Precise Flow Research Articles

Optimization and Analysis of Flow Field Simulations Across Different Mach Regimes Using Discrete Numerical Methods

This article explores the development of flow field models in steady-state environments utilizing Euler equations and potential flow equations, with verification processes conducted using Python. The models demonstrate stability and high accuracy in low-velocity scenarios, capturing essential dynamics effectively. However, as the conditions transition to supersonic speeds, the models begin to exhibit increased errors. This discrepancy highlights the challenges faced in simulating high-speed aerodynamics accurately. The research underscores the importance of improving model fidelity in diverse Mach regimes, particularly in supersonic conditions where traditional methods struggle. Future research directions identified include the development of unsteady flow field models, which are crucial for dynamic analyses, optimization of grid structures for three-dimensional complex fields to improve computational efficiency, and the creation of extensive model libraries. These advancements aim to enhance the accuracy, reliability, and practicality of flow field simulations, extending their applicability in both academic studies and industry applications, particularly in aerospace engineering where precise flow modeling is critical.

Design and Analysis of a Thermal Flowmeter for Microfluidic Applications: A Study on Sensitivity at Low Flow Rates

To address the challenge of precise flow rate measurement in microchannels, this research details the conceptualization and comprehensive evaluation of a thermal flowmeter which works on the principle of calorimetry for measuring small flow rates between 0.1 and 180 mL/h. The thermal flowmeter is composed of a silicone pipe, a heater, three platinum thermal sensors (T1, T2, T3), and water as the working fluid. The flowmeter is strategically placed to monitor the complex thermodynamics between upstream and downstream flows. The analysis revealed a notable decay in the slope of the temperature differences beyond a flow rate of 40 mL/h, indicating the exceptional sensitivity of the device at lower flow rates and making it an ideal choice for medical applications. Parametric analysis was also carried out to place the sensors at optimized locations for better sensitivity.

GraphSmart: a method for green and accurate IoT water monitoring

Water scarcity is nowadays a critical global concern and an efficient management of water resources is paramount. This paper presents an original approach for monitoring Water Distribution Systems (WDSs) through Internet of Things (IoT) that involves the integration of multiple sensors placed across the distribution network to accurately measure water flow. To enhance energy efficiency for green monitoring and communication process, we harness the power of graph theory and graph signal processing to represent in a tunable and accurate way the water flow and simultaneously minimize the number of IoT sensors communicating those measurements. We propose a graph model where water flow is represented as signal on graph and we introduce an algorithm, named GraphSmart, designed to reconstruct the graph signal when certain measurements are unknown or missing. Our framework is applied on synthetic realistic environment within the context of LoRaWAN (Long Range Wide Area Network), an infrastructure and protocol designed for ultra-low-power IoT devices. Our findings show that GraphSmart significantly reduces energy consumption while ensuring precise flow estimation. Our research demonstrates high potential for energy-efficient and accurate water flow monitoring, paving the way to improve the management of WDSs and enabling water operators to address water scarcity challenges.

Wind turbine dynamic wake flow estimation (DWFE) from sparse data via reduced-order modeling-based machine learning approach

Wind turbine wake poses a significant challenge in wind farm operations, affecting power generation efficiency. This study introduces a Dynamic Wake Flow Estimation (DWFE) framework designed to predict wind turbine wake evolution from sparse measurement data. The framework integrates Gaussian Process Regression (GPR), Proper Orthogonal Decomposition (POD), and Long Short-Term Memory (LSTM) networks. Specifically, GPR plays a pivotal role in DWFE by enabling the transformation of flow fields discrete sensor signals into coherent, low-dimensional flow fields which is crucial for accurate flow field predictions, while POD aids in dimensionality reduction and LSTM forecasts temporal wake dynamics, improving both predictive accuracy and computational efficiency. Parametric analysis demonstrates that the robustness and adaptability of the framework improve prediction accuracy with increased sensor density and flexible POD modes. The DWFE framework demonstrates high accuracy in wake flow estimation even with limited data, effectively capturing dynamic wake behavior. Future work will extend this approach to various topographic and climatic conditions, optimizing computational efficiency, and improving interpretability. These advancements will expand the framework's applicability in wind energy and other engineering fields requiring precise flow prediction, emphasizing DWFE's potential in advancing wind farm design, operation and renewable energy optimization.

