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In-flight icing significantly influences the design of large passenger aircraft. Relevant aspects include sizing of the main aerodynamic surfaces, provision of anti-icing systems, and setting of operational restrictions. Empennages of large passenger aircraft are particularly affected due to the small leading edge radius, and the requirement to generate considerable lift for round out and flare, following an extended period of descent often in icing conditions. This paper describes a CFD-based investigation of the effects of sweep on the aerodynamic performance of a novel forward-swept horizontal stabilizer concept in icing conditions. The concept features an unconventional forward sweep, combined with a high lift leading edge extension (LEX) located within a fuselage induced droplet shadow zone, providing passive protection from icing.

This paper introduces the Lagrangian particle tracking technology readily available in Ansys Fluent in the in-flight icing simulation workflow, which normally uses the Eulerian approach for droplet flows. The Lagrangian solver is incorporated in the Fluent Icing workspace which is to become the next-gen in-flight icing simulation tool provided by Ansys. Lagrangian tracking will eventually be used for SLD and ice crystal rebound and re-impingement calculations in the Ansys workflow. Here we introduce some preliminary results with the current state of its implementation as of Fluent Icing release 2023R2. Example cases include several selections from the 1st Ice prediction workshop with experimental comparisons as well as results obtained earlier with the Eulerian droplet solution strategy. Collection efficiency comparisons on clean geometries show good agreement between Eulerian and Lagrangian methods when the particle seeds are in the millions range.

This paper presents the current state of a three-layer surface icing model for ice crystal icing risk assessment in aircraft engines, being developed jointly by Ansys and Honeywell to account for possible heat transfer from inside an engine into the flow path where ice accretion occurs. The bottom layer of the proposed model represents a thin metal sheet as a substrate surface to conductively transfer heat from an engine-internal reservoir to the ice layer. The middle layer is accretion ice with a porous structure able to hold a certain amount of liquid water. A shallow water film layer on the top receives impinged ice crystals. A mass and energy balance calculation for the film determines ice accretion rate. Water wicking and recovery is introduced to transfer liquid water between film layer and porous ice accretion layer.

This paper studies the level of confidence and applicability of CFD simulations using steady-state Reynolds-Averaged Navier-Stokes (RANS) in predicting aerodynamic performance losses on swept-wings due to contamination with ice accreted in-flight. The wing geometry selected for the study is the 65%-scale Common Research Model (CRM65) main wing, for which NASA Glenn Research Center’s Icing Research Tunnel has generated experimental ice shapes for the inboard, mid-span, and outboard sections. The reproductions at various levels of fidelity from detailed 3D scans of these ice shapes have been used in recent aerodynamic testing at the Office National d’Etudes et Recherches Aérospatiales (ONERA) and Wichita State University (WSU) wind tunnels. The ONERA tests were at higher Reynolds number range in the order of 10 million, while the WSU tests were in the order of 1 million.

Due to the increasingly stringent environmental regulations all around the world confronted by exhaust emission and energy consumption, improving fuel economy has been the top priority for most automotive manufacturers. In this context, the basic process for vehicle shape development has evolved into optimizing the design to achieve better aerodynamic characteristics, especially drag reduction. Of all the optimization approaches, the gradient-based adjoint method has currently received extensive attention for its high efficiency in calculating the objective sensitivity with respect to geometry parameters, which is the first and foremost step for subsequent shape modification. In this work, the main goal is to explore the adjoint method through optimizing the vehicle shape for a lower drag based on a production SUV. Firstly, the influence of different mesh schemes was discussed on sensitivity prediction of aerodynamic drag.

A full-automated CFD mesh generation technique has been developed and implemented for 3-D aircraft icing simulations to permit robust 45-minute ice accretion simulations in support of icing certification campaigns. The changes in the shape of the aircraft surfaces due to accreting ice and their effects on the air and droplet flow are accounted for in a quasi-steady manner by subdividing the total icing time into sequential steps of shorter duration, updating the computational grid at each step. This “multi-shot” ice accretion approach requires robust and accurate grid re-meshing for it to be embedded in engineering design and analysis workflows. ANSYS FENSAP-ICE has been coupled to Fluent Meshing to take advantage of generic and highly automated surface displacement and mesh wrapping tools. A wide spectrum of geometries is supported, ranging from full-size aircraft to air data probes, turbomachinery components, rotors and propellers.

A 3D CFD methodology is presented to simulate ice build-up on propeller blades exposed to known icing conditions in flight, with automatic blade pitch variation at constant RPM to maintain the desired thrust. One blade of a six-blade propeller and a 70-passenger twin-engine turboprop are analyzed as stand-alone components in a multi-shot quasi-steady icing simulation. The thrust that must be generated by the propellers is obtained from the drag computed on the aircraft. The flight conditions are typical for a 70-passenger twin-engine turboprop in a holding pattern in Appendix C icing conditions: 190 kts at an altitude of 6,000 ft. The rotation rate remains constant at 850 rpm, a typical operating condition for this flight envelope.

