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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.

Spray processes, such as primary breakup, play an important role for subsequent combustion processes and emissions formation. Accurate modeling of these spray physics is therefore key to ensure faithful representation of both the global and local characteristics of the spray. However, the governing physical mechanisms underlying primary breakup in fuel sprays are still not known. Several theories have been proposed and incorporated into different engineering models for the primary breakup of fuel sprays, with the most widely employed models following an approach based on aerodynamically-induced breakup, or more recently, based on liquid turbulence-induced breakup. However, a complete validation of these breakup models and theories is lacking since no existing measurements have yielded the joint liquid mass and drop size distribution needed to fully define the spray, especially in the near-nozzle region.

The Elytron 2S is a prototype aircraft concept to allow VTOL capabilities together with fixed wing aircraft performance. It has a box wing design with a centrally mounted tilt-wing supporting two rotors. This paper explores the aerodynamic characteristics of the aircraft using computational fluid dynamics in hover and low speed forward flight, as well as analyzing the unique control system in place for hover. The results are then used to build an input set for NASA Design and Analysis if Rotorcraft software allowing trim and flight stability and control estimations to be made with SIMPLI-FLYD.

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.

An integrated approach for modeling the ice accretion and shedding of ice on helicopter rotors is presented. A modular framework is used that includes state of the art computational fluid dynamics, computational structural dynamics, rotor trim, ice accretion, and shedding tools. Results are presented for performance degradation due to icing, collection efficiency, surface temperature and water film properties associated with runback-refreeze phenomena, and shedding. Comparisons with other published simulations and test data are given.

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”.

The wing of the Learjet Model 60 was tailored for improved aerodynamic characteristics using the TRANAIR transonic full-potential CFD code. A root leading edge glove and wing tip fairing were shaped to reduce shock strength, improve cruise drag and extend the buffet limit. The aerodynamic design was validated by wind tunnel test and flight test data.

Three-component Particle Image Velocimetry (3D PIV) is a fluid velocity measurement technique that has evolved from the laboratory to become a method appropriate for use in large-scale wind tunnel testing. An example application of 3D PIV in a wind tunnel test is described. The PIV technique was applied to characterize the wake of The Ground Transportation System (GTS) model developed for the Department of Energy (DOE) Heavy Vehicle Drag Reduction (HVDR) program. The test was performed in the Ames/Army 7×10 foot wind tunnel. The objective of the PIV measurements was to validate the HVDR computational fluid dynamics code. The PIV method and PIV system are described. Sample truck wake data with and without boattail attachments are shown. 3D PIV system successfully captured the effects of the boattails on the truck wake.

The desire to provide integrated surface pressures for aerodynamic loads measurements has been a driving force behind the development of pressure-sensitive paint (PSP). To demonstrate the suitability of PSP for this purpose, it is not sufficient to simply show that PSP is accurate as compared to pressure taps. PSP errors due to misregistration or temperature sensitivity may be high near model edges, where pressure taps are rarely installed. Thus, PSP results will appear good compared to the taps, but will yield inaccurate results when integrated. A more stringent technique is to compare integrated PSP data over the entire model surface with balance and/or CFD results. This paper describes a simple integration method for PSP data and presents comparisons of balance and PSP results for three experiments. PSP is shown quite accurate for normal force measurements, but less effective at determining axial force and moments.

An overset grid approach is used to analyze a 3-element trapezoidal wing high-lift configuration. A new software system was developed to automate the overset computational fluid dynamics process. A three-dimensional grid resolution study is conducted, and comparisons of numerical results are made to experimental data which were obtained after the simulations. Comparisons between numerical and experimental data are in good agreement for the lift coefficient over a wide range of angles of attack, up to and including CLmax. Comparisons of chordwise distributions of the pressure coefficient between numerical and experimental data are in good agreement for all three elements, except the lift is under-predicted for the tip region when the wing is near CLmax.

This paper describes research and development for reducing the aerodynamic drag of heavy vehicles by demonstrating new approaches for the numerical simulation and analysis of aerodynamic flow. In addition, greater use of newly developed computational tools holds promise for reducing the number of prototype tests, for cutting manufacturing costs, and for reducing overall time to market. Experimental verification and validation of new computational fluid dynamics methods are also an important part of this approach. Experiments on a model of an integrated tractor-trailer are underway at NASA Ames Research Center and the University of Southern California. Companion computer simulations are being performed by Sandia National Laboratories, Lawrence Livermore National Laboratory, and California Institute of Technology using state-of- the-art techniques, with the intention of implementing more complex methods in the future.

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.

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.

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.

This paper describes research and development for reducing the aerodynamic drag of heavy vehicles by demonstrating new approaches for the numerical simulation and analysis of aerodynamic flow. Experimental validation of new computational fluid dynamics methods are also an important part of this approach. Experiments on a model of an integrated tractor-trailer are underway at NASA Ames Research Center and the University of Southern California (USC). Companion computer simulations are being performed by Sandia National Laboratories (SNL), Lawrence Livermore National Laboratory (LLNL), and California Institute of Technology (Caltech) using state-of-the-art techniques.