Numerical simulation of scour dynamics around series of spur dikes using FLOW-3D

Spur dikes are vital structures are used to control erosion and manage flow dynamics. This study evaluates the effectiveness of multiple spur dikes in reducing scour depth around the first dike by adjusting their spacing and length. Numerical simulations were performed using the FLOW-3D-hydro model, incorporating the RNG k-ϵ turbulence model to account for low-intensity flow conditions. Results showed that parallel spur dikes significantly influenced flow direction, reducing scour depth near the first dike. Optimal configurations, with spacing set at twice the length of the dike, reduced scour depth by up to 30%. The numerical model used a nested mesh configuration for precise flow capture. A comparison of experimental and numerical results showed a strong correlation, with an R² of 0.94, RMSE of 0.03, and P-bias of 2.5%. These findings confirm the accuracy of the FLOW-3D model in simulating scour dynamics, offering key insights for hydraulic engineering applications.

A Novel Approach Integrating the Method of Characteristics with Large Time-Step Scheme (MOC-LTS) for Efficient Transient Flow Simulation in Liquid Pipelines

Water hammer incidents pose a significant risk to the safety and stability of pipeline operations. Therefore, rapid and precise transient flow simulation is essential for efficiently developing scientific water hammer control strategies. Nevertheless, the prevailing transient flow simulation methods for liquid pipelines predominantly employ explicit schemes to solve transient flow control equations, necessitating adherence to the stability criterion of Courant-Friedrichs-Lewy (CFL) ≤ 1. This results in limited time step sizes, which in turn constrains computational efficiency, particularly when simulating hydraulic behavior in large-scale pipeline networks. In this paper, a novel approach integrating the method of characteristics (MOC) with a large time-step scheme (LTS) is proposed to enable rapid and accurate simulation of transient flow in liquid pipelines. The proposed approach discretizes the computational domain into contiguous control volumes, ategorizing them as either boundary or internal control volumes depending on whether they are affected by boundary conditions within a large time step. For internal control volumes, an LTS scheme based on the first-order Godunov format is employed to improve computational efficiency. For boundary control volumes, MOC is applied iteratively to accurately capture boundary dynamics until the simulated time matches that of the internal control volumes. Quantitative analysis is conducted to verify the performance of the proposed approach. The results confirm that the proposed approach outperforms the MOC in computational efficiency while maintaining minimal accuracy loss.

Influence of input parameters on the measurement accuracy of external clamp-on ultrasonic flowmeters: An experimental study

Abstract This study comprehensively evaluated the performance of clamp-on ultrasonic gas flowmeters at a natural gas field. The research focused on the influence of key input parameters on flow measurement accuracy during practical application of the instrument and proposed specific measures to improve measurement results. It was found that errors in outer diameter and wall thickness not only lead to flow calculation inaccuracies but also directly impact the propagation path of ultrasonic waves. Therefore, accurate input parameters are crucial to ensure precise flow results. Additionally, the study revealed that changes in installation distance have minimal effects on flow measurement results and adjustments can be made as needed to obtain better signal parameters. Variations in input temperature and pressure mainly affect the conversion coefficient from operating conditions to standard conditions, with minor impacts on flow velocity and operating flow rate. Thus, the velocity ratio method can be considered during on-site calibration to mitigate the effects of temperature and pressure changes.

Fuzzy Logic-based Current Control Logic for Proportional Flow Control Valve System of Medical Ventilators

