Search

Cryogenic carbon capture (CCC) is an innovative technology to desublimate $\text {CO}_2$ out of industrial flue gases. A comprehensive understanding of $\text {CO}_2$ desublimation and sublimation is essential for widespread application of CCC, which is highly challenging due to the complex physics behind. In this work, a lattice Boltzmann (LB) model is proposed to study $\text {CO}_2$ desublimation and sublimation for different operating conditions, including the bed temperature (subcooling degree $\Delta T_s$), gas feed rate (Péclet number $Pe $) and bed porosity ($\psi$). The $\text {CO}_2$ desublimation and sublimation properties are reproduced. Interactions between convective $\text {CO}_2$ supply and desublimation/sublimation intensity are analysed. In the single-grain case, $Pe $ is suggested to exceed a critical value $Pe _c$ at each $\Delta T_s$ to avoid the convection-limited regime. Beyond $Pe _c$ , the $\text {CO}_2$ capture rate ($v_c$) grows monotonically with $\Delta T_s$ , indicating a desublimation-limited regime. In the packed bed case, multiple grains render the convective $\text {CO}_2$ supply insufficient and make CCC operate under the convection-limited mechanism. Besides, in small- $\Delta T_s$ and high- $Pe $ tests, $\text {CO}_2$ desublimation becomes insufficient compared with convective $\text {CO}_2$ supply, thus introducing the desublimation-limited regime with severe $\text {CO}_2$ capture capacity loss ($\eta _d$). Moreover, large $\psi$ enhances gas mobility while decreasing cold grain volume. A moderate porosity $\psi _c$ is recommended for improving the $\text {CO}_2$ capture performance. By analysing $v_c$ and $\eta _d$ , regime diagrams are proposed in $\Delta T_s$ – $Pe $ space to show distributions of convection-limited and desublimation-limited regimes, thus suggesting optimal conditions for efficient $\text {CO}_2$ capture. This work develops a viable LB model to examine CCC under extensive operating conditions, contributing to facilitating its application. [ABSTRACT FROM AUTHOR]

The present work assesses the impact - in terms of time to solution, throughput analysis, and hardware scalability - of transferring computationally intensive tasks, found in compressible reacting flow solvers, to the GPU. Attention is focused on outlining the workflow and data transfer penalties associated with "plugging in" a recently developed GPU-based chemistry library into (a) a purely CPU-based solver and (b) a GPU-based solver, where, except for the chemistry, all other variables are computed on the GPU. This comparison allows quantification of host-to-device (and vice versa) data transfer penalties on the overall solver speedup as a function of mesh and reaction mechanism size. To this end, a recently developed GPU-based chemistry library known as UMChemGPU is employed to treat the kinetics in the flow solver KARFS. UMChemGPU replaces conventional CPU-based Cantera routines using a matrix-based formulation. The impact of i) data transfer times, ii) chemistry acceleration, and iii) the hardware architecture is studied in detail in the context of GPU saturation limits. Hydrogen and dimethyl ether (DME) reaction mechanisms are used to assess the impact of the number of species/reactions on overall/chemistry-only speedup. It was found that offloading the source term computation to UMChemGPU results in up to 7X reduction in overall time to solution and four orders of magnitude faster source term computation compared to conventional CPU-based methods. Furthermore, the metrics for achieving maximum performance gain using GPU chemistry with an MPI + CUDA solver are explained using the Roofline model. Integrating the UMChemGPU with an MPI + OpenMP solver does not improve the overall performance due to the associated data copy time between the device (GPU) and host (CPU) memory spaces. The performance portability was demonstrated using three different GPU architectures, and the findings are expected to translate to a wide variety of high-performance codes in the combustion community. [ABSTRACT FROM AUTHOR]

The development of reduced-order combustion models able to accurately reproduce the physics of reactive systems has been a highly challenging aspect of numerical combustion research in the recent past. The complexity of the problem can be reduced by identifying and using low-dimensional manifolds able to account for turbulence-chemistry interactions. Recently, Principal Components Analysis (PCA) has shown its potential in reducing the dimensionality of a chemically reactive system while minimizing the reconstruction error. The present work demonstrates the application of the Manifold Generated by Local PCA (MG-L-PCA) approach in direct numerical simulation (DNS) of turbulent flames. The approach is enhanced with an unsupervised clustering based on Vector Quantization PCA (VQPCA) and an on-the-fly PCA-based classification technique. The reduced model is then applied on a three-dimensional (3D) turbulent premixed NH 3 /air flame by transporting only a subset of the original state-space variables on the computational grid and using the PCA basis to reconstruct the non-transported variables. Results are compared with both a detailed reaction mechanism and a Computational Singular Perturbation (CSP) reduced skeletal mechanism. A comparison between training the reduced model using one-dimensional (1D) and 3D data sets is also included. Overall, the MG-L-PCA allows not only for a reduction in the number of transport equations, but also a significant reduction in the stiffness of the system, while providing highly accurate results. [ABSTRACT FROM AUTHOR]

