IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i8p1967-d1129453.html
   My bibliography  Save this article

Preparation and Analysis of Experimental Findings on the Thermal and Mechanical Characteristics of Pulsating Gas Flows in the Intake System of a Piston Engine for Modelling and Machine Learning

Author

Listed:
  • Leonid Plotnikov

    (Turbines and Engines Department, Ural Federal University named after the first President of Russia B.N. Yeltsin, Str. Mira, 19, 620002 Yekaterinburg, Russia)

Abstract

Today, reciprocating internal combustion engines are used in many branches of the economy (power engineering, machine engineering, transportation, and others). In order for piston engines to meet stringent environmental and economic regulations, it is necessary to develop complex and accurate control systems for the physical processes in engine elements based on digital twins, machine learning, and artificial intelligence algorithms. This article is aimed at preparing and analysing experimental data on the gas dynamics and heat transfer of pulsating air flows in a piston engine’s intake system for modelling and machine learning. The key studies were carried out on a full-scale model of a single-cylinder piston engine under dynamic conditions. Some experimental findings on the gas-dynamic and heat-exchange characteristics of the flows were obtained with the thermal anemometry method and a corresponding measuring system. The effects of the inlet channel diameter on the air flow, the intensity of turbulence, and the heat transfer coefficient of pulsating air flows in a piston engine’s inlet system are shown. A mathematical description of the dependences of the turbulence intensity, heat transfer coefficient, and Nusselt number on operation factors (crankshaft speed, air flow velocity, Reynolds number) and the inlet channel’s geometric dimensions are proposed. Based on the mathematical modelling of the thermodynamic cycle, the operational and environmental performance of a piston engine with intake systems containing channels with different diameters were assessed. The presented data could be useful for refining engineering calculations and mathematical models, as well as for developing digital twins and engine control systems.

Suggested Citation

  • Leonid Plotnikov, 2023. "Preparation and Analysis of Experimental Findings on the Thermal and Mechanical Characteristics of Pulsating Gas Flows in the Intake System of a Piston Engine for Modelling and Machine Learning," Mathematics, MDPI, vol. 11(8), pages 1-16, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1967-:d:1129453
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/8/1967/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/8/1967/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Denis Sidorov, 2023. "Preface to “Model Predictive Control and Optimization for Cyber-Physical Systems”," Mathematics, MDPI, vol. 11(4), pages 1-3, February.
    2. Leng, Ling & Qiu, Hongjian & Li, Xiannan & Zhong, Jie & Shi, Lei & Deng, Kangyao, 2022. "Effects on the transient energy distribution of turbocharging mode switching for marine diesel engines," Energy, Elsevier, vol. 249(C).
    3. Yuehjen E. Shao & Yu-Ting Hu, 2020. "Using Machine Learning Classifiers to Recognize the Mixture Control Chart Patterns for a Multiple-Input Multiple-Output Process," Mathematics, MDPI, vol. 8(1), pages 1-14, January.
    4. Boru Jia & Andrew Smallbone & Rikard Mikalsen & K.V. Shivaprasad & Sumit Roy & Anthony Paul Roskilly, 2019. "Performance Analysis of a Flexi-Fuel Turbine-Combined Free-Piston Engine Generator," Energies, MDPI, vol. 12(14), pages 1-22, July.
    5. Zhao, Deyang & An, Yanzhao & Pei, Yiqiang & Shi, Hao & Wang, Kun, 2023. "Numerical study on the asymmetrical jets formation from active pre-chamber under super-lean combustion conditions," Energy, Elsevier, vol. 262(PA).
    6. Zhishuang Li & Ziman Wang & Haoyang Mo & Han Wu, 2022. "Effect of the Air Flow on the Combustion Process and Preheating Effect of the Intake Manifold Burner," Energies, MDPI, vol. 15(9), pages 1-17, April.
    7. Yoon, Wonjun & Kim, Jonghyun & Chung, Chungsoo & Park, Jungsoo, 2022. "Numerical study on prediction of icing phenomena in intake system of diesel engine: Operating conditions with low-to-middle velocity of inlet air," Energy, Elsevier, vol. 248(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. Shiyuan Yang & Hongtao Wang & Yihe Xu & Yongqiang Guo & Lidong Pan & Jiaming Zhang & Xinkai Guo & Debiao Meng & Jiapeng Wang, 2023. "A Coupled Simulated Annealing and Particle Swarm Optimization Reliability-Based Design Optimization Strategy under Hybrid Uncertainties," Mathematics, MDPI, vol. 11(23), pages 1-26, 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. Wei, Tianyi & Zhang, Biao & Wang, Shuguang & Tan, Sichao & Li, Dongyang & Qiao, Shouxu, 2023. "Numerical analysis of passive safety injection driven by natural circulation in floating nuclear power plant," Energy, Elsevier, vol. 263(PE).
    2. Zhang, Zhongjie & Peng, Qikai & Liu, Riulin & Dong, Surong & Zhou, Guangmeng & Liu, Zengyong & Zhao, Xumin & Yang, Chunhao & Wang, Zengquan & Xia, Xu, 2024. "A matching method for Twin-VGT systems under varying expansion ratios at high altitudes," Energy, Elsevier, vol. 289(C).
    3. Xuewen Zhang & Xiang Huang & Peiyong Ni & Xiang Li, 2023. "Strategies to Reduce Emissions from Diesel Engines under Cold Start Conditions: A Review," Energies, MDPI, vol. 16(13), pages 1-21, July.
    4. Ethel García & Rita Peñabaena-Niebles & Maria Jubiz-Diaz & Angie Perez-Tafur, 2022. "Concurrent Control Chart Pattern Recognition: A Systematic Review," Mathematics, MDPI, vol. 10(6), pages 1-31, March.
    5. Wang, Bin & Xie, Fangxi & Hong, Wei & Du, Jiakun & Chen, Hong & Li, Xiaoping, 2023. "Extending ultra-lean burn performance of high compression ratio pre-chamber jet ignition engines based on injection strategy and optimized structure," Energy, Elsevier, vol. 282(C).
    6. Hu, Junnan & Pei, Yiqiang & An, Yanzhao & Zhao, Deyang & Zhang, Zhiyong & Sun, Jian & Gao, Dingwei, 2023. "Study of active pre-chamber jet flames based on the synergy of airflow with different nozzle swirl angle," Energy, Elsevier, vol. 282(C).
    7. Zongyu Yue & Haifeng Liu, 2023. "Advanced Research on Internal Combustion Engines and Engine Fuels," Energies, MDPI, vol. 16(16), pages 1-8, August.
    8. Yihui Lei & Zhengqi Dai & Bolin Liao & Guangping Xia & Yongjun He, 2022. "Double Features Zeroing Neural Network Model for Solving the Pseudoninverse of a Complex-Valued Time-Varying Matrix," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
    9. Rina Ren & Tiexiong Su & Fukang Ma & Wei Yang & Xin Zhao & Chunlong Xu, 2022. "Research on the Effect of the Outlet Throttle Diameter Deviation on the Pressure Relief Rate of the Injector Control Valve," Energies, MDPI, vol. 16(1), pages 1-19, December.

    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:11:y:2023:i:8:p:1967-:d:1129453. 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.