Vertical Pipe Research Articles

An improved theoretical model for the dynamics and stability of a vertical cantilevered pipe aspirating fluid

In this paper, a new theoretical model for the dynamics and stability of a vertical cantilevered aspirating pipe is developed based on the Newtonian method. The effects of the hydrodynamic forces at the free end on the dynamics and stability of the cantilevered pipe are examined in detail. A new comprehensive governing equation is discretized using the Galerkin method. Numerical results are presented to demonstrate the effects of the axial flow velocity ratio, flow angle ratio, and tangential velocity ratio on the eigenfrequency and critical velocity of the cantilevered pipe system. The theoretical model results are also found to be in good quantitative agreement with experimental results.

Optimal design of heat pipes for city gate station heaters by applying genetic and Bayesian optimization algorithms to an artificial neural network model

This study contains a novel idea to improve the performance of city gate station heaters, using pulsating heat pipes with optimized structure. In this research, a hybrid method including Bayesian and genetic algorithms is implemented to optimize the architecture of an artificial neural network (ANN) model and find the optimal operating point for heat pipes. In the previous study, the authors have proposed a neural network-based model to predict the thermal performance of heat pipes, based on a wide range of their design parameters, including dimensions of heat pipe, number of turns, working fluid, inclination angle, filling ratio, and heat input. In the present study, the prediction model architecture is optimized using Bayesian optimization algorithm. The best performance is achieved when iterations of the employed Bayesian optimization is set to 300 iterations or samples, which 150 samples are produced to train the Bayesian model and other 150 iterations are utilized in order to find the optimal ANN structure and hyper-parameter tuning of the model. The optimal ANN model with structure of 9-97-21-68-100-1 has evaluation parameters of 0.980 and 0.014 for R2 and MSE of total dataset, respectively. The performance metrics indicate an improvement in accuracy of the ANN model with a 53.33% reduction in MSE value and a 3.15% increase in R2 score. Then, the genetic algorithm is applied to the optimal model to find the optimum operating parameters of the heat pipe. In this regard, the design parameters of the best heat pipe in order to use in the city gate station heaters, are obtained by setting the genetic algorithm population equal to 300. Finally, as a practical case study, a real heater with capacity of 10,000 SCMH which is located in Iran is selected. Considering constraints and limitations of this heater, the proposed model indicates that a vertical pulsating heat pipe with four turns which is filled 55% with water as the working fluid, has the optimal thermal resistance of 0.104 K/W. Utilizing the optimal heat pipe in the mentioned heater is a promising solution for efficiency improvement and fuel consumption and CO2 emission reduction, which decreases the operating costs of the heater as well.

Techno-enviro-exergo-economic evaluation of hot water production by waste heat recovery using U-shaped pulsating heat pipe – an experimental study

ABSTRACT The energy crisis and increasing energy demand have prompted scientists and engineers to find ways to recover energy from waste heat. Also, environmental pollution caused by fossil fuels and planning to reduce environmental effects are other reasons for using wasted heat. Many studies have used pulsating heat pipes to transfer thermal energy from high-temperature systems to low-temperature applications and the energy and exergy efficiency of those systems have been investigated, but economic and environmental studies about them have not provided. In this study, the performance of a pulsating heat pipe on the waste heat recovery of a chimney for heating water for household consumption was experimentally investigated. The distilled water with a filling ratio of 60% was considered as the working fluid, and the results are presented for different pulsating heat pipe angles to the horizon from 0 to 90 degrees. Energy and energy analysis and economic and environmental assessments of the waste heat recovery system are presented and discussed. The highest hot water temperature in the reservoir outlet was about 58°C. Also, the CO2 mitigation and cost per cubic meter of hot water generation of the waste heat recovery system were 84.82 tons and 0.1$/m3. Moreover, the efficiency varied from 19% to 54% for horizontal and vertical pulsating heat pipes, respectively.

