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Investigating combustion characteristics of oxygenated gasoline and gasoline blended ethanol is a subject of recent interest. The non-linearity in the interaction of fuel components in the oxygenated gasoline can be studied by developing chemical kinetics of relevant surrogate of fewer components. This work proposes a new reduced four-component (isooctane, heptane, toluene, and ethanol) oxygenated gasoline surrogate mechanism consisting of 67 species and 325 reactions, applicable for dynamic CFD applications in engine combustion and sprays. The model introduces the addition of eight C1-C3 species into the previous model (Li et al; 2019) followed by extensive tuning of reaction rate constants of C7 - C8 chemistry. The current mechanism delivers excellent prediction capabilities in comprehensive combustion applications with an improved performance in lean conditions.

The investigation and measurement of particle emissions from foundation brakes require the use of a special adaptation of inertia dynamometer test systems. To have proper measurements for particle mass and particle number, the sampling system needs to minimize transport losses and reduce residence times inside the brake enclosure. Existing models and spreadsheets estimate key transport losses (diffusion, turbophoretic, contractions, gravitational, bends, and sampling isokinetics). A significant limitation of such models is that they cannot assess the turbulent flow and associated particle dynamics inside the brake enclosure; which are anticipated to be important. This paper presents a Design of Experiments (DOE) approach using Computational Fluid Dynamics (CFD) to predict the flow within a dynamometer enclosure under relevant operating conditions. The systematic approach allows the quantification of turbulence intensity, mean velocity profiles, and residence times.

Vehicle surface contamination can degrade not only soldier vision but also the effectiveness of camera and sensor systems mounted externally on the vehicle for autonomy and situational awareness. In order to control vehicle surface contamination, a better understanding of dust particle generation, transport and accumulation is necessary. The focus of the present work is simulation of vehicle surface contamination on the rear part of the vehicle due to the interaction of the combat vehicle track with the ground and dust in the surrounding ambient atmosphere. A notional tracked military vehicle is used for the Computational fluid dynamics (CFD) simulation. A CFD methodology with one-way-coupled Lagrangian particle modeling is used. The simulation is initially run with only air flow to solve the air pressure, velocity, and turbulence quantities in a steady state condition.

Wet clutches are complex hydrodynamic devices used in both conventional and electrified drivetrain systems. They couple or de-couple powertrain components for applications such as automatic shifting, engine disconnect and torque vectoring. Clutch engagement behaviors vary greatly, depending on design parameters and operating conditions. Because of their direct impact on vehicle drivability and fuel economy, a predictive CAE model is desired for enabling analytical design verification processes. During engagement, a wet clutch transmits torque through viscous shear and asperity contact. A conventional Coulomb’s model, which is routinely utilized in shift simulations, is inadequate to capture non-linear hydrodynamic effects for higher fidelity analysis. Extensive research has been conducted over the years to derive hydrodynamic torque transfer models based on 1D squeeze film or 3D CFD. They are typically coupled with an elastic asperity contact model for mechanical torque transfer.

Flow control devices can enable vehicle drag reduction through the mitigation of separation and by modifying local and global flow features. Passive vortex generators (VG) are an example of a flow control device that can be designed to re-energize weakly-attached boundary layers to prevent or minimize separation regions that can increase drag. Accurate numerical simulation of such devices and their impact on the vehicle aerodynamics is an important step towards enabling automated drag reduction and shape optimization for a wide range of vehicle concepts. This work demonstrates the use of an open-source computational-fluid dynamics (CFD) framework to enable an accurate and robust evaluation of passive vortex generators in support of vehicle drag reduction. Specifically, the backlight separation of the Ahmed body with a 25° slant is used to evaluate different turbulence models including variants of the RANS, DES, and LES formulations.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

The US Army Tank Automotive Research, Development and Engineering Center (TARDEC) has developed a unique physics based modeling & simulation (M&S) capability using Computational Fluid Dynamics (CFD) techniques to optimize automatic fire extinguishing system (AFES) designs and complement vehicle testing for both occupied and unoccupied spaces of military ground vehicles. The modeling techniques developed are based on reduced global kinetics for computational efficiency and are applicable to fire suppressants that are being used in Army vehicles namely, bromotrifluoromethane (Halon 1301), heptafluoropropane (HFC-227ea, trade name FM200), sodium-bicarbonate (SBC) powder, water + potassium acetate mixture, and pentafluoroethane (HFC-125, trade name, FE-25). These CFD simulations are performed using High Performance Computers (HPC) that enable the Army to assess AFES designs in a virtual world at far less cost than physical-fire tests.

This paper presents a computationally-efficient model of heat convection due to air circulation produced by rotor motion in the air gap of an electric machine. The model calculates heat flux at the boundaries of the rotor and stator as a function of the rotor and stator temperatures and rotor speed. It is shown that, under certain assumptions, this mapping has the homogeneity property. This property, among others, is used to pose a structure for the proposed model. The coefficients of the model are then determined by fitting the model to the results of a commercial Computational Fluid Dynamics (CFD) simulation program. The accuracy of the new model is compared to the CFD results, shown an error of less than 0.3% over the studied operating range.

Pre-chambers are a means to enable lean burn combustion strategies which can increase the thermal efficiency of gasoline spark ignition internal combustion engines. A new engine concept is evaluated in this work using computational simulations of non-reacting flow. The objective of the computational study was to evaluate the feasibility of several engine design configurations combined with fuel injection strategies to create local fuel/air mixtures in the pre-chambers above the ignition and flammability limits, while maintaining lean conditions in the main combustion chamber. The current work used computational fluid dynamics to develop a novel combustion chamber geometry where the flow was evaluated through a series of six design iterations to create ignitable mixtures (based on fuel-to-air equivalence ratio, ϕ) using fuel injection profiles and flow control via the piston, cylinder head, and pre-chamber geometry.