The critical control parameters in ventilators that provide life support to patients are the flow of air and oxygen. Ventilators typically use Proportional Flow Control Valves (PFCV) and flow sensors to achieve precise flow accuracy. Maintaining accurate flow from the PFCV is essential to minimize the thrust exerted on the patient's lungs. Fuzzy logic is particularly well-suited for this task, as it effectively captures the subjective human judgments often required in clinical settings. This study aimed to develop a fuzzy logic algorithm to control pressure support ventilation. The research describes the fuzzy logic algorithm and presents experimental studies that evaluated the flow accuracy of a commercially used PFCV in ventilators. Additionally, the reduction in output flow due to thermal effects was investigated. A correlation between the solenoid coil current (measured as voltage across the coil) and the actual output flow through the PFCV was experimentally established using a current sensing circuit. Based on the characteristic curves obtained from the test setup, a Fuzzy Logic system was developed to minimize the error in the PFCV's flow. The implementation of PFCV using this Fuzzy Logic-based current control approach demonstrated a significant reduction in error, from 10% to 3%, in airflow delivery across its operating range, with additional sample results discussed. This reduction in flow error is crucial for assessing the suitability of PFCVs in infant ventilators. The described methodology can be experimentally applied to any PFCV variant before its use in medical ventilator applications to enhance delivered flow accuracy.

Particle motion under turbulent eddies: Inspiration for fine minerals flotation

Turbulent flow ubiquitous in flotation machines and contain multi-scale eddies. Compared to static environments, turbulence can increase particle kinetic energy and promote particle-bubble collision in mineral flotation. However, there have been few quantitative studies on turbulent eddies that affect particle motion, which limits the precise flow control of flotation processes. In this study, the motion characteristics of particles in isotropic turbulence were measured by particle tracking velocimetry, and the relationship between turbulent eddy and particle motion was quantitatively analyzed by 7-scale wavelet transform and fast Fourier transform. The measurement results show that the particle moves upward following a rotating turbulent eddy, and turbulent eddies with sizes of 35–119 µm and 127–288 µm drives the motion of dp = 74 µm and dp = 200 µm particles respectively. The turbulent acceleration of particles within a turbulent eddy can be calculated as aλ=Cε2/3λ-1/3. This study provides an eddy control basis for mineral flotation performance improvement.

Evaluation of cavitation phenomena in three-way globe valve through computational analysis and visualization test

A three-way valve has a multi-port structure with three openings, which allows control of the fluid direction. However, owing to the complicated trim shape of the internal flow, an irregular fluid flow occurs, which hinders precise fluid flow control. In severe cases, cavitation induces mechanical damage owing to abrupt changes in the fluid direction. In this study conducted a computational fluid dynamics (CFD) analysis was performed to estimate the localized cavitation around the bottom plug of the three-way valve. To quantify localized cavitation, the percentage of cavitation (POC) was derived using the vapor volume fraction (VVF). The POC, defined by the cavitation occurrence zone with VVF > 0.5 divided by the volume of the cavitation danger zone, was 34.90%. Cavitation at this POC level could cause mechanical damage; therefore, a size optimization was performed. The lengths of the optimized waist and tail regions of the bottom plug were obtained wherein the POC level decreased by 19.06%. In addition, experiments were conducted using a flow visualization test setup. The experimental results were quantified into the POC employing the image gradients method, and the results were in good agreement with the CFD analysis.

Microbubble tracking based on partial smoothing-based adaptive generalized labelled Multi-Bernoulli filter for super-resolution imaging

Super-resolution ultrasound (SRUS) can image the vasculature at microscopic resolution according to microbubble (MB) localization, with velocity vector maps obtained based on MB tracking information. High MB concentrations can reduce the acquisition time of SRUS imaging, however adjacent and intersecting vessels are difficult to distinguish, thus decreasing resolution. Low acquisition frame rates affect the precision of flow velocity estimation. This study proposes a partial smoothing-based adaptive generalized labeled multi-Bernoulli filter (SAGLMB) to precisely track the MB motion at different flow velocities. SAGLMB employs a generalized labelled multi-Bernoulli filter (GLMB) for MB trajectory allocation to separate adjacent and intersecting vessels. Furthermore, the nonlinear motion of MB was predicted by an unscented Kalman filter, and a cardinalized probability hypothesis density filter was applied to suppress clutter interference. Finally, the trajectories were smoothed by unscented Rauch-Tung-Striebel to improve the resolution of the SRUS image. The simulation results demonstrate that SAGLMB outperforms the conventional bipartite graph-based tracking at high MB concentrations, achieving at least an 8.55 % improvement in the correctly paired precision, with 3 times increase in the structural similarity index measure. Moreover, SAGLMB can obtain more precise flow velocity estimations with a 4 times improvement than the conventional method. The SRUS results of rabbit kidney show that the proposed method significantly improves resolution of adjacent and intersecting vessels at higher MB concentrations and maintains this performance as the acquisition frame rate decreases. Furthermore, the rat brain microvascular network was reconstructed with 9.21 μm (λ/11.1) resolution. Therefore, SAGLMB can achieve robust SRUS imaging at high concentrations and low acquisition frame rates.

