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The paper describes a numerical study, supported by experiments, on light aircraft 2-Stroke Direct Injected Diesel engines, typically rated up to 110 kW (corresponding to about 150 imperial HP). The engines must be as light as possible and they are to be directly coupled to the propeller, without reduction drive. The ensuing main design constraints are: i) in-cylinder peak pressure as low as possible (typically, no more than 120 bar); ii) maximum rotational speed limited to 2600 rpm. As far as exhaust emissions are concerned, piston aircraft engines remain unregulated but lack of visible smoke is a customer requirement, so that a value of 1 is assumed as maximum Smoke number. For the reasons clarified in the paper, only three cylinder in line engines are investigated. Reference is made to two types of scavenging and combustion systems, designed by the authors with the assistance of state-of-the-art CFD tools and described in detail in a parallel paper.

The main objective of the current paper was to investigate the fluid flow and pressure loss characteristics of DPF substrates with asymmetric channels utilizing 3-D Computational Fluid Dynamics (CFD) methods. The ratio of inlet to outlet channel width is 1.2. First, CFD results of velocity and static pressure distributions inside the inlet and outlet channels are discussed for the baseline case with both forward and reversed exhaust flow. Results were also compared with the regular DPF of same cell structure and wall material properties. It was found that asymmetrical channel design has higher pressure loss. The lowest pressure loss was found for the asymmetrical channel design with smaller inlet channels. Then, the effects of DPF length and filter wall permeability on pressure loss, flow and pressure distributions were investigated.

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.

In CFD (Computational Fluid Dynamics) verification of vehicle aerodynamics, detailed velocity measurements are required. The conventional 2D-PIV (Two Dimensional Particle Image Velocimetry) needs at least twice the number of operations to measure the three components of velocity ( u,v,w ), thus it is difficult to set up precise measurement positions. Furthermore, there are some areas where measurements are rendered impossible due to the relative position of the object and the optical system. That is why the acquisition of detailed velocity data around a vehicle has not yet been attained. In this study, a detailed velocity measurement was conducted using a 3D-PIV measurement system. The measurement target was a quarter scale SAE standard vehicle model. The wind tunnel system which was also designed for a quarter scale car model was utilized. It consisted of a moving belt and a boundary suction system.

In this work, a newly developed iced-aircraft modeling tool is applied to wings, engine inlets, and helicopter rotors. The tool is based on a multiscale-physics, unstructured finite-volume CFD approach and is applicable to general purpose aircraft icing applications. The present approach combines an Eulerian-based droplet-trajectory solver that is loosely coupled, in a time-accurate manner, to a surface-film and ice-evolution model. The goal of the model is to improve the fidelity of ice accretion modeling on dynamic geometries and for three-dimensional ice shapes typical of helicopter rotors. The numerical formulation is discussed and presented alongside 2D and 3D static validation cases, and dynamic helicopter rotors. The present results display good validation for predicting ice shape on a variety of geometries, and a strong initial capability of modeling ice forming on helicopters in forward flight.

A series calculation methodology from the injector nozzle internal flow to the fuel spray was applied to investigate the internal flow and spray of a nozzle whose orifices distributed in different space layers. The nozzle internal flow calculation using an Eulerian three-fluid model and a cavitation model was performed. The needle valve movement during the injection period was taken into account in this calculation. The transient data of spatial distributions of velocity, turbulent kinetic energy, dissipation rate, void fraction rate, etc. at the nozzle exit were extracted. These output data were transferred to the spray calculation, in which a primary break-up model was applied to the Discrete Droplet Model (DDM). The calculation results were compared with the results of the measurement data of spray. Predicted spray morphology and penetration showed good agreement with the experiental data.

