.
[3] Lassen M, Balslev-Harder D, Brusch A, et al. Applied Optics, 2018, 57(4): 802.
[4] CHENG Gang, CAO Yuan, LIU Kun, et al(程 刚,曹 渊,刘 锟,等). Acta Physica Sinica(物理学报), 2019, 68(7): 139.
[5] CHENG Gang, CAO Ya-nan, TIAN Xing, et al(程 刚,曹亚南,田 兴,等). Acta Photonica Sinica(光子学报), 2021, 50(2): 200.
[6] Zhang C, Wang Q, Yin X. Optics Communications, 2021, 487: 126764.
[7] LI Ze-hao, YANG Chun-yong, TANG Zi-hao, et al(李泽昊,杨春勇,唐梓豪,等). Chinese Journal of Lasers(中国激光), 2021, 48(1): 186.
[8] Liu L, Huan H, Mandelis A, et al. Optics & Laser Technology, 2022, 148: 107695.
[9] SHI Qiang, HU Shui-ming, CHEN Jun, et al(史 强,胡水明,陈 军,等). Chinese Journal of Chemical Physics(化学物理学报), 1998, 11(1): 20.
[10] ZHAO Jun-juan, ZHAO Zhan, DU Li-dong, et al(赵俊娟,赵 湛,杜利东,等). Chinese Journal of Sensors and Actuators(传感技术学报), 2012, 25(3): 289.
[11] Jiao Y, Fan H, Gong Z, et al. Applied Sciences, 2021, 11(11): 4997.
[12] Zhao N, Zhao D, Ma L, et al. Analytical Methods, 2022, 14(15): 157.
[13] YU Xin,LI Zhen-gang,LIU Jia-xiang, et al(于 欣,李振钢,刘家祥,等). Acta Optica Sinica(光学学报), 2021, 41(16): 120.
[14] Yin X, Wu H, Dong L, et al. ACS Sensors, 2020, 5(2): 549.
[15] Ma Y, Qiao S, He Y, et al. Optics Express, 2019, 27(10): 14163.
[16] DING Shu-ye, XIA Lei, LIU Jian-feng, et al(丁树业,夏 垒,刘建峰,等). Journal of Harbin University of Science and Technology(哈尔滨理工大学学报), 2018, 23(6): 57.
[17] LIU Qiang, NIU Ming-sheng, WANG Gui-shi, et al(刘 强,牛明生,王贵师,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2013, 33(7): 1729.
[18] WANG Yong-ming, LI Wei, TAN Li-bin, et al(汪永明,李 偎,谈莉斌,等). Forging & Stamping Technology(锻压技术), 2021, 46(12): 46.