Flow corrosion simulation study of local defects in CO2 saturated solution

The inner walls of oil and gas transportation pipelines are prone to the formation of localized pitting defects due to the presence of solid particles in multiphase flow. The continuous flow poses a risk of perforation leakage in the pipe wall. To investigate the development of defects under flow corrosion and assess the impact of flow, a multi-field coupling finite element model incorporating fluid dynamics, reactions, and mass transfer was developed. The flow corrosion of local defects with various depths in a CO2-saturated solution was simulated. The calculation of mass transfer in corrosion is coupled with the precise flow field solved by large eddy simulation (LES) method. It has been observed that the distribution of corrosive substances is significantly affected by the flow due to local defects. Within these defects, the maximum concentration of corrosion product Fe2+ is observed on the upstream surface of defects. While the H+ accumulates at the downstream wall, which affects the corrosion rate. The local turbulent state is influenced by the depth of defects, and the interplay of the turbulence intensity with reflux velocity determines the mass transfer.

Reliability analysis of a grid-connected hybrid renewable energy system using hybrid Monte-Carlo and Newton Raphson methods

The integration of renewable energy sources into the power grid is essential for sustainable development, yet it presents significant dependability challenges, particularly in terms of reliability, stability, and robustness due to the inherent variability of these sources. This research introduces a novel hybrid methodology that combines Monte Carlo simulation with Newton-Raphson power flow analysis to enhance the reliability assessment of grid-connected hybrid renewable energy systems. This innovative approach uniquely addresses the limitations of existing methodologies by merging the probabilistic handling of uncertainties with precise deterministic power flow analysis. Our hybrid method significantly reduces the Loss of Load Expectation (LOLE) to 5 h per year and the Loss of Load Energy Expectation (LOEE) to 200 MWh per year, outperforming traditional methods which typically report LOLEs of 2020 h/year and LOEEs of 10001000 MWh/year. Additionally, the hybrid method achieves a reduction in power losses to 1.2%, showcasing its superior efficiency compared to the 2.5% losses seen with standalone Monte Carlo methods. Real-time validation using the IEEE-30 bus model further confirms the practical applicability and robustness of our approach, making it a pivotal tool for enhancing grid stability and optimizing renewable energy integration. This research not only advances the methodology for reliability assessment but also sets a new standard for balancing accuracy and computational efficiency in energy system management. The implications of this work are far-reaching, offering significant contributions to both grid reliability and the sustainable management of renewable energy resources.

Adsorption and decomposition of perfluorinated compounds using NiSBA-15 and CuSBA-15 catalysts for greenhouse gas reduction

BackgroundThe persistence of the environmental effects of perfluorinated compounds (PFCs) and fluorinated compounds (FCs) has raised concerns due to their widespread use and long-term impact on ecosystems and human health. MethodsIn this study, we investigated the use of NiSBA-15 and CuSBA-15 catalysts for the adsorption and decomposition of PFCs/FCs (CF₄, SF₆, NF₃, C₃F₈, and C₄F₈) by varying parameters such as weight percentage and contact time. The catalysts were synthesized through an impregnation method with stirring at 300 rpm for 24 h, followed by calcination at 550 °C for 6 h. The catalytic decomposition of NF₃ was conducted using a glass reactor with precise flow rate control and FT-IR monitoring. Variations in acid concentration during synthesis led to structural changes, transitioning from elongated rods to doughnut-like shapes and eventually spherical structures. Impregnation with nickel and copper nitrates successfully modified SBA-15, forming NiSBA-15 and CuSBA-15, as confirmed by HR-TEM images displaying black spots. Catalytic PFC decomposition experiments using unmodified SBA-15 showed limited efficiency, achieving only 15 % NF₃ removal at 500 ppm and 500 °C over 1000 min. Subsequent modification with nickel and copper significantly improved NF₃ removal efficiency. Significant ResultsCuSBA-15 exhibited superior performance compared to NiSBA-15, reaching a remarkable 95 % removal efficiency of NF3. Kinetic analysis using a pseudo-first-order reaction model demonstrated the enhanced catalytic efficiency of the modified SBA-15 catalysts, with increased reaction rate constants (K) for NF3 decomposition. This study reveals the potential of NiSBA-15 and CuSBA-15 catalysts for the adsorption and decomposition of specific PFCs/FCs, offering valuable insights into the underlying mechanisms and practical applications of these catalysts.

