Pressure Loss Model Research Articles

Low-order-model-based design of additive-manufactured heat exchanger

Abstract This paper discusses a comprehensive approach to the design of an additive-manufactured heat exchanger for a high-temperature application. This manufacturing route is attractive because of the flexibility afforded in design, but there is a requirement for calibration of internal friction factors and heat transfer coefficients because of uncertainty regarding the characteristics of the manufactured internal surfaces. The design was informed by physics-based low-order models (total pressure loss model; conjugate heat transfer model) calibrated against experimental data. To extract heat transfer coefficients we use transient experiments performed over timescales for which the surfaces can be regarded as semi-infinite. The calibrated models are used to predict accurate performance characteristics for the heat exchanger. Experimental results for a prototype design were found to be in excellent agreement with the model over a wide operational range, validating both the design methodology and the utility of the particular design for the given application. Our process, though not unique, has wide applicability, has been conducted with considerable care, and will be of interest to those engaged in low-order-model-based heat exchanger design.

Pressure Loss Modeling for Multi-Stage Obstacles in Pressurized Ducts

Estimating singular pressure losses for multi-stage obstacles in pressurized hydraulic ducts is a challenging task. An experimental study was conducted in a closed-loop hydrodynamic tunnel to characterize the pressure losses of a system consisting of a porous fibrous foam placed in front of a bar rack. The pressure losses of different foam–rack configurations were measured over a range of inlet velocities in order to highlight the mutual influence of their characteristics on the flow. The interdependence between the two stages has been evidenced by both the experimental results and additional numerical simulations using RANS (Reynolds-Averaged Navier–Stokes Equations) simulations with a k-ω SST turbulent closure model. The pressure losses were first modeled using two approaches based on the assumption of either independence or full dependence between the stages. The respective advantages and limitations of these approaches led to an improved analytical formula that considers the transition of the flow from the porous foam to the bar rack. By taking into account an empirical transition factor, the proposed model improves the head loss prediction for all tested configurations, with an average relative error between the formula and experimental results less than that of the two simpler approaches. This study improves our understanding of global pressure losses in multi-stage systems that include a porous foam or other filtering or clogging media in front of bar racks.

Assessment of MARS-KS prediction capability for natural circulation flow in passive heat removal system

Considering that system analysis codes are used for the evaluation of the performance of Passive Safety Systems (PSSs), it is important to investigate the capability of the system analysis code to reliably predict the heat transfer and natural circulation flow, which are the main phenomena governing the performance of a PSS. Since MARS-KS has been widely validated for heat transfer models, this study focuses on evaluating its capability to predict the single and two-phase pressure drops and natural circulation flow. The straight pipe simulation results indicate that the pressure drop predictions are reliable within ±5 % error margin for the single-phase flow and the errors of pressure drop up to −30 % for the two-phase flow. Through single-phase natural circulation flow analysis, it is concluded that the use of the appropriate K-factor modeling based on the flow regimes is important since the natural circulation flow rate in MARS-KS is mainly affected by the form loss factor modeling. With two-phase natural circulation flow analysis, this study emphasizes the behavior of the system could change significantly depending on the two-phase wall friction and pressure loss modeling. With the analysis results, modeling considerations for the PSS performance evaluation with the system analysis codes are proposed.

Predictive method of pressure loss in wet clutch caused by seal wear based on stacking ensemble learning

The harsh operating conditions of heavy-duty vehicles accelerates the wear of the sealing ring in the transmission, leading to increased oil leakage and a reduction of the operating pressure in the piston cylinder of wet clutch. This impairs the proper functioning of the transmission in the heavy-duty vehicle. Therefore, it is necessary to predict the pressure loss inside the transmission quickly and effectively after the wear of the sealing ring. The wear of the sealing ring under different operating conditions is calculated through the modified Archard model. The relationship between the oil leakage and pressure loss after the wear of the sealing ring is analyzed using Fluent software. The analysis involves the effects of different wear levels of the sealing ring. The simulation results are validated through a high-speed oil cylinder performance test rig. Based on the validated simulation data and test data, a prediction model for pressure loss is established by using stacking ensemble learning with MLR (multiple linear regression), DTR (decision tree regression), and SVR (support vector regression) as the base learners and RF (random forest) as the meta-learner. The risk of model overfitting is reduced through k-fold cross-validation. The research results indicate that the fused stacking ensemble learning algorithm fully utilizes the advantages of each base learner and can effectively predict the pressure loss after the wear of the sealing ring, and achieve a higher accuracy. The establishment of this model provides theoretical support for real-time prediction of pressure loss after the wear of the sealing ring in actual heavy-duty vehicles.