The aim of the study is to understand risks associated with a crew member accessing behind the closeout panel or space. Since there is a possibility that a particular closeout space is filled with a harmful gas mixture that is different from the cabin atmosphere, the time needed to ventilate this space should be evaluated. The three-dimensional Computational Fluid Dynamics (CFD) model developed for prediction of time-dependent turbulent flow and concentration fields inside and near a suddenly-opened box is described in the paper. Several cases with different positions of the closeout space, initially filled with pure oxygen, are analyzed under the U.S. Laboratory (USL) ventilation conditions. A simplified flow model, where a suddenly-opened box is ventilated by uniform external throughflow, is considered as well.

Within the frame of a series of initiatives aimed at improving effectiveness of its aircraft design and analysis capabilities, the Military Division of Daimler-Benz Aerospace (Dasa) is developing MIDAS, a multidisciplinary integration framework for a suite of numerical codes suitable to quickly and still accurately assess aircraft performance. As MIDAS specifically targets support of configurational studies in a Conceptual and Preliminary Design environment, peculiar requirements such as scope, range of applicability, and robustness of the system components, reliability of results, care-free operability, and fast response times have to be properly addressed.

It is important to accurately predict the aerodynamic properties for designing applications which involves fluid flows, particularly in the aerospace industry. Traditionally, this is done through complex numerical simulations, which are computationally expensive, resource-intensive and time-consuming, making them less than ideal for iterative design processes and rapid prototyping. Machine learning, powered by vast datasets and advanced algorithms, offers an innovative approach to predict airfoil characteristics with remarkable accuracy, speed, and cost-effectiveness. Machine learning techniques have been applied to fluid dynamics and have shown promising results. In this study, machine learning model called the back-propagation neural network (BPNN) is used to predict key aerodynamic coefficients of lift and drag for airfoils.

Two turbulence models have been studied to determine which of the models should be used in further Computational Fluid Dynamics (CFD) research. A zero-equation turbulence model, Baldwin-Lomax (B-L), is easy to use, requires no history of the flow, and requires little in the way of additional computations or additional computer memory space [1]. A two-equation k-ε model, Yang-Shih (Y-S), is more difficult to implement, does require flow history, and requires many more computations and much more computer space; however, it is potentially more accurate than the B-L model [2]. Using both Navier-Stokes (NS) and Parabolized Navier-Stokes (PNS) solvers, the two models and their codes were validated against the testbed of the Wright Laboratory (WL) Mach 12 wind tunnel nozzle.

Multiphase CFD simulations of air and water play a critical role in aircraft icing analysis. Specifically for air data sensors mounted near the front of an aircraft, simulations that predict the concentration of water surrounding an aircraft fuselage are necessary for understanding their performance in icing conditions. Those simulations can aid in sensor design and placement, and are central for defining critical conditions to test during icing qualification campaigns. There are several methods available in CFD that solve a multiphase flow field. Two of the most common methods used are Lagrangian and Eulerian. While these methods are similar, important differences can be viewed in the results, specifically in how the water shadow zones are predicted. This paper compares a Lagrangian and Eulerian CFD method for solving a multiphase flow field, and assesses their performance for use for analyzing installation locations and critical icing conditions of air data probes.

For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

A computational process for early stage vehicle shape assessment for automotive front window buffeting and greenhouse wind noise is presented. It is a challenging problem in an experimental process as the vehicle geometry is not always finalized. For example, the buffeting behavior typically worsens during the vehicle development process as the vehicle gets tighter, leading to expensive late counter measures. We present a solution using previously validated CFD/CAA software based on the Lattice Boltzmann Method (LBM). A CAD model with realistic automotive geometry was chosen to simultaneously study the potential of different side mirror geometries to influence the front window buffeting and greenhouse wind noise phenomena. A glass mounted mirror and a door mounted mirror were used for this comparative study. Interior noise is investigated for the two phenomena studied. The unsteady flow is visualized and changes in the buffeting and wind noise behavior are explored.