Urban energy transition: Sustainable model simulation for social house district

Energy communities (EC) play a crucial role in driving the transition towards renewable energy sources within urban areas. This study focuses on the implementation of EC within linear mass housing in Rome, with particular attention given to the Tor Bella Monaca district. The research proposes and simulates six energy community distinct scenarios using the Urban Modelling Interface (UMI) and Simulink in order to advance understanding of this topic. These scenarios evaluate the integration of photovoltaic systems, heat pumps, and energy storage systems to determine their comprehensive effect on renewable energy production, CO2 emission reduction, and the enhancement of self-consumption. The study findings show that higher electrification levels in an energy community lead to greater consumption of renewable energy and reduced reliance on the grid. The integration of heat pumps and energy storage further enhances energy consumption and self-sufficiency creating sustainable energy models in urban environments. With an increase in self-consumption factor and self-sufficiency factor of 0.15–0.30 and 0.11–0.13, respectively, depending on the scenario. The research highlights the importance of a thorough assessment of technology sizing and integration in order to enhance self-consumption and decrease CO2 emissions. It proposes investigating the incorporation of both thermal and electrical storage to optimize self-consumption. Finally, the simulated scenarios underwent flexibility analyses to determine the precise energy flow capacity and the optimal setting identified through economic evaluation.

Glacier dynamic study of the Terre de Lambert glacier in Greenland based on Landsat 8 and Sentinel-1 data

With global temperatures on the rise, the trend of glacial melting is becoming increasingly evident. This study focuses on the northeastern region of Greenland as the research subject, utilizing remote sensing technology and geographic information technology to study glacial dynamics. Initially, the research processes Landsat 8 data using QGIS to classify the widespread snow and ice cover, facilitating the observation and analysis of its temporal variations. The study then narrows its focus to Terre de Lambert for further analysis. Subsequently, using satellite data from Sentinel-1 and employing SNAP, the research conducts an in-depth analysis of glacier flow speed in specific regions. Through intricate computational models and algorithms, precise glacier flow direction and speed maps are generated. By combining historical data, the study compares and analyzes the glacier flow speed between 2018 and from June 20th to July 14th, 2023. Results indicate that the glacier flow speed in 2023 during the same time frame was faster. Throughout the research process, limitations in current data acquisition and processing methods were identified. Thus, the paper suggests improvements to data acquisition and processing tools to enhance the efficiency of glacier flow speed studies. Theres a fervent hope for the emergence of more convenient, streamlined, and customizable temporal dimension tools for glacier flow speed data in the future. The research findings aim to draw global citizens attention to the issue of glacial melting and inspire collective actions to protect our planet.

Development and validation of a precise flow injection method for the assessment of brexpiprazole, with application to pharmaceutical dosage forms and human plasma analysis

A novel antipsychotic medication named brexpiprazole (BRX) is currently employed for the treatment of schizophrenia and other psychotic disorders. Because BRX’s molecular structure includes a benzothiophene ring, it natively fluoresces. To detect BRX with precision and speed, a flow injection-fluorometric method, which is both sensitive and selective, is recommended. The fluorescence detection was conducted at 364 nm following excitation at 326 nm to capture the strong intrinsic fluorescence of BRX. The carrier solution employed was a mixture of phosphate buffer (pH 4, 10 mM) and acetonitrile (50: 50, v/v), with a flow rate of 0.5 mL min− 1. The calibration curve, based on peak areas, exhibited linearity within the concentration range of 20–350 ng mL− 1, with a remarkable correlation coefficient (r2) of 0.9999. The limit of quantitation was 9.7 ng mL− 1, and the limit of detection was found to be 3.2 ng mL− 1. This method was applied to quantify BRX in Neopression® tablets, achieving recovery within an acceptable range without interference from the tablet’s additives. Additionally, the proposed approach was successfully utilised to quantify the drug in spiked human plasma. The approach underwent validation following ICH requirements.

