Experimental study on drag reduction performance of mixed polymer and surfactant solutions

Armored Superhydrophobic Surfaces with Excellent Drag Reduction in Complex Environmental Conditions

Superhydrophobic surfaces (SHSs) have possibilities for achieving significantly reduced solid-liquid frictional drag in the marine sector due to their excellent water-repelling properties. Although the stability of SHSs plays a key role in drag reduction, little consideration was given to the effect of extreme environments on the ability of SHSs to achieve drag reduction underwater, particularly when subjected to acidic conditions. Here, we propose interconnected microstructures to protect superhydrophobic coatings with the aim of enhancing the stability of SHSs in extreme environments. The stability of armored SHSs (ASHSs) was demonstrated by the contact angle and bounce time of droplets on superhydrophobic surfaces treated by various methods, resulting in an ASHS surface with excellent stability under extreme environmental conditions. Additionally, inspired by microstructures protecting superhydrophobic nanomaterials from frictional wear, the armored superhydrophobic spheres (ASSPs) were designed to explain from theoretical and experimental perspectives why ASSPs can achieve sustainable drag reduction and demonstrate that the ASSPs can achieve drag reduction of over 90.4% at a Reynolds number of 6.25 × 104 by conducting water entry experiments on spheres treated in various solutions. These studies promote a fundamental understanding of what drives the application of SHSs under extreme environmental conditions and provide practical strategies to maximize frictional drag reduction.

Synthesis and drag reduction properties of a hydrophobically associative polymer containing ultra-long side chains

Different from common hydrophobic associative polymers, a new hydrophobic associative polyacrylamide (HAPAM) with ultra-long side chains was synthesized and aimed to be used as drag reducer in this work. Firstly, a water-soluble hydrophobic monomer (named AT114) was obtained by alcoholysis reaction with acryloyl chloride and triton 114, then the drag reducer was obtained by radical copolymerization of AM, AMPS and AT114. The structures of AT114 and drag reducer were characterized by IR and NMR. Slick water was obtained by dissolving a small amount drag reducer in water. Although the viscosity of slick water varied greatly in fresh water and brine, the drag reduction rate always remained at a high level when flowing in pipelines. When the concentration of the drag reducer was 0.03% in fresh water, drag reduction rate can be up to 76.7%, while in high concentration brine, still as high as 76.2%. It shows that salt has no obvious negative impact on the drag reduction rate. That is also to say, in the case of low viscosity, the viscosity change has no obvious impact on drag reduction rate. From the Cryo-TEM observation, it can be concluded that the drag reducer forms sparse network structures in water, which is the direct reason for drag reducing effect. This finding provides knowledge regarding the development of new drag reducers.

The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network

Due to the addition of the drag reducer in refined oil pipelines for increasing the pipeline throughput as well as reducing energy consumption, the classical method based on the Darcy-Weisbach Formula for precise pressure loss calculation presents a large error. Additionally, the way to accurately calculate the pressure loss of the refined oil pipeline with the drag reducer is in urgent need. The accurate pressure loss value can be used as the input parameter of pump scheduling or batch scheduling models of refined oil pipelines, which can ensure the safe operation of the pipeline system, achieving the goal of energy-saving and cost reduction. This paper proposes the data-driven modeling of pressure loss for multi-batch refined oil pipelines with the drag reducer in high accuracy. The multi-batch sequential transportation process and the differences in the physical properties between different kinds of refined oil in the pipelines are taken into account. By analyzing the changes of the drag reduction rate over time and the autocorrelation of the pressure loss sequence data, the sequential time effect of the drag reducer on calculating pressure loss is considered and therefore, the long short-term memory (LSTM) network is utilized. The neural network structure with two LSTM layers is designed. Moreover, the input features of the proposed model are naturally inherited from the Darcy-Weisbach Formula and on adaptation to the multi-batch sequential transportation process in refined oil pipelines, using the particle swarm optimization (PSO) algorithm for network hyperparameter tuning. Case studies show that the proposed data-driven model based on the LSTM network is valid and capable of considering the multi-batch sequential transportation process. Furthermore, the proposed model outperforms the models based on the Darcy-Weisbach Formula and multilayer perceptron (MLP) from previous studies in accuracy. The MAPEs of the proposed model of pipelines with the drag reducer are all less than 4.7% and the best performance on the testing data is 1.3627%, which can provide the calculation results of pressure loss in high accuracy. The results also indicate that the model’s capturing sequential effect of the drag reducer from the input data set contributed to improving the calculation accuracy and generalization ability.

