Browse Topic: Computational fluid dynamics (CFD)
ABSTRACT The both CFD (Computational Fluid Dynamics) and thermal analyses are used to predict a vehicle system thermal performance during the design development. The vehicle wall temperatures and compartments temperatures under various climatic conditions are predicted in MuSES thermal analyses. The temperature and air flow distributions inside the vehicle compartment are predicted in Star CCM+ CFD analyses. Recently, GDLS, Thermal Analytics, and CD-adapco jointly developed a CFD thermal analysis panel. This panel can be used to apply all boundary conditions to MuSES model and StarCCM+ CFD model by a few button clicks. It can map convection coefficients predicted in CFD analysis to the MuSES model boundaries; and vise versa, map wall temperatures and heat rates predicted in MuSES models to the boundaries in StarCCM+ models. Using this panel, the MuSES analysis and StarCCM+ analysis can be coupled to predict vehicle thermal performance with higher accuracy. Besides, most model inputs
ABSTRACT This paper examines the current state of scalable CFD for high-performance computing (HPC) clusters at industry-scale, and provides a review of novel technologies that can enable additional levels of CFD parallelism beyond today’s conventional approach. Recent trends in HPC offer opportunities for CFD solution performance increases from the use of parallel file systems for parallel I/O, and a second level of solver parallelism through hybrid CPU-GPU co-processing
The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies has significantly changed various industries. This study demonstrates the application of a Convolutional Neural Network (CNN) model in Computational Fluid Dynamics (CFD) to predict the drag coefficient of a complete vehicle profile. We have developed a design advisor that uses a custom 3D CNN with a U-net architecture in the DEP MeshWorks environment to predict drag coefficients (Cd) based on car shapes. This model understands the relationship between car shapes and air drag coefficients calculated using computational fluid dynamics (CFD). The AI/ML-based design advisor feature has the potential to significantly decrease the time required for predicting drag coefficients by conducting CFD calculations. During the initial development phase, it will serve as an efficient tool for analyzing the correlation between multiple design proposals and aerodynamic drag forces within a short time frame
This SAE Aerospace Information Report (AIR) contains information on the thermal design requirements of airborne avionic systems used in military airborne applications. Methods are explored which are commonly used to provide thermal control of avionic systems. Both air and liquid cooled systems are discussed
Effective thermal management is crucial for vehicles, impacting both passenger comfort and safety, as well as overall energy efficiency. Electric vehicles (EVs) are particularly sensitive to thermal considerations, as customers often experience range anxiety. Improving efficiency not only benefits customers by extending vehicle range and reducing operational costs but also provides manufacturers with a competitive edge and potential revenue growth. Additionally, efficient thermal management contributes to minimizing the environmental impact of the vehicle throughout its lifespan. Digital twins have gained prominence across various industries due to their ability to accelerate development while minimizing testing costs. Some applications have transitioned to comprehensive three-dimensional models, while others employ model reduction techniques or hybrid approaches that combine different modeling methods. The discovery of unknown working mechanisms, more efficient and effective control
Nowadays, Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are becoming popular globally due to increasing pollution levels in the environment and expensive conventional non-renewable fuels. Li-ion battery EV’s have gained attention because of their higher specific energy density, better power density and thermal stability as compared to other cell chemistries. Performance of the Li-ion battery is affected by temperatures of the cells. For Li-ion cells, optimum operating temperature range should be between 15-35 °C [1]. Initially, small battery packs which are cooled by air were used but nowadays, large battery packs with high power output capacities being used in EV’s for higher vehicle performance. Air based cooling system is not sufficient for such batteries, hence, liquid coolant based cooling systems are being introduced in EV’s. Computational Fluid Dynamics (CFD) simulation can be used to get better insight of cell temperature inside battery. But it is complex, time
