Search Results

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

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.

We present a framework for the robust optimization of the heat flux distribution for an anti-ice electro-thermal ice protection system (AI-ETIPS) and iced airfoil performance analysis under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud i.e. the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices i.e., the static temperature probe, uncertain parameters are modeled as uniform random variables. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work. Two bi-objective deterministic optimizations aim to minimize power consumption and either minimize ice formations or the iced airfoil drag coefficient.

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.

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.

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.

In the next years, the upcoming emission legislations are expected to introduce further restrictions on the admittable level of pollutants from vehicles measured on homologation cycles and real drive tests. In this context, the strict control of pollutant emissions at the cold start will become a crucial point to comply with the new regulation standards. This will necessarily require the implementation of novel strategies to speed-up the light-off of the reactions occurring in the after-treatment system, since the cold start conditions are the most critical one for cumulative emissions. Among the different possible technological solutions, this paper focuses on the evaluation of the potential of a burner system, which is activated before the engine start. The hypothetical burner exploits the lean combustion of an air-gasoline mixture to generate a high temperature gas stream which is directed to the catalyst section promoting a fast heating of the substrate.

The paper investigates the dynamics of the tire and brake during hard braking or wheel locking, from the view point of a brake manufacturer. A new test rig, named BRAD (BRembo Automotive Dynamometer) is presented which measures the forces acting both at the brake and at the tire-ground interface. Lateral forces are not measured. In the test rig, the ground is represented by a drum. The features of the test rig are presented. The measurement accuracy is declared. The first result is that, near wheel locking, a substantial part of the braking power is generated by the tire and not by the brake. The test rig quantifies such a partitioning of brake power, which is important for current and future electric motorsport activities. Some 30% of the braking power is due to tire during hard braking. The second result is that, due to such important braking power at the tire, the tire is heated up, which increases considerably the maximum friction.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

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.

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.

Partially premixed combustion (PPC) can be applied to decrease emissions and increase fuel efficiency in direct injection, compression ignition (DICI) combustion engines. PPC is strongly influenced by the mixing of fuel and oxidizer, which for a given fuel is controlled mainly by (a) the fuel injection, (b) the in-cylinder flow, and (c) the geometry and dynamics of the engine. As the injection timings can vary over a wide range in PPC combustion, detailed knowledge of the in-cylinder flow over the whole intake and compression strokes can improve our understanding of PPC combustion. In computational fluid dynamics (CFD) the in-cylinder flow is sometimes simplified and modeled as a solid-body rotation profile at some time prior to injection to produce a realistic flow field at the moment of injection. In real engines, the in-cylinder flow motion is governed by the intake manifold, the valve motion, and the engine geometry.

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.

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.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

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.

The dynamics and evolution of turbulent structures inside an engine-like geometry are investigated by means of Large Eddy Simulation. A simplified configuration consisting of a flat-top cylinder head with a fixed, axis-centered valve and low-speed piston has been simulated by the finite volume CFD code OpenFOAM®; the standard version of the software has been extended to include the compressible WALE subgrid-scale model, models for the generation of synthetic turbulence, some improvements to the mesh motion strategy and algorithms for LES data post-processing. In order to study both the initial transient and the quasi- steady operating conditions, ten complete engine cycles have been simulated. Phase and spatial averages have been performed over cycles three to ten in order to extract first and second moment of velocity; these quantities have then been used to validate the numerical procedure by comparison against experimental data.

In this study two different simulation approaches to large eddy simulation of spark-ignition engines are compared. Additionally, some of the simulation results are compared to experimentally obtained in-cylinder velocity measurements. The first approach applies unstructured grids with an automated meshing procedure, using OpenFoam and Lib-ICE with a mapping approach. The second approach applies the efficient in-house code PsiPhi on equidistant, Cartesian grids, representing walls by immersed boundaries, where the moving piston and valves are described as topologically connected groups of Lagrangian particles. In the experiments, two-dimensional two-component particle image velocimetry is applied in the central tumble plane of the cylinder of an optically accessible engine. Good agreement between numerical results and experiment are obtained by both approaches.

A new electric powertrain and axle for light/medium trucks is presented. The indoor testing and the simulation of the dynamic behavior are performed. The powertrain and axle has been produced by Streparava and tested at the Laboratory for the Safety of Transport of the Politecnico di Milano. The tests were aimed at defining the multi-physics perfomance of the powertrain and axle (efficiency, acceleration and braking, temperature and NVH). The whole system for indoor tests was composed by the powertrain and axle (electric motor, driveline, suspensions, wheels) and by the test rig (drums, driveline and electric motor). The (driving) axle was positioned on a couple of drums, and the drums provided the proper torques to the wheels to reproduce acceleration and braking. Additionally a cleat fixed on one drum excited the vibration of the suspensions and allowed assessing NVH performance. The simulations were based on a special co-simulation between 1D-AMESIM and VIRTUAL.LAB.