Centrifugal pumps are widely used in engineering applications, consuming a considerable amount of energy across the globe. However, in many cases they operate under off-design conditions, such as multiphase flows, implying in an even higher energy consumption. A prominent example is the mixture of water and viscous oil, where the phases may exhibit a dispersed flow pattern depending on superficial velocities. Understanding the flow dynamics within the impeller during two-phase liquid–liquid operation is crucial for grasping the mechanisms underlying energy dissipation and pump performance. In this work, we investigate experimentally oil–water flows in dispersed regime within a centrifugal pump impeller, and propose a framework for automatically identifying the dispersed phase and measuring the velocity field of the continuous phase. For that, we carried out time-resolved particle image velocimetry (TR-PIV) in a transparent pump operating under two-phase flow conditions. An image processing technique based on deep learning was developed to dynamically mask oil droplets (dispersed phase) and distinguish them from water-seeded particles (continuous phase) in the raw TR-PIV data. Additionally, a method to evaluate the phase-ensemble average velocity was designed and implemented. The results revealed that neglecting dynamic masking in the TR-PIV images caused an inversion of velocity values between the pressure and suction blades, driven by the accumulation of oil droplets in recirculation zones near the suction blade. This result highlights the importance of accurately tracking the dispersed phase. Our findings indicate higher turbulent kinetic energy (TKE) values at lower flow rates when the dispersed phase consists of larger oil droplets. These findings expand our understanding of multiphase flows in centrifugal pumps, which can be proven useful for validating numerical simulations, proposing new mathematical models, and contributing to the design of improved and energy-saving impellers.
Tag: centrifugal pump
Time-resolved PIV measurements of an unsteady viscous oil flow in a centrifugal pump
Centrifugal pumps are essential for many human activities, accounting for a considerable portion of the global electricity consumption. However, despite decades of study, the flow within the pump’s impeller and its effects on the performance are far from being fully understood, particularly when the flow involves fluids more viscous than water. In this context, this paper reports experiments using time-resolved particle image velocimetry (TR-PIV) for investigating the flow of a 14-cP-viscosity mineral oil in a transparent pump with radial impeller. We found that: (i) at low flow rates, the positions of vortices depend on the fluid properties; (ii) at higher flow rates, the oil flows aligned in the radial direction, while the water flows following closely the blade curvature; (iii) the velocity profiles for the oil are approximately parabolic, whereas those for water are flatter; (iv) the average deflection angle of the velocity vectors relative to the blade curvature changes significantly with viscosity; (v) contrary to common expectation, the turbulent kinetic energy is up to four times higher for oil than for water; (vi) vortices are periodically formed and dissipated with a frequency proportional to the rotational speed. Our results provide new insights into the flow of viscous fluids in pumps, with valuable information for their design and installation.
Analysis of energy losses and head produced by a radial impeller using particle image velocimetry
Centrifugal pumps play a crucial role in industrial operations involving fluid transport. The quest for optimizing efficiency and reducing energy usage is a driving force behind research into their performance. The literature continues to offer opportunities for the creation of models that accurately depict the head generated by pumps, with a particular focus on impellers. The current pumps, however, are still far from being completely optimized. The idea of this paper is to conduct an analysis of energy losses and propose a mathematical expression to represent the head produced by a radial impeller, P23 model, working with water flow, considering that head is influenced by losses due to recirculation, shock/incidence, internal friction. The head losses are quantitatively evaluated from experimental data acquired via particle image velocimetry, which provides information on velocity vector direction and wall shear stress, both useful for the analysis. Our results reveal that the loss due to friction is the most significant, accounting for 40–90% of the total head loss, while shock and recirculation losses are restricted to 35% and 25%, respectively. Friction factors vary from 1.0 to 26 depending on the flow rate, as a result of wall shear stresses reaching up to 430 N/m2, mainly influenced by pressure and pseudoforces. The head calculated through the new proposed expression is finally compared with the actual head generated by the impeller, measured via experiments dedicated to assess the pump performance. According to our results, the relative deviations between the calculated and measured heads are limited to 5%. Although our results have been validated for a single P23 impeller geometry, the methodology developed here can be extended to other impellers in the future. The results may thus represent a step forward for designing more efficient and power-saving pumps.
Particle image velocimetry in the impeller of a centrifugal pump: Relationship between turbulent flow and energy loss
Turbulent flows play a dominant role in the operation of centrifugal pumps, which find widespread use in industrial settings and various aspects of human life. The dissipation rate of turbulent kinetic energy emerges as a key parameter within these devices, with its local values exerting a significant influence on centrifugal pump performance. Recent advances in particle image velocimetry (PIV) techniques have expanded the ability to analyze complex turbulent flows across a broad spectrum of scales. In this context, this paper aims to deepen our understanding of the turbulent flow field and its correlation with energy loss in centrifugal pump impellers. To achieve this, experiments were conducted using PIV on a transparent pump operating under different conditions. Statistics of the turbulent flow were then obtained from phase-ensemble averages of velocities, vorticity, turbulence production, and local dissipation of turbulent kinetic energy. To overcome the limited spatial resolution constraint of PIV, the large-eddy PIV (LES-PIV) method was employed to estimate the local dissipation rate. In this method, it is assumed that the motion of larger scales is measured by the PIV technique, while the smaller scales (unresolved scales) are modeled by a sub-grid scale model, calculated from the strain rate tensors obtained from the measured fields. Energy losses in the impeller were studied using two methodologies: (i) a conventional method based on power measurements, and (ii) an alternative approach based on the budget of turbulent kinetic energy. Our results reveal that turbulent loss caused by turbulence production is the main source of energy loss in the pump impeller, and it is particularly pronounced in low-flow operating conditions characterized by large-scale structures. On the other hand, in situations where flow rates exceed the best efficiency point (BEP) condition, the predominant flow structures are marked by small-scale features, mainly attributed to local dissipation of turbulence. Our findings clarify the characteristics of energy losses in centrifugal pump impellers and their relationship with the turbulent flow field, and, in addition, providing a methodology for calculating the local turbulent dissipation rate and its limitations when derived from PIV measurements.
Particle image velocimetry in a centrifugal pump: Influence of walls on the flow at different axial positions
For almost a century, humans have relied on centrifugal pumps for the transport of low-viscous fluids in commercial, agricultural, and industrial activities. Details of the fluid flow in impellers often influence the overall performance of the centrifugal pump and may explain unstable and inefficient operations taking place sometimes. However, most studies in the literature were devoted to understanding the flow in the midaxial position of the impeller, only with a few focusing their analysis on regions closer to solid walls. This paper aims to study the water flow in the vicinity of the front and rear covers (shroud and hub) of a radial impeller to address the influence of these walls on the fluid dynamics. For that, experiments using particle image velocimetry (PIV) were conducted in a transparent pump at three different axial planes, and the PIV images were processed to obtain the average velocity fields and profiles, as well as turbulence levels. Our results suggest that: (i) significant angular deviations are observed when the velocity vectors on the peripheral planes are compared with those on the central plane; (ii) the velocity profiles close to the border are similar to those in the middle, but the magnitudes are lower close to the hub than to the shroud; (iii) the turbulent kinetic energy on the periphery is up to eight times greater than that measured at the center. Our results bring new insights that can help propose mathematical models and improve the design of new impellers. A database and technical drawings of the centrifugal pump are also available in this paper so that other researchers can perform numerical simulations and validate them against experimental data.
Particle image velocimetry in the impeller of a centrifugal pump: A POD-based analysis
The flow field within the channels of a centrifugal pump impeller is usually complex, containing turbulent structures in a wide range of time and length scales. Identifying the different structures and their dynamics in this rotating frame is, therefore, a difficult task. However, modal decomposition can be a useful tool for detecting coherent structures. In this paper, we make use of proper orthogonal decomposition (POD) of time-resolved flow fields in order to investigate the flow in a centrifugal pump. For that, we carried out experiments using time-resolved particle image velocimetry (TR-PIV) in a pump of transparent material operating at different conditions and obtained the statistical characteristics of the turbulent flow from phase-ensemble averages of velocities and turbulent kinetic energy. The results reveal that at the pump’s best efficiency point (BEP) the flow is well-organized, with no significant flow separation. For flow rates below the BEP, flow separation and vortex structures appear in the impeller channels, making the flow unstable. At flow rates above the BEP, intense jets appear close to the suction blades, while small instabilities occur on the pressure side. The POD analysis shows that at low flow rates, the flow is dominated by large-scale structures with intense energy levels, while at the BEP and higher flow rates, the flow is dominated by small-scale structures. Our results shed light on the turbulence characteristics inside the impeller, providing relevant information for reduced-order models capable of computing the flow in turbomachinery at much lower costs when compared to traditional methods.
A Droplet-Based Image Velocimetry Technique for the Measurement of Liquid Velocity Fields in Two-Phase Water-Oil Dispersion Flows
The present work describes a measurement technique to estimate the continuous liquid velocity fields in twophase water-oil dispersion flows. A transparent pump prototype made of acrylic was firstly developed and installed to enable the use of flow visualization and optical measurement techniques. Then, in the experiments, water droplets were injected into the impeller channels of the centrifugal pump, where a mineral oil with a viscosity of µo = 18.0 cP was used as the continuous phase. The two-phase water-oil dispersion flow was then filmed with a high-speed camera, and the water droplets were black-dyed for a better contrast with the white background. When injecting the water drops, breakage events were frequently observed due to turbulence and shear effects, resulting in the birth of small droplets with a size in the range from 100 µm to 500 µm. The occurrence of small water droplets in combination with the viscous continuous oil phase meant that those droplets could be assumed as tracer particles from the continuous phase. Therefore, by computing the
small water droplet velocities, it is possible to estimate the velocity field of the continuous oil phase within an acceptable error margin. This is the main idea of the technique presented in this work, which does not require the addition of intrusive tracer particles, and thus can be seen as a cheap and simple alternative to PIV in two-phase dispersions with continuous viscous phases. After a series of image processing steps, the small water droplets in the range from 100 µm to 500 µm are identified, and the PTV technique computes their instantaneous velocity. In order to assess the method capabilities, the PTV ensemble-averaged liquid flow rate is compared against experimental values from a Coriolis flowmeter installed in the experimental setup. The technique is then applied to study the flow within a pump impeller, resulting in similar flow patterns found in the literature for studies using LDV and PIV studies.
Development and assessment of a particle tracking velocimetry (PTV) measurement technique for the experimental investigation of oil drops behaviour in dispersed oil–water two-phase flow within a centrifugal pump impeller
The objective of the current work is to present the development of a Particle Tracking Velocimetry (PTV) algorithm for the analysis of oil drops behaviour in two-phase oil–water dispersions within a centrifugal pump impeller. The drop tracking was realized through high-speed camera images in a transparent pump prototype, which enabled the visualization of oil drops dispersed in water in all the impeller channels. The PTV algorithm is based on deep-learning techniques for image processing. The drops are detected by a combined U-Net and Convolutional Neural Network (CNN) method, with the former generating a binary image and the latter detecting valid oil drop contours. After detection, the Labelled Object Velocimetry (LOV) is adopted to calculate the instantaneous oil drop velocity. A synthetic image generator based on a Generative Adversarial Network (GAN) is then developed to assess the results from the U-Net, CNN, and LOV models. Additional validation studies are performed using the results from Perissinotto et al. (2019a). The results reveal that the presented deep-learning PTV algorithm is robust and provides consistent and reliable data for the dispersed oil phase in two-phase oil–water flows.
Particle image velocimetry in a centrifugal pump: Details of the fluid flow at different operation conditions
Centrifugal pumps are present in the daily life of human beings. They are essential to several industrial processes that transport single- and multi-phase flows with the presence of water, gases, and emulsions, for example. When pumping low-viscous liquids, the flow behavior in impellers and diffusers may affect the centrifugal pump performance. For these flows, complex structures promote instabilities and inefficiencies that may represent a waste of energetic and financial resources. In this context, this paper aims at characterizing single-phase water flows in one complete stage of a centrifugal pump to improve our understanding of the relationship between flow behavior and pump performance. For that, a transparent pump prototype was designed, manufactured and installed in a test facility, and experiments using particle image velocimetry (PIV) were conducted at different conditions. The acquired images were then processed to obtain instantaneous flow fields, from which the flow characteristics were determined. Our results indicate that the flow morphology depends on the rotational speed of the impeller and water flow rate: (i) the flow is uniform when the pump works at the best efficiency point (BEP), with streamlines aligned with the blades, and low vorticity and turbulence in the impeller; (ii) the velocity field becomes complex as the pump begins to operate at off-design conditions, away from BEP. In this case, velocity fluctuations and energy losses due to turbulence increase to higher numbers. Those results bring new insights into the problem, helping validate numerical simulations, propose mathematical models, and improve the design of new impellers.