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Carbon-neutral (CN) fuels will be part of the solution to reducing global warming effects of the transportation sector, along with electrification. CN fuels such as hydrogen, ammonia, biofuels, and e-fuels can play a primary role in some segments (aviation, shipping, heavy-duty road vehicles) and a secondary role in others (light-duty road vehicles). The composition and properties of these fuels vary substantially from existing fossil fuels. Fuel effects on performance and emissions are complex, especially when these fuels are blended with fossil fuels. Predictively modeling the combustion of these fuels in engine and combustor CFD simulations requires accurate representation of the fuel blends. We discuss a methodology for matching the targeted fuel properties of specific CN fuels, using a blend of surrogate fuel components, to form a fuel model that can accurately capture fuel effects in an engine simulation.

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.

The importance of the variation of relative humidity across turbomachinery engine components for in-flight icing is shown by numerical analysis. A species transport equation for vapor has been added to the existing CFD methodology for the simulation of ice growth and water flow on engine components that are subject to ice crystal icing. This entire system couples several partial differential equations that consider heat and mass transfer between droplets, crystals and air, adding the cooling of the air due to particle evaporation to the icing simulation, increasing the accuracy of the evaporative heat fluxes on wetted walls. Three validation cases are presented for the new methodology: the first one compares with the numerical results of droplets traveling inside an icing tunnel with an existing evaporation model proposed by the National Research Council of Canada (NRC).

Development of quick and efficient numerical tools is key to the design of industrial machines. While Computational Fluid Dynamics (CFD) techniques based on Navier Stokes (N-S) and Lattice Boltzman methods are becoming popular, predicting aeroacoustic behavior for complex geometries remains computationally intensive for design process and iteration. The goal of this paper is to evaluate application Navier-Stokes approach coupled with Ffowcs Williams and Hawkings (FW-H), and Broad-band Noise Model (BNS) to evaluate noise levels and predict design direction for industrial applications. Steady-state RANS based approaches are used to evaluate under-hood cooling performance and fan power demand. At each design iteration, noise levels and strength of noise source are evaluated using Gutin’s and broad-band noise models, respectively along with cooling performance. Each design feature selected for the final design has lower fan power and noise level with improved cooling.

A linear parameter varying (LPV) reduced order model (ROM) is used to approximate the volume-averaged temperature of battery cells in one of the modules of the battery pack with varying mass flow rate of cooling fluid using uniform heat source as inputs. The ROM runs orders of magnitude faster than the original CFD model. To reduce the time it takes to generate training data, used in building LPV ROM, a divide-and-conquer approach is introduced. This is done by dividing the battery module into a series of mid-cell and end-cell units. A mid-cell unit is composed of a cooling channel sandwiched in between two half -cells. A half-cell has half as much heat capacity as a full-cell. An end-cell unit is composed of a cooling channel sandwiched in between full-cell and a half-cell. A mass flow rate distribution look-up-table is generated from a set of steady-state simulations obtained by running the full CFD model at different inlet manifold mass flow rate samples.

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.

This paper introduces a model-based systems and embedded software engineering, workflow for the design of control systems. The interdisciplinary approach that is presented relies on an integrated set of tools that addresses the needs of various engineering groups, including system architecture, design, and validation. For each of these groups, a set of best practices has been established and targeted tools are proposed and integrated in a unique platform, thus allowing efficient communication between the various groups. In the initial stages of system design, including functional and architectural design, a SysML-based approach is proposed. This solution is the basis to develop systems that have to obey both functional and certification standards such as ARINC 653 (IMA) and ARP 4754A. Detailed system design typically requires modeling and simulation of each individual physical component of the system by various engineering groups (mechanical, electrical, etc.).

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.

The purpose of present study is to use Immersed Boundary (IB) method in flow field simulations of a simplified generic ground transportation system (GTS) at 0° yaw. The IB method is usually employed in conjunction with a body non-conforming Cartesian grid. Thus, grid generation is greatly simplified. This plays an important role in reducing the cost and time in design process. This paper demonstrates the ease of use of IB method compared to body fitted mesh method and possible use of IB method to automate the external aerodynamics simulations. Also in order to assess the accuracy, the results are compared with corresponding experimental data reported in literature.