A CFD simulation methodology for the inclusion of the post-impact trajectories of splashing/bouncing Supercooled Large Droplets (SLDs) and film detachment is introduced and validated. Several scenarios are tested to demonstrate how different parameters affect the simulations. Including re-injecting droplet flows due to splashing/bouncing and film detachment has a significant effect on the accuracy of the validations shown in the article. Validation results demonstrate very good agreement with the experimental data. This approach is then applied to a full-scale twin-engine turboprop to compute water impingement on the wings and the empennage.

A CFD simulation methodology is presented to evaluate the ice that sheds from rotating components. The shedding detection is handled by coupling the ice accretion and stress analysis solvers to periodically check for the propagation of crack fronts and possible detachment. A novel approach for crack propagation is highlighted where no change in mesh topology is required. The entire computation from flow to impingement, ice accretion and crack analysis only requires a single mesh. The accretion and stress module are validated individually with published data. The analysis is extended to demonstrate potential shedding scenarios on three complex industrially-relevant 3D cases: a helicopter blade, an engine fan blade and a turboprop propeller. The largest shed fragment will be analyzed in the context of FOD damage to neighboring aircraft/component surfaces.

One of the best tools to explore complicated in-cylinder physics is computational fluid dynamics (CFD). In order to assess the accuracy and reliability of the CFD simulations, it is critical to perform validation studies over different engine operating conditions. Simulation-based design of SI engines requires predictive capabilities, where results do not need to be tuned for each operating condition. This requires the models adopted to simulate their respective engine physics to be reliable under a broad range of conditions. A detailed set of experimental data was obtained to validate the CFD predictions of SI engine combustion.

Gasoline Direct Injection (GDI) is a key technology in the automotive industry for improving fuel economy and performance of gasoline internal combustion engines. GDI engine performance and emission characteristics are mainly determined by the complex interaction of in-cylinder flow, mixture formation and subsequent combustion processes. In a GDI engine, mixture formation depends on spray characteristics. Spray evolution and mixture formation is critical to GDI engine operation. In this work, a multi-component surrogate fuel blend was used to represent the chemical and physical properties of the gasoline employed in the experimental engine tests. Multi-component spray models were also validated in this study against experimental spray injection measurements in a chamber. The spray-chamber data include spray-penetration lengths, transient spray velocities and droplet Sauter mean diameter (SMD) at different axial and radial distances from the spray tip, obtained using a PDPA system.

Cylinder head design is one of the most involved disciplines in engine design. Whether designing an altogether new head or revamping an old one, several different coupled and inter-dependent technologies ranging from heat transfer, fluid flow, combustion, material non-linearity, structural and fatigue have to be accounted. Simultaneous designing of ports, jacket and combustion chamber leads to cylinder head design, which is then tested for its strength and durability. Traditionally a series of analytical, empirical, test-based and simulation based exercises are conducted to design cylinder heads. With increasing pressure on reducing cost and turnaround time, focus on moving towards a quasi-simulation based design and development of cylinder heads is gaining strength. This paper talks about how a simulation driven process for cylinder head design can be developed.

Increased energy costs make optimal aerodynamic design even more critical today as even small improvements in aerodynamic performance can result in significant savings in fuel costs. Energy conscious industries like transportation (aviation and ground based) are particularly affected. There have been a number of different optimization methods, some of which require geometrically parameterized models. For non-parameterized models (as it is the case often in reality where models and shapes are very complex). Shape optimization and adjoin solvers are some of the latest approaches. In our study we are focusing on generating best practices and investigating different strategies of employing the commercially available shape optimizer tool from ANSYS'CFD solver Fluent. The shape optimizer is based on a polynomial mesh-morphing algorithm. The simple case of a low speed, airfoil/flap combination is used as a case study with the objective being the lift to drag ratio.

With advances in computing power and Computational Fluid Dynamics (CFD) algorithms, the complexity of CutCell based simulation models has significantly increased. In this study three dimensional numerical simulations were created for steady incompressible flow around airfoil shape. The NACA-0012 airfoil was used for this study. Boundary layer thickness, mesh expansion ratio, and mesh density variation parameters were investigated. Drag and lift coefficients were compared to experimental data. Use of the CutCell method results in a good agreement between CFD results and experimental data.

Battery thermal management for high power applications such as electrical/hybrid vehicles is crucial. Modeling is an indispensable tool to help engineers design better battery cooling systems. While Computational Fluid Dynamics (CFD) has been used quite successfully for battery thermal management, CFD models can be too large and too slow for repeated transient thermal analysis especially for a battery module or pack. An accurate but much smaller battery thermal model using a state space representation is proposed. The parameters in the state space model are extracted from CFD results. The state space model is then shown to provide identical results as those from CFD under transient power inputs. While a CFD model may take hours to run depending on the size of the problem, the corresponding state space model runs in seconds.