Multi-objective optimization of hydrocyclones using meta-heuristic algorithms and preference-informed decision-making

• VTPS Efficiency: The vane-type pipe separator (VTPS) is effective for compact, high-efficiency oil-water separation in constrained oilfield environments. • Advanced Modeling: A computational framework using the AIAD model within an Euler-Euler multiphase context is developed and experimentally validated. • Key Parameters Identified: Sensitivity analysis reveals guide vane angle and oil fraction as dominant factors affecting pressure drop and oil recovery. • Optimization Approach: Multi-objective optimization using SPEA2 and TOPSIS identifies the best trade-off between oil recovery and hydraulic loss. • Optimal Design Achieved: An optimal VTPS setup (25.4° vane angle, 3.57 m³/h flow rate, 18.4% oil fraction, 0.12 split ratio) achieves a 0.162 oil recovery factor at 2422 Pa pressure drop. Efficient oil-water separation is increasingly vital in mature oilfields, where enhanced water production challenges conventional downhole separation technologies. The vane-type pipe separator (VTPS) offers a promising solution due to its compact configuration and superior phase separation efficiency in constrained environments. However, the inherent complexities of swirling multiphase flow necessitate advanced modeling approaches for performance optimization. In this study, a comprehensive computational framework based on the Algebraic Interfacial Area Density (AIAD) model within an Euler-Euler multiphase context is developed and validated against benchmarked experimental data. Sensitivity analysis employing response surface methodology (RSM) and global-local indices quantifies the influence of key decision parameters, including guide vane installation angle, inlet flow rate, oil fraction, and split ratio, on separator performance. The study elucidates the parametric interplay affecting pressure drop and oil recovery, revealing guide vane angle and oil fraction as the dominant factors for hydraulic and separation performance, respectively. A multi-objective optimization is conducted using the Strength Pareto Evolutionary Algorithm 2 (SPEA2), with final selection by TOPSIS, to maximize oil recovery while minimizing hydraulic losses. The proposed methodology identifies an optimal configuration with a 25.4° vane angle, 3.57 m³/h flow rate, 18.4% oil fraction, and 0.12 split ratio, achieving a 0.162 oil recovery factor at a pressure drop of 2422 Pa. These findings provide actionable guidelines for VTPS design and operation, facilitating more efficient separation in oilfield applications and demonstrating the AIAD model's efficacy for industrial-scale multiphase flow optimization.

Multi-objective optimization of guide vanes for axial flow cyclone using CFD, SVM, and NSGA II algorithm

The purpose of this paper is to study the pressure drop of an axial flow cyclone separator as a function of inlet velocities using experimental and computational fluid dynamics (CFD) methods. First, the resistance performance of the separator was acquired under ambient pressure and temperature with little change by wind tunnel experiments. Then, numerical simulations were carried out in CFD code Fluent 6.3 under standard operating conditions. A comparison between the experimental and CFD data demonstrates that the CFD method can predict the pressure drop of the axial cyclone separator excellently. Additionally, the results show that the axial flow cyclone separators have a pressure drop coefficient of approximately 7.5. To study the effect of ambient pressure and temperature on pressure drops, the same CFD method was employed to predict the resistance performance under various operating conditions. Then the numerical results were compared with the data of a normalization process method of pressure drops raised in this paper. Their comparison demonstrated that the normalization method had a high precision in predicting the influence of ambient operating parameters on pressure drops of an axial flow cyclone separator.

Multi-objective optimization of cyclone separators in series based on computational fluid dynamics

As an excellent representative of MOEAs, the strength Pareto evolutionary algorithm 2(SPEA2) becomes an important method for solving MOPs and has been widely applied. However, traditional genetic operators in SPEA2 have strong randomness, which inevitably break the discovered linkage relationship between variables. Therefore, it is more possible for SPEA2 to premature or non-convergence. Fortunately, Markov networks with good linkage learning ability can help SPEA2 improve its performance. This paper presents an improved SPEA2 (MN-SPEA2) by building and sampling Markov network to generate new population. Machine learning in MN-SPEA2 can provide an intelligent search towards global optimal Pareto front. Experimental results also show that MN-SPEA2 has better global convergence than SPEA2.