A slowly evolving conical pendulum

The idea of this work originally arose from a question pertaining to a laboratory experiment on circular motion in our departmental lab manual. The experiment itself involves rotating a bob along a horizontal circle (Figure 1), where the tension in the string attached to the bob provides the centripetal acceleration of the bob, the string itself passing through a smooth vertical pipe. It is assumed that the rotation is fast enough for the effect of gravity to be neglected and therefore the orientation of the part of the string between the top end of the pipe and the bob can be taken to be horizontal. The abovementioned question enquires what happens to the speed of the bob in the case that the bottom end of the string is hand-held and pulled slowly so that the radius of the circular orbit decreases. The answer to the question is straightforward. Either a work-energy argument or an argument involving the conservation of angular momentum provides the same correct answer.

Two-phase oil and water flow pattern identification in vertical pipes applying long short-term memory networks

Accurate biphasic flow pattern recognition is essential in the design of coatings for the oil and gas sector because it enables engineers to create materials that are tailored to specific flow conditions. This results in enhanced corrosion protection, erosion resistance, flow efficiency, and overall performance of equipment and infrastructure in the challenging environments of the oil and gas industry. The development of flow maps has been based on empirical correlations that incorporate characteristics such as superficial velocities, volume fractions, and physical properties such as the density and viscosity of the analyzed substances. In addition, geometric parameters such as the inclination and the internal diameter of the pipes are considered. However, due to the difficult working conditions on offshore platforms and the limitations in monitoring internal flow patterns, technological advances have been implemented to improve this process using artificial intelligence techniques. In this context, this study proposes using a long-term memory (LSTM) recurrent neural network to predict the flow patterns generated in vertical pipes. This LSTM network was trained and validated using data obtained from a literature database. The results obtained showed that the model has a prediction error of less than 1%. These technological advances represent an important step towards optimizing the flow pattern identification process in the hydrocarbons industry. By leveraging the capabilities of artificial intelligence, more accurate and reliable forecasts can be obtained, enabling informed decisions and improving the efficiency and safety of operations.

Virtual Meter with Flow Pattern Recognition Using Deep Learning Neural Networks: Experiments and Analyses

Summary Operators often require real-time measurement of fluid flow rates in each well of their fields, which allows better control of production. However, petroleum is a complex multiphase mixture composed of water, gas, oil, and other sediments, which makes its flow challenging to measure and monitor. A critical issue is how the liquid component interacts with the gaseous phase, also known as the flow pattern. For example, sometimes liquids can accumulate in the lower part of the pipeline and block the flow completely, causing a gas pressure buildup that can lead to unstable flow regimes or even accidents (blowouts). On the other hand, some flow patterns can also facilitate sediment deposition, leading to obstructions and reduced production. Thus, this work aims to show that deep neural networks can act as a virtual flowmeter (VFM) using only a history of production, pressure, and temperature telemetry, accurately estimating the flow of all fluids in real time. In addition, these networks can also use the same input data to detect and recognize flow patterns that can harm the regular operation of the wells, allowing greater control without requiring additional costs or the installation of any new equipment. To demonstrate the feasibility of this approach and provide data to train the neural networks, a water-air loop was constructed to resemble an oil well. This setup featured inclined and vertical transparent pipes to generate and observe different flow patterns and sensors to record temperature, pressure, and volumetric flow rates. The results show that deep neural networks achieved up to 98% accuracy in flow pattern prediction and 1% mean absolute prediction error (MAPE) in flow rates, highlighting the capability of this technique to provide crucial insights into the behavior of multiphase flow in risers and pipelines.

