A chemical-diffusive model for simulating detonative combustion with constrained detonation cell sizes

2021 ◽  
Vol 230 ◽  
pp. 111417
Author(s):  
Xiaoyi Lu ◽  
Carolyn R. Kaplan ◽  
Elaine S. Oran
2021 ◽  
Author(s):  
Xiaoyi Lu ◽  
Carolyn R. Kaplan ◽  
Elaine S. Oran

2021 ◽  
Vol 232 ◽  
pp. 111517
Author(s):  
Xiaoyi Lu ◽  
Carolyn R. Kaplan ◽  
Elaine S. Oran

2021 ◽  
pp. 126512
Author(s):  
Cristiana Di Cristo ◽  
Michele Iervolino ◽  
Tommaso Moramarco ◽  
Andrea Vacca
Keyword(s):  

Author(s):  
D. A. Kessler ◽  
V. N. Gamezo ◽  
E. S. Oran

The propagation of detonations through several fuel–air mixtures with spatially varying fuel concentrations is examined numerically. The detonations propagate through two-dimensional channels, inside of which the gradient of mixture composition is oriented normal to the direction of propagation. The simulations are performed using a two-component, single-step reaction model calibrated so that one-dimensional detonation properties of model low- and high-activation-energy mixtures are similar to those observed in a typical hydrocarbon–air mixture. In the low-activation-energy mixture, the reaction zone structure is complex, consisting of curved fuel-lean and fuel-rich detonations near the line of stoichiometry that transition to decoupled shocks and turbulent deflagrations near the channel walls where the mixture is extremely fuel-lean or fuel-rich. Reactants that are not consumed by the leading detonation combine downstream and burn in a diffusion flame. Detonation cells produced by the unstable reaction front vary in size across the channel, growing larger away from the line of stoichiometry. As the size of the channel decreases relative to the size of a detonation cell, the effect of the mixture composition gradient is lessened and cells of similar sizes form. In the high-activation-energy mixture, detonations propagate more slowly as the magnitude of the mixture composition gradient is increased and can be quenched in a large enough gradient.


2021 ◽  
Author(s):  
Ahmed Monofy ◽  
Fulvio Boano ◽  
Stanley B. Grant ◽  
Megan A. Rippy

<p>In-stream environments, many biogeochemical processes occur in the benthic biolayer, i.e., within sediments at a very shallow depth close to the sediment-water interface (SWI). These processes are important for stream ecology and the overall environment.</p><p>Here, a 1D diffusive model is used to analyze the vertical exchange of solutes through the SWI and in the benthic biolayer. The model is applied to an extensive set of previously published laboratory experiments of solute exchange with different bed morphologies: flatbeds, dunes, and alternate bars. Although these different bed features induce mixing that is controlled by different physical processes at the SWI, overall mixing within the sediment is well represented by a parsimonious diffusive model, provided that the diffusivity profile declines exponentially with sediment depth.</p><p>For all morphology types, mixing is better simulated by an exponential diffusivity model than a constant diffusivity approach. Two parameters define the exponential diffusivity model; the effective diffusivity at the SWI, and a depth scale over which the exponential profile decays. Using a combination of classification and regression trees (CART) and multiple linear regression approaches, we demonstrate that a single predictive model captures measured variability in the effective diffusivity coefficient at the SWI across all morphological types. The best predictive model for the decay depth scale, on the other hand, is tailored to each morphological type separately.</p><p>The predictive framework developed here contributes to our understanding of the physical processes responsible for mixing across the SWI,  and therefore the in-bed processes that contribute to the biogeochemical processing of nutrients and other contaminants in streams.</p>


2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Alexandros Roniotis ◽  
Kostas Marias ◽  
Vangelis Sakkalis ◽  
Georgios C. Manikis ◽  
Michalis Zervakis

Applying diffusive models for simulating the spatiotemporal change of concentration of tumour cells is a modern application of predictive oncology. Diffusive models are used for modelling glioblastoma, the most aggressive type of glioma. This paper presents the results of applying a linear quadratic model for simulating the effects of radiotherapy on an advanced diffusive glioma model. This diffusive model takes into consideration the heterogeneous velocity of glioma in gray and white matter and the anisotropic migration of tumor cells, which is facilitated along white fibers. This work uses normal brain atlases for extracting the proportions of white and gray matter and the diffusion tensors used for anisotropy. The paper also presents the results of applying this glioma model on real clinical datasets.


1998 ◽  
Vol 258 (1-2) ◽  
pp. 109-122 ◽  
Author(s):  
O.J. O’Loan ◽  
M.R. Evans ◽  
M.E. Cates
Keyword(s):  

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