Flow Measurement and Instrumentation最新文献

{"title":"Electrical resistance tomography-based prediction for solid phase fraction by CNN with inaccurate samples","authors":"Shenglu Yue,&nbsp;Xinshan Zhu,&nbsp;Yibo Wang,&nbsp;Ming Zeng","doi":"10.1016/j.flowmeasinst.2025.102914","DOIUrl":"10.1016/j.flowmeasinst.2025.102914","url":null,"abstract":"<div><div>Electrical resistance tomography (ERT) faces critical challenges in solid-liquid two-phase flow measurement, particularly in mud monitoring, due to unreliable samples caused by uncertain mud conductivity and nonstationary working cycles. This paper proposes a hybrid data-model framework to enhance ERT-based solid-phase fraction (SPF) prediction. First, a kernel-based similarity metric with dynamic time warping (DTW) partitions time-series ERT data, achieving high accuracy in valid sample identification through double-linear weighting averaging (DWLA) that incorporates boundary distance and neighborhood density. Second, a bidirectional long/short-term memory (BiLSTM) network replaces conventional CNNs to capture temporal dependencies in conductivity fluctuations, integrating physical constraints from Maxwell's equations. Experimental results demonstrate significant improvements in both accuracy and stability. The proposed DWLA-BiLSTM framework provides a systematic solution for industry application under complex flow patterns.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102914"},"PeriodicalIF":2.3,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886449","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":"New method for estimation of velocity distribution in the river based on single point of velocity measurement","authors":"Hanieh Kakavandi,&nbsp;Mohammad Mehdi Heidari,&nbsp;Rasool Ghobadian","doi":"10.1016/j.flowmeasinst.2025.102915","DOIUrl":"10.1016/j.flowmeasinst.2025.102915","url":null,"abstract":"<div><div>Investigating the velocity distribution within open channels is crucial for both hydraulic engineering and research due to its extensive practical uses. This study introduces an improved two-dimensional flow velocity model based on the simplified Reynolds-averaged Navier-Stokes equations for predicting velocity distribution and estimating discharge in open channels. The finite volume method, integrated with an unstructured triangular mesh, is employed for the numerical solution of the equations. The approach to calculating turbulent viscosity significantly affects the model's precision. In this case, the turbulent eddy viscosity is determined using the mixing-length theory. The eddy viscosity in open channels is ascertained by measuring velocity at a central point in the river's cross-section, which then informs the computation of eddy viscosity and velocity distribution throughout the channel. Various experimental scenarios, including different channel cross-sections and roughness conditions, were examined to validate the model. The findings confirm that the model reliably predicts velocity distribution and river discharge.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102915"},"PeriodicalIF":2.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843619","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":"Improved method for sample mixing, handling and analysis in high water cut samples","authors":"Pamela I. Chacon ,&nbsp;Richard Guilbeau ,&nbsp;Gary Potten ,&nbsp;James Strawn","doi":"10.1016/j.flowmeasinst.2025.102912","DOIUrl":"10.1016/j.flowmeasinst.2025.102912","url":null,"abstract":"<div><div>Operating production facilites in mature fields globally pose both measurement challenges and opportunities. When production depletes, facility operations may transition from three-phase to two-phase production separation resulting in allocation measurement of oil and water mixtures.</div><div>There are two common approaches used for production allocation measurement to determine water cut: online water cut analyzers (WCA) and sampling.Sampling can be spot or automatic, with automatic sampling preferred for custody applications when water content is less than 5 % by volume. Spot sampling is the common method used for field verifying WCA. The most common technique for determining water content in a sample is by centrifuge; however, the centrifuge methods lack published reproducibility and repeatability data at high water cuts (&gt;5 % water in oil by volume). Sample handling and mixing with high water concentrations are also a severe challenge, especially with light oils and products which don't mix well. As WCAs are used more and more in high water cut production allocation, an accurate methodology for verifying the instruments is required for broad industry acceptance but the current industry guidance is very limited.