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Coriolis mass flowmeters are highly customized products involving high-degree fluid-structure coupling dynamics and high-precision manufacture. The typical delay from from order to shipment is at least 4 months. This paper presents some important design considerations through simulation and experiments, so as to provide manufacturers with a more ti...
Citations
... However, Gace [26] adopted the SST k-ω turbulence model in their FSI framework and achieved a deviation of only 0.1% between FSI calculations and experimental results, demonstrating the suitability of the SST k-ω model for CMF modeling. Additionally, FEM and lattice Boltzmann methods (LBM) have been employed to model the fluid domain of CMFs [28][29][30], both yielding good agreement with experimental results. For instance, Birjandi's FEM-based model [30] exhibited a deviation of 2%, while Haussmann's LBM-based model [29] had a deviation of 5%. ...
... Kumar [15] investigated the effects of the transition from turbulent to laminar on the measurement sensitivity of CMF [9,10,14] based on the iterative partitioned coupling method, and the results revealed the additional shear force caused by the secondary turbulent flow will weaken the Coriolis force. The effects of viscosity, gravity, structural asymmetry, pressure, the additional mass of sensors and so on were also analyzed by researchers based on the same methods [20][21][22][23][24][25][26]. After comparing the results based on the Reynolds stresses model and eddy viscosity-based turbulence models, Shavrina [23] pointed out the importance of the turbulence model to obtain accurate results for U-type CMF, which complements Bobovnik's research results [10]. ...
... The results can be used for high flow velocity (26 m/s) and a pipe diameter in the range of DN6~DN1600. Hu, Y.-C [17] studied at simulating the fluid-structure coupling dynamics of a dual U-tube Coriolis mass flowmeter through the COMSOL simulation package. However, the zero drift will occur when the dual U-tube structure is unbalanced that can be appeared on the board of car. ...
... Based on previous studies and analyses, results have been obtained that can be used in the design of heat exchange elements of new structures with optimal parameters for high-efficiency heating of liquid heat transfer fluids [16][17][18][19][20][21]. ...
The article analyses the influence, relationship and value of the design parameters of the thermal flowmeter on its radial and axial heat fluxes in the tube. The purpose of the analyses is to check the change in the error of fuel flow measurement by the thermal flowmeter directly on the vehicle when using heating elements of different diameters. The influence of the radial heat flux of the flowmeter tube on the accuracy of fuel flow measurement is substantiated. Recommendations on the choice of design parameters of a thermal flowmeter at the stage of its design, development or use are developed under the condition of reducing the influence of the radial heat flow on the axial one, which will reduce the total error in the measurement of fuel flow rate.
... The main advantages of the Coriolis mass flow meter are (1): usable at high pressure (5 MPa), (2): easy calibration, and (3): measuring true mass flow rate [50]. In addition, high accuracy, a wide-range ratio, and good repeatability are the other advantages of them [48]. ...
... However, due to difficult installation and significant pressure drop creation in the pipes (due to the installation of the Coriolis tubes) is criticized [49]. Also, this systems should be isolated from exterior vibrations, the imbalanced vibration may cause mass flow measurement error [50]. ...
Selecting the applicable measurement method in the measuring process of solid particle’s mass flow rate is of great importance in pneumatic conveying. Accurate prioritization of measurement methods from the important indices viewpoint’s such as cost, repeatability, low calibration, ability to run, and response time can assess this selection. In the present study, the solid particle’s mass flow rate measurement methods in two phase flows were studied comprehensively. Then, as a novelty, a systematic method namely analytic hierarchy process (AHP), was applied to prioritize measurement indices and methods. Results revealed that the repeatability index has the greatest priority in selecting the appropriate method. Based on this index, the coriolis force meter method was identified as the best measuring method. Additionally, regarding all the indices, acoustic method is selected as the most appropriate method. In this study, provided a systematic decision process and a knowledge base for using AHP in prioritizing measurement methods.
... For example, Enz [12] investigated the time shift dependence on the velocity profile by the simulation based on this model. In addition, Hu et al. [13] investigated the influence of the fluid viscosity on the CFM operation by the FSI model based on the methodology by Bobovnik et al. [11]. Kumar and Anklin [14] studied the Reynolds number influence on the CFM operation by the FSI simulation. ...
... Finally, the modification of this FSI methodology was used by Athanase [15] and Romanov and Beskachko [16] to study the CFM operation during the multiphase metering and the influence of fluid dissipation characteristics on the CFM modelling, respectively. However, different turbulence models were applied in these studies to complement the RANS equations [11,13,[15][16][17]. The shear stress transport (SST) turbulence model was employed by Athanase [15], Hu et al. [13], and Romanov and Beskachko [16], while Bobovnik et al. [11,18], Kumar and Anklin [14], Hua et al. [19] and Enz [12] used the k-ε turbulence model. ...