Two-dimensional Numerical Analysis of Waves at Interface of Laminar Core-annular Flow in Vertical Pipe: Detailed Investigation of Influence of Several Physical Parameters

Two-dimensional Numerical Analysis of Waves at Interface of Laminar Core-annular Flow in Vertical Pipe: Detailed Investigation of Influence of Several Physical Parameters

Theoretical and Experimental Investigation of Liquid and Gas Flow Pressure Drop through Different Sections of A Partially Closed Piping system

Multiphase flow is found in various places in nature and practice. However, multiphase flow is prevalent in the petroleum production industry. This phenomenon gives rise to a significant issue of pressure loss within piping systems, resulting in a loss in production. Multiphase flow has been studied for decades; however, with the increase in unconventional engineering methods, there is now a greater need for its study. This study investigates phenomena related to multiphase flow, such as flow regimes and pressure loss produced by friction, pipe orientation, and various fluid phase properties. An experimental system was designed, and different fluid phases were used to represent varying situations in piping systems. The system included sections of horizontal, inclined, and vertical pipe orientations experienced during hydrocarbon migration from the reservoir to the surface. To replicate industry multiphase flow in the experimental system, we used water to represent the oil and compressed air to represent gas. The pressure differences throughout the system were calculated using the Beggs and Brill Correlation, the Lockhart-Martinelli Parameter, and the Chisholm Equation. Experimental pressure differences and the effect of the choke valve positions were also recorded for the different sections of the system while observing the flow regimes produced by multiphase fluid interaction. Through the research methods, we found that most pressure losses occurred in the elbows, and most frictional pressure loss occurred in the vertical 3ft pipe, while the 45° and 90° downhill pipes experienced increased pressure.

Two-Phase Flow Pattern Identification in Vertical Pipes Using Transformer Neural Networks

The oil and gas industry consistently embraces innovative technologies due to the significant expenses associated with hydrocarbon transportation, pipeline corrosion issues, and the necessity to gain a deeper understanding of two-phase flow characteristics. These solutions involve the implementation of predictive models utilizing neural networks. In this research paper, a comprehensive database comprising 4864 data points, encompassing information pertaining to oil–water two-phase flow properties within vertical pipelines, was meticulously curated. Subsequently, an encoder-only type transformer neural network (TNN) was employed to identify two-phase flow patterns. Various configurations for the TNN model were proposed, involving parameter adjustments such as the number of attention heads, activation function, dropout rate, and learning rate, with the aim of selecting the configuration yielding optimal outcomes. Following the training of the network, predictions were generated using a reserved dataset, thus facilitating the creation of flow maps depicting the patterns anticipated by the model. The developed TNN model successfully predicted 9 out of the 10 flow patterns present in the database, achieving a peak accuracy of 53.07%. Furthermore, the various predicted flow patterns exhibited an average precision of 63.21% and an average accuracy of 86.51%.

Numerical analysis of air–water two-phase upflow in artificial upwelling of deep ocean water by airlift pump

Artificial upwelling by the use of airlift pump is regarded as an effective way in utilizing deep ocean water and actualizing ocean fertilization. This paper focuses on numerical analysis of steady air–water two-phase flow in a vertical pipe of an airlift system based on one-dimensional multi-fluid model. The depth distributions of 6 physical quantities such as volumetric fractions and axial velocities of two phases, air density and pressure are calculated by solving the governing equations or by integrating the vector form of nonhomogeneous ordinary differential equation for two-phase flow interval. Upon successful verification of the present numerical model through a comparison with precedent theoretical and experimental results in case of a vertical pipe with length of 7.86 m, the model is extended to the case of artificial upwelling from water depth of 2000 m. The effects of submerged depth of air–water mixer on the pumped amount of water and the depth distributions of 6 physical quantities are considered.

Experimental and numerical investigation of a small scale storm sewer geyser

The violent nature of storm sewer geysers has been puzzling researchers worldwide for a very long time. This paper investigates the geyser simulation methodology using a small-scale set-up, where important flow structures such as slugs, eruption patterns, and pressure oscillations are compared with experimental results to test the fidelity of the numerical modelling. In this exercise, a geyser-like process is produced using a continuous insertion of air in the horizontal pipe. The established methodology is used to simulate the hypothesized scenario of a finite trapped air pocket in the relatively longer pipe system. A geyser produced from a finitely trapped air pocket shows a different eruption mechanism compared to those found in previous studies. First, no slug is observed in the horizontal pipe, resulting in continuous air release. Second, the interface continuously atomizes in the vertical pipe, creating a churn-slug flow that produces a large number of small eruptions.

