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Swirling flows are very dominant in applied technical problems, especially in IC engines, and their prediction requires rather sophisticated modeling. An adaptive low-pass filtering procedure for the modeled turbulent length and time scales is derived and applied to Menter' original k - ω SST turbulence model. The modeled length and time scales are compared to what can potentially be resolved by the computational grid and time step. If the modeled scales are larger than the resolvable scales, the resolvable scales will replace the modeled scales in the formulation of the eddy viscosity; therefore, the filtering technique helps the turbulence model to adapt in accordance with the mesh resolution and the scales to capture.

Cycle-To-Cycle Variability (CCV) must be properly considered when modeling the ignition process in SI engines operating with ultra-lean mixtures. In this work, a strategy to model the impact of the ignition type on the CCV was developed using the RANS approach for turbulence modelling, performing multi-cycle simulations for the power-cycle only. The spark-discharge was modelled through a set of Lagrangian particles, introduced along the sparkgap and interacting with the surrounding Eulerian gas flow. Then, at each discharge event, the velocity of each particle was modified with a zero-divergence perturbation of the velocity field with respect to average conditions. Finally, the particles velocity was evolved according to the Simplified Langevin Model (SLM), which keeps memory of the initial perturbation and applies a Wiener process to simulate the stochastic interaction of each channel particle with the surrounding gas flow.

The Lockheed Martin Low-Speed Wind Tunnel (LSWT) is a closed-return wind tunnel with two solid-wall test sections. This facility originally entered into service in 1967 for aerodynamic research of aircraft in low-speed and vertical/short take-off and landing (V/STOL) flight. Since this time, the client base has evolved to include a significant level of automotive aerodynamic testing, and the needs of the automotive clientele have progressed to include acoustic testing capability. The LSWT was therefore acoustically upgraded in 2016 to reduce background noise levels and to minimize acoustic reflections within the low-speed test section (LSTS). The acoustic upgrade involved detailed analysis, design, specification, and installation of acoustically treated wall surfaces and turning vanes in the circuit as well as low self-noise acoustic wall and ceiling treatment in the solid-wall LSTS.

Many studies have been carried out to optimize the aerodynamic performances of a single car or a single vehicle. In present days the traffic increases and sophisticated technologies are developing to guarantee the drivers safety, to minimize the fuel consumption and be more environmentally friendly. Within this research area a new technique that is being studied is Platooning: this means that different vehicles travel in a configuration that minimizes the aerodynamic drag and therefore the fuel consumption and the longitudinal space. In the present study platoons with different vehicles and configurations are taken into account, to analyze the influence of car shape and relative distance between the vehicles. The research has been carried out using CFD techniques to investigate the different flow fields around different platoons, while wind tunnel tests have been used to validate the results of the CFD simulations.

In the paper, a procedure to assess the quality of the shielding effect of wind barriers to protect large sided vehicles crossing the wake of a bridge pylon under cross wind conditions is proposed. The methodology is based on Multi-Body simulations of the response of the vehicle-driver system when it is subjected to the sudden change of the aerodynamic forces due to the wind-tower interaction. The aerodynamic forces that are instantaneously acting on the vehicle are computed according to a force distribution approach that relies on wind tunnel tests that may be performed on still scaled models. From the knowledge of the aerodynamic force distribution along the vehicle at different yaw angles and of the mean wind profile across the tower wake, the aerodynamic force, acting on the moving vehicle, is reconstructed at each time step taking into consideration the actual vehicle-driver dynamics.

The General Motors Reduced Scale Wind Tunnel Facility, which came into operation in the fall of 2015, is a new state-of-the-art scale model aerodynamic test facility that expands GM’s test capabilities. The new facility also increases GM’s aerodynamic testing through-put and provides the resources needed to achieve the growing demand for higher fuel economy requirements for next generation of vehicles. The wind tunnel was designed for a nominal model scale of 40%. The nozzle and test section were sized to keep wind tunnel interference effects to a minimum. Flow quality and other wind tunnel performance parameters are on par with or better than the latest industry standards. A 5-belt system with a long center belt and boundary layer suction and blowing system are used to model underbody flow conditions. An overhead probe traverse system is installed in the test section along with a model positioning robot used to move the model in an out of the test section.

The General Motors Aero Lab’s Full-Scale Wind Tunnel Facility, which came into operation in August of 1980[1], has undergone the significant upgrade of installing a state-of-the-art moving ground plane system. After almost four decades of continuous use the full-scale wind tunnel also received some significant maintenance to other areas, including a new heat exchanger, main fan overhaul, and replacement of the test section acoustic treatment. A 5-belt system was installed along with an integrated vehicle lift system. The center belt measures 8.5m long and can accommodate two belt widths of 1100mm and 950mm. Flow quality and other wind tunnel performance parameters were maintained to prior specifications which are on par with the latest industry standards [2]. The new 5-belt rolling road system maintains GM’s industry leading vehicle aerodynamic development and the improved acoustic panels ensure GM continues to develop vehicles with leading class acoustics.

The primary objective of the research discussed here was to compare the commercial computational fluid dynamics (CFD) software, CONVERGE, and a prevalent open-source code, OpenFOAM, with regard to their ability to predict spray and combustion characteristics. The high-fidelity data were obtained from the Engine Combustion Network (ECN) at Sandia National Laboratory in a constant-volume combustion vessel under well-defined, controlled conditions. The experiments and simulations were performed by using two diesel surrogate fuels (i.e., n-heptane and n-dodecane) under both non-reacting and reacting conditions. Specifically, ECN data on spray penetration, liquid length, vapor penetration, mixture fraction, ignition delay, and flame lift-off length (LOL) were used to validate both codes. Results indicate that both codes can predict the above experimental characteristics very well.