Gas cyclone has two main parameters for evaluating separation performance, separation efficiency and pressure drop through cyclone. They are closely influenced by the geometrical design variables of the cyclone. This study performed optimization of the cyclone performance for the cyclone shape based on computational fluid dynamics (CFD), GMDH type neural network and genetic algorithm (GA). First, CFD was used to obtain the data of the cyclone performance parameters. As result of the CFD validation, the errors of the reference model and CFD were 0.5 % and 2 % for the pressure drop and the separation efficiency. Secondly, the meta-model of the cyclone performance was derived by using GMDH algorithm based on supervised learning of machine learning. The fitness of the modelling results was shown using the correlation coefficient. As results of the GMDH, the correlation coefficients of meta models of the separation efficiency and the pressure drop were 98.9 %, 99.7 %, respectively. Finally, we performed optimization of the meta model by applying GA. When the optimal point was compared with the reference model, the performance of the optimal point was improved by 24.31 % and 8.32 % for pressure drop and the separation efficiency, respectively.

Computational fluid dynamics (CFD) has been used for developing and evaluating the performance of a novel design of the cardiac axial blood pump (CABP). This device could be used as an implantable pump for boosting blood circulation in patients whose hearts are not providing sufficient output. Based on the Berlin Heart configuration the blood pump has been designed for a flow rate of 5 L/mine and 100 mmHg of head pressure. Finite element analysis method has been performed to predict the shear stress, pressure, velocity, pressure drop on the fluid through the pump and the shear stress on the pump impeller. Also, flow streamlines has been discussed in detail in this study to predict the flow streamlines behavior and the stagnation points. The goal of this work is to design an efficient blood pump to support the blood circulatory system and reduce the shear stress and blood hemolysis during transport through the pump. Our design simulated at several rotational speeds (5000 to 7000) rpm to investigate the relationship between the rotational speeds and shear stress. Results indicate that the rotational speed has a direct correlation with shear stress and pressure drop and at 6500 rpm the pump gives its optimal pressure drop.

Background Currently, gas control stations use the gas cleaning systems based on filter net, which is the most cost effective for cleaning purposes. Aims and Objectives Development of a mathematical model to substantiate the value of pressure drop in the mesh-type filter element, at which the filter must be cleaned from mechanical impurities Results In this paper it is proved that the value of the pressure drop at the gas net-type filter element inversely impact on the capital investment into the filter, on the one hand, and on the operating costs associated with the removal of solid particles, on the other hand. On this basis a mathematical model was developed to substantiate the maximum allowed pressure drop in the filter element, caused by gradual clogging of the filter net. The model includes a block diagram, the efficiency function of the integral costs, equations of the balance of expenditure, and limitations of the control parameter. Minimal integral cost of the filter is the taken as a criterion to determine optimum of the efficiency function of the mathematical model. The adopted efficiency function is featured by fractional powers, which makes necessary to solve a complex transcendental equation, and this is a rather time-consuming process of successive iterations. Therefore, to determine the optimal pressure drop across the filter element the numerical method of solving the problem was used, that is, a set of values of the pressure drop with known geometric filter parameters being given, we determine the integral costs. The optimal pressure drop on filter element corresponds to the option with minimal costs. The proposed mathematical model determines the optimal value of the maximum allowable pressure drop on the gas filter.

The pressure drop and mass transfer efficiency for two‐phase flow in a structured packed column were simulated using a commercial CFD package, CFX version 10. The distillation of the methanol/isopropanol system was carried out in a 0.073 m diameter column, with an element composed of a ceramic structured packing and 0.053 m in height. The Height Equivalent to Theoretical Plate (HETP) value varied from 0.106–0.146 m. Pressure drop experiments were measured with an air/water system. The pressure drops at the flooding and loading points were ca. 173 and 580 Pa/m of packing, respectively. HETPs and pressure drops calculated from the Computational Fluid Dynamics (CFD) model were compared to their experimental counterparts. The average relative error between CFD predictions and the experimental data for the prediction of dry pressure drop, irrigated pressure drop and mass transfer efficiency are 20.3 %, 23 % and 9.15 %, respectively. In all cases, the CFD predictions show a good agreement with the experimental data, indicating that CFD is a reliable, cost saving and suitable technique for the design and optimization of separation processes.