... However, different turbulence models were applied in these studies to complement the RANS equations [11,13,[15][16][17]. The shear stress transport (SST) turbulence model was employed by Athanase [15], Hu et al. [13], and Romanov and Beskachko [16], while Bobovnik et al. [11,18], Kumar and Anklin [14], Hua et al. [19] and Enz [12] used the k-ε turbulence model. In addition, Bobovnik et al. [20] conducted a comparison of the Reynolds stress model (RSM) and k-ε models and reported an insignificant difference. ...
Numerical simulation is a widely used tool for Coriolis flowmeter (CFM) operation analysis. However, there is a lack of experimentally validated methodologies for the CFM simulation. Moreover, there is no consensus on suitable turbulence models and configuration simplifications. The present study intends to address these questions in a framework of a fluid–solid interaction simulation methodology by coupling the finite volume method and finite element method for fluid and solid domains, respectively. The Reynolds stresses (RSM) and eddy viscosity-based turbulence models are explored and compared for CFM simulations. The effects of different configuration simplifications are investigated. It is demonstrated that the RSM model is favorable for the CFM operation simulations. It is also shown that the configuration simplifications should not include the braces neglect or the equivalent flowmeter tube length assumption. The simulation results are validated by earlier experimental data, showing a less than 5% discrepancy. The proposed methodology will increase the confidence in CFM operation simulations and consequently provide the foundation for further studies of flowmeter usage in various fields.
Flow sensing facilitates the development of fisheries and marine security. However, previously-reported flow sensors can typically measure the average flow velocity within a large-scale geographical area. Herein a self-adaptive sensor for measuring fixed-position, small area, real-time and all-day planarly velocity vector is proposed. Based on the vortex-induced tortional swing motion mode, the arc-shaped device with a hall sensor or a piezoelectric sensor enables to recognize the 2D magnitude and direction of the flow velocity. The working mechanism is first elaborated through the boundary layer principle of fluid mechanics. A vibration mechanical model is proposed and solved by Galerkin method to numerically investigate the relation between swing amplitude and torsional frequency for flow speed and direction sensing simultaneously. The model is subsequently validated by experiments. The proposed water velocity sensor shows a rapid response time (0.4 s) for velocity direction sensing and high linearity (1.7%) for velocity magnitude sensing. This work pioneers velocity vector sensing using Kármán vortex streets and will benefit to fixed-position, small area, real-time ocean flow sensing applications.
In order to improve the signal processing effect and efficiency of Coriolis mass flowmeter, a signal processing system of Coriolis mass flowmeter based on time-varying signal model is designed. Based on the analysis of the structure and working principle of Coriolis mass flowmeter, the environmental factors affecting the performance of Coriolis mass flowmeter are discussed. Based on the above analysis, the signal processing environment is designed, including serial signal processing environment and dual core parallel signal processing environment. Then the effective signal processing of Coriolis mass flowmeter is completed from three aspects: initial processing, phase calculation and frequency tracking. The experimental results show that after the time-varying signal model is applied, a complete signal frame can be collected in less than 50 ms in the pre-processing process, and the signal processing frame can be completed in less than 80 ms in the post-processing process. This shows that the signal processing time of the system is short, and the phase difference detection accuracy of the signal processing system based on the time-varying signal model is high, which is of great value to further improve the application effect of Coriolis mass flowmeter.
Measuring mass flow rate in refrigeration systems with flow meters can be expensive when taking into account the cost of the equipment itself and the costs related to installation and maintenance. A mode based on Artificial Neural Networks can be used to predict the value of the mass flow, at a low cost, through easily observed and measured parameters, like temperatures. Additionally, well-known correlations to calculate parameters that directly influence the mass flow rate can be used as input data for the model to improve its accuracy. Within this context, the present study aims to develop a Multilayer Perceptrons model to predict the mass flow rate of a refrigeration systems. The model developed was optimized using one hidden layer with four neurons, Adam as the optimizer and softplus as the activation function. Later, it is presented an alternative mass flow rate meter, using an Artificial Neural Network model programmed in a microcontrolled circuit with only three temperatures as inputs. To develop the model, experimental data were collected in a refrigeration machine at several operating points. Step disturbances were introduced in the mass flow rate to produce transient data. Two different data sets were considered in the training process. The first data set contained only steady-state data and in the second data set, there were steady-state plus transient data. The mass flow rate estimated through the proposed model presented an average error of 0.79 % when considering steady-state and transient data in the training process, and 0.81 % when considering only steady-state data in the training procedure. The final embedded system developed predicted the mass flow rate with an average error of 1.22 %.
