Eddy Simulation
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Fuel ◽  
2022 ◽  
Vol 313 ◽  
pp. 122735
Author(s):  
Jiun Cai Ong ◽  
Min Zhang ◽  
Morten Skov Jensen ◽  
Jens Honoré Walther

Fuel ◽  
2022 ◽  
Vol 313 ◽  
pp. 123031
Author(s):  
Wubingyi Shen ◽  
Yue Huang ◽  
Wei Yao ◽  
Hedong Liu ◽  
Yancheng You

2022 ◽  
Vol 120 ◽  
pp. 103051
Author(s):  
Chia-Ren Chu ◽  
Le-Em Huynh ◽  
Tso-Ren Wu

2022 ◽  
Vol 54 (1) ◽  
pp. 015502
Author(s):  
W A McMullan

Abstract This paper assesses the prediction of inert tracer gas dispersion within a cavity of height (H) 1.0 m, and unity aspect ratio, using large Eddy simulation (LES). The flow Reynolds number was 67 000, based on the freestream velocity and cavity height. The flow upstream of the cavity was laminar, producing a cavity shear layer which underwent a transition to turbulence over the cavity. Three distinct meshes are used, with grid spacings of H / 100 (coarse), H / 200 (intermediate), and H / 400 (fine) respectively. The Smagorinsky, WALE, and Germano-Lilly subgrid-scale models are used on each grid to quantify the effects of subgrid-scale modelling on the simulated flow. Coarsening the grid led to small changes in the predicted velocity field, and to substantial over-prediction of the tracer gas concentration statistics. Quantitative metric analysis of the tracer gas statistics showed that the coarse grid simulations yielded results outside of acceptable tolerances, while the intermediate and fine grids produced acceptable output. Interrogation of the fluid dynamics present in each simulation showed that the evolution of the cavity shear layer is heavily influenced by the grid and subgrid scale model. On the coarse and intermediate grids the development of the shear layer is delayed, inhibiting the entrainment and mixing of the tracer gas into the shear layer, reducing the removal of the tracer gas from the cavity. On the fine grid, the shear layer developed more rapidly, resulting in enhanced removal of the tracer gas from the cavity. Concentration probability density functions showed that the fine grid simulations accurately predicted the range, and the most probable value, of the tracer gas concentration towards both walls of the cavity. The results presented in this paper show that the WALE and Germano-Lilly models may be advantageous over the standard Smagorinsky model for simulations of pollutant dispersion in the urban environment.


2022 ◽  
pp. 146808742110703
Author(s):  
Shervin Karimkashi ◽  
Mahmoud Gadalla ◽  
Jeevananthan Kannan ◽  
Bulut Tekgül ◽  
Ossi Kaario ◽  
...  

In dual-fuel compression-ignition engines, replacing common fuels such as methane with renewable and widely available fuels such as methanol is desirable. However, a fine-grained understanding of diesel/methanol ignition compared to diesel/methane is lacking. Here, large-eddy simulation (LES) coupled with finite rate chemistry is utilized to study diesel spray-assisted ignition of methane and methanol. A diesel surrogate fuel ( n-dodecane) spray is injected into ambient methane-air or methanol-air mixtures at a fixed lean equivalence ratio [Formula: see text] = 0.5 at various ambient temperatures ([Formula: see text] = 900, 950, 1000 K). The main objectives are to (1) compare the ignition characteristics of diesel/methanol with diesel/methane at different [Formula: see text], (2) explore the relative importance of low-temperature chemistry (LTC) to high-temperature chemistry (HTC), and (3) identify the key differences between oxidation reactions of n-dodecane with methane or methanol. Results from homogeneous reactor calculations as well as 3 + 3 LES are reported. For both DF configurations, increasing [Formula: see text] leads to earlier first- and second-stage ignition. Methanol/ n-dodecane mixture is observed to have a longer ignition delay time (IDT) compared to methane/ n-dodecane, for example ≈ three times longer IDT at [Formula: see text] = 950 K. While the ignition response of methane to [Formula: see text] is systematic and robust, the [Formula: see text] window for n-dodecane/methanol ignition is very narrow and for the investigated conditions, only at 950 K robust ignition is observed. For methanol at [Formula: see text] = 1000 K, the lean ambient mixture autoignites before spray ignition while at [Formula: see text] = 900 K full ignition is not observed after 3 ms, although the first-stage ignition is reported. For methanol, LTC is considerably weaker than for methane and in fully igniting cases, heat release map analysis demonstrates the dominant contribution of HTC to total heat release rate for methanol. Reaction sensitivity analysis shows that stronger consumption of OH radicals by methanol compared to methane leads to the further delay in the spray ignition of n-dodecane/methanol. Finally, a simple and novel approach is developed to estimate IDT in reacting LES using zero-dimensional IDT calculations weighted by residence time from non-reacting LES data.


2022 ◽  
Vol 22 (1) ◽  
pp. 319-333
Author(s):  
Ian Boutle ◽  
Wayne Angevine ◽  
Jian-Wen Bao ◽  
Thierry Bergot ◽  
Ritthik Bhattacharya ◽  
...  

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.


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