Karim Ragui¹, Mengshuai Chen^1,2, Lin Chen^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-2, 2023, DOI:10.32604/icces.2023.010378

Abstract The ambiguous dynamics associated with heat and mass transfer of invading carbon dioxide in sub-critical and supercritical states, as well as the response of pore-scale resident fluids, play a key role in understanding CO₂ capture and storage (CCUS) and the corresponding phase equilibrium mechanisms. To this end, this paper reveals the transport mechanisms of invading supercritical carbon dioxide (sCO₂) in polluted micromodels using a variant of Lattice-Boltzmann Color Fluid model and descriptive experimental data. The breakthrough time is evaluated by characterizing the displacement velocity, the capillary to pressuredifference ratio, and the transient heat and mass diffusion at a series of… More >

Jinguang Yang, Feng Zhao, Min Zhang^*, Yan Liu, Xiaofang Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 935-953, 2021, DOI:10.32604/cmes.2021.014176

Abstract For a radial inflow turbine (RIT), leakage flow in impeller backface cavity has critical impacts on aerodynamic performance of the RIT and axial force acting on the RIT impeller. In order to control this leakage flow, different types of labyrinth seals are numerically studied in this paper based on a supercritical carbon dioxide (S-CO₂) RIT. The effects of seal clearance and cavity outlet pressure are first analyzed, and the impacts of seal design parameters, including height, number and shape of seal teeth, are evaluated. Results indicate that adding labyrinth seal can improve cavity pressure and hence adequately inhibits leakage flow.… More >

Amin Bemani¹, Alireza Baghban², Shahaboddin Shamshirband^{3, 4, *}, Amir Mosavi^{5, 6, 7}, Peter Csiba⁷, Annamaria R. Varkonyi-Koczy^{5, 7}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1175-1204, 2020, DOI:10.32604/cmc.2020.07723

Abstract In the present work, a novel machine learning computational investigation is carried out to accurately predict the solubility of different acids in supercritical carbon dioxide. Four different machine learning algorithms of radial basis function, multi-layer perceptron (MLP), artificial neural networks (ANN), least squares support vector machine (LSSVM) and adaptive neuro-fuzzy inference system (ANFIS) are used to model the solubility of different acids in carbon dioxide based on the temperature, pressure, hydrogen number, carbon number, molecular weight, and the dissociation constant of acid. To evaluate the proposed models, different graphical and statistical analyses, along with novel sensitivity analysis, are carried out.… More >

Xiaofeng Yang^{1, *}, Yanhong Li¹, Aiguo Nie¹, Sheng Zhi², Liyuan Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 1141-1157, 2020, DOI:10.32604/cmes.2020.08538

Abstract Supercritical carbon dioxide (Sc-CO₂) jet rock breaking is a nonlinear impact dynamics problem involving many factors. Considering the complexity of the physical properties of the Sc-CO₂ jet and the mesh distortion problem in dealing with large deformation problems using the finite element method, the smoothed particle hydrodynamics (SPH) method is used to simulate and analyze the rock breaking process by Sc-CO₂ jet based on the derivation of the jet velocity-density evolution mathematical model. The results indicate that there exisits an optimal rock breaking temperature by Sc-CO₂. The volume and length of the rock fracture increase with the rising of the… More >