Open-source spring-driven syringe pump with 3D-printed components for microfluidic applications

The operation of microfluidic devices requires precise and constant fluid flow. Microfluidic systems in low-resource settings require a portable, inexpensive, and electricity-free pumping approach due to the rising demand for microfluidics in point-of-care testing (POCT). Open-source alternatives, employing 3D printing and motors, offer affordability. However, using motors require electrical power, which often relies on external sources, hindering the on-site use of open-source pumps. This study introduces a spring-driven, 3D-printed syringe pump, eliminating the need for an external power source. The syringe pump is operated by the flat spiral spring’s torque. By manually winding up the mainspring, the syringe pump can be operated without electricity. Various flow rates can be achieved by utilizing different syringe sizes and choosing the right gear combinations. All the parts of the syringe pump can be fabricated by 3D printing, requiring no additional components that require electricity. It operates by winding a mainspring and is user-friendly, allowing flow rate adjustments by assembling gears that modulate syringe plunger pushing velocity. The fabrication cost is $25–30 and can be assembled easily by following the instructions. We expect that the proposed syringe pump will enable the utilization of microfluidic technologies in resource-limited settings, promoting the adoption of microfluidics. Detailed information and results are available in the original research paper (https://doi.org/10.1016/j.snb.2024.135289).

Viscosity-model-independent generalized Reynolds number for laminar pipe flow of shear-thinning and viscoplastic fluids

Understanding the flow dynamics of non-Newtonian fluids is crucial in various engineering, industrial, and biomedical applications. However, the existing generalized Reynolds number formulations for non-Newtonian fluids have limited applicability due to their dependencies on their specific viscosity models. In this study, we propose a new viscosity-model-independent generalized Reynolds number formulation for laminar pipe flow. The proposed method is based on the direct adaptation of the measurement principles of rotational viscometers for wall shear rate estimation. We assess the accuracy of this proposed formulation for power-law and Carreau-Yasuda viscosity models through robust friction factor experiments. The experimental results demonstrate the applicability and effectiveness of the proposed viscosity-model-independent Reynolds number, as the measured friction factor data align closely with our Reynolds number predictions. Furthermore, we compare the accuracy of our Reynolds number formulation against established generalized Reynolds formulations for pure shear-thinning (Carreau-Yasuda) and viscoplastic (Herschel-Bulkley-extended) models. The results of the comparative analysis confirm the reliability and robustness of this generalized Reynolds number in characterizing and interpreting flow behavior in systems with visco-inelastic non-Newtonian fluids. This unified generalized Reynolds number formulation presents new and significant opportunities for precise pipe flow characterization and interpretation as it is applicable to any visco-inelastic (time-independent) viscosity model without requiring additional derivations.

A modified lattice Boltzmann approach based on radial basis function approximation for the non‐uniform rectangular mesh

AbstractWe have presented a novel lattice Boltzmann approach for the non‐uniform rectangular mesh based on the radial basis function approximation (RBF‐LBM). The non‐uniform rectangular mesh is a good option for local grid refinement, especially for the wall boundaries and flow areas with intensive change of flow quantities. Which allows, the total number of grid cells to be reduced and so the computational cost, therefore improving the computational efficiency. But the grid structure of the non‐uniform rectangular mesh is no longer applicable to the classic lattice Boltzmann method (CLBM), which is based on the famous BGK collision‐streaming evolution. This is why the present study is inspired by the idea of the interpolation‐supplemented LBM (ISLBM) methodology. The ISLBM algorithm is improved in the present manuscript and developed into a novel LBM approach through the radial basis function approximation instead of the Lagrangian interpolation scheme. The new approach is validated for both steady states and unsteady periodic solutions. The comparison between the radial basis function approximation and the Lagrangian interpolation is discussed. It is found that the novel approach has a good performance on computational accuracy and efficiency. Proving that the non‐uniform rectangular mesh allows grid refinement while obtaining precise flow predictions.