Molecular Insight into the Possible Mechanism of Drag Reduction of Surfactant Aqueous Solution in Pipe Flow

The phenomenon of drag reduction (known as the “Toms effect”) has many industrial and engineering applications, but a definitive molecular-level theory has not yet been constructed. This is due both to the multiscale nature of complex fluids and to the difficulty of directly observing self-assembled structures in nonequilibrium states. On the basis of a large-scale coarse-grained molecular simulation that we conducted, we propose a possible mechanism of turbulence suppression in surfactant aqueous solution. We demonstrate that maintaining sufficiently large micellar structures and a homogeneous radial distribution of surfactant molecules is necessary to obtain the drag-reduction effect. This is the first molecular-simulation evidence that a micellar structure is responsible for drag reduction in pipe flow, and should help in understanding the mechanisms underlying drag reduction by surfactant molecules under nonequilibrium conditions.

Experimental Study on the Drag Reduction Performance of Clear Fracturing Fluid Using Wormlike Surfactant Micelles and Magnetic Nanoparticles under a Magnetic Field

This paper examines a new study on the synergistic effect of magnetic nanoparticles and wormlike micelles (WLMs) on drag reduction. Fe₃O₄ magnetic nanoparticles (FE-NPs) are utilized to improve the performance of viscoelastic surfactant (VES) solutions used as fracturing fluids. The chemical composition and micromorphology of the FE-NPs were analyzed with FT-IR and an electron microscope. The stability and interaction of the WLM-particle system were studied by zeta potential and cryo-TEM measurements. More importantly, the influences of the temperature, FE-NP concentration, magnetic field intensity, and direction on the drag reduction rate of WLMs were systematically investigated in a circuit pipe flow system with an electromagnetic unit. The experimental results show that a suitable content of magnetic nanoparticles can enhance the settlement stability and temperature resistance of WLMs. A magnetic field along the flow direction of the fracturing fluid can improve the drag reduction performance of the magnetic WLM system. However, under a magnetic field perpendicular to the direction of fluid flow, an additional flow resistance is generated by the vertical chaining behavior of FE-NPs, which is unfavorable for the drag reduction performance of magnetic VES fracturing fluids. This study may shed light on the mechanism of the synergistic drag reduction effects of magnetic nanoparticles and wormlike micelles.

Interfacial Interaction Enhanced Rheological Behavior in PAM/CTAC/Salt Aqueous Solution-A Coarse-Grained Molecular Dynamics Study

Interfacial interactions within a multi-phase polymer solution play critical roles in processing control and mass transportation in chemical engineering. However, the understandings of these roles remain unexplored due to the complexity of the system. In this study, we used an efficient analytical method-a nonequilibrium molecular dynamics (NEMD) simulation-to unveil the molecular interactions and rheology of a multiphase solution containing cetyltrimethyl ammonium chloride (CTAC), polyacrylamide (PAM), and sodium salicylate (NaSal). The associated macroscopic rheological characteristics and shear viscosity of the polymer/surfactant solution were investigated, where the computational results agreed well with the experimental data. The relation between the characteristic time and shear rate was consistent with the power law. By simulating the shear viscosity of the polymer/surfactant solution, we found that the phase transition of micelles within the mixture led to a non-monotonic increase in the viscosity of the mixed solution with the increase in concentration of CTAC or PAM. We expect this optimized molecular dynamic approach to advance the current understanding on chemical-physical interactions within polymer/surfactant mixtures at the molecular level and enable emerging engineering solutions.

Research Progress on the Collaborative Drag Reduction Effect of Polymers and Surfactants

Polymer additives and surfactants as drag reduction agents have been widely used in the field of fluid drag reduction. Polymer additives can reduce drag effectively with only a small amount, but they degrade easily. Surfactants have an anti-degradation ability. This paper categorizes the mechanism of drag reducing agents and the influencing factors of drag reduction characteristics. The factors affecting the degradation of polymer additives and the anti-degradation properties of surfactants are discussed. A mixture of polymer additive and surfactant has the characteristics of high shear resistance, a lower critical micelle concentration (CMC), and a good drag reduction effect at higher Reynolds numbers. Therefore, this paper focuses more on a drag reducing agent mixed with a polymer and a surfactant, including the mechanism model, drag reduction characteristics, and anti-degradation ability.