Search Results

We propose a novel Split Ring Resonator (SRR) metamaterial capable of achieving a total (or complete) bandgap in the material’s band structure, thereby reflecting airborne and structure-borne noise in a targeted frequency range. Electric Vehicles (EVs) experience tonal excitation arising from switching frequencies associated with motors and inverters, which can significantly affect occupant perception of vehicle quality. Recently proposed metamaterial designs reflect airborne noise and structure-borne transverse waves over a band of frequencies, but do not address structure-borne longitudinal waves in the same band. To achieve isolation of acoustic, transverse, and longitudinal elastic waves associated with tonal frequencies, we propose a metamaterial super cell with transverse and longitudinal resonant frequencies falling in a total bandgap. We calculate the resonant frequencies and corresponding mode shapes using finite element (FE) modal analysis.

Conventional spark-ignition engines are currently incapable of meeting rising customer performance demands while complying with even stringent pollutant-emissions regulations. As a result, innovative ignition systems are being developed to accomplish these targets. Radio-Frequency corona igniters stand out for their ability to accelerate early flame growth speed by exploiting the combined action of kinetic, thermal and transport effects. Furthermore, a volumetric discharge enables the promotion of combustion over a wide area, as opposed to the local ignition of traditional spark. The present work wants to evaluate the advantages of a Streamer-type Radio Frequency corona discharge at about 100 kHz with respect to those of traditional spark igniter.

Emission legislation for light and heavy duty vehicles is requiring a drastic reduction of exhaust pollutants from internal combustion engines (ICE). Achieving a quick heating-up of the catalyst is of paramount importance to cut down cold start emissions and meet current and new regulation requirements. This paper describes the development and the basic characteristics of a novel burner for diesel engines exhaust systems designed for being activated immediately at engine cold start or during vehicle cruise. The burner is comprised of a swirled fuel dosing system, an air system, and an ignition device. The main design characteristics are presented, with a detailed description of the atomization, air-fuel interaction and mixture formation processes. An atomizer prototype has been extensively analyzed and tested in various conditions, to characterize the resulting fuel spray under cold-start and ambient operating conditions.

The goal of mitigating climate change has driven research to the use of carbon-free energy sources. In this regards, green hydrogen appears as one of the best options, however, its storage remains difficult and expensive. Indeed, there is room to consider the use of ammonia (an efficient hydrogen carrier) directly as a fuel for internal combustion engines or gas turbines. Currently, there are very few works in the literature describing liquid ammonia sprays, both from experimental and modeling point of view, and especially dealing with flash-boiling conditions. In this research work, the direct injection ammonia spray is modeled with the Lagrangian particle approach, building up a numerical model within the OpenFOAM framework, for transient analyses using the U-RANS approach.

Computational fluid dynamics is used with the aim to gain further insights of the hydrogen injection process in internal combustion engines. To this end, three-dimensional RANS simulations of hydrogen under-expanded jets under a variety of injection pressures and temperatures and chamber backpressure are performed. A numerical framework that accounts for real-fluid effects is used which includes accurate non-linear mixing rules for thermodynamic and transport properties with multiple species. Jet formation process, transition to turbulent regime, and mixing process are investigated which are key aspects for the design of efficient injection and combustion. Different simulations are discussed to investigate the structures in the near field, such as Mach disk, barrel, and reflected shocks. It is found that for direct injection applications, especially in high back-pressure cases, accounting for real fluid behavior of hydrogen-air mixtures is important for accurate predictions.

An intelligent connected vehicle (ICV) swarm system that includes N vehicles is considered. Based on the special properties of potential functions, a kinematic model describing the swarm performances is proposed, which allows all vehicles to enclose the tracking target and show both tracking and formation characteristics. Treating the performances as the desired constraints, the analytical form of constraint forces can be obtained inspired by the Udwadia-Kalaba approaches. A special approach of uncertainty decomposition to deal with uncertain interferences is proposed, and a switching-type robust control method is addressed for each vehicle agent in the swarm system. The features and validity of the addressed control are demonstrated in the numerical simulations.

Emission legislation for passenger cars is requiring a drastic reduction of exhaust pollutants from internal combustion engines (ICE). In this framework, achieving a quick heating-up of the catalyst is of paramount importance to cut down the cold start emissions and meet future regulation requirements. This paper describes the development and the basic characteristics of a novel burner for gasoline engines exhaust systems designed for being activated immediately at engine cold start. The burner is comprised of a fuel injector, an air system, and an ignition device. The design of the combustion chamber is first presented, with a description of the air-fuel interactions and mixture formation processes. Swirl is used along with a flame-holder concept to anchor the flame at the mixer exit. Spray-swirl and spray-walls interaction are also discussed. Computational Fluid Dynamics (CFD) analyses have been used to investigate these aspects.

