Flow Measurement and Instrumentation最新文献

{"title":"Sparse reconstruction of ECT based on L1 regularization and nuclear regularization with the split Bregman iteration","authors":"Xianglong Liu ,&nbsp;Nan Wang ,&nbsp;Ying Wang ,&nbsp;Huilin Feng ,&nbsp;Kun Zhang","doi":"10.1016/j.flowmeasinst.2025.103002","DOIUrl":"10.1016/j.flowmeasinst.2025.103002","url":null,"abstract":"<div><div>Electrical capacitance tomography (ECT), which is a versatile tomography technique for imaging the permittivity distribution based on the capacitance measurements. Image reconstruction of electrical capacitance tomography is ill-posed and ill-conditioned, which makes the solutions not unique and sensitive to measurement disturbance. In this study, a multi-feature objective functional that combines <em>L</em>₂-norm as data fidelity term, <em>L</em>₁ regularization and nuclear regularization as regularizers is proposed to improve the imaging quality. The proposed method emphasizes the sparsity and low-rank characteristics of the imaging object and transforms the image reconstruction task into an optimization problem. The Split Bregman algorithm is introduced to efficiently solve the proposed objective functional by decomposing the complex optimization problems into several simple iterative sub-tasks. Numerical simulations verified the effectiveness of the proposed method. In addition, a flexible modular 8-electrode ring-shaped ECT system is constructed to further test the effectiveness of the proposed method.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 103002"},"PeriodicalIF":2.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on flow and pressure pulsation optimization of roller piston pump with triangular damping groove","authors":"Chenchen Zhang ,&nbsp;Dexun Zhang ,&nbsp;Yuzhe Lu ,&nbsp;Sheng Li ,&nbsp;Jian Ruan","doi":"10.1016/j.flowmeasinst.2025.103000","DOIUrl":"10.1016/j.flowmeasinst.2025.103000","url":null,"abstract":"<div><div>The roller piston pump uses rolling bearings to replace the sliding friction pairs of the axial piston pump, which significantly improves working efficiency and widens the applicable speed range. Flow and pressure pulsations are critical factors affecting the vibration and noise of roller piston pumps. To achieve low-noise stable operation, this paper proposes an optimization strategy using triangular damping grooves for pulsation suppression. Since reverse flow directly affects the amplitude of pressure pulsation, this paper first establishes an analytical model of the backflow before and after optimization, and compares and analyzes the effect of the triangular damping groove on reducing backflow. Secondly, CFD numerical simulations are conducted to analyze the pressure and flow changes in the piston chamber before and after optimization. The results showed that at 3000 rpm/5 MPa, the flow pulsation rate decreased from 23.4 % to 11.1 %, and the pressure pulsation rate decreased from 9.8 % to 4.2 %. At 5000 rpm/5 MPa, the flow pulsation rate decreased from 22.1 % to 9.9 %, and the pressure pulsation rate decreased from 10.6 % to 7.4 %. The optimized distribution grooves significantly reduced pulsation levels by suppressing backflow. Finally, a dedicated test bench is constructed to validate the results. The experiments demonstrated that at 3000 rpm/5 MPa, the pressure pulsation rate decreased from 11.2 % to 5.3 %, and at 5000 rpm/5 MPa, it decreased from 11.9 % to 6.8 %. The experimental results are in good agreement with the CFD simulations, confirming the effectiveness of the triangular damping groove optimization and the accuracy of the numerical simulations. This study provides theoretical foundations and practical engineering guidance for the design of low-pulsation roller piston pump.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 103000"},"PeriodicalIF":2.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive flow rate measurement using self-mixing optical feedback interferometry for point-of-use microfluidic applications","authors":"Vibhor Kumar Bhardwaj ,&nbsp;Amita Thakur ,&nbsp;Surita Maini","doi":"10.1016/j.flowmeasinst.2025.103003","DOIUrl":"10.1016/j.flowmeasinst.2025.103003","url":null,"abstract":"<div><div>A precise knowledge of the flow rate in microscale fluidic devices is one of the key challenges in modern diagnostics. Flow rate has a direct impact on diffusion rates during chemical processing, which in turn minimizes the quantity of minute samples needed for testing. The flow rate measurement methods reported to date either require a relatively bulky optical arrangement, or maintaining their form factor at a low cost is not feasible. To address this