A novel cyclodextrin (CD) derivative, m‐xylenediamine‐β‐cyclodextrin (m‐XDA‐β‐CD), has been synthesized and used to graft β‐CD on membrane surface for the pervaporation separation of butanol isomers. The reaction mechanisms for the m‐XDA‐β‐CD synthesis and the membrane surface grafting are confirmed by FTIR and TGA. The as‐fabricated novel CD‐grafted polyamide‐imide (PAI) membranes show homogeneous morphology and significant improved separation performance as compared to the unmodified PAI membranes and PAI/CD mixed matrix membranes made of physical blends. The effects of chemical modification time and dope concentration on the asymmetric membrane have been studied. The optimal separation performance can be found with the CD‐grafted PAI membrane cast from a 22 wt % dope concentration, which exhibits a total butanol flux of 15 g/m2/h and a separation factor of 2.03. This newly developed membrane with surface‐immobilized CD may open new perspective for the development of next‐generation high‐performance pervaporation membranes for liquid separations. © 2010 American Institute of Chemical Engineers AIChE J, 2011

The technology of Down-hole Gas Liquid Separation and Water Re-injection (DGLSWR) is an economical and effective method to solve gas well fluid accumulation. The separation performance of designed Down-hole Gas Liquid Separator (DGLS) is very important for DGLSWR systems applications. The principle of work and Characteristics of DGLSWR systems are introduced in this paper. Separation performance of DGLS was studied using computational fluid dynamics (CFD) simulation combining laboratory experiment. Relations of main operating parameters, such as flow rate and gas liquid ratio with pressure drop were studied. The effect of flow rate, gas liquid ratio and main structural parameters such as cone angle and exhaust on DGLS separation performance was also studied. Appropriate structure and operating parameters were determined. Field tests indicated satisfactory results as well.

Multiple cyclones working in series are sufficient for heavy separation tasks at the cost of significant energy consumption. The majority of researchers conducting optimization studies on multiple cyclones have attempted to find the best possible compromise between pressure drop and collection efficiency by optimizing the geometry of the cyclones. In a departure from this approach, we report a novel design. Using the proposed method, exit gas is divided into dirty and clean gas by inserting a secondary vortex finder (SVF) into the primary vortex finder (PVF) of the previous cyclone. The dirty gas flows into the succeeding cyclone, whereas the clean gas passes over the succeeding cyclone and directly flows into the device farther behind. Methodologically, the separation performance was tested experimentally, and computational fluid dynamics (CFD) simulations were employed. The Reynolds Stress Model (RSM) for turbulence and the Discrete Phase Model (DPM) were used to simulate the turbulent two-phase flow within the gas–solid separator, capturing the three-dimensional, transient, and turbulent characteristics of the flow. Our performance test results showed that the new series configuration clearly reduces energy consumption while not hindering overall efficiency. The CFD simulation was used to optimize the SVF’s diameter and length. The results indicated that having an SVF with optimal dimensions significantly enhances the vortex flow in the separation space and thus improves the efficiency of the previous cyclone. In addition, an equation was established that describes the volume of gas flowing into a succeeding cyclone.

BackgroundEffective relief of tracheal stenosis (TS) caused by complete vascular ring (CRV) is mandatory for vascular ring surgery (VRS).Even the forced expiratory volume in the first second (FEV1) measurement is...

This study presents an experimental and numerical investigation on the use of high-resolution injection techniques to deliver sample plugs within a capillary electrophoresis (CE) microchip. The CE microfluidic device was integrated into a U-shaped injection system and an expansion chamber located at the inlet of the separation channel, which can miniize the sample leakage effect and deliver a high-quality sample plug into the separation channel so that the detection performance of the device is enhanced. The proposed 45° U-shaped injection system was investigated using a sample of Rhodamine B dye. Meanwhile, the analysis of the current CE microfluidic chip was studied by considering the separation of Hae III digested ϕx-174 DNA samples. The experimental and numerical results indicate that the included 45° U-shaped injector completely eliminates the sample leakage and an expansion separation channel with an expansion ratio of 2.5 delivers a sample plug with a perfect detection shape and highest concentration intensity, hence enabling an optimal injection and separation performance.

Engineering metal–organic frameworks (MOFs) based thin-film nanocomposite (TFN) membranes for molecular separation