Babanezhad Meisam, Nakhjiri Ali Taghvaie, Shirazian Saeed
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam.
Faculty of Electrical - Electronic Engineering, Duy Tan University, Da Nang 550000, Vietnam.
ACS Omega. 2020 Jun 23;5(26):16284-16291. doi: 10.1021/acsomega.0c02117. eCollection 2020 Jul 7.
A 2D-bubble column reactor (BCR) including gas and liquid phases is simulated, and fluid characteristics such as gas-phase volume fraction and gas-phase turbulence are extracted from the CFD simulations. A type of heuristic algorithm called adaptive network-based fuzzy inference system (ANFIS) is applied here to simulate the gas-phase volume fraction in a physical system. Indeed, the direction, the direction, and gas-phase turbulence are considered as the ANFIS inputs. Changes in the number of inputs as well as membership functions are evaluated and studied to obtain a high level of ANFIS intelligence. By implementing the highest ANFIS intelligence, a surface is predicted, which suggests that the gas-phase volume fraction is based on and directions. It provides capability to achieve the amount of gas-phase volume fraction in different points of a 2D-BCR.
对包含气相和液相的二维鼓泡塔反应器（BCR）进行了模拟，并从计算流体力学（CFD）模拟中提取了诸如气相体积分数和气相湍流等流体特性。这里应用了一种称为基于自适应网络的模糊推理系统（ANFIS）的启发式算法来模拟物理系统中的气相体积分数。实际上，将x方向、y方向和气相湍流视为ANFIS的输入。对输入数量以及隶属函数的变化进行了评估和研究，以获得高水平的ANFIS智能。通过实现最高水平的ANFIS智能，预测了一个表面，这表明气相体积分数基于x和y方向。它提供了在二维鼓泡塔反应器不同点实现气相体积分数的能力。