issue, Self-Mixing Optical Feedback Interferometry (SM-OFI) is being widely explored for the design of microfluidic flowmetry devices, owing to its portability and cost-effective structure. However, measuring the variable flow rate is still a limitation for SM-OFI systems. In this paper, the authors present a predictive analysis-based measurement method to estimate the flow rate. The proposed method is based on an auto-regressive least mean square algorithm, and the variations in the flow rates are solved as a Quadratic Performance Surface (QPS) problem. The proposed method was experimentally verified using different test samples prepared with distilled water, benzyl chloride, and methylene iodide. The statistical analysis performed on the experimental results revealed a strong linear correlation with the true values, with an R-squared value of 0.9997 and a standard error of 0.0013. The proposed method achieves a resolution of 1.1828 μL/min with a standard uncertainty of 0.1860 μL/min. It also features a well-aligned, real-time measurement scheme integrated into a compact optical structure.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 103003"},"PeriodicalIF":2.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of noise reduction for ultra high speed electric air compressor in fuel cell vehicles based on multi method fusion","authors":"Donghai Hu ,&nbsp;Jonathan Emmanuel Mangeleka ,&nbsp;Yan Sun ,&nbsp;Jing Wang ,&nbsp;Wenxuan Wei ,&nbsp;Xiaoyan Zhang ,&nbsp;Jianwei Li","doi":"10.1016/j.flowmeasinst.2025.103001","DOIUrl":"10.1016/j.flowmeasinst.2025.103001","url":null,"abstract":"<div><div>Operation of super-high-speed electric air compressors (SHSEAC) induces intense turbulent airflow and noise, significantly degrading user comfort. Existing noise studies, primarily focused on low-speed compressors, fail to address SHSEAC's distinct structural, flow, and acoustic characteristics. In this paper, aerodynam-ic noise generated by the SHSEAC is improved based on internal flow performance using a coupled computational fluid dynamics-computational aeroacoustic (CFD-CAA) simulation method. Firstly, a numerical model of SHSEAC was established, and the accuracy of the model was verified through experiments under idle, rated, and peak operating conditions (corresponding to 34000 rpm, 86500 rpm, and 95000 rpm, respectively). Secondly, propose a multi-objective optimization approach (MOOA)-Pareto-based to structure optimization is performed to improve both internal flow and acoustic field. The coupled simulation results indicate that the optimized structure improves the airflow and reduces turbulence between the two stages. The mean noise level (SPL) of the SHSEAC at 1m away from the boundary is minimized by 7.85 %,4.45 %, and 5.15 % at 34000 rpm, 86500 rpm, and 95000 rpm, respectively.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 103001"},"PeriodicalIF":2.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CFD-based flow field study of Triple-crossed elliptical injector nozzle","authors":"Hailong Ji ,&nbsp;Ruichuan Li ,&nbsp;Wentao Yuan ,&nbsp;Ning Guo ,&nbsp;Qingguang Zhang ,&nbsp;Lanzheng Chen","doi":"10.1016/j.flowmeasinst.2025.102998","DOIUrl":"10.1016/j.flowmeasinst.2025.102998","url":null,"abstract":"<div><div>As a third-generation electronically controlled fuel injection system, the high-pressure common rail injection system for diesel engines plays a crucial role in improving fuel efficiency and reducing exhaust emissions. In this paper, an in-depth analysis and improvement of the flow field characteristics of the injector nozzle is carried out, with a view to improving the flow characteristics of the injector nozzle and committing to the development of high-pressure injectors with high flow performance. This paper uses CFD to analyse and improve the original injector nozzle, establishes and verifies the fluid simulation model of SAC-type ultra-high-pressure injector nozzle, and improves the structure of the original injector nozzle, and designs a triple-crossed elliptical orifice-shaped injector nozzle. A comparative analysis shows that the cavitation intensity in the improved scheme is significantly reduced, and in addition, the average flow coefficient of the injector nozzles under the improved triple-crossed elliptical orifice is significantly better than the average mass flow rate of the original circular orifice scheme by about 57.82 % in the Inlet Pressure range of 100–200 MPa, and its average flow velocity is increased by about 25.86 %. Also the mass flow rate and velocity of the improved nozzle under 5–45 MPa back pressure was increased by about 46.01 % and 30.55 % respectively.