IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i4p398-d501088.html
   My bibliography  Save this article

Modeling, Simulation and Uncertain Optimization of the Gun Engraving System

Author

Listed:
  • Tong Xin

    (Department of Mechanical Engineering, School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Guolai Yang

    (Department of Mechanical Engineering, School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Fengjie Xu

    (Department of Mechanical Engineering, School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Quanzhao Sun

    (Department of Mechanical Engineering, School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Alexandi Minak

    (Department of Mechanical Engineering, Faculty of Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada)

Abstract

The system designed to accomplish the engraving process of a rotating band projectile is called the gun engraving system. To obtain higher performance, the optimal design of the size parameters of the gun engraving system was carried out. First, a fluid–solid coupling computational model of the gun engraving system was built and validated by the gun launch experiment. Subsequently, three mathematic variable values, like performance evaluation indexes, were obtained. Second, a sensitivity analysis was performed, and four high-influence size parameters were selected as design variables. Finally, an optimization model based on the affine arithmetic was set up and solved, and then the optimized intervals of performance evaluation indexes were obtained. After the optimal design, the percent decrease of the maximum engraving resistance force ranged from 6.34% to 18.24%; the percent decrease of the maximum propellant gas temperature ranged from 1.91% to 7.45%; the percent increase of minimum pressure wave of the propellant gas ranged from 0.12% to 0.36%.

Suggested Citation

  • Tong Xin & Guolai Yang & Fengjie Xu & Quanzhao Sun & Alexandi Minak, 2021. "Modeling, Simulation and Uncertain Optimization of the Gun Engraving System," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:398-:d:501088
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/4/398/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/4/398/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiang, C. & Han, X. & Liu, G.R. & Liu, G.P., 2008. "A nonlinear interval number programming method for uncertain optimization problems," European Journal of Operational Research, Elsevier, vol. 188(1), pages 1-13, July.
    2. Luque, Mariano & Marcenaro-Gutierrez, Oscar D. & Ruiz, Ana B., 2020. "Evaluating the global efficiency of teachers through a multi-criteria approach," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali Kamil Gumar & Funda Demir, 2022. "Solar Photovoltaic Power Estimation Using Meta-Optimized Neural Networks," Energies, MDPI, vol. 15(22), pages 1-15, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    2. Mahdi Zarghami & Nasim Safari & Ferenc Szidarovszky & Shafiqul Islam, 2015. "Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4285-4303, September.
    3. Samir A. Abass, 2012. "0-1 integer interval number programming approach for the multilevel generalized assignment problem," E3 Journal of Business Management and Economics., E3 Journals, vol. 3(9), pages 326-329.
    4. Rahaman, Mostafijur & Mondal, Sankar Prasad & Alam, Shariful & Metwally, Ahmed Sayed M. & Salahshour, Soheil & Salimi, Mehdi & Ahmadian, Ali, 2022. "Manifestation of interval uncertainties for fractional differential equations under conformable derivative," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    5. Xiaobin Yang & Haitao Lin & Gang Xiao & Huanbin Xue & Xiaopeng Yang, 2019. "Resolution of Max-Product Fuzzy Relation Equation with Interval-Valued Parameter," Complexity, Hindawi, vol. 2019, pages 1-16, February.
    6. He, Li & Huang, Guo H. & Lu, Hongwei, 2011. "Bivariate interval semi-infinite programming with an application to environmental decision-making analysis," European Journal of Operational Research, Elsevier, vol. 211(3), pages 452-465, June.
    7. Mrinal Jana & Geetanjali Panda, 2018. "$$\chi$$ χ -Optimal solution of single objective nonlinear optimization problem with uncertain parameters," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 165-186, March.
    8. P. Kumar & G. Panda, 2017. "Solving nonlinear interval optimization problem using stochastic programming technique," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 752-765, December.
    9. Tong Xin & Guolai Yang & Liqun Wang & Quanzhao Sun, 2020. "Numerical Calculation and Uncertain Optimization of Energy Conversion in Interior Ballistics Stage," Energies, MDPI, vol. 13(21), pages 1-21, November.
    10. Bao, Tiantian & Liu, Yifan & Yang, Zhongzhen & Wu, Shanhua & Yan, Zhenli, 2024. "Evaluating sustainable service quality in higher education from a multi-stakeholder perspective: An integrated fuzzy group decision-making method," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    11. Ana B. Ruiz & Mariano Luque & Oscar D. Marcenaro-Gutierrez, 2022. "On the use of Synthetic Indexes Based on Multi-Criteria Decision Making to Study the Efficiency of Teachers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(3), pages 1269-1300, October.
    12. Chen, J.J. & Zhuang, Y.B. & Li, Y.Z. & Wang, P. & Zhao, Y.L. & Zhang, C.S., 2017. "Risk-aware short term hydro-wind-thermal scheduling using a probability interval optimization model," Applied Energy, Elsevier, vol. 189(C), pages 534-554.
    13. Chongxin Huang & Dong Yue & Song Deng & Jun Xie, 2017. "Optimal Scheduling of Microgrid with Multiple Distributed Resources Using Interval Optimization," Energies, MDPI, vol. 10(3), pages 1-23, March.
    14. Huang, Min & Qian, Xiaohu & Fang, Shu-Cherng & Wang, Xingwei, 2016. "Winner determination for risk aversion buyers in multi-attribute reverse auction," Omega, Elsevier, vol. 59(PB), pages 184-200.
    15. Dapeng Wang & Cong Zhang & Wanqing Jia & Qian Liu & Long Cheng & Huaizhi Yang & Yufeng Luo & Na Kuang, 2022. "A Novel Interval Programming Method and Its Application in Power System Optimization Considering Uncertainties in Load Demands and Renewable Power Generation," Energies, MDPI, vol. 15(20), pages 1-19, October.
    16. A. Bhurjee & G. Panda, 2012. "Efficient solution of interval optimization problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(3), pages 273-288, December.
    17. Abhijit Baidya & Uttam Kumar Bera & Manoranjan Maiti, 2016. "The grey linear programming approach and its application to multi-objective multi-stage solid transportation problem," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 500-522, September.
    18. Banafsheh Nematollahi & Mohammad Reza Nikoo & Amir H. Gandomi & Nasser Talebbeydokhti & Gholam Reza Rakhshandehroo, 2022. "A Multi-criteria Decision-making Optimization Model for Flood Management in Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 4933-4949, October.
    19. Fanyong Meng & Xiaohong Chen & Chunqiao Tan, 2016. "Cooperative fuzzy games with interval characteristic functions," Operational Research, Springer, vol. 16(1), pages 1-24, April.
    20. Debdas Ghosh, 2016. "A Newton method for capturing efficient solutions of interval optimization problems," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 648-665, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:398-:d:501088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.