Startseite Numerical study of catalytic converter geometries and their impact on exhaust back pressure and energy conversion in engine exhaust systems using parametric simulation: insights into non-equilibrium thermodynamics
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Numerical study of catalytic converter geometries and their impact on exhaust back pressure and energy conversion in engine exhaust systems using parametric simulation: insights into non-equilibrium thermodynamics

  • Arpit Thakur , Ashish Sharma , Rajeev Kumar EMAIL logo , Shubham Sharma ORCID logo EMAIL logo , Nagaraj Patil , Sumit Kanchan , V.K. Bupesh Raja ORCID logo , Abinash Mahapatro ORCID logo , Deepak Gupta und Ehab El Sayed Massoud
Veröffentlicht/Copyright: 19. Februar 2025
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Abstract

In this investigation, the principles of non-equilibrium thermodynamics are employed to investigate the implications of geometric parameters on engine performance and exhaust back pressure in catalytic converters. The effects of components utilized for engine exhaust management on exhaust back pressure and anomalous engine operation have been extensively studied. This study explores how the geometric parameters of catalytic converters influence back pressure in the exhaust manifold through a detailed numerical analysis. Five models of catalytic converter with different geometric parameters at the inlet section, outlet section, inlet cone angle, outlet cone angle, and porous zone were tested to determine the variations in back pressure. For the monolith, a porous region is used where inertia and viscosity are defined by Darcy’s law, and discrete channel simulation is performed using the “Reynolds-average Naiver-Stokes (RANS) equations”, k-ω turbulence model, and a pressure-based solver. The numerical findings revealed that back pressure increased by up to 15 % with the rise in exhaust gas velocity from 0 to 25 m/s. Among the five models, the optimal configuration reduced back pressure by approximately 20 % compared to the baseline model, primarily due to adjustments in the length of the porous zone and conical sections. The outcomes demonstrate that the back pressure rises as the velocity of exhaust gas rises, and the optimization of configurations is determined by the design of the porous zone and conical sections. The findings prove that the efficiency of catalytic converters is considerably enhanced through the role of transport processes of mass, momentum, and energy, as variations in geometric configurations have a substantial effect on back pressure. Ultimately, this research offers valuable insights that could lead to the development of more efficient catalytic converters, thereby enhancing the control of automotive emissions and sustainable environmental practices. Key contributions of this study include a systematic evaluation of back pressure variations across multiple geometries, offering a pathway for enhanced engine performance and reduced environmental impact. The results have practical implications in improving design methodologies for catalytic converters, with potential applications in real-world automotive manufacturing.


Corresponding authors: Rajeev Kumar, School of Mechanical Engineering, Lovely Professional University, Phagwara 144411, India, E-mail: ; and Shubham Sharma, Department of Technical Sciences, Western Caspian University, Baku, Azerbaijan; Centre for Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India; and Jadara University Research Center, Jadara University, Jordan. E-mail:

Funding source: Deanship of Scientific Research at King Khalid University

Award Identifier / Grant number: RGP2/28/44

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Conceptualization, AT, AS, RK, SK, SS; formal analysis, AT, AS, RK, SK, SS; investigation, AT, AS, RK, SK, SS; writing – original draft preparation, AT, AS, RK, SK, SS; writing – review and editing, NP, SK, VKBR, AM, DG, EESM; supervision, NP, SK, VKBR, AM, DG, EESM; project administration, NP, SK, VKBR, AM, DG, EESM; funding acquisition, NP, SK, VKBR, AM, DG, EESM. All authors have read and agreed to the published version of the manuscript.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors declare no competing interests.

  6. Research funding: The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RGP2/28/44.

  7. Data availability: My manuscript has no associate data.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijcre-2024-0220)


Received: 2024-11-09
Accepted: 2025-01-31
Published Online: 2025-02-19

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Heruntergeladen am 21.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijcre-2024-0220/html
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