The OpenFOAM® CFD methodology is nowadays employed for simulation in internal combustion engines and a lot of work has been done for an appropriate description of all complex phenomena. At the moment in the RANS turbulence models available in the OpenFOAM® toolbox the turbulence modulation is not yet included, and the present work analyzes the predictive capabilities of the code in simulating high injection pressure fuel sprays after modeling the influence of the dispersed phase on the turbulence structure. Different experiments were employed for the validation. At first, non-evaporating diesel spray was considered in a constant volume and quiescent vessel. The validation was performed via the available experimental spray evolution in terms of penetrations and spatial/temporal fuel distributions. Then the Sandia combustion chamber was chosen for diesel spray simulation in non-reacting conditions.

Direct-injection technology represents today a very interesting solution to the typical problems that are generally encountered in SI, gas-fueled engines such as reduced volumetric efficiency, backfire and knock. However, development of suitable injection systems and combustion chamber geometry is necessary to optimize the fuel-air mixing and combustion processes. To this end, CFD models are widely applied even if the influence of the mesh structure, numerical and turbulence models on the computed results are still matter of investigation. In this work, a numerical methodology for the simulation of the gas exchange and injection processes in gas-fueled engines was developed within the Lib-ICE framework, which is a set of libraries and applications for IC engine modeling developed using the OpenFOAM® technology. The gas exchange and fuel injection processes were simulated into a four-valve, pent-roof hydrogen-fueled engine with optical access.

This paper presents a computational fluid dynamics (CFD) model for predicting power losses associated with churning of oil by gears or other similar rotating components. The modeling approach and parameters are optimized to ensure the accuracy, robustness, and computational efficiency of these predictions. These studies include a look at two types of mesh and a turbulence model selection. The focus is on multiple reference frame (MRF) modeling technique for its computational efficiency advantage. Model predictions are compared to previously published experimental data [1] under varying operating conditions typical for an automotive transmission application. The model shows good agreement with the hardware both quantitatively and qualitatively, capturing the trends with speed and submersion level. The paper concludes with presenting some key lessons learned, and recommendation for future work to ultimately build a highly reliable tool as part of the virtual product development.

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

This study examines the impact of slip in aero-thermal conditions of supercooled large droplets (SLD) produced in an Icing Wind Tunnel (IWT) on the ice accretion characteristics. The study identifies potential biases in the SLD model development based on IWT data and numerical predictions that assume the SLD to be in aerothermal equilibrium with the IWT airflow. To obtain realistic temperature and velocity data for each droplet size class in the test section of the Braunschweig Icing Wind Tunnel (BIWT), a Lagrangian droplet tracking solver was used within a Monte Carlo framework. Results showed that SLDs experience considerable slips in velocity and temperature due to their higher inertia and short residence time in the Braunschweig IWT. Large droplets were found to be warmer and slower than the flow in the test section, with larger droplets experiencing larger aerothermal slips.

Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Ducted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling.

Very little is currently known of the aerodynamic interaction between neighboring cycloidal rotors. Such knowledge is, however, of crucial importance to tune the controller and rotor disposition of a cyclogiro aircraft. Thus, a three-dimensional computational fluid dynamics (CFD) model is developed, validated, and used to analyze the D-Dalus L1 four-rotor unmanned aircraft operating under several configurations. The model solves the Euler equations using the OpenFOAM toolbox in order to provide fast results on a desktop computer. Validation is performed against thrust forces and flow streamlines obtained during wind tunnel experiments at various flight velocities. Numerical results from CFD match the trends of the experimental data. Flow behavior matches the video footage of the wind tunnel tests. Although boundary layer effects are neglected, satisfactory results are obtained both qualitatively and quantitatively.

Turbulence modeling for fuel spray simulation plays a prominent role in the understanding of the flow behavior in Internal Combustion Engines (ICEs). Currently, a lot of research work is actively spent on Large Eddy Simulation (LES) turbulence modeling as a replacement option of standard Reynolds averaged approaches in the Eulerian-Lagrangian spray modeling framework, due to its capability to accurately describe flow-induced spray variability and to the lower dependence of the results on the specific turbulence model and/or modeling coefficients. The introduction of LES poses, however, additional questions related to the implementation/adaptation of spray-related turbulence sources and to the rise of conflicting numerics and grid requirements between the Lagrangian and Eulerian parts of the simulated flow.

The paper focuses on the development of a mesh moving method based on non-conformal topologically changing grids applied to the simulation of IC engines, where the prescribed motion of piston and valves is accomplished by rigidly translating the sub-domain representing the moving component. With respect to authors previous work, a more robust and efficient algorithm to handle the connectivity of non-conformal interfaces and a mesh-motion solver supporting multiple layer addition/removal of cells, to decouple the time-step constraints of the mesh motion and of the fluid dynamics, has been implemented as a C++ library to extend the already existing classes for dynamic mesh handling of the finite-volume, open-source CFD code OpenFOAM®. Other new features include automatic decomposition of large multiple region domains to preserve processors load balance with topological changes for parallel computations and additional tools for automatic preprocessing and case setup.

Metallic open-cell foams have proven to be valuable for many engineering applications. Their success is mainly related to mechanical strength, low density, high specific surface, good thermal exchange, low flow resistance and sound absorption properties. The present work aims to investigate three principal aspects of real foams: the geometrical characterization, the flow regime characterization, the effects of the pore size and the porosity on the pressure drop. The first aspect is very important, since the geometrical properties depend on other parameters, such as porosity, cell/pore size and specific surface. A statistical evaluation of the cell size of a foam sample is necessary to define both its geometrical characteristics and the flow pattern at a given input velocity. To this purpose, a procedure which statistically computes the number of cells and pores with a given size has been implemented in order to obtain the diameter distribution.