Work

Advanced Computational Investigation of Brush Seal Thermo-Fluid–Mechanical Performance Through Novel Porous Media Coefficient Derivation

Year: 2026

Type: article

Abstract: Brush seals represent the most effective sealing technology, offering 5 to 10 times lower leakage flow rates, resulting in an 80% to 90% increase in sealing efficiency. However, key challenges remain in optimizing brush seal performance, including managing high frictional heat, maintaining consistent leakage flow, and preventing mechanical deformation failures within the bristle pack. This study uses a fluid–mechanical coupling method to establish and refine numerical investigation procedures. Using porous media and local thermal non-equilibrium (LTNE) approaches, the effects of the pressure ratio on seal performance are analyzed. The results reveal that the difference between the maximum directional and total deformations is 0.9108 mm, with the total deformation being approximately 79,666% larger than the directional deformation. These findings highlight that the bristle pack must be designed with primary consideration of total deformation to enhance performance and efficiency. The proposed methodologies enable more robust comparative evaluations of alternative brush seal configurations, including two-stage bristle packs and inline structural models. This facilitates the identification of optimized structures that minimize leakage, enhance energy dissipation, and improve the overall seal performance, thereby advancing the porous media model from a general approximation to a design-optimized tool.

Source: Computation

DOI: 10.3390/computation14040083

Authors: Altyib Abdallah Mahmoud Ahmed, Juan Wang, Meihong Liu, Aboubaker I. B. Idriss, Abdelgalal O. I. Abaker

Institutions: Kunming University of Science and Technology, University of Nyala, Northeast Forestry University, King Khalid University

Language: English

Topic: Heat and Mass Transfer in Porous Media

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,172

Funder: King Khalid University