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Micro-Macro Acoustic Modeling of Heterogeneous Foams with Nucleation Perturbation

Duke University-Johann Guilleminot
Ecole des Ponts ParisTech-Michel BORNERT
  • Technical Paper
  • 2020-01-1526
To be published on 2020-06-03 by SAE International in United States
The properties of a polyurethane foam are greatly influenced by the addition of graphite particles during the manufacturing process, initially used as a fire retardant. These thin solid particles perturbate the nucleation process by generating bubbles in its immediate vicinity. The preponderance of work so far has focused on foams that are locally relatively homogeneous. We propose a model for locally inhomogeneous foams (including membrane effects) consisting of a random stack of spheres that permits one to represent certain pore size distribution functions. The cellular structure of the foam is obtained through a Laguerre tessellation and the solid skeleton determined from the minimization of surface energy (Surface Evolver). The structure of real foam samples is analyzed using X-ray computed tomography and scanning electron microscopy followed by image processing to create computerized three-dimensional models of the samples. The corresponding effective material parameters, including the permeability, the tortuosity and the viscous characteristic length are computed by applying a numerical homogenization approach. All the numerical data are presented, discussed and further compared with experimental results.
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Hybrid phenomenological and mathematical-based modeling approach for diesel engine emission predictio

IAV Automotive Engineering Inc.-Thaddaeus Delebinski
IAV GmbH-Reza Rezaei, Christopher Hayduk, Emre Alkan, Thomas Kemski, Christoph Bertram
  • Technical Paper
  • 2020-01-0660
To be published on 2020-04-14 by SAE International in United States
Due to the negative health effects associated with engine pollutants, environmental problems caused by combustion engine emissions and the current strict emission standards, it is essential to better understand and model the emission formation process in order to reduce them. Further development of emission models, improves the accuracy of the model-based optimization approach, which is used as a decisive tool for combustion system development and engine-out emission reduction. The numerical approaches for emission simulation are closely coupled to the combustion model. Using a detailed emission model, considering the 3D mixture preparation simulation incl. chemical reactions, demands high computational effort. Phenomenological models, used in 1-D approaches for model-based system optimization can deliver heat release rate and using a two-zone approach can estimate the NOx emissions. Due to the lack in modeling of 3D mixture preparation phenomena, such models are not capable to predict soot or HC emissions. However, employing physical-based air-path and combustion modeling, these models can predict the engine behavior outside of the training points. Mathematical models are very fast and accurate enough in the…
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A Competitive Approach to an Active Exhaust Heat Recovery System Solution

Tenneco Inc.-Adam Kotrba, Timothy Gardner, John Stanavich, Raphael Bellard, Brian Kunkel, Nicholas Morley
  • Technical Paper
  • 2020-01-0161
To be published on 2020-04-14 by SAE International in United States
As greenhouse gas regulations continue to tighten, more opportunities to improve engine efficiency emerge, including exhaust gas heat recovery. Upon cold starts, engine exhaust gases downstream of the catalysts are redirected with a bypass valve into a heat exchanger, transferring its heat to the engine coolant to accelerate engine warm-up. This has several advantages, including reduced fuel consumption, as the engine’s efficiency improves with temperature. Furthermore, this accelerates readiness to defrost the windshield, improving both safety as well as comfort, with greater benefits in colder climates, particularly when combined with hybridization’s need for engine on-time just for cabin heating. Such products have been in the market now for several years; however they are bulky, heavy and expensive, yielding opportunities for competitive alternatives. Customer voice expresses needs for less complex designs that reduce package space, mass, and part count (i.e. cost) while maintaining or improving performance, including the integration of an active rather than passive exhaust bypass control valve. This paper highlights the design evolution of EHRS, including relative benchmarking of competing products, comparing various aspects…
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The Prospect and Benefits of Using the Partial-Averaged Navier-Stokes Method for Engine Flows

AVL LIST GmbH-Branislav Basara, Zoran Pavlovic
Texas A&M University-Sharath Girimaji
  • Technical Paper
  • 2020-01-1107
To be published on 2020-04-14 by SAE International in United States
This paper presents calculations of engine flows by using the Partially-Averaged Navier-Stokes (PANS) method [1]. The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. In the conventional well-established PANS, the unresolved to total kinetic energy ratio fk known as the cut-off control parameter, is calculated from the grid spacing and the computed integral turbulence length scale. Several formulations have been derived up to now. In most of these formulations, fk is obtained by summing up the resolved turbulence, while the unresolved motion is computed from the modelled equation. The PANS method was successfully used on large number applications but mainly on static geometries, e.g. [2]; [3]. This is due to calculations of the resolved kinetic energy which is obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as…
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Large-Scale Simulation of PEM Fuel Cell Using a “3D+1D” Model

Imperial College London-Yang Jiang
Tianjin University-Biao Xie, Guobin Zhang, Yan Yin, Qing Du, Kui Jiao
  • Technical Paper
  • 2020-01-0860
To be published on 2020-04-14 by SAE International in United States
Nowadays, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA). Therefore in this study, a “3D+1D” model is developed in which the 3D domain contains flow field and gas diffusion layer (GDL) of cathode side. The remaining part of MEA and the anode side are treated as 1D domain. The model considers two-phase flow…
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Improving battery safety and longevity through uncertainty modeling of lithium-ion batteries and preventing the local over-charge/over-discharge