Cryogenic carbon capture (CCC) can preferentially desublimate $\text {CO}_2$ out of the flue gas. A widespread application of CCC requires a comprehensive understanding of $\text {CO}_2$ desublimation properties. This is, however, highly challenging due to the multiphysics behind it. This study proposes a lattice Boltzmann (LB) model to study $\text {CO}_2$ desublimation on a cooled cylinder surface during CCC. In two-dimensional (2-D) simulations, various $\text {CO}_2$ desublimation and capture behaviours are produced in response to different operation conditions, namely, gas velocity (Péclet number $\textit {Pe}$) and cylinder temperature (subcooling degree $\Delta T_{sub}$). As $\textit {Pe}$ increases or $\Delta T_{sub}$ decreases, the desublimation rate gradually becomes insufficient compared with the $\text {CO}_2$ supply via convection/diffusion. Correspondingly, the desublimated solid $\text {CO}_2$ layer (SCL) transforms from a loose (i.e. cluster-like, dendritic or incomplete) structure to a dense one. Four desublimation regimes are thus classified as diffusion-controlled, joint-controlled, convection-controlled and desublimation-controlled regimes. The joint-controlled regime shows quantitatively a desirable $\text {CO}_2$ capture performance: fast desublimation rate, high capture capacity, and full cylinder utilization. Regime distributions are summarized on a $\textit {Pe}$ – $\Delta T_{sub}$ space to determine operation parameters for the joint-controlled regime. Moreover, three-dimensional simulations demonstrate four similar desublimation regimes, verifying the reliability of 2-D results. Under regimes with loose SCLs, however, the desublimation process shows an improved $\text {CO}_2$ capture performance in three dimensions. This is attributed to the enhanced availability of gas–solid interface and flow paths. This work develops a reliable LB model to study $\text {CO}_2$ desublimation, which can facilitate applications of CCC for mitigating climate change. [ABSTRACT FROM AUTHOR]

A premixed H 2 /air flame impinging onto a flat surface in statistically stationary state is studied for both reactive and inert wall cases to gain insights into the effects of the heterogeneous surface reactions. Direct numerical simulation (DNS) results with detailed gas-phase chemistry and surface adsorption and desorption mechanisms indicate differences in the flame front topology and near-wall flame dynamics between these two cases. In the reactive surface case, gas-phase free radicals are inclined to be adsorbed with much reduced near-wall concentration. Consequently, the gas-phase heat release rate (HRR) close to the wall decreases as well because of the low availability of free radicals. However, extra heat released from the reactive surface partially compensates for such difference. Moreover, wall reactions will intensify the turbulent fluctuations of the wall temperature and wall heat flux, while for these two cases the mean temperature profile along the flame propagating direction remains similar. [ABSTRACT FROM AUTHOR]

In this work, a hybrid breakup model tailored for direct-injection spark-ignition engine sprays is developed and implemented in the OpenFOAM CFD code. The model uses the Lagrangian–Eulerian approach whereby parcels of liquid fuel are injected into the computational domain. Atomization and breakup of the liquid parcels are described by two submodels based on the breakup mechanisms reported in the literature. Evaluation of the model has been carried out by comparing large-eddy simulation results with experimental measurements under multiple direct-injection spark-ignition engine-like conditions. Spray characteristics including liquid and vapor penetration curves, droplet velocities, and Sauter mean diameter distributions are examined in detail. The model has been found to perform well for the spray conditions considered in this work. Results also show that after the end of injection, most of the residual droplets that are still in the breakup process are driven by the bag and bag–stamen breakup mechanisms. Finally, an effort to unify the breakup length parameter is made, and the given value is tested under various ambient density and temperature conditions. The predicted trends follow the measured data closely for the penetration rates, even though the model is not specifically tuned for individual cases. [ABSTRACT FROM AUTHOR]