In this study, we present a comprehensive analysis of the temperature field distribution in an engine cylinder block and cylinder head using a bidirectional fluid-structure coupling (FSI) approach. By incorporating heat flux correction based on comparative statistical analysis, we aim to enhance the accuracy of simulation results and validate them against experimental measurements. The methodology, results, and implications for engine design are discussed in detail below.
1. Introduction
The thermal management of internal combustion engines is critical for ensuring durability, efficiency, and performance. High-temperature gases in combustion chambers, coupled with heat transfer through exhaust systems, impose significant thermal stresses on the engine cylinder block and cylinder head. Traditional methods for temperature field analysis often fail to account for the complex interplay of fluid dynamics and structural heat transfer, leading to inaccuracies in predictions.
This study addresses these challenges by employing a bidirectional FSI framework, integrating computational fluid dynamics (CFD) for fluid domains and finite element analysis (FEA) for solid components. Key innovations include the application of heat flux correction coefficients derived from comparative analysis between 3D and 1D thermal models. The validated results demonstrate the reliability of this approach for optimizing the design of engine cylinder blocks and heads.
2. Methodology
2.1 Bidirectional Fluid-Structure Coupling
The bidirectional FSI method couples the energy exchange between fluid and solid domains. At the interface, heat transfer equilibrium is governed by:Kcond∂T∂n=qconv=hconv(Tf−Ts)Kcond∂n∂T=qconv=hconv(Tf−Ts)
where KcondKcond is the thermal conductivity of the solid, hconvhconv is the convective heat transfer coefficient, TfTf is the fluid temperature, and TsTs is the solid surface temperature.
For fluid-side analysis, the k−ϵk−ϵ turbulence model resolves convective heat transfer:∂∂t(ρk)+∂∂xi(ρkui)=∂∂xj[(μ+μtσk)∂k∂xj]+Gk+Gb−ρϵ−YM+Sk∂t∂(ρk)+∂xi∂(ρkui)=∂xj∂[(μ+σkμt)∂xj∂k]+Gk+Gb−ρϵ−YM+Sk∂∂t(ρϵ)+∂∂xi(ρϵui)=∂∂xj[(μ+μtσϵ)∂ϵ∂xj]+C1ϵϵk(Gk+C3ϵGb)−C2ϵρϵ2k+Sϵ∂t∂(ρϵ)+∂xi∂(ρϵui)=∂xj∂[(μ+σϵμt)∂xj∂ϵ]+C1ϵkϵ(Gk+C3ϵGb)−C2ϵρkϵ2+Sϵ
where kk is turbulent kinetic energy, ϵϵ is dissipation rate, GkGk and GbGb represent turbulence generation terms, and σkσk, σϵσϵ, C1ϵC1ϵ, C2ϵC2ϵ, and C3ϵC3ϵ are model constants.
For the solid domain (engine cylinder block and head), steady-state heat conduction is modeled as:∂∂x(kx∂T∂x)+∂∂y(ky∂T∂y)+∂∂z(kz∂T∂z)=0∂x∂(kx∂x∂T)+∂y∂(ky∂y∂T)+∂z∂(kz∂z∂T)=0
2.2 Heat Flux Correction
Discrepancies between 3D CFD and 1D thermal models necessitated heat flux adjustments. Key regions—combustion chamber, exhaust ports, and cylinder liners—were analyzed. The correction coefficient αα is defined as:α=Q1DQ3Dα=Q3DQ1D
where Q1DQ1D and Q3DQ3D are heat flux values from 1D and 3D models, respectively.
Table 1: Heat Flux Comparison and Correction Coefficients
| Region | 3D Heat Flux (kW) | 1D Heat Flux (kW) | Correction Coefficient (αα) |
|---|---|---|---|
| Combustion Chamber | 1.32 | 2.20 | 1.67 |
| Exhaust Port | 16.00 | 18.20 | 1.14 |
| Cylinder Liner | 2.54 | 2.20 | 0.87 |
3. Temperature Field Simulation
3.1 Cylinder Head Analysis
The highest temperature (214°C) was observed near the exhaust valve bridge, while the intake valve bridge registered 180°C. A temperature gradient of 34°C between intake and exhaust regions highlighted significant thermal stress risks.
3.2 Engine Cylinder Block Analysis
In the engine cylinder block, the peak temperature (177°C) occurred at the inter-cylinder top surface. A secondary temperature peak emerged at 38 mm depth due to coolant flow limitations.
4. Experimental Validation
4.1 Thermocouple Measurements
Thermocouples (1.5 mm diameter) were embedded at 18 critical locations (7 in the cylinder head, 11 in the engine cylinder block). Sensor placement ensured direct contact with target surfaces to minimize measurement errors.
4.2 Simulation vs. Experimental Results
Table 2: Cylinder Head Temperature Validation
| Region | Sensor | Simulated Temp. (°C) | Measured Temp. (°C) | Error (%) |
|---|---|---|---|---|
| Combustion Chamber | 1 | 186.4 | 194.2 | 4.2 |
| Combustion Chamber | 2 | 184.2 | 190.3 | 3.3 |
| Combustion Chamber | 3 | 186.0 | 194.6 | 4.6 |
| Combustion Chamber | 4 | 185.7 | 194.7 | 4.8 |
| Exhaust Port | 5 | 162.7 | 161.2 | -0.9 |
| Exhaust Port | 6 | 183.3 | 189.5 | 3.4 |
| Exhaust Port | 7 | 168.2 | 168.4 | 0.1 |
Table 3: Engine Cylinder Block Temperature Validation
| Sensor | Simulated Temp. (°C) | Measured Temp. (°C) | Error (%) |
|---|---|---|---|
| 1 | 169.0 | 161.6 | -4.1 |
| 2 | 168.9 | 162.2 | -4.1 |
| 3 | 165.7 | 161.5 | -2.4 |
| 4 | 164.2 | 160.2 | -2.4 |
| 5 | 161.6 | 166.1 | 2.5 |
| 6 | 162.3 | 162.5 | 0.1 |
| 7 | 158.2 | 137.2 | -0.1 |
| 8 | 129.5 | 134.1 | 3.8 |
| 9 | 132.8 | 133.7 | 0.7 |
| 10 | 132.8 | 133.1 | 0.8 |
| 11 | 137.6 | 143.2 | 3.9 |
Maximum errors for the cylinder head and engine cylinder block were 4.8% and 4.1%, respectively, with minimum errors below 0.1%.
5. Discussion
5.1 Accuracy of Heat Flux Correction
The correction method effectively bridged discrepancies between simulation and reality. For instance, the combustion chamber required upward adjustment (α=1.67α=1.67) due to underestimated 3D heat flux, while the cylinder liner necessitated downward correction (α=0.87α=0.87).
5.2 Thermal Stress Implications
The temperature gradient in the engine cylinder block and head—particularly near exhaust valves—underscores the need for optimized cooling designs. Regions with gradients exceeding 30°C are prone to fatigue cracking, demanding material upgrades or geometry modifications.
5.3 Limitations and Future Work
Sensor placement constraints in complex geometries (e.g., cylinder head) limited data resolution. Future studies could incorporate transient thermal analysis and phase-change cooling effects.
6. Conclusion
This study demonstrates the efficacy of bidirectional FSI combined with heat flux correction for temperature field analysis in engine cylinder blocks and heads. With maximum errors below 5%, the method offers a reliable tool for thermal management in engine design. The engine cylinder block exhibited robust thermal performance, while the cylinder head required targeted cooling enhancements. These insights pave the way for advanced cooling strategies, ensuring durability and efficiency in next-generation engines.