相关论文: Skeletal Reaction Models for Methane Combustion
Due to severe societal and environmental impacts, wildfire prediction using multi-modal sensing data has become a highly sought-after data-analytical tool by various stakeholders (such as state governments and power utility companies) to…
The inherent behavioral variability exhibited by stochastic biochemical systems makes it a challenging task for human experts to manually analyze them. Computational modeling of such systems helps in investigating and predicting the…
Sensitivity analysis is a process of computing sensitivity indices, which are certain measures of importance of parameters in influencing the outputs of mathematical models. Sensitivity indices computed in variance-based sensitivity…
Skeleton-based human action recognition is a powerful approach for understanding human behaviour from pose data, but collecting large-scale, diverse, and well-annotated 3D skeleton datasets is both expensive and labor-intensive. To address…
This paper presents simulations of stoichiometric methane/air premixed flames into a microchannel at atmospheric pressure. These simulations result from numerical resolutions of reduced-order models. Indeed, combustion control into…
We present a theoretical and computational framework based on fractional calculus for the analysis of the nonlocal static response of cylindrical shell panels. The differ-integral nature of fractional derivatives allows an efficient and…
The present study proposes an optimized computational fluid dynamics (CFD) modelling framework to provide a complete and accurate representation of combustion and heat transfer phenomena in the radiation section of an industrial top-fired…
It is essential that mesoscopic simulations of reactive systems reproduce the correct statistical distributions at thermodynamic equilibrium. By considering a compressible fluctuating hydrodynamics (FHD) simulation method of ideal gas…
We treat the accurate simulation of the calcination reaction in particles, where the particles are large and, thus, the inner-particle processes must be resolved. Because these processes need to be described with coupled partial…
The development of computational models for the numerical simulation of chemically reacting flows operating in the turbulent regime requires the solution of partial differential equations that represent the balance of mass, linear momentum,…
Among the numerous questions that arise concerning the exploitation of petroleum from unconventional reservoirs, lie the questions of the composition of hydrocarbons present in deep seated HP-HT reservoirs or produced during in-situ…
This study performs a linear analysis of a turbulent reacting methane-air jet flame, with the goal of predicting the response of the reacting flow to upstream acoustic actuation. Accounting for heat release fluctuations is a vital component…
Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…
Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data remains a major challenge due to limited throughput and model flexibility. Recent advances…
Model reduction methods are relevant when the computation time of a full convection-diffusion-reaction simulation based on detailed chemical reaction mechanisms is too large. In this article, we review a model reduction approach based on…
Recent developments of the Cascade-Exciton Model (CEM) of nuclear reactions to describe high energy particle induced fission are briefly described. The increased accuracy and predictive power of the CEM are shown by several examples.…
Performing a shell model calculation for heavy nuclei has been a long-standing problem in nuclear physics. Here we propose one possible solution. The central idea of this proposal is to take the advantages of two existing models, the…
A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with examples for three…
The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems, including combustion, is to couple them to physical and…
Recently, methanol was identified as a sensitive target system to probe variations of the proton-to-electron mass ratio $\mu$ [Jansen \emph{et al.} Phys. Rev. Lett. \textbf{106}, 100801 (2011)]. The high sensitivity of methanol originates…