A pressure-loss model for flow-through round-hole perforated plates of moderate porosity and thickness in laminar and turbulent flow regimes

In this paper, we proposed a novel fluid flow model for pressure loss through plates with circular perforations in both laminar and turbulent flows. The design of this model is based on the recent measurements conducted at ONERA in the framework of the ongoing European Union H2020 INVENTOR project, as well as an existing model for laminar flows. The new model is then validated against existing numerical simulations in the laminar regime and experiments in the turbulent regime. Overall, the predictions given by the new model agree well with the numerical simulations and experiments, and are superior to other models in the literature. This is significant, considering that the present model is much simpler than these previous models. To demonstrate the applicability of the new model in numerical simulations, two-dimensional channel flows are simulated using Reynolds-averaged Navier–Stokes (RANS) equations with the new model as a pressure-drop source term added to the momentum equations. Results show that the RANS predictions agree very well with the present model predictions.

Modeling of High Pressure Loss (Head Loss) in a Flow Measurement Unit with Various Pipe Network Manifold Openings

The head loss in water flowing through pipes often turns out to be different from what we assume, which is the occurrence of incompressible flow. However, this assumption is not always true because the flow pattern inside the pipe is not visible and can only be measured with precise equipment. The presence of water in the pipes can only be tested on a clear scale, especially when it is part of the network within a multi-story building. Determining the need for a pipe network within a building is not an easy calculation due to differences in length, diameter, and bends. Hydraulic experts often overlook these differences, which can become a problem when clogs occur during the flow process. To find a solution to this problem, it is necessary to conduct tests using a device called a Water Measurement Unit. This is rarely done in laboratories. Testing the water pressure with this device requires various instruments and a variety of valve openings supplied with pressurized water by a pump at a certain capacity. To analyze the flow rates resulting from the tests with different valve openings, researchers test and measure the flow rate capacity for each opening, starting with openings of 0.5, 0.75, 1.00, and so on. They read the instrument, move the copper from one height to another, and create a graph of the test results in the form of a pair of connectors. The researchers test the device and its openings three times for each opening, recording and mapping the pressure values and the time it takes on the measuring instrument. Subsequently, the results of the pressure test (Head Loss) are recommended to provide information to water pipe installation planners that the test results with various valve openings under certain conditions have different pressure values and travel times. It turns out that in the placement of hose or copper number 2, stability is observed with pressure, and there is no significant differential pressure increase. In the experiment with hose or copper number 2, it can be said that everything is stable enough to conclude that there is no head loss, and it is recommended to be safe for modeling.

Modeling of pressure losses in a cylindrical duct with rectangular ribs

AbstractIn order to improve the thermal performance of heat exchangers and air collectors, we insert various forms of artificial roughness, known as ribs, into the useful duct. These ribs promote the creation of turbulent flows and enhance heat transfer by conduction, convection and radiation.However, the introduction of these ribs leads to an increase in pressure drop, requiring higher mechanical power to pump the heat transfer fluid. This experimental study focuses on estimating, using empirical approaches, the pressure losses induced by rectangular ribs with an inclined top. The ribs are made from 0.4 mm galvanized sheet steel.An experimental set-up was designed to measure the head losses generated by the ribs, from the point of entry to the point of exit from the useful duct. Using the dimensional analysis method, correlations were established to evaluate head losses as a function of flow regime and rib geometry and configuration (including different geometries for rib arrangement over the configuration area).

