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Electric motors and generators produce vibrations and noise associated with many physical mechanisms. In this study, we look at the vibrations and noise produced by the transient electromagnetic forces on the stator of a permanent magnet motor. In the first stage, electromagnetic simulation is carried out to calculate the forces per tooth segment of the stator. The harmonic orders of the electromagnetic forces are then calculated using Fourier analysis, and forces are mapped to the mechanical harmonic analysis of the second stage. As a third stage, the vibrations of the structure are used to drive the boundary of acoustic domain to predict the noise. Finally, optimization studies are made over the complete system to improve the motor design and reduce noise. A simulation environment (ANSYS Workbench) is used to integrate a seamless workflow.

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.

Airflow over the Ahmed body is simulated by means of the Embedded LES technique. This is a zonal approach which allows the LES turbulence model to be used in a sub-domain while the rest of the domain is solved using a RANS turbulence model, i.e., the kω-SST model. This allows the LES zone to be restricted to the rear end of the vehicle where the unsteadiness of the flow must be accurately predicted. A comparison with full RANS modeling and experiments is reported.

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.

Thorough design exploration is essential for improving vehicle performance in various aspects such as aerodynamic drag. Shape optimization algorithms in combination with computational tools such as Computational Fluid Dynamics (CFD) play an important role in design exploration. The present work describes a Free-Form Deformation (FFD) approach implemented within a general purpose CFD code for parameterization and modification of the aerodynamic shape of real-life vehicle models. Various vehicle shape parameters are constructed and utilized to change the shape of a vehicle using a mesh morphing technique based on the FFD algorithm. Based on input and output parameters, a design of experiments (DOE) matrix is created. CFD simulations are run and a response surface is constructed to study the sensitivity of the output parameter (aerodynamic drag) to variations in each input parameter.

Demands for higher power engines have led to higher pressures in fuel injectors. Internal nozzle flow plays a critical role in the near nozzle flow and subsequent spray pattern. The internal flow becomes more difficult to model when the injector pressure and internal shape make it more prone to cavitation. Two Bosch injectors, proposed for experimental and computational studies under the Engine Combustion Network (namely “Spray C” and “Spray D”) are modeled in the computational fluid dynamics code ANSYS Fluent. Both injectors operate with n-dodecane as fuel at 150 MPa inlet pressures. The computational model includes cavitation effects to characterize any cavitating regions. Including compressibility of both liquid and vapor is found to be critical. Also, due to high velocity gradients and stresses in the nozzle, turbulent viscous energy dissipation is considered along with pressure work resulting from significant pressure changes in the injector.

Brake squeal is an instability issue with many parameters. This study attempts to assess the effect of thermal load on brake squeal behavior through finite element computation. The research can be divided into two parts. The first step is to analyze the thermal conditions of a brake assembly based on ANSYS Fluent. Modeling of transient temperature and thermal-structural analysis are then used in coupled thermal-mechanical analysis using complex eigenvalue methods in ANSYS Mechanical to determine the deformation and the stress established in both the disk and the pad. Thus, the influence of thermal load may be observed when using finite element methods for prediction of brake squeal propensity. A detailed finite element model of a commercial brake disc was developed and verified by experimental modal analysis and structure free-free modal analysis.

A methodology has been implemented to calculate local turbulent flame speeds for spark ignition engines accurately and on-the-fly in 3-D CFD modeling. The approach dynamically captures fuel effects, based on detailed chemistry calculations of laminar flame speeds. Accurately modeling flame propagation is critical to predicting heat release rates and emissions. Fuels used in spark ignition engines are increasingly complex, which necessitates the use of multi-component fuels or fuel surrogates for predictive simulation. Flame speeds of the individual components in these multi-component fuels may vary substantially, making it difficult to define flame speed values, especially for stratified mixtures. In addition to fuel effects, a wide range of local conditions of temperature, pressure, equivalence ratio and EGR are expected in spark ignition engines.

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.

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.

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.

Computational Fluid Dynamics (CFD) is widely used in vehicle aerodynamics development today, but typically used to study one vehicle shape at a time. In order to be used for aerodynamic shape exploration and optimization the CFD simulation process has to be able to study a large set of design alternatives (vehicle shape variants) within the short period of time typically available in the overall aerodynamics development process. This paper reports the development and testing of a process, referred to as the 50:50:50 Method, which is developed to study a large set of design alternatives in a highly automated way, while ensuring that each design alternative is simulated with a high fidelity CFD simulation.

A commonly used physics based electrochemisty model for a lithium-ion battery cell was first proposed by professor Newman in 1993. The model consists of a tightly coupled set of partial differential equations. Due to the tight coupling between the equations and the 2d implementation due to the particle modeling, and thus called pseudo-2d in literature, numerically obtaining a solution turns out to be challenging even for a lot of commercial softwares. In this paper, the VHDL-AMS language is used to solve the set of equations. VHDL-AMS allows the user to focus on the physical modeling rather than numerically solving the governing equations. In using VHDL-AMS, the user only needs to specify the governing equations after spatial discretization. A simulation environment, which supports VHDL-AMS, can then be used to solve the governing equations and also provides both pre- and post- processing tools.

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.).

In this case study, the thermoforming of an automotive instrument panel is considered. The effect of different oven settings on the final material distribution is studied using structural FEA simulation. The variable thickness distribution of the thermoformed part is mapped onto a structural model using a new simple mapping algorithm, and a structural FEA simulation is carried out to examine the final warpage of the instrument panel. The simulation predicts that the minimum thickness of the formed part can be increased by 10% by optimizing the oven settings. Although the optimized process uses oven settings that are less uniform than the baseline settings, the model indicates that warpage experienced by the optimized part will be less than that of the baseline case.

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.