The Diesel engine combustion process results in harmful exhaust emissions, mainly composed of Particulate Matter (PM), Hydro Carbon (HC), Carbon monoxide (CO) and Nitrogen Oxides (NOx). Several technologies have been developed in the past decades to control these diesel emissions. One of the promising and well matured technology of reducing NOx is to implement Selective Catalytic Reduction (SCR) using ammonia (NH3) as the reducing agent. For an effective SCR system, the aqueous urea solutions should be fully decomposed into ammonia and it should be well distributed across the SCR. In the catalyst, all the ammonia is utilized for NOx reduction process. In the design stage, it is more viable to implement Computational Fluid Dynamics (CFD) for design iterations to determine an optimized SCR system based on SCR flow distribution. And in later stage, experimental test is required to predict the after-treatment system performance based on NOx reduction.

Diesel exhaust aftertreatment solutions using injection, such as urea-based SCR and lean NOx trap systems, effectively reduce the emission NOx level in various light vehicles, commercial vehicles, and industrial applications. The performance of the injector plays an important role in successfully utilizing this type of technology, and the CFD tool provides not only a time and cost-saving, but also a reliable solution for extensively design iterations for optimizing the injector internal nozzle flow design. Inspired by this fact, a virtual test methodology on injector dosing rate utilizing CFD was proposed for the design process of injector internal nozzle flows.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

With introductions of stringent diesel engine emission regulations, the DOC and DPF systems have become the mainstream technology to eliminate soot particles through diesel combustion under various operation conditions. Urea-based SCR has been the mainstream technical direction to reduce NOx emissions. For both technologies, low-temperature conditions or cold start conditions pose challenges to activate DOC or SCR emission-reduction performance. To address this issue, mini or full flow burner systems may be used to increase exhaust temperature to reach DOC light-off or SCR initiation temperature by combustion of diesel fuel. In essence, the burner systems incorporate a fuel injector, spray atomization, proper fuel / air mixing mechanisms, and combustion control as independent heat sources.

This paper presents a hybrid method that predicts the whistle occurrence of an automotive exhaust tuning device. The method utilizes inputs from a limited amount of test work or numerical simulation to predict the whistle occurrence in a wider range of flow conditions (temperature and velocity). It has the advantages of being quick and low cost compared with extensive tests or the computational fluid dynamics approach.

In order to satisfy tightening global emissions regulations, diesel truck manufacturers are striving to meet increasingly stringent Oxides of Nitrogen (NOx) reduction standards. The majority of heavy duty diesel trucks have integrated urea SCR NOx abatement strategies. To this end, aftertreatment systems need to be properly engineered to achieve high conversion efficiencies. A EuroV intent urea SCR system is evaluated and failed to meet NOx conversion targets with severe urea deposit formation. Systematic enhancements of the design have been performed to enable it to meet targets, including emission reduction efficiency via improved reagent mixing, evaporation, distribution, back pressure, and removing of urea deposits. Multiple urea mixers, injector mounting positions and various system layouts are developed and evaluated, including both CFD analysis and full scale laboratory tests.

A numerical study has been conducted to investigate possible extension of the low load limit of the HCCI operating range by charge stratification using direct injection. A wide range of SOI timings at a low load HCCI engine operating condition were numerically examined to investigate the effect of DI. A multidimensional CFD code KIVA3v with a turbulent combustion model based on a modified flamelet approach was used for the numerical study. The CFD code was validated against experimental data by comparing pressure traces at different SOI’s. A parametric study on the effect of SOI on combustion has been carried out using the validated code. Two parameters, the combustion efficiency and CO emissions, were chosen to examine the effect of SOI on combustion, which showed good agreement between numerical results and experiments. Analysis of the in-cylinder flow field was carried out to identify the source of CO emissions at various SOI’s.

Diesel burners introduce combustion of diesel fuel to raise exhaust gas temperature to Diesel Oxidization Catalyst (DOC) light-off or Diesel Particulate Filter (DPF) regeneration conditions, thereby eliminating the need of engine measures such as post-injections. Such diesel combustion requirement nevertheless poses challenges to burner development especially in combustion control and risk mitigation of DPF material failure. In particular, burner design must satisfy good soot distribution and heat distribution at DPF front face after meeting minimum requirements of ignition, heat release, and backpressure. In burner development, Computational Fluid Dynamics (CFD) models have been developed based on commercial codes for burner thermal and flow management with capability of predicting comprehensive physical and chemical phenomena including turbulence induced mixing, fuel injection, fuel droplet transport, diesel combustion, radiation, conjugate heat transfer and etc.

Multi-zone CFD simulations with detailed kinetics were used to model iso-octane HCCI experiments performed on a single-cylinder research engine. The modeling goals were to validate the method (multi-zone combustion modeling) and the reaction mechanism (LLNL 857 species iso-octane) by comparing model results to detailed exhaust speciation data, which was obtained with gas chromatography. The model is compared to experiments run at 1200 RPM and 1.35 bar boost pressure over an equivalence ratio range from 0.08 to 0.28. Fuel was introduced far upstream to ensure fuel and air homogeneity prior to entering the 13.8:1 compression ratio, shallow-bowl combustion chamber of this 4-stroke engine. The CFD grid incorporated a very detailed representation of the crevices, including the top-land ring crevice and head-gasket crevice. The ring crevice is resolved all the way into the ring pocket volume. The detailed grid was required to capture regions where emission species are formed and retained.