Heat Transfer Enhancement in Heat Exchanger using Double Sinusoidal Shape Fins

Heat Transfer Enhancement in Heat Exchanger using Double Sinusoidal Shape Fins

Experimental and Numerical Investigation on Finned Vortex Reducer in a Rotating Cavity with a Radial Inflow

In aero-engines, a secondary air system is used to cool the rotor discs and seal cavities between rotor and stator parts. The pressure loss caused by bleed air can be effectively reduced by setting the finned vortex reducer. Thus, the bleed system design can be optimized by researching the flow structure and pressure loss of each section in the cavity with a finned vortex reducer. In this study, the influence of different installation positions of a finned vortex reducer on the pressure loss characteristics was investigated through experimental and numerical simulation methods, focusing on the radial inflow of the secondary air system. The results indicate that the inlet and outlet positions of the fins affect the flow structure in the cavity. The aerodynamic parameters (rotational Reynolds number ReΦ and mass flow rate coefficient Cw), together with the inlet and outlet radii of the fins, influence the pressure loss in the cavity. Considering the swirl ratio β constrained by the fins, a pressure loss model was established, which showed good agreement with the experimentally measured pressure loss. This model reflects the impact of the inlet and outlet positions of the fins on the pressure loss characteristics.

An Experimental Study on the Elbow Pressure Drop and Conveying Stability of Pneumatic Conveying for Stiff Shotcrete Based on Response Surface Methodology

The pressure drop and conveying stability caused by the bend significantly affect the pneumatic conveying process of stiff shotcrete, which is the key to solving the problem of long-distance transportation. In this paper, the effects of different air velocities (32 m/s, 36 m/s, 40 m/s), water-cement ratios (0.1, 0.2, and 0.3), and bending-diameter ratios (4, 12, and 20) on the pressure drop of the elbow R1 and conveying stability R2 are studied using the response surface method. The conveying stability is characterized by the pressure variation coefficient (C.V). The response surface graph aids in the intuitive analysis of the effects of these variables. The results show that the impact of air velocity on R1 and R2 is exceptionally significant, and the interaction of each factor on the response value is analyzed. The response value and the quadratic polynomial regression equation between the various factors are obtained in addition to the flow characteristics of stiff shotcrete under different working conditions. The relationship established by the statistical processing of the experimental results can provide some reference for specifying the pressure loss model of stiff shotcrete.

Численное исследование сверхзвуковой ступени осевого компрессора. Влияние втулочного отношения на ее параметры

Countless combinations of sizes and shapes of the flow path could ensure the specified flow rate and pressure ratio of the axial compressor stage. Programs based on the mathematical models are an effective tool in initial design and preliminary selection of the optimal option. The RROK-GPD-22 software program is briefly being described, it solves the problem on the basis of the pressure loss model and deflection capacity of the A. Komarov lattice, theoretic rigorous calculation of oblique and direct shocks, as well as empirical equations and coefficients. Models were checked by comparison with data on the Rotor 37 NASA test stage. Stages were calculated with different ratio of the cross-sectional area at the outlet of the impeller to that at its inlet and stages with the hub-tip ratios of 0.400 ... 0.728 with different swirl at the impeller inlet. Results are provided in determining the hub-tip ratio influence on the efficiency, pressure ratio and specific stage performance.

Mathematical Modeling Study of Pressure Loss in the Flow Channels of Additive Manufacturing Aviation Hydraulic Valves

The application of additive manufacturing in the field of aviation hydraulics greatly improves the design freedom of hydraulic valve internal flow channels. Pressure loss in hydraulic valve internal flow channels is a primary factor that designers need to consider, and the rapid prediction of pressure loss is very helpful for flow channel design. At present, most studies only focus on how much the pressure loss in an additive manufacturing (AM) hydraulic channel is reduced compared with an original hydraulic channel, and a mathematical model of pressure loss in an AM curved channel is still lacking. In this paper, the pressure loss in a curved flow channel was firstly studied, and the main parameters affecting the pressure loss were determined using the dimensionless analysis method. Using computational fluid dynamics simulation, the relationships between the flow channel diameter, the flow channel length, the flow channel curvature radius, the fluid velocity and pressure loss were studied. According to the multiple regression analysis method, the mathematical model of pressure loss in aviation hydraulic channels was developed, and the model was solved based on the orthogonal experimental results. The pressure loss in the flow channel samples fabricated using selective laser melting was tested, and the results showed that the average error between the test results and the mathematical model calculation results was 7.72%. This model can be used to quickly predict the pressure loss in curved flow channels in the aviation hydraulic field.