Buoyant miscible viscoplastic displacements in vertical pipes: Flow regimes and their characterizations

We experimentally study miscible displacement flows of a light Newtonian fluid by a heavy viscoplastic fluid, in a vertical pipe with a large aspect ratio (δ−1≫1). We use camera imaging, laser-induced fluorescence, and ultrasound Doppler velocimetry techniques, to capture and process data. Four dimensionless parameters, namely, the Reynolds (Re), Bingham (B), viscosity ratio (M), and densimetric Froude (Fr) numbers (or their combinations), mainly govern the flow dynamics. We identify and characterize three distinct flow regimes, including plug, separation, and mixing regimes, while we describe each regime's dynamics in detail, particularly in terms of the velocity and concentration fields as well as the displacement front velocity. In addition, we analyze the plug regime concerning the residual wall layers, the separation regime in terms of the separation dynamics, spatiotemporal separation zone, and viscoplastic layer thinning, and the mixing regime regarding the mixing index and macroscopic diffusion. Finally, we develop a simplified model to help delineate the flow regime classification, in the plane of Re/Fr2 and M.

EFFECTS OF PIPE DIAMETER ON INTERFACIAL AND WALL FRICTION FACTORS OF SWIRLING ANNULAR FLOWS IN A VERTICAL PIPE

Interfacial and wall friction factors, <i>f<sub>i</sub></i> and <i>f<sub>w</sub></i>, of swirling annular flows in a vertical pipe of 20 mm in diameter D were measured for comparison with those in a vertical pipe of <i>D </i>= 30 mm. A three-fluid model was applied to evaluate the friction factors. Measurements were carried out in two sections, one near the swirler and the other far downstream the swirler. The swirl intensity of the flow was evaluated by the interfacial swirl number si defined by the ratio of the azimuthal to the axial components of interfacial wave velocity. The interfacial swirl numbers were smaller in the smaller pipe. The ratio of <i>f<sub>i</sub></i> in swirling annular flows to that in non-swirling annular flows decreased to unity with decreasing <i>s<sub>i</sub></i>* which is the arithmetic mean value of <i>s<sub>i</sub></i> for 0 ≤ <i>z</i>* (= <i>z/D</i>) ≤ 3.8, where <i>z</i> is the axial coordinate in the test section, and is higher in <i>D </i>= 20 mm than in <i>D </i>= 30 mm. The ratio of <i>f<sub>w</sub></i> in swirling annular flows to that in non-swirling annular flows decreased to less than unity with decreasing <i>s<sub>i</sub></i>* and is higher in <i>D </i>= mm than in <i>D </i>=30 mm.

Intensification of Heat Transfer during Steam Condensation in Process Condenser of NPP Unit Cooling System

The paper investigates heat transfer during condensation of water vapor on vertical pipes of the process condenser of the cooling system of a nuclear power unit. The numerical study was performed at different mass flow rates of steam in the range of its change from 20 kg/s to 40 kg/s. Intensification of heat exchange is provided by the use of highly efficient heat exchange profiled tubes. The study used a set of heat exchange tubes (25 mm in diameter and 1.4 mm wall thickness) with the following values of the distance between the grooves of the profiled tube: 0.007075 m, 0.00875 m, 0.00925 m, 0.0105 m. The effect of the groove depth (from 0.0007 to 0.0009 m) on heat transfer during water vapor condensation on vertical pipes was also studied. The study was carried out for the range of changes in the Reynolds number for the condensate film from 5254.2 to 10508.5. The study obtained data indicating an increase in the heat transfer coefficient on the pipe with an intensifier compared to the heat transfer coefficient on a smooth pipe. This analysis did not take into account the change in tube wall temperature.