Trine University-Changhong Liu
  • Technical Paper
  • 2020-01-0450
To be published on 2020-04-14 by SAE International in United States
The battery electrodes are porous and have complicated microstructures due to irregular sizes and shapes of pores. Electrode design parameters like porosity, thickness, particle size, and conductivity can vary from one local area to another in one cell. Even under the normal operating range, some local areas may experience over-charge/over-discharge, extensive degradation, and rapid heat generation. These local events are not easy to observe or measure at the beginning and can eventually lead to catastrophic failure of the whole cell if no actions are taken. Therefore, the uncertainty of these parameters has a significant effect on the longevity and safety of batteries. Most of the electrochemical battery models assume design parameters have constant values in a cell which is not able to capture the uncertainty described above. To prevent any catastrophic failure, the applied current should be cut off before any over-charge/over-discharge and rapid heat generation caused by these random local areas. In this work, a new method is developed to simulate random local events and design new control strategies to increase longevity and safety.…
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Efficient Surrogate-based NVH Optimization of a Full Vehicle Using FRF Based Substructuring

Beta CAE Systems USA Inc.-Inseok Park
Oakland University-Dimitrios Papadimitriou
  • Technical Paper
  • 2020-01-0629
To be published on 2020-04-14 by SAE International in United States
The computer simulation with the Finite Element (FE) code for the structural dynamics becomes more attractive in the industry since it enables quickly evaluating the dynamic performances of the mechanical products like automobile in development with improved accuracy owing to modern technological advancements. However, it normally takes a prohibitive amount of computation time when design optimization is performed with conducting a dynamic analysis using a large-scale FE model many times. Exploiting Dynamic Structuring (DS) leads to alleviating the computational complexity since DS necessities iterative reanalysis of only the substructure(s) to be optimally designed. In this research, FRF Based Substructuring (FBS) is implemented to realize the benefits of DS for fast single- and multi-objective evolutionary design optimization. Also, Differential Evolution (DE) is first combined with two sorting approaches of NSGA-II and Infeasibility Driven Evolutionary Algorithm (IDEA) for effective constrained single- and multi-objective evolutionary optimization. The effectiveness of the proposed algorithm (NSGA-II/DE-IDEA) is verified using several test functions for constrained single- and multi-objective optimization. To circumvent the need for frequent time-consuming simulation runs, Kriging surrogate models are…
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Numerical Investigation and Experimental Comparison of ECN Spray G at Flash Boiling Conditions

AVL List GmbH-Bejoy Mandumpala Devassy, Zvonimir Petranovic, Wilfried Edelbauer
  • Technical Paper
  • 2020-01-0827
To be published on 2020-04-14 by SAE International in United States
Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling process occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved. It is noticed that immediately after the removal of the rupture disk, a sudden depressurization occurs at the pipe’s exit resulting in the onset of violent evaporation due to flashing which limits the pressure decrease to a value slightly below the saturation pressure. Later, the flash boiling model is applied to investigate a real-size 8-hole GDI injector from Engine Combustion…
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Real Fuel Modeling for Gasoline Compression Ignition Engine

Hyundai-Kia America Technical Center Inc.-Mayuri Wagh, Nahm Roh Joo, Philip Zoldak
Michigan Technological University-Hyejun Won, Youngchul Ra
  • Technical Paper
  • 2020-01-0784
To be published on 2020-04-14 by SAE International in United States
Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI, and RCCI for gasoline light duty (LD) engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. 3D CFD combustion modeling is used to model auto-ignition of gasoline fuel under compression ignition condition necessitating the need for a gasoline fuel properties and chemistry model. Using the entire fuel consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the fuel is represented by few major components of the desired fuel. Real fuel modeling consists of modeling the physical properties (e.g. evaporation) using the spray model and the chemical kinetic properties (e.g. combustion) using the chemistry model. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode. The fuels differentiate in the number and concentration of components in their surrogate models, which are between 10…
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Automotive Wheel Metamodeling using Response Surface Methodology (RSM) Technique

FCA Engineering India Pvt. Ltd.-Gurumoorthy S, Muthukumar Arunachalam, Sundaravadivelu Mohan
FCA US LLC-Thomas Oery
  • Technical Paper
  • 2020-01-1234
To be published on 2020-04-14 by SAE International in United States
Computational cost plays a major role in the performance of scientific and engineering simulation. This in turn makes the virtual validation process complex and time consuming. In the simulation process, achievement of appropriate level of accurate models as close as physical testing is the root for increase in the computational cost. During preliminary phase of product development, it is difficult to identify the appropriate size, shape and other parameters of the component and they will undergo several modifications in concept and other stages. An approximation model called metamodel or surrogate model has developed for reducing these effects and minimizing the computational cost. Metamodel can be used in the place of actual simulation models. Metamodel can be an algorithm or a mathematical relation representing the relations between input and output parameters. The scope of this paper is to generate approximate models (metamodels) for the automotive wheel with help of response surface methodology (RSM) using Isight commercial tool and to arrive at the optimum shape, size and weight of the wheels by considering all necessary loading conditions.…