</div><div>This paper describes an improved method for sample handling, and mixing and describes the proof of concept of using existing methods for analysis of high water cut samples for production allocation measurement developed in support of WCA verification. The testing described in this paper used water cuts 15–95 % by volume, and three hydrocarbons: two crudes and one distillate oil. The data demonstrates the range of the standard methods (API 10.3 and API 10.4) could be expanded while meeting or exceeding the current reproducibility requirements of API MPMS Ch 8 and Ch 10.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102912"},"PeriodicalIF":2.3,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854984","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":"Choke flow oil rate through surface data: Modeling via rigorous methods","authors":"Jian Shen ,&nbsp;Muntadher Abed Hussein ,&nbsp;Bhavesh Kanabar ,&nbsp;Anupam Yadav ,&nbsp;Asha Rajiv ,&nbsp;Aman Shankhyan ,&nbsp;Sachin Jaidka ,&nbsp;Manu Mehul ,&nbsp;Issa Mohammed Kadhim ,&nbsp;Zainab Jamal Hamoodah ,&nbsp;Fadhil Faez ,&nbsp;Mohammad Mahtab Alam ,&nbsp;Hojjat Abbasi","doi":"10.1016/j.flowmeasinst.2025.102911","DOIUrl":"10.1016/j.flowmeasinst.2025.102911","url":null,"abstract":"<div><div>Accurate estimation of choke flow oil rates under critical flow conditions is essential to optimizing crude oil production. This study utilizes field data derived from a Middle Eastern oil production area, incorporating surface parameters such as choke size, wellhead pressure, gas-oil ratio (GOR), basic sediments and water content (BS&amp;W), and oil API to predict oil flow rates through Random Forest machine learning models. Advanced metaheuristic optimization techniques enhanced hyperparameter tuning and model performance, including the Bat Algorithm, Genetic Algorithm, Cuckoo Search Algorithm, and Dragonfly Algorithm. The data-driven models were developed using k-fold cross-validation to ensure robustness and minimize overfitting. Comparative analysis of optimization methods reveals that the Genetic Algorithm delivers superior results across key performance metrics, including R², MSE, and AARE%, validating its efficacy for predictive tasks. This study emphasizes integrating advanced optimization methods with machine learning models to improve oil extraction operations' reliability, predictive accuracy, and production efficiency.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102911"},"PeriodicalIF":2.3,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865050","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 design and stability investigation of non-circular planetary gears transmission system","authors":"Junhai Guo ,&nbsp;Changbin Dong ,&nbsp;Yongping Liu ,&nbsp;Dawei Li ,&nbsp;Juan Wang","doi":"10.1016/j.flowmeasinst.2025.102910","DOIUrl":"10.1016/j.flowmeasinst.2025.102910","url":null,"abstract":"<div><div>The accuracy of the mathematical model for non-circular planetary gears is crucial for improving the stability and lifespan of hydraulic motors. Traditional mathematical models have limitations in terms of precision and construction complexity, often leading to tooth interference issues during gear meshing. To address these problems, this paper uses Fourier fitting to construct high-order elliptical and double-arc pitch curves, obtaining continuous and precise mathematical expressions. Further, the negative modification coefficient of the planetary gears is optimized through multibody dynamic simulations to prevent tooth interference. A comparison of the stability characteristics of the two non-circular planetary gear structures shows that the high-order elliptical gear exhibits superior stability and lower flow pulsation compared to the double-arc gear. The findings provide a more accurate theoretical basis for optimizing non-circular planetary gear hydraulic motors.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102910"},"PeriodicalIF":2.3,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850258","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":"Intelligent non-intrusive thermal flow rate meter designed for small diameter applications","authors":"J.L.M. Amaral ,&nbsp;T.M. Quirino ,&nbsp;J.M. Quirino ,&nbsp;J.R.C. Silva","doi":"10.1016/j.flowmeasinst.2025.102902","DOIUrl":"10.1016/j.flowmeasinst.2025.102902","url":null,"abstract":"<div><div>Current non-intrusive flow measurement techniques still need improvements as they have disadvantages in small-diameter applications. This work proposes to develop a non-intrusive thermal flow meter to obtain the slightest full-scale deflection possible in low liquid flows. The meter uses a copper duct with an internal diameter of <span><math><mrow><mn>22</mn><mspace></mspace><mi>m</mi><mi>m</mi></mrow></math></span>, six commercial K-type thermocouples, a microtubular heating resistance, and artificial intelligence to infer the flow rate from the thermal distribution on the duct surface. The sensors and the heater layout were calculated based on the theoretical temperature spread obtained from the physical model. To evaluate the meter, a test bench was built to control the heating resistor’s flow rate and temperature. The test bench is equipped with an electromagnetic flowmeter calibrated and certified in an external laboratory for reference and comparison, according to the ABNT (Brazilian Association of Norms Techniques) guidelines and the good practices used in the industries and calibration laboratories. In the meter evaluation, the resistance was activated so that the duct’s central region’s temperature remained at 70 degrees Celsius, and the thermal distribution data was collected with flow rates between 0.05 and <span><math><mrow><mn>0</mn><mo>.