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Diesel exhaust after treatment 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 is crucial for successfully utilizing this type of technology, and a simulation tool plays an important role in the virtual design, that the performance of the injector is evaluated to reach the optimized design. The virtual test methodology using CFD to capture the fluid dynamics of the injector internal flow has been previously developed and validated for quantifying the dosing rate of the test injector. In this study, the capability of the virtual test methodology was extended to determine the spray angle of the test injector, and the effect of the manufacturing process on the injector internal nozzle flow characteristics was investigated using the enhanced virtual test methodology.

Thermo-mechanical fatigue (TMF) resistance characterization and life assessment are extremely important in the durability/reliability design and validation of vehicle exhaust components/systems, which are subjected to combined thermal and mechanical loadings during operation. The current thermal-fatigue related design and validation for exhaust products are essentially based on testing and the interpretation of test results. However, thermal-fatigue testing are costly and time consuming, therefore, computer aided engineering (CAE) based virtual thermal-fatigue life assessment tools with predictive powers are strongly desired. Many thermal-fatigue methods have been developed and eventually implemented into the CAE tools; however, most of them are based on deterministic life assessment approach, which cannot provide satisfactory explanation for the observed uncertainties introduced in thermal-fatigue failure data.

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.

To meet EPA Tier IV large diesel engine emission targets, intensive development efforts are necessary to achieve NOx reduction and Particulate Matter (PM) reduction targets [1]. With respect to NOx reduction, liquid urea is typically used as the reagent to react with NOx via SCR catalyst [2]. Regarding to PM reduction, additional heat is required to raise exhaust temperature to reach DPF active / passive regeneration performance window [3]. Typically the heat can be generated by external diesel burners which allow diesel liquid droplets to react directly with oxygen in the exhaust gas [4]. Alternatively the heat can be generated by catalytic burners which enable diesel vapor to react with oxygen via DOC catalyst mostly through surface reactions [5].

Stringent global emissions legislation demands effective NOx reduction strategies, particularly for the aftertreatment, and current typical liquid urea SCR systems achieve efficiencies greater than 90% [1]. However, with such high-performing systems comes the trade-off of requiring a tank of reductant (urea water solution) to be filled regularly, usually as soon as the fuel fillings or as far as oil changes. Advantages of solid reductants, particularly ammonium carbamate, include greater ammonia densities, enabling the reductant refill interval to be extended several multiples versus a given reductant volume of urea, or diesel exhaust fluid (DEF) [2]. An additional advantage is direct gaseous ammonia dosing, enabling reductant injection at lower exhaust temperatures to widen its operational coverage achieving greater emissions reduction potential [3], as well as eliminating deposits, reducing mixing lengths, and avoiding freeze/thaw risks and investments.

As Selective Catalytic Reduction (SCR) NOx abatement systems gain commercial acceptance and popularity, the need for efficiency predictive capabilities increases. To this end, a flow bench was developed capable of varying steady state inputs (temperature, flow rate and NOx concentration). The efficiencies of various SCR systems was measured and compared. This concept of a steady state flow bench approach allows for an efficient and cost effective means to evaluate comparable system designs.

In 2007 emissions regulations for on-road light to heavy duty Diesel trucks will require the use of Diesel Particulate Filters (DPFs). The uniform distribution of soot on the DPF is critical for adequate long term performance of these DPFs. This is especially true when cordierite is used instead of silicon carbide for the DPF substrate, due to the reduced thermal conductivity and reduced peak temperature capability of cordierite. In addition to flow uniformity, an inverted flow pattern where more of the flow is forced radially outward on the substrate face could be beneficial to counteract thermal losses in the converter. This paper describes a dispersion device that can improve flow geometry with a low backpressure penalty. Computational fluid dynamics (CFD) results and experimental data are presented for this device. Additionally, cone design options are explored, and CFD analysis results of the cone design are presented.

The Objective of this paper is to explain a procedure for using Arbitrary Shape Deformation (ASD) technology coupled with Computational Fluid Dynamics (CFD) software for product development of a generic catalytic converter inlet-cone diffuser. The paper uses the development of an inlet-cone diffuser as an example of such a process. The non-uniformities of the flow field at the inlet of the catalytic converter bricks are considered to have a negative impact on the converter performance. Computational Fluid Dynamics (CFD) is a powerful tool for computing the flow field in the exhaust system and the catalytic converter which enables the engineers to optimize the geometry of the inlet cone at a very early design stage. The goal of this study is to optimize the shape of an inlet-cone diffuser upstream of a catalytic converter to reduce the pressure drop and maximize the uniformity of exhaust gas distribution on the catalytic converter inlet.

A numerical study of transient, compressible, reacting flow inside an adiabatic catalytic converter is carried out with the one–dimensional model. The important physical/chemical phenomena existing in the catalyzed monolith are included in the model. The effects of the time dependent inlet mass flow rate and some important geometrical parameters on the gas/solid phase temperatures along the converter and the conversion efficiency are investigated. Results show that the monolith (wall) temperature along the converter, the maximum monolith temperature, the location of the reaction front, and the conversion efficiency are affected by time dependent fluctuations of the inlet mass flow rate. In addition, the converter characteristics and the conversion efficiency are very sensitive to the geometrical parameters (such as the cell density, the void fraction, and the wall thickness).