The use of external jets issuing normal to the surface of a body for aerodynamic control has received attention in the past due to experimental observations of favorable interactions between the free stream flow and the jet wake which, in effect, augment the force produced by the jet. The purpose of this study was to perform preliminary trades to determine the effect of variables such as reaction jet location, free stream Mach number, reaction jet stagnation pressure, and reaction jet exit Mach number on augmentation factors for a representative lifting body cruise missile configuration. A computational fluid dynamic analysis, solving the Euler equations, was used to perform the trades listed above. It is shown that the reaction jet augmentation factors are greater, and hence the reaction jet is more effective, at higher free stream dynamic pressures in the subsonic regime.

This Aerospace Information Report (AIR) addresses the subject of aircraft inlet-swirl distortion. A structured methodology for characterizing steady-state swirl distortion in terms of swirl descriptors and for correlating the swirl descriptors with loss in stability pressure ratio is presented. The methodology is to be considered in conjunction with other SAE inlet distortion methodologies. In particular, the combined effects of swirl and total-pressure distortion on stability margin are considered. However, dynamic swirl, i.e., time-variant swirl, is not considered. The implementation of the swirl assessment methodology is shown through both computational and experimental examples. Different types of swirl distortion encountered in various engine installations and operations are described, and case studies which highlight the impact of swirl on engine stability are provided. Supplemental material is included in the appendices.

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.

Nautilus S.p.A. and the Polytechnic of Turin, in cooperation with Blue Engineering, have developed a very versatile product, the ELETTRA Twin Flyers [6] (ETF), which consists in a very innovative remotely-piloted airship equipped with high precision sensors and communication devices. This multipurpose platform is particularly suitable for border and maritime surveillance missions and for telecommunication, both in military and civil area. To assess the actual maneuver capabilities of the airship [14], a prototype of reduced size and complexity has been assembled [16]. Before the flight tests a further assessment on the flight simulator is needed, because the first version of the software is tuned on the full scale prototype. Steady state performance and static stability of the demonstrator have been evaluated with CFD analysis.

A new converter concept is introduced, which utilizes the additional space in the inlet cone of the converter. An optimized design is obtained by the application of computational fluid dynamics (CFD) and flow distribution measurements, resulting in up to 20% improved flow distribution through the substrate. In addition, the volume of the converter can be increased by approximately 15% using the same space envelope. Durability tests of the converter system have been performed using a thermal cycling test on an engine test bench for 135 hours. No deterioration of the substrate or mounting system occurred. The emissions performance was evaluated on a stationary dynamometer. The impact of the flow distribution on the temperature field and the conversion behavior during light-off and steady state operation were investigated. Under the current testing conditions, no differences in light-off behavior were determined, despite significant differences in the temperature field.

This project investigates methods to capture an astronaut's exhaled carbon dioxide (CO2) before it becomes diluted with the high volumetric oxygen flow present within a space suit. Typical expired breath contains CO2 partial pressures (pCO2) in the range of 20-35 mm Hg (.0226-.046 atm). This research investigates methods to capture the concentrated CO2 gas stream prior to its dilution with the low pCO2 ventilation flow. Specifically this research is looking at potential designs for a collection cup for use inside the space suit helmet. The collection cup concept is not the same as a breathing mask typical of that worn by firefighters and pilots. It is well known that most members of the astronaut corps view a mask as a serious deficiency in any space suit helmet design. Instead, the collection cup is a non-contact device that will be designed using a detailed Computational Fluid Dynamic (CFD) analysis of the ventilation flow environment within the helmet.

This paper is a preliminary step in the direction of the definition of a radically new wing concept that has been conceived to maximize the lift even at low speeds. It is expected to equip new aerial vehicle concepts that aim to compete against helicopters and tilt rotors. They aim achieving very good performance at very low speed (5 to 30 m/s) by mean of an innovative concept of morphing ducted-fan propelled wing that has been designed to maximize the lift force. This paper presents an effective bibliographic analysis of the problem that is a preliminary necessary step in the direction of the preliminary design of the wing. A preliminary CFD evaluation allows demonstrating that the claimed results are in line with the initial expectations. According to the CFD, results it has been produced a preliminary energetic evaluation of the vehicle in a flying car configuration by EMIPS method.