| PHYSICS OF GASES, PLASMAS, AND ELECTRIC DISCHARGES |
Prev
Next
|
|
|
Modeling and optimization of the multichannel spark discharge |
| Zhi-Bo Zhang(张志波)1, Yun Wu(吴云)1,2, Min Jia(贾敏)1, Hui-Min Song(宋慧敏)1, Zheng-Zhong Sun(孙正中)3, Ying-Hong Li(李应红)1 |
1 Science and Technology on Plasma Dynamics Laboratory, Air Force Engineering University, Xi'an 710038, China;
2 Science and Technology on Plasma Dynamics Laboratory, Xi'an Jiaotong University, Xi'an 710049, China;
3 Department of Mechanical Engineering and Aeronautics, City University London, London, United Kingdom |
|
|
|
|
Abstract This paper reports a novel analytic model of this multichannel spark discharge, considering the delay time in the breakdown process, the electric transforming of the discharge channel from a capacitor to a resistor induced by the air breakdown, and the varying plasma resistance in the discharge process. The good agreement between the experimental and the simulated results validated the accuracy of this model. Based on this model, the influence of the circuit parameters on the maximum discharge channel number (MDCN) is investigated. Both the input voltage amplitude and the breakdown voltage threshold of each discharge channel play a critical role. With the increase of the input voltage and the decrease of the breakdown voltage, the MCDN increases almost linearly. With the increase of the discharge capacitance, the MDCN first rises and then remains almost constant. With the increase of the circuit inductance, the MDCN increases slowly but decreases quickly when the inductance increases over a certain value. There is an optimal value of the capacitor connected to the discharge channel corresponding to the MDCN. Finally, based on these results, to shorten the discharge time, a modified multichannel discharge circuit is developed and validated by the experiment. With only 6-kV input voltage, 31-channels discharge is achieved. The breakdown voltage of each electrode gap is larger than 3 kV. The modified discharge circuit is certain to be widely used in the PSJA flow control field.
|
Received: 13 December 2016
Revised: 19 February 2017
Accepted manuscript online:
|
|
PACS:
|
52.50.Dg
|
(Plasma sources)
|
| |
52.30.-q
|
(Plasma dynamics and flow)
|
| |
52.80.Mg
|
(Arcs; sparks; lightning; atmospheric electricity)
|
| |
47.85.L-
|
(Flow control)
|
|
| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 51336011, 51522606, 91541120, 51611130198, 51407197, and 11472306) and Royal Society (Grant No. IE150612). |
Corresponding Authors:
Yun Wu
E-mail: wuyun1223@126.com
|
Cite this article:
Zhi-Bo Zhang(张志波), Yun Wu(吴云), Min Jia(贾敏), Hui-Min Song(宋慧敏), Zheng-Zhong Sun(孙正中), Ying-Hong Li(李应红) Modeling and optimization of the multichannel spark discharge 2017 Chin. Phys. B 26 065204
|
| [1] |
Corke T C, Enloe C L and Wilkinson S P 2010 Ann. Rev. Fluid Mech. 42 505
|
| [2] |
Cattafesta III L N and Sheplak M 2011 Ann. Rev. Fluid Mech. 43 247
|
| [3] |
Bletzinger P, Ganguly B N, Wie D V and Garscadden A 2005 J. Phys. D: Appl. Phys. 38 R33
|
| [4] |
Webb N, Clifford C and Samimy M. 2013 Exp. Fluids 54 1545
|
| [5] |
Hahn C, Kearney-Fischer M and Samimy M 2011 Exp. Fluids 51 1591
|
| [6] |
Samimy M, Kim J H, Kastner J, Adamovich I and Utkin Y 2007 AIAA J. 45 890
|
| [7] |
Narayanaswamy V, Raja L L and Clemens N T 2012 Phys. Fluids 24 076101
|
| [8] |
Greene B R, Clemens N T, Magari P and Micka D 2015 Shock Waves 25 495
|
| [9] |
Narayanaswamy V, Raja L L and Clemens N T 2010 AIAA J. 48 297
|
| [10] |
Emerick T, Ali M Y, Foster C, Alvi F S and Popkin S 2014 Exp. Fluids 55 1858
|
| [11] |
Golbabaei-Asl M, Knight D and Wilkinson S 2015 AIAA J. 53 501
|
| [12] |
Popkin S H, Cybyk B Z, Foster C H and Alvi F S 2016 AIAA J. 54 1831
|
| [13] |
Zong H, Wu Y, Song H and Jia M 2016 AIAA J. 54 3409
|
| [14] |
Zong H, Wu Y, Li Y, Song H, Zhang Z and Jia M 2015 Physics of Fluids 27 027105
|
| [15] |
Wu Y, Li J, Jia M, Liang H and Song H 2012 Chin. Phys. B 21 045202
|
| [16] |
Wang L, Luo Z, Xia Z and Liu B 2013 Acta Phys. Sin. 62 125207 (in Chinese)
|
| [17] |
Wang L, Xia Z, Luo Z, Zhou Y and Zhang Y 2014 Acta Phys. Sin. 63 194702 (in Chinese)
|
| [18] |
Zhang C, Wang Y, Zhou Y, Xie Q, Wang R, Yan P and Shao T 2016 IEEE T. Plasma Sci. 44 2772
|
| [19] |
Shao T, Jiang H, Zhang C, Yan P, Lomaev M I and Tarasenko V F 2013 Europhys. Lett. 101 45002
|
| [20] |
Tie W, Liu X, Liu S and Zhang Q 2015 IEEE T. Plasma Sci. 43 937
|
| [21] |
Zhang Z, Wu Y, Jia M, Song H, Sun Z, Zong H and Li Y 2017 Sensor Actuat A-Phys. 253 112
|
| [22] |
Schavemaker P H and Van der Slui L 2000 IEEE T. Power Deliver 15 580
|
| [23] |
Martin T H 1989. Sandia National Labs. Albuquerque, NM (USA) pp. 73-79
|
| [24] |
Hippler R, Kersten H and Schmidt M 2008 Low temperature plasma: fundamentals, technologies and techniques, 2nd edn., Vol. 2, (Wiler-VCH) p. 465
|
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