</mo><mn>6</mn><mspace></mspace><msup><mrow><mi>m</mi></mrow><mrow><mn>3</mn></mrow></msup><mo>/</mo><mi>h</mi></mrow></math></span> with intermediate increases of <span><math><mrow><mn>0</mn><mo>.</mo><mn>01</mn><mspace></mspace><msup><mrow><mi>m</mi></mrow><mrow><mn>3</mn></mrow></msup><mo>/</mo><mi>h</mi></mrow></math></span>. The experiment’s collected data were used to train the following models: linear regression, K-Nearest Neighbor (K-NN), Decision Tree, Random Forests, and Gradient Boosting. Deep learning models were also trained. The best result was obtained with k-NN, demonstrating that the built prototype could infer the flow rate with a full-scale deflection equal to 0.14%. As a result, the evaluation indicated that artificial intelligence algorithms could improve non-intrusive flow measurement systems compared to the proposed analytical thermal flow model.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102902"},"PeriodicalIF":2.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815012","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":"A compact and cost effective GRU flow sensor to estimate propellant flow rate and mixture ratio for payload capacity enhancement in Liquid Propellant Rocket Engines","authors":"R. Anisha Selva Kala ,&nbsp;D. Jeraldin Auxillia ,&nbsp;J. Jessi Flora","doi":"10.1016/j.flowmeasinst.2025.102908","DOIUrl":"10.1016/j.flowmeasinst.2025.102908","url":null,"abstract":"<div><div>This research focusses on developing a single GRU flow sensor to estimate the volumetric flow rate of propellants, Liquid Hydrogen (fuel) and Liquid Oxygen (oxidiser) and to compute Mixture ratio in Liquid Propellant Rocket Engine (LPRE). This single GRU flow sensor replaces a pair of massive Turbine flow meters in LPRE. This enhances the payload capacity (satellite weight) of the launch vehicle. The raw engine data is collected from the ground hot test of LPRE conducted for a duration of 100 s. The significance of this research is to estimate the flow rate of propellants from the functionally dependent pressure parameters such as Combustion chamber pressure (<span><math><mrow><msub><mi>P</mi><mi>C</mi></msub></mrow></math></span>), Fuel injection pressure (<span><math><mrow><msub><mi>P</mi><mn>1</mn></msub></mrow></math></span>) and Oxidiser injection pressure (<span><math><mrow><msub><mi>P</mi><mn>2</mn></msub></mrow></math></span>). The GRU network learns the temporal flow rate dependencies and estimates the fuel and oxidiser flow rate in the three engine operating phases. Mixture Ratio is computed from the GRU estimated flow rate and compared with the actual. Analysis on transient errors in the engine operating phases, estimation performance evaluation with metrices, Root mean square error (RMSE), Mean absolute error (MAE) and R-squared (R²), and performance agreement using Bland Altman approach conducted to assess the estimation effectiveness of GRU flow sensor. An RMSE of 0.3640 and 0.3725 for fuel and oxidiser flow rate respectively and an error less than ±2 % in computed mixture ratio proves that GRU flow sensor estimation is accurate. Additional analysis on weight and cost from literatures show that the hardware model weighs approximately 1.5 kg with a cost benefit of around $71,000. This facilitates a three - fold enhancement in payload capacity of launch vehicle.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102908"},"PeriodicalIF":2.3,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821109","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":"Balanced deep learning-based bubble segmentation: Model comparison, optimization, and application in microbubble detection","authors":"Tianyi Cai ,&nbsp;Ao Tang ,&nbsp;Rixin Xu ,&nbsp;Jiawen Zhou ,&nbsp;Wenchao Gong ,&nbsp;Wu Zhou","doi":"10.1016/j.flowmeasinst.2025.102907","DOIUrl":"10.1016/j.flowmeasinst.2025.102907","url":null,"abstract":"<div><div>The accurate segmentation and analysis of bubbles are crucial for understanding bubble generation mechanisms and improving industrial microbubble detection. This study aims to evaluate and optimize deep learning-based bubble segmentation models. Firstly, a systematic model evaluation matrix is proposed, including the general model performance, defocused bubble size prediction accuracy, and overlapping bubble segmentation. Secondly, four models, including SplineDist, StarDist, YOLOv8-seg, and Mask R-CNN, are compared. The SplineDist-M16 model demonstrates superior image processing speed (7.84 FPS) and high accuracy in bubble size prediction