Computational Fluid Dynamics Simulation of an Opposed-Piston Two-Stroke Gasoline Compression Ignition Engine

2018 ◽  
Author(s):  
Ahmed Abdul Moiz ◽  
Janardhan Kodavasal ◽  
Sibendu Som ◽  
Reed Hanson ◽  
Fabien Redon ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Dynamics Simulation ◽  
System Level ◽  
Experimental Program ◽  
Compression Ignition ◽  
Compression Ignition Engine ◽  
Cfd Simulations ◽  
System Level Simulation ◽  
Light Duty

The paper describes the results from a computational fluid dynamics (CFD) simulation campaign that is complementary to an ongoing experimental program to develop an opposed-piston (OP) two-stroke gasoline compression ignition (GCI) engine for application in light-duty trucks. The simulation workflow and results are explained. First, open-cycle 3-D CFD simulations (in Converge CFD) are performed to simulate the scavenging process—gas exchange through the intake ports, cylinder, and exhaust ports. The results from these scavenging calculations are then fed into a model of this engine built in the system-level simulation tool (in GT-POWER), which in turn provides initial conditions for closed-cycle 3-D CFD simulations. These simulations are used to assess combustion by employing standard spray models and a chemical kinetic mechanism for gasoline. Validation of a representative set of engine operating points is performed in this way to gain confidence in the CFD model setup. Six injectors were then screened according to metrics of wall-wetting, maximum pressure rise rate, combustion efficiency and emission levels. Further CFD simulations have been carried out with parameter sweeps applying design of experiments (DoE) methods to finalize on candidate injectors, piston-bowls and injection strategies. The intended outcome of this program is a three-cylinder OP GCI engine equipped with a turbocharger and a supercharger targeting a 30% improvement in brake thermal efficiency (BTE) over conventional light-duty diesel engines.

Microscale Computational Fluid Dynamics Simulation for Wind Mapping Over Complex Topographic Terrains

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Ashkan Rasouli ◽  
Horia Hangan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Spatial Resolution ◽  
Three Dimensional ◽  
Dynamics Simulation ◽  
Scale Model ◽  
Cfd Model ◽  
Cfd Simulations ◽  
Wide Range ◽  
Wind Mapping

Wind mapping is of utmost importance in various wind energy and wind engineering applications. The available wind atlases usually provide wind data with low spatial resolution relative to the wind turbine height and usually neglect the effect of topographic features with relatively large or sudden changes in elevation. Two benchmark cases are studied for computational fluid dynamics (CFD) model evaluation on smooth two-dimensional (2D) and three-dimensional (3D) hills. Thereafter, a procedure is introduced to build CFD model of a complex terrain with high terrain roughness heights (dense urban area with skyscrapers) starting from existing topography maps in order to properly extend the wind atlas data over complex terrains. CFD simulations are carried out on a 1:3000 scale model of complex topographic area using Reynolds averaged Navier–Stokes (RANS) equations along with shear stress transport (SST) k-ω turbulence model and the results are compared with the wind tunnel measurements on the same model. The study shows that CFD simulations can be successfully used in qualifying and quantifying the flow over complex topography consisting of a wide range of roughness heights, enabling to map the flow structure with very high spatial resolution.

Computational Fluid Dynamics Simulation of Gasoline Compression Ignition

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Janardhan Kodavasal ◽  
Christopher P. Kolodziej ◽  
Stephen A. Ciatti ◽  
Sibendu Som
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Turbulence Model ◽  
Turbulence Models ◽  
Chemical Kinetic ◽  
Dynamics Simulation ◽  
Combustion Model ◽  
Compression Ignition ◽  
Simulation Results ◽  
The Impact

Gasoline compression ignition (GCI) is a low temperature combustion (LTC) concept that has been gaining increasing interest over the recent years owing to its potential to achieve diesel-like thermal efficiencies with significantly reduced engine-out nitrogen oxides (NOx) and soot emissions compared to diesel engines. In this work, closed-cycle computational fluid dynamics (CFD) simulations are performed of this combustion mode using a sector mesh in an effort to understand effects of model settings on simulation results. One goal of this work is to provide recommendations for grid resolution, combustion model, chemical kinetic mechanism, and turbulence model to accurately capture experimental combustion characteristics. Grid resolutions ranging from 0.7 mm to 0.1 mm minimum cell sizes were evaluated in conjunction with both Reynolds averaged Navier–Stokes (RANS) and large eddy simulation (LES) based turbulence models. Solution of chemical kinetics using the multizone approach is evaluated against the detailed approach of solving chemistry in every cell. The relatively small primary reference fuel (PRF) mechanism (48 species) used in this study is also evaluated against a larger 312-species gasoline mechanism. Based on these studies, the following model settings are chosen keeping in mind both accuracy and computation costs—0.175 mm minimum cell size grid, RANS turbulence model, 48-species PRF mechanism, and multizone chemistry solution with bin limits of 5 K in temperature and 0.05 in equivalence ratio. With these settings, the performance of the CFD model is evaluated against experimental results corresponding to a low load start of injection (SOI) timing sweep. The model is then exercised to investigate the effect of SOI on combustion phasing with constant intake valve closing (IVC) conditions and fueling over a range of SOI timings to isolate the impact of SOI on charge preparation and ignition. Simulation results indicate that there is an optimum SOI timing, in this case −30 deg aTDC (after top dead center), which results in the most stable combustion. Advancing injection with respect to this point leads to significant fuel mass burning in the colder squish region, leading to retarded phasing and ultimately misfire for SOI timings earlier than −42 deg aTDC. On the other hand, retarding injection beyond this optimum timing results in reduced residence time available for gasoline ignition kinetics, and also leads to retarded phasing, with misfire at SOI timings later than −15 deg aTDC.

An Eulerian Approach to Computational Fluid Dynamics Simulation of a Chemical-Looping Combustion Reactor With Chemical Reactions

2015 ◽  
Vol 138 (4) ◽  
Author(s):  
Subhodeep Banerjee ◽  
Ramesh K. Agarwal
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Fluidized Bed ◽  
Dynamics Simulation ◽  
Chemical Looping Combustion ◽  
Great Promise ◽  
Chemical Looping ◽  
Cfd Simulations ◽  
Eulerian Approach ◽  
Dual Fluidized Bed

Chemical-looping combustion (CLC) is a next-generation combustion technology that shows great promise in addressing the need for high-efficiency low-cost carbon capture from fossil fueled power plants. Although there have been a number of experimental studies on CLC in recent years, computational fluid dynamics (CFD) simulations have been limited in the literature. In this paper, simulation of a CLC reactor is conducted using the Eulerian approach in the commercial CFD solver ansys fluent based on a laboratory-scale experiment with a dual fluidized bed CLC reactor. The solid phase consists of a Fe-based oxygen carrier while the gaseous fuel used is syngas. The salient features of the fluidization behavior in the air reactor and fuel reactor beds representing a riser and a bubbling bed, respectively, as well as the down-comer, are accurately captured in the simulation. This work is among the few CFD simulations of a complete circulating dual fluidized bed system for CLC in 3D in the literature. It highlights the importance of 3D simulation of CLC systems and the need for more accurate empirical reaction rate data for future CLC simulations.

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