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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.

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.

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.

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.

In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions.

This presentation is an assessment of the turbulence-stress scale-similarity in an IC engine, which is used for modeling subgrid dissipation in LES. Residual stresses and Leonard stresses were computed after applying progressively smaller spatial filters to measured and simulated velocity distributions. The velocity was measured in the TCC-II engine using planar and stereo PIV taken in three different planes and with three different spatial resolutions, thus yielding two and three velocity components, respectively. Comparisons are made between the stresses computed from the measured velocity and stress computed from the LES resolved-scale velocity from an LES simulation. The results present the degree of similarity between the residual stresses and the Leonard stresses at adjacent scales. The specified filters are systematically reduced in size to the resolution limits of the measurements and simulation.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

This paper brings together three special aspects of bluff-body aeromechanics. Experiments using our Continuous Rotation method have developed a knowledge base on the 6-degree-of-freedom aerodynamic loads on over 50 different configurations including parametric variations of canonical shapes, and several practical shapes of interest. Models are mounted on a rod attached to a stepper motor placed on a 6-DOF load cell in a low speed wind tunnel. The aerodynamic loads are ensemble-averaged as phase-resolved azimuthal variations. The load component variations are obtained as discrete Fourier series for each load component versus azimuth about each of 3 primary axes. This capability has enabled aeromechanical simulation of the dynamics of roadable vehicles slung below rotorcraft. In this paper, we explore the genesis of the loads on a CONEX model, as well as models of a short and long container, using the “ROTCFD” family of unstructured Navier-Stokes solvers.

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

The atomization and initial spray formation processes in direct injection engines are not well understood due to the experimental and computational challenges associated with resolving these processes. Although different physical mechanisms, such as aerodynamic-induced instabilities and nozzle-generated turbulence and cavitation, have been proposed in the literature to describe these processes, direct validation of the theoretical basis of these models under engine-relevant conditions has not been possible to date. Recent developments in droplet sizing measurement techniques offer a new opportunity to evaluate droplet size distributions formed in the central and peripheral regions of the spray. There is therefore a need to understand how these measurements might be utilized to validate unobservable physics in the near nozzle-region.

This study investigates the role of turbulent-chemistry interaction in simulations of diesel spray combustion phenomena after end-of-injection (EOI), using the commercially-available CFD code CONVERGE. Recent experimental and computational studies have shown that the spray flame dynamics and mixture formation after EOI are governed by turbulent entrainment, coupled with rapid evolution of the thermo-chemical state of the mixture field. A few studies have shown that after EOI, mixtures between the injector nozzle and the lifted diffusion flame can ignite and appear to propagate back towards the injector nozzle via an auto-ignition reaction sequence; referred to as “combustion recession”.

Coaxial rotors are finding use in advanced rotorcraft concepts. Combined with lift offset rotor technology, they offer a solution to the problems of dynamic stall and reverse flow that often limit single rotor forward flight speeds. In addition, coaxial rotorcraft systems do not need a tail rotor, a major boon during operation in confined areas. However, the operation of two counter-rotating rotors in close proximity generates many possible aerodynamic interactions between rotor blades, blades and vortices, and between vortices. With two rotors, the parameter design space is very large, and requires efficient computations as well as basic experiments to explore aerodynamics of a coaxial rotor and the effects on performance, loads, and acoustics.

The Georgia Tech EcoCAR 3 team’s selection of a parallel hybrid electric vehicle (HEV) architecture for the EcoCAR 3 competition is presented in detail, with a focus on the team’s modeling and simulation efforts and how they informed the team’s architecture selection and subsequent component decisions. EcoCAR 3, sponsored by the United States Department of Energy and General Motors, is the latest in a series of Advanced Vehicle Technology Competitions (AVTCs) and features 16 universities from the United States and Canada competing to transform the 2016 Chevrolet Camaro into a hybrid electric American performance vehicle. Team vehicles will be scored on performance, emissions, fuel economy, consumer acceptability, and more over the course of the four-year competition. During the first year, the Georgia Tech team considered numerous component combinations and HEV architectures, including series RWD and AWD, parallel, and power-split.

The interest in flying cars comes with the question of characterizing aerodynamic loads on shapes that go beyond traditional aircraft shapes. When carried as slung loads under aircraft, vehicles can encounter severe aerodynamic loads, which may also cause them to go into divergent oscillations that can threaten the vehicle and aircraft. Slung loads can encounter the wind at arbitrary attitudes. Flight test certification for every vehicle-aircraft combination is prohibitive. Characterizing the aerodynamic loads with sufficient resolution for use in dynamic simulation, has in the past been extremely arduous. Sharp changes that drive instabilities arise over small ranges of yaw and pitch. With the Continuous Rotation technique developed by our group, aerodynamic load characterization is viable and efficient. With two well-chosen attitude sweeps and appropriate transformations, the entire 6-DOF load map can be obtained, for several rates.

At high angles of attack, the flow over a swept wing generates counter-rotating vortical features. These features can amplify into a nearly sinusoidal fluctuation of velocity components. The result is excitation of twin-fin buffeting, driven at clearly predictable frequencies, or at nearby lock-in frequencies of the fin structure. This is distinct from the traditional model of fin buffeting as a structural resonant response to broadband, large-amplitude excitation from vortex core bursting. Hot-film anemometry was conducted ahead of the vertical fins of a 1:48 scale model of the F-35B aircraft, in the angle of attack range between 18 and 30 degrees. Auto spectral density functions from these data showed a sharp spectral peak in the flow ahead of the fins for angles of attack between 20 and 28 degrees. Small fences placed on the top surface of the wing eliminated the spectral peak, leaving only a broadband turbulent spectrum.

The formation of ice over lifting surfaces can affect aerodynamic performance. In the case of helicopters, this loss in lift and the increase in sectional drag forces will have a dramatic effect on vehicle performance. The ability to predict ice accumulation and the resulting degradation in rotor performance is essential to determine the limitations of rotorcraft in icing encounters. The consequences of underestimating performance degradation can be serious and so it is important to produce accurate predictions, particularly for severe icing conditions. The simulation of rotorcraft ice accretion is a challenging multidisciplinary problem that until recently has lagged in development over its counterparts in the fixed wing community. But now, several approaches for the robust coupling of a computational fluid dynamics code, a rotorcraft structural dynamics code and an ice accretion code have been demonstrated.

We analyze the frequency response of structural dynamic systems with uncertainties in load and material properties. We introduce uncertainties in the system as interval numbers, and use Interval Finite Element Method (IFEM). Overestimation due to dependency is reduced using a new decomposition for the stiffness and mass matrices, as well as for the nodal equivalent load. In addition, primary and derived quantities are simultaneously obtained by means of Lagrangian multipliers that are introduced in the total energy of the system. The obtained interval equations are solved by means of a new variant of the iterative enclosure method resulting in guaranteed enclosures of relevant quantities. Several numerical examples show the accuracy and efficiency of the new formulation.

This work contributes to the understanding of physical mechanisms that control flashback, or more appropriately combustion recession, in diesel sprays. A large dataset, comprising many fuels, injection pressures, ambient temperatures, ambient oxygen concentrations, ambient densities, and nozzle diameters is used to explore experimental trends for the behavior of combustion recession. Then, a reduced-order model, capable of modeling non-reacting and reacting conditions, is used to help interpret the experimental trends. Finally, the reduced-order model is used to predict how a controlled ramp-down rate-of-injection can enhance the likelihood of combustion recession for conditions that would not normally exhibit combustion recession. In general, fuel, ambient conditions, and the end-of-injection transient determine the success or failure of combustion recession.