Flow state monitoring of gas-water two-phase flow using multi-Gaussian mixture model based on canonical variate analysis

As a highly complex and time-varying process, gas-water two-phase flow is commonly encountered in industries. It has a variety of typical flow states and transition flow states. Accurate identification and monitoring of flow states is not only beneficial to further study of