To understand effect of thermal hazards of LIBs during TR event, it is important to study flame propagation behaviour of LIBs during storage and transport applications. The process of flame propagation involves complex phenomena of gas phase behavior of LIBs. Present paper attempts a numerical investigation to portray this complex phenomenon. This paper investigates 18650 lithium cell considering two different chemistries NMC and LFP. A 3D numerical CFD model has been constructed to predict the gas phase behavior, threshold internal pressure, and cell gas venting of an 18650-lithium cell under thermal runaway conditions. The gas phase processes are modelled using the 4-equation thermal abuse model, while the cell's venting mechanism is modelled using Darcy's equation. Present work is divided into two parts: 1) Venting gas Internal pressure prediction 2) modeling thermal runaway event. Both procedures are implemented on two different cell chemistries to understand and evaluate following
Heavy-duty vehicle regulations from the European Union specify a 43% carbon emissions reduction by 2030. The EU's carbon emissions reduction mandate climbs to 64% by 2035 before soaring to 90% by 2040. “The hydrogen combustion engine has a role to play to reduce CO2 emissions,” said Vincent Giuffrida, CFD engineer for IFP Energies novellas (IFPEN), a Rueil-Malmaison, France-headquartered public research and innovation organization. Giuffrida and IFPEN colleague and research engineer Olivier Colin were the presenters for a webinar addressing the “Development of a Dedicated Hydrogen Combustion System for Heavy-Duty Applications” in July. The webinar was hosted by Madison, Wisconsin-headquartered Convergent Science, whose CONVERGE CFD software simulates three-dimensional fluid flows. Features of the CFD software include autonomous meshing, complex moving geometries, a detailed chemical kinetics solver, advanced physical models, conjugate heat transfer model, fluid structure interaction
Liquid jet atomization is one of the key processes in many engineering applications, such as IC engines, gas turbines, and the like, to name a few. Simulating this process using a pure Eulerian or a pure Lagrangian framework has its own drawbacks. The Eulerian–Lagrangian spray atomization (ELSA) modeling seems like a viable alternative in such scenarios. ELSA simulations consist of solving an additional transport equation for the surface area density (Σ) of the issuing jet. In this study we have proposed a dynamic approach to compute the turbulent timescale constant (α1), which appears in the source of Σ-transport equation and is responsible for restoring the surface area back to its equilibrium. The dynamic approach involves an analytical computation of the turbulent timescale constant (α1), thereby eliminating the need for ad hoc adjustments to surface area values during computational fluid dynamics (CFD) simulations. Unlike previous research which suggests using constant values in
This study aims to design a supersonic ejector, referred to as a liquid spray gun, with a simple operating procedure for producing an aerosol spray with adjustable droplet size distributions. A CFD model was developed to determine the influence of nozzle exit position and the primary air pressure on the supersonic patterns formed within the ejectors, providing a valuable insight into their internal physics. Based on the single-phase numerical results, at an air primary pressure of 2 bar, the flow may not reach a choking condition, possibly resulting in unstable ejector operation. However, at pressures exceeding 5 bar, the jet patterns emerging from the primary nozzle cause flow separation or the formation of vortex rings. This phenomenon leads to a flow configuration comparable to the diameter of the mixing tube, thereby reducing the available area for entrainment of suction flow. The suitable ejector was identified with a nozzle exit position of 13 mm and a primary pressure ranging
Summary: With the electrification of powertrains, noise inside vehicles has reached very satisfactory levels of silence. Powertrain noise, which used to dominate on combustion-powered vehicles, is now giving way to other sources of noise: rolling noise and wind noise. These noises are encountered when driving on roads and freeways and generate considerable fatigue on long journeys. Wind noise is the result of turbulent and acoustic pressure fluctuations created within the flow. They are transmitted to the passenger compartment via the vibro-acoustic excitation of vehicle surfaces such as windows, floorboards, and headlining. Because of their mechanical properties, windows are the surfaces that transmit the most noise into the passenger compartment. Even though acoustic pressure is much weaker in amplitude than turbulent pressure fluctuations, it still accounts for most of the noise perceived by occupants. This is because its wavelength is closer to the characteristic wavelengths of
Items per page:
50
1 – 50 of 4389