Ducted Fuel Injection (DFI) is a new technology recently developed with the aim of reducing soot emission formation in diesel compression ignition engines. DFI concept consists of the injection of fuel spray through a small duct located downstream of the injector nozzle leaving a certain gap, the so-called Stand-off distance. Currently, CFD modelers have investigated its performance using classical spray modeling techniques such as the Discrete Drops Method (DDM). However, as discussed in the literature, this type of technique is inappropriate when applied to dense jets as those occurring in diesel sprays, especially in the near-nozzle region (where the duct is placed). Therefore, considering a more appropriate modeling technique for such a problem is mandatory. In this research work, an Eulerian single-fluid diffuse-interface model called Σ-Y and implemented in the OpenFOAM framework is utilized for the simulation of non-reacting conditions.

Close-coupled aftertreatment systems (ATS) for automotive Diesel engines composed of DOC and SCR offer a significant potential in terms of pollutant emission control capability even with the introduction of more aggressive driving cycles and rigorous limits for type-approval tests. This is particularly important for incoming certification standards where the forecast is showing a trade-off towards ultra-low NOx emissions values. As the SCR system NOx conversion capability largely relies on both the UWS mixing device and on NOx sensors used to detect the actual NH3 slip and residual NOx concentration, developing numerical simulation tools for the analysis of the actual flow pattern and species concentration over peculiar sections of the exhaust system is crucial to support the ATS development process.

Currently, conventional spark-ignition engines are unfit to satisfy the growing customer requirements on efficiency while complying with the legislations on pollutant emissions. New ignition systems are being developed to extend the engine stable operating range towards increasing lean conditions. Among these, the Radio-Frequency corona igniters represent an interesting solution for the capability to promote the combustion in a much wider region than the one involved by the traditional spark channel. Moreover, the flame kernel development is enhanced by means of the production of non-thermal plasma, where low-temperature active radicals are ignition promoters. However, at low pressure and at high voltage the low temperature plasma benefits can be lost due to occurrences of spark-like events. Recently, RF barrier discharge igniters (BDI) have been investigated for the ability to prevent the arc formation thanks to a strong-breakdown resistance.

Nowadays internal combustion engines can operate under lean combustion conditions to maximize efficiency, as long as combustion stability is guaranteed. The robustness of combustion initiation is one of the main issues of actual spark-ignition engines, especially at high level of excess-air or dilution. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity. During the ignition process, the excessive charge motion can hinder the spark discharge and eventually cause a misfire. In this perspective, the interaction between the igniter and the flow field is a fundamental aspect which still needs to be explored in more detail to understand how the combustion originates and develops. In this work, a combined experimental and numerical study is carried out to investigate the flow field around the spark gap, and its effect on the spark discharge evolution.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

Among plasma-assisted ignition technologies, the Radio-Frequency (RF) corona family represents an interesting solution for the ability to extend the engine operating range. These systems generate transient, non-thermal plasma, which is able to enhance the combustion onset by means of thermal, kinetic and transport effects. Streamer-type RF corona discharge, at about 1 MHz, ignites the air-fuel mixture in multiple filaments, resulting in many different flame kernels. The main issue of this system is that at high electrode voltage and low combustion chamber pressure a transition between streamer and arc easily occurs: in this case transient plasma benefits are lost. A barrier discharge igniter (BDI), supplied with the same RF energy input, instead, is more breakdown-resistant, so that voltage can be raised to higher levels. In this work, a streamer-type RF corona igniter and a BDI were tested in a single-cylinder optical engine fueled with gasoline.

Spray modeling techniques have evolved from the classic DDM (Discrete Drops Method) approach, where the continuous liquid jet is discretized into “drops” or “parcels” till advanced spray models often based on Eulerian approaches. The former technique, although computationally efficient, is essentially inadequate in highly dense jets, as in the near nozzle region of compression ignition engines, while the latter could lead to extreme levels of computational effort when resolved interface capturing methods, such as VoF (Volume of Fluids) and LS (Level-Set) types, are used. However, in a typical engineering calculation, the mesh resolution is considerably coarser than in these high fidelity computations. If one presumes that these interfacial details are far smaller than the mesh size, smoothing features over at least one cell ultimately results in a diffuse-interface treatment in a Eulerian framework.