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102998"},"PeriodicalIF":2.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic pressure measurement of ionic wind, generated by multi-emitter discharge for drying systems","authors":"Pejman Naderi,&nbsp;Alex Martynenko","doi":"10.1016/j.flowmeasinst.2025.102997","DOIUrl":"10.1016/j.flowmeasinst.2025.102997","url":null,"abstract":"<div><div>The ionic wind, generated by corona discharge from sharp emitters, is extensively used for propulsion and heat/mass transfer enhancement. Accurate speed measurement is critical to optimize the performance of ionic wind generators, especially in systems with multiple emitters where non-uniform flow is prevalent. To address this, a digital balance is used to measure the average speed of the ionic wind using dynamic pressure. The comparison with hot-wire and vane anemometers showed the advantages of dynamic pressure measurement of non-uniform ionic wind speed.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102997"},"PeriodicalIF":2.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144656125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of transient differential pressure signal features and flow pattern identification in horizontal two-phase flow through a constriction with machine learning models","authors":"T.F.B. Camargo ,&nbsp;E.E. Paladino","doi":"10.1016/j.flowmeasinst.2025.102985","DOIUrl":"10.1016/j.flowmeasinst.2025.102985","url":null,"abstract":"<div><div>Flow pattern identification and phase flow rate measurement of two-phase gas–liquid flows are of fundamental importance for process monitoring and control in several industrial applications. Differential pressure (<span><math><mrow><mi>Δ</mi><mi>p</mi></mrow></math></span>) based flow sensors are robust and reliable devices, with no moving parts, therefore very suitable for extreme environment applications such as deep offshore. These well-known sensors typically relate the mean differential pressure across a throttle device to the mixture flow rate. However, for the determination of phase flow rates, information about phase fraction is necessary. Beyond the average differential pressure, a wealth of information can be extracted from the transient <span><math><mrow><mi>Δ</mi><mi>p</mi></mrow></math></span> signal that can be useful for flow pattern identification and phase flow rate determination, without the use of additional sensors. In this paper, we present a thorough analysis of those features that have been extracted from the PDF, PSD, and DWT representations of the differential pressure signal. These features are then used for flow pattern determination based on deep neural networks, support vector machine, and K-nearest neighbor classifiers. The data are extracted for the flow of water–air mixture ranging from 0.03 to 1.28 m/s liquid superficial velocity <span><math><msub><mrow><mi>j</mi></mrow><mrow><mi>l</mi></mrow></msub></math></span> and 0.03 to 20 m/s of gas superficial velocity <span><math><msub><mrow><mi>j</mi></mrow><mrow><mi>g</mi></mrow></msub></math></span> in a horizontal configuration of a 25.4 mm internal diameter, therefore covering most flow patterns encountered in gas–liquid flows. Two orifice plates with diameters of 12.7 mm and 18.8 mm were used as throttle devices. Through data correlation analysis, a feature selection was performed following a geometry independence criterion. Therefore, the selected features are expected to be representative of the underlying flow characteristics of the upstream flow, irrespective of the orifice geometry. Results show that the prioritization of these selected parameters as inputs for the classifiers results in a more generalizable model.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102985"},"PeriodicalIF":2.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144656123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid model for dynamic fluid level measurement in oil wells","authors":"Hui Deng ,&nbsp;Liming Han","doi":"10.1016/j.flowmeasinst.2025.102987","DOIUrl":"10.1016/j.flowmeasinst.2025.102987","url":null,"abstract":"<div><div>Real-time monitoring of dynamic fluid levels in oil wells is crucial for ensuring production efficiency and safety. Traditional acoustic signal-based dynamic fluid level measurement methods often encounter significant noise interference, leading to inaccurate measurements. This paper proposes a hybrid model that combines machine learning and deep learning models to address this issue. First, raw audio data is preprocessed with wavelet transform to minimize noise. Then, a lightGBM classifier classifies the data into low- and high-noise