Surrogate modeling of pressure loss & mass transfer in membrane channels via coupling of computational fluid dynamics and machine learning

Spacers are integral to the operation of membrane systems for both structural purposes and improving mass transfer dynamics that drive water permeation at the cost of increased pressure losses. 321 computational fluid dynamics (CFD) simulations were performed to provide high-fidelity data on hydrodynamic and mass transport behavior of spacer-filled membrane channels. CFD simulations were used to investigate the impact of the geometric parameters of spacers on pressure loss and concentration polarization in membrane channels. Spacer designs were characterized using six parameters that were varied in simulations to sample the domain of commercially available designs. Machine learning models were trained on CFD data to produce surrogate models for predicting pressure loss and mass transfer coefficients. These surrogate models consider more geometric parameters than existing empirical equations resulting in more representative and flexible models that can be integrated into existing module-scale or system-scale modeling software. Surrogate models were coupled with a particle swarm optimization algorithm and found that spacer designs with a diameter of 0.3 mm, length of 3.6 mm, angle between 42 and 46°, and moderate diameter necking (~60 %) best balances the trade-off between reduced concentration polarization and increased pressure losses in membrane channels with channel velocities between 0.05 and 0.35 m/s.

Rigorous modeling of frictional pressure loss in inclined annuli using artificial intelligence methods

One of the challenging issues during underbalanced drilling (UBD) is the prediction of frictional loss in the presence of three-phases of drilling fluid, cuttings, and air. In the current work, three innovative machine learning-based algorithms based-on Gradient tree boosting (GTB), Adaptive neuro-fuzzy inference system (ANFIS), and Extreme learning machine (ELM) have been suggested to calculate the frictional loss in gas-based drilling fluids containing cuttings in inclined annuli. A number of 216 real frictional pressure loss data in terms of hole inclination, pipe rotation, rate of penetration, and flow rates of each phase have been collected to train and validate the frictional pressure loss models. The visual and statistical comparisons of the frictional pressure loss models and actual values reveal that models have a fascinating ability in prediction of the frictional pressure loss for inclined wells. Besides, the GTB model has the best performance with R2 = 1, RMSE = 0.0031, MRE = 0.415, STD = 0.0023, and MSE≈0 in comparison with actual frictional pressure loss values. Furthermore, an exciting sensitivity analysis has been used to identify the effectiveness of each operational parameter on frictional pressure loss for inclined annuli. Due to these facts, the current work can be applied as an assistant in the development of drilling simulators in complicated field conditions.

Analytical model of transverse pressure loss in a rod array

The present paper proposes some new computational methods and results in the framework of flow computation through congested domains seen as porous media, as it can be found in the core of a Pressurized Water Reactor (PWR). The flow is thus mostly governed by the distribution of pressure losses, both through the porous structures, such as fuel assemblies, and in the thin fluid layers between them. The purpose of the present paper is to consider the question of the interaction of a flow and a rod bundle from an analytical point of view gathering all the contributions through a set of equations as simple and representative as possible. It aims at demonstrating a sound understanding of the relevant phenomena governing the flow establishment in the geometry of interest instead of relying mainly on a posteriori observations obtained both experimentally and numerically. Comparison with two set of experimental results showed good agreement. The model proposed being analytical it appears easily implementable for studies needing an expression of fluid forces in a rod array as for fuel assembly bowing issue. It would be interesting to test the reliability of the model on other geometry with different P/R ratios.

