# On the Accuracy of Turbulence Model Simulations of the Exhaust Manifold
## 1 Introduction  
The exhaust manifold is a fundamental component within the vehicle's infrastructure, serving the essential function of expelling harmful gases emanating from the engine (see [PERSON] et al. [1], [PERSON] et al. [2], and [PERSON] et al. [3]). The primary objective of this critical subsystem revolves around the reduction of noise and the effective control of emissions. In the context of a scientific article, understanding and optimizing the exhaust manifold's role is imperative for advancing both vehicle performance and environmental considerations. Turbulence is a complex phenomenon that is a challenge for precise modeling in CFD simulations. A range of turbulence models is available, each with its own limitations and assumptions, underscoring the importance of selecting the most suitable model for our study. Leveraging CFD methods allows for the simulation of flow patterns within the exhaust manifold, facilitating the optimization of its design parameters (see [PERSON] et al. [4] and [PERSON] et al. [5]). The primary aim of this study is to conduct a transient CFD analysis of an exhaust manifold using five turbulence models. The objective is to compare these models and identify the most accurate one for predicting velocity, temperature, and turbulent kinetic energy within the exhaust manifold. Many studies have been conducted to compare different turbulence models for different flow situations. [PERSON] et al. [6] discussed using CFD simulations to analyze an exhaust manifold's flow and emissions characteristics. The objective of the study was to find ways to decrease emissions by enhancing the design of the manifold. This research offers significant insights into the use of CFD simulations to optimize exhaust manifold designs to reduce emissions. The results of this study can be utilized to create more efficient and environmentally friendly automotive engines. [PERSON] and [PERSON] [7] compared the performance of five turbulence models when modeling the nearshore hydrodynamics of coral reefs using the open-source solver OlaFlow. They found that the k-omega SST turbulence model showed the best agreement with the field measurements, followed by the k-epsilon turbulence model. The standard k-omega model was unsuitable for modeling the coral reefs' nearshore hydrodynamics, due to its inability to capture complex flow patterns. [PERSON] et al. [8] underscore the critical importance of accurately predicting airflow around turbine rotors to optimize wind farm layout design. The study evaluates numerical turbulence models, including Reynolds-Averaged Navier Stokes (RANS) and two-equation transport models k-\(\varepsilon\) and k-\(\omega\), emphasizing their respective strengths and limitations. The findings indicate that the k-\(\omega\) model, particularly the combinatorial shear stress transport version, offers a comparative advantage in resolving eddies and addressing the closure problem. [PERSON] [9] compared two turbulence models, omega RSM and RNG k-\(\varepsilon\), to simulate a hydro cyclone used in mineral processing. The Eulerian-Eulerian approach was used to simulate water and solid particle flow. Both models were compared based on velocity field, pressure drop, and separation efficiency. The omega RSM model provided a more accurate prediction of the velocity field near the wall. [PERSON] et al. [10] compared a developed SST k-\(\omega\) turbulence model with other turbulence models for predicting turbulent slot jet impingement in heat transfer. CFD simulations were used, showing that the SST k-\(\omega\) turbulence model provided more accurate predictions of the heat transfer coefficient. The model captured primary features such as the jet impingement zone, the wall jet, and the recirculation zone. [PERSON] et al. [11] investigated the heat transfer characteristics of pipes with twisted tapes using CFD simulations and experimental validation. Twisted tapes promote turbulent flow and enhance heat transfer by creating vortices.