data classes based on waveform features. Finally, for low-noise data, YOLOv7 is employed for target detection to evaluate fluid levels, as the imaging characteristics of such data are more precise; for high-noise data, the CNN-LSTM time series model is utilized, leveraging historical production data to forecast fluid levels, as image-based methodologies are inadequate. Unlike conventional techniques, which are limited to analyzing ideal low-noise waveforms for dynamic fluid level measurements, this hybrid model offers superior accuracy and resilience in fluid level measurements. It also broadens the applicability of acoustic-based dynamic fluid level assessment in oil wells. Consequently, this advanced hybrid approach for measuring dynamic fluid levels surpasses traditional methods, significantly contributing to blowout prevention, production strategy optimization, and overall enhancement of oil well management safety and efficiency.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102987"},"PeriodicalIF":2.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method and validity analysis of time-sharing and continuous measuring axial temperature and pressure in ejector","authors":"Huilan Huang ,&nbsp;Qimeng Fang ,&nbsp;Gang Li","doi":"10.1016/j.flowmeasinst.2025.102995","DOIUrl":"10.1016/j.flowmeasinst.2025.102995","url":null,"abstract":"<div><div>The conventional methods measuring flow parameters in ejector usually install some fixed instruments near the wall surface. Often only the fluid parameters and flow changes near the wall can be obtained. In order to obtain the axial fluid data of internal flow field in ejector, a time-sharing and continuous measuring axial temperature and pressure device is proposed in this paper. An ejector system experimental platform is setup based on the axial moving measurement device, and the experiment data is compared with the numerical simulation. The results show that the time-sharing and continuous measurement method is feasible, and the axial moving measurement device is a reliable, low-cost and convenient operation.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102995"},"PeriodicalIF":2.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144656122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gas-liquid two-phase flow rate measurement with differential pressure and density ratio synergistic dual neural network","authors":"Fachun Liang ,&nbsp;Boyu Duan ,&nbsp;Changrong Li ,&nbsp;Weibiao Zheng ,&nbsp;Yixuan Zhu ,&nbsp;Mengyuan Li ,&nbsp;Manqing Jin","doi":"10.1016/j.flowmeasinst.2025.102994","DOIUrl":"10.1016/j.flowmeasinst.2025.102994","url":null,"abstract":"<div><div>Machine learning has been widely applied in the field of fluid measurement. Establishing the mapping relationship between feature data, quality, and total mass flow rate is crucial for accurate measurement of gas-liquid two-phase flow. This study proposes two MLP models for gas-liquid two-phase flow measurement. A throttling experiment was conducted using a nozzle with a throat diameter of 12 mm, a total of 122 sets of experimental data were collected, with superficial gas velocity and superficial liquid velocity coverage ranges of 1.73–20.72 m/s and 0.0173–0.242 m/s, respectively, covering four flow patterns: stratified flow, wave flow, slug flow, and annular flow. By combining throttling mechanisms for feature selection, the input features of the quality prediction model are determined to be square root differential pressure ratio and square root gas-liquid density ratio, while the input features of the total mass flow rate prediction model are square root difference of double differential pressure and square root gas-liquid density ratio. And validate the effectiveness of features using Spearman and Pearson correlation analysis methods. The study results indicate that the relative error of the test samples for quality prediction model is within ±7 %, and the mean absolute percentage error (MAPE) is 2.78 %. The relative error of the test samples for total mass flow rate prediction model is within ±6 %, and the MAPE is 2.05 %. Both models were validated through 5-fold cross validation to ensure no overfitting occurred. This work avoids the problem of error accumulation through a dual model parallel prediction architecture, and achieves high-precision flow rate prediction with a small number of features and a small sample dataset, providing a data-driven new solution with practical engineering value for gas-liquid two-phase flow rate measurement.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 102994"},"PeriodicalIF":2.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}