A Prediction Model of Pressure Loss of Cement Slurry in Deep-Water HTHP Directional Wells

The exploitations of deep-water wells often use directional well drilling to reach the target layer. Affected by special environments in deep water, the prediction of pressure loss of cement slurry is particularly important. This paper presents a prediction model of pressure loss suitable for deep-water directional wells. This model takes the complex interaction between the temperature, pressure and hydration kinetics of cement slurry into account. Based on the initial and boundary conditions, the finite difference method is used to discretize and calculate the model to ensure the stability and convergence of the result calculated by this model. Finally, the calculation equation of the model is used to predict the transient temperature and pressure loss of Wells X1 and X2, and a comparison is made between the predicted value and the monitoring data. The comparison results show that the maximum error between the temperature and pressure predicted by the model and the field measured value is within 6%. Thus, this model is of high accuracy and can meet the needs of site construction. It is concluded that this result can provide reliable theoretical guidance for temperature and pressure prediction, as well as the anti-channeling design of HTHP directional wells.

Examine Fuzzy System to Present an Equilibrium Model for the Internal Pressure Losses of Alpha Type Stirling Engine: Comparison with ANN Model

Global warming associated with the greenhouse effect urge finding alternative energy strategies concerned with sustainable energy resources that are environmentally friendly and provide energy saving. Waste heat recovery engines are attracting devices that convert usually wasted energy to valuable mechanical or electrical energy. The current research aims to develop a mathematical model to investigate the effects of regenerator physical dimensions on the alpha Stirling engine performance indicators. A mathematical model integrating an internal pressure drop has been proposed to act as a thermodynamic optimization tool for the Stirling engine. The main conclusion was that both geometrical factors and working fluid initial charge (gas mass) craft the performance parameters of alpha type Stirling engine that operates with air as working material. After that, Artificial neural networks of Levenberg Marquardt and Orthogonal Distance Regression models, and Fuzzy systems trained for Mass Charge from M = 0.002 to 0.004 Kg are compared to find the least uncertainty. Results revealed that the Fuzzy system and Orthogonal Distance Regression model could predict more effectively than the Levenberg Marquardt model.

스윕을 가지는 축류 팬의 성능예측 방법

The present study provides a performance analysis method of forward swept axial flow fan. The present performance analysis method of forward swept axial flow fan incorporates the radial equilibrium equation formulated along swept-blade coordinate with spanwise pressure loss and flow deviation models. The pressure losses in fan are categorized into blade profile, secondary flow, end-wall boundary layer and tip clearance losses, and they are calculated by the corresponding correlations expressed in terms of the flow variables defined on swept-blade coordinate. The flow deviation at fan blade outlet is also calculated by the correlation model considering on- and off-design effects. The present analysis method predicts overall performance characteristics by the mass-weighted averaging of spanwise flow calculation results. For the verification of the present fan performance prediction method, various forward-swept fan models with different design specifications and operation conditions are considered and their prediction results are compared with the test and the CFD results. The comparisons between the present calculation and the test/C FD results show very good agreements in f low field and overall fan performance predictions.

Investigations on the mitigation of ventilation air methane and energy recovery in site trial thermal flow-reversal reactor

In this paper, the key influencing factors on the ventilation air methane (VAM) utilization site trials were discussed. A new model of pressure loss and heat transfer between gas and solid phase in regenerative bed was innovatively developed. The factors of inlet gas flow rate, methane concentration fluctuations, the channel size in the monolith blocks and the energy recovery on the behaviors of site trial thermal flow-reversal reactor (TFRR) were studied systematically. Results show that the predicted temperature profile matched well compared with the site trial results. The shape of temperature profile in the reactor gradually evolves from M-shaped to ∩-shaped with the increase of the channel size of the honeycomb monolith bed. The residual methane concentration in the exhaust gas can be lower than that of 0.00079 vol% when the TFRR is filled with optimal monolith blocks with channel size of 3 ×3 mm. Using the heat exchanger in the reactor, about 40% to 44% thermal energy can be recovered from the TFRR site pilot plant.

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.