In-vehicle infotainment (IVI) platforms are getting increasingly connected. Besides OEM apps and services, the next generation of IVI platforms are expected to offer integration of third-party apps. Under this anticipated business model, vehicular sensor and event data can be collected and shared with selected third-party apps. To accommodate this trend, Google has been pushing towards standardization among proprietary IVI operating systems with their Android Automotive platform which runs natively on the vehicle’s IVI platform. Unlike Android Auto’s limited functionality of display-projecting certain smartphone apps to the IVI screen, Android Automotive will have access to the in-vehicle network (IVN), and will be able to read and share various vehicular sensor data with third-party apps. This increased connectivity opens new business opportunities for both the car manufacturer as well as third-party businesses, but also introduces a new attack surface on the vehicle.

Hybrid-electric gas turbine generators are considered a promising technology for more efficient and sustainable air transportation. The Ohio State University is leading the NASA University Leadership Initiative (ULI) Electric Propulsion: Challenges and Opportunities, focused on the design and demonstration of advanced components and systems to enable high-efficiency hybrid turboelectric powertrains in regional aircraft to be deployed in 2030. Within this large effort, the team is optimizing the design of the battery energy storage system (ESS) and, concurrently, developing a supervisory energy management strategy for the hybrid system to reduce fuel burn while mitigating the impact on the ESS life. In this paper, an energy-based model was developed to predict the performance of a battery-hybrid turboelectric distributed-propulsion (BHTeDP) regional jet.

Vertical takeoff and landing vehicle platforms with many small rotors are gaining importance for small UAVs as well as distributed electric propulsion for larger vehicles. To predict vehicle performance, it must be possible to gauge interaction effects. These rotors operate in the less-known regime of low Reynolds number, with different blade geometry. As a first step, two identical commercial UAV rotors from a flight test program are studied in isolation, experimentally and computationally. Load measurements were performed in Georgia Tech’s 2.13 m × 2.74 m wind tunnel. Simulations were done using the RotCFD solver which uses a Navier-Stokes wake computation along with rotor-disc loads calculation using low-Reynolds number blade section data. It is found that in hover, small rotors available in the market vary noticeably in performance at low rotor speeds, the data converging at higher RPM and Reynolds number.

Ongoing development of a CFD framework for the simulation of primary atomization of a high pressure diesel jet is presented in this work. The numerical model is based on a second order accurate, polyhedral Finite Volume (FV) method implemented in foam-extend-4.1, a community driven fork of the OpenFOAM software. A geometric Volume-of-Fluid (VOF) method isoAdvector is used for interface advection, while the Ghost Fluid Method (GFM) is used to handle the discontinuity of the pressure and the pressure gradient at the interface between the two phases: n-dodecane and air in the combustion chamber. In order to obtain highly resolved interface while minimizing computational time, an Adaptive Grid Refinement (AGR) strategy for arbitrary polyhedral cells is employed in order to refine the parts of the grid near the interface. Dynamic Load Balancing (DLB) is used in order to preserve parallel efficiency during AGR.

Natural gas (NG) is an alternative fuel for spark-ignition engines. In addition to its cleaner combustion, recent breakthroughs in drilling technologies increased its availability and lowered its cost. NG consists of mostly methane, but it also contains heavier hydrocarbons and inert diluents, the levels of which vary substantially with geographical source, time of the year and treatments applied during production or transportation. To investigate the effects of NG composition on engine performance and emissions, a 3D CFD model of a heavy-duty diesel engine retrofitted to NG spark ignition simulated lean-combustion engine operation at low speed and medium load conditions. The work investigated three NG blends with similar lower heating value (i.e., similar energy density) but different Methane Number (MN). The results indicated that a lower MN increased flame propagation speed and thus increased in-cylinder pressure and indicated mean effective pressure.

A comprehensive experimental and numerical analysis of two state-of-the-art diesel AfterTreatment Systems (ATS) for automotive applications is presented in this work. Both systems, designed to fulfill Euro 6 emissions regulations standards, consist of a closed-coupled Diesel Oxidation Catalyst (DOC) followed by a Selective Catalytic Reduction (SCR) catalyst coated on a Diesel Particulate Filter (DPF), also known as SCR on Filter (SCRoF or SCRF). While the two systems feature the same Urea Water Solution (UWS) injector, major differences could be observed in the UWS mixing device, which is placed upstream of the SCRoF, whose design represents a crucial challenge due to the severe flow uniformity and compact packaging requirements.