with minimal misdetection (6.1 %). Compared to other models, SplineDist-M16 excels in edge fitting and overlapping bubble identification. The optimized model provides rapid, accurate measurement of bubble quantity, size, and shape, offering insights into bubble formation and guiding microbubble generator design. This study paves the way for real-time microbubble detection in industrial applications and suggests further model improvements through simulated data training and enhanced overlapping bubble segmentation. Furthermore, the SplineDist-M16 model was utilized to analyse the impact of flow rate and backpressure on microbubble characteristics generated by a Venturi-tube microbubble generator. The results show that increased flow rate reduces bubble size and increases bubble circularity, while backpressure has minimal impact on bubble size distribution and shape.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102907"},"PeriodicalIF":2.3,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815010","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":"Design, simulation, and experimental analysis of water hydraulic artificial muscle joint flow replenishment valve","authors":"Yong Yang ,&nbsp;Zengmeng Zhang ,&nbsp;Yunrui Jia ,&nbsp;Dayong Ning ,&nbsp;Yongjun Gong","doi":"10.1016/j.flowmeasinst.2025.102903","DOIUrl":"10.1016/j.flowmeasinst.2025.102903","url":null,"abstract":"<div><div>The movement speed and energy consumption of the water hydraulic artificial muscle joint (WHAMJ) increase with the increase of the control valve flow rate. To achieve both fast movement speed and low energy consumption, a new-type flow replenishment valve was proposed. The flow replenishment valve is connected between the pressure difference valve and the WHAMJ. It opens when the WHAMJ is moving to increase the movement speed, and closes when the WHAMJ is stable to prevent additional flow rate generation. Based on the principle, several flow replenishment structure forms were designed, and the simulation analysis was carried out. Through comparison, the best replenishment form was chosen, and a prototype was manufactured. The replenishment effect was further analyzed by experiments. The results show that the flow replenishment valve can increase the WHAMJ speed without affecting the steady system flow rate, improving the practicability of the valve-controlled WHAMJs.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102903"},"PeriodicalIF":2.3,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783957","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":"Study of rheological vibration of high-pressure differential string multistage control valve","authors":"Haozhe Jin,&nbsp;Zhansong Xu,&nbsp;Xiaofei Liu,&nbsp;Chao Wang","doi":"10.1016/j.flowmeasinst.2025.102906","DOIUrl":"10.1016/j.flowmeasinst.2025.102906","url":null,"abstract":"<div><div>Coal chemical system is faced with high temperature, high pressure difference and large flow rate and other harsh conditions, and the control valve is a key control element in the whole coal chemical system. This study employs experimental methods to validate the numerical model accuracy and utilizes fluid-structure interaction analysis to investigate the vibration characteristics and underlying mechanisms of series multi-stage control valves. Set the inlet pressure to 18.7 MPa, the outlet pressure to 2.9 MPa, and the fluid is water, based on the flow characteristics of the string multi-stage valve under complex working conditions. The vibration characteristics of the valve under five different openings are compared and analyzed, and the resonance response of the intrinsic frequency and modal frequency are studied. The results show that the maximum deformation of the valve reaches 0.011763 mm at 80 % opening; the maximum stress intensity value can reach 199.7Mpa, which has the risk of fluid impact damage; The valve opening directly affects the flow rate and fluid velocity. When the opening is small, the fluid velocity increases, which can easily lead to turbulence and vortex formation, thereby inducing vibrations. Conversely, when the opening is large, the fluid velocity decreases, resulting in smoother flow and reduced vibrations. The vibration damage caused by the tandem multistage regulating valve is mainly due to the influence of vibration positive stress. The location of stress and deformation changes will not change with the change of opening, while the change of opening has a significant effect on the stress value and deformation value. The resonance frequency of the control valve is about 671HZ at low frequency, which has a greater impact on the upper valve body and valve stem. To provide a research basis for the study of vibration and noise reduction of string type multistage control valve.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"104 ","pages":"Article 102906"},"PeriodicalIF":2.3,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767763","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}