Frequency analysis of food bolus fragmentation through a vertical pipe

Frequency analysis of food bolus fragmentation through a vertical pipe

Natural Convection Heat Transfer In Heated Vertical Tube Without Internal Rings

An experimental investigation of natural convection heat transfer in heated vertical pipes dissipating heat from the internal surface is presented. The pipes are open-ended and circular in cross section. The test section is electrically heated imposing the circumferentially and axially constant wall heat flux. The purpose of this work is to study experimentally the natural convection pipe flows at different heating levels. The test section is a vertical, open-ended cylindrical pipe dissipating heat from the internal surface. The test section is electrically heated imposing the circumferentially and axially constant wall heat flux. Heat transfer experiment is carried out for four different channels of 45mm internal diameter and 3.8mm thickness with length 450 mm. Ratios of length to diameter of the channel is taken as L/D = 10. Wall heat fluxes are maintained at q// = 250 to 3341 W/m2. A systematic experimental database for the local steady state natural convection heat transfer behaviour is obtained. A correlation is developed for average Nusselt number and modified Rayleigh number and another correlation is also developed for modified Rayleigh number and modified Reynolds number.

Direct numerical simulation of flow and heat transfer of supercritical water with different heat fluxes

The flow and heat transfer characteristics of supercritical water (SCW) are important considerations in the thermal-hydraulic design of the Supercritical Water-Cooled Reactor (SCWR). In the present study, the direct numerical simulation (DNS), developed with OpenFOAM, was utilized to investigate the effect of heat flux on the flow and heat transfer of SCW in a vertical circular pipe. The investigation involves detailed analyses of the wall temperature, velocity distribution, and turbulent statistics at various heat fluxes. It was found that buoyancy first impairs heat transfer, and then recovers heat transfer. This is attributed to the variation of buoyancy production and turbulence production, which are resulted from the buoyancy direct effect and indirect effect, respectively. As the heat flux increases, the recovery occurs earlier with higher magnitude. The vortex structures based on Q-criterion clearly illustrate the same process as well. Several heat-transfer correlations were assessed based on the DNS results. It indicates that Dittus and Boelter correlation (1930) cannot accurately predict the heat-transfer characteristics of SCW, while Chen and Fang correlation (2014) exhibits a higher level of predictive accuracy for Nusselt number. In addition, several turbulence models were evaluated against the DNS data. The results show significant deviations in predicting the heat transfer of SCW. The large discrepancy may be due to the inappropriate model coefficients, the failed predication of turbulence kinetic energy, as well as the constant turbulent Prandtl number commonly applied.

An improved method combined modified drag model and modified erosion model based on LES for solid-liquid multiphase flow and erosion with application in a 90° elbow

In various industrial processes, solid-liquid multiphase flows involving continuous carrier and discrete particle phases have erosion challenges. In this work, a modified drag model that considers the influence of turbulence intensity and a modified erosion model that considers the effect of low-angle impact are developed. An improved method combined modified drag model and modified erosion model based on LES is proposed for numerical simulation of solid-liquid multiphase flow and erosion. The commercial software ICEM for grid generation and ANSYS FLUENT for LES are used in the present work. In validation test of velocity distribution of solid-liquid multiphase flow in a vertical pipe, the mean relative error of the liquid phase pulsation velocity is 10.01 % for modified drag model, whereas the mean relative error is 16.11 % for original drag model. In validation test of the maximum erosion depth from a submerged impact test at a tilt angle of 45°, the relative error is 0.23 % for modified erosion model, while the relative error is 13.39 % for original erosion model. Then, the improved method is employed to compute the characteristics of solid-liquid flow and erosion in a 90° elbow. Particles have a significant influence on liquid flow in the shear layer area where the inner arch separation zone interacts with the main flow, and this influence is most pronounced at the position of r* = 0.3 at yd = 0.4D. At this position, particles result in 15.27 % reduction in liquid velocity and 8.75 % increase in turbulence intensity. The mean relative error of the elbow erosion rate by using the improved method is 16.95 %, whereas it is 31.34 % of the reference work. The erosion is affected by impact velocity, angle, and particle number, and the most significant parameter is the particle number in the severe erosion area.

Critical heat flux for downward flows in vertical round pipes

Pressurized thermal shock (PTS) is one of the causes of pressure vessel failure during nuclear reactor accidents. Critical heat flux (CHF) for downward flow is an essential thermohydraulic parameter for predicting PTS using nuclear reactor system codes. While many experimental data have been accumulated and many correlations have been proposed for CHF for upward flow, only a few studies exist on downward flow. This study reviewed the literature that measured CHF for downward flow in round pipes and arranged the proposed correlations. Then, we extracted the parameter values that determine experimental conditions and CHF values from the literature and compared the CHF values predicted from the correlation in each study and the measured CHF values under those conditions across the literature. Each correlation shows relatively good prediction accuracy (average prediction accuracy of 10%–30%) for experimental data from their literature, but the accuracies sometimes decrease for experimental data from other literature. No correlation accurately predicts all the experimental data of the literature, indicating an issue in extrapolating existing correlations. Therefore, we developed a correlation that can accurately predict the experimental data of the collected literature. First, we used a neural network to select the essential dimensionless quantities that comprise the correlation. Then, we regarded the prediction accuracy when all candidate dimensionless quantities extracted from the literature were used for the input variables of the network as the achievable limit prediction accuracy and searched for the minimum combination of dimensionless quantities required to achieve it. The results showed that only the dimensionless mass flux (G*) and the ratio of the heating length to the channel diameter (L/D) are the essential parameters to achieve it. We developed a correlation equation using these two dimensionless quantities and achieved 17.6% of the average prediction accuracy. This result considerably improved existing correlation equations with 25%–40% average prediction accuracy for the same experimental data. Furthermore, unlike many existing correlations, it has excellent practical features, such as applicability over wide parameter ranges and no need to separate cases.

MATHEMATICAL MODELING OF NON-STATIONARY HEAT PROCESSES IN THE GROUND HEAT PUMP SYSTEM

In the work, an analytical study of the efficiency of heat pumps using soil energy for heating, taking into account the climatic conditions of theregion of operation, is performed, which meets the tasks of energy saving and allows reducing emissions of harmful substances into the environment. The main attention is paid to increasing the efficiency of utilization of the technical potential of the soil energy source by the heat pump system using vertical soil heat exchangers. A methodology based on use of the mathematical modeling apparatus as a scientifically based toolkit for calculating non-stationary thermal processes, capable of ensuring the stability and reliability of the ground heat pump system in the short and long term, is proposed. The developed toolkit for calculation and analysis of heat exchange processes allows determining the power of the heat flow, which is removed from the soil, taking into account changes in climatic factors, temperature distribution in the soil around the soil tube and along its length over time, schematic and structural features of the soil tubes for further optimization of the parameters of the heat pump system . It was established that the power of the heat flow, which enters the evaporator of the heat pump from vertical soil pipes, depends on a number of influencing factors: the flow regime of the working fluid circulating in the soil circuit; physical properties of the working body; number of soil heat exchangers; temperature distribution in the soil around the soil tube along its entire length, which changes significantly during long-term operation of the system, affecting the course of heat exchange processes in the system elements. The proposed method makes it possible to perform numerical modeling of thermal processes in the elements of the heat pump, to determine the energy efficiency of the ground heat pump system, which is able to reliably provide consumers with heat during a long period of operation, which can be considered an innovative approach to the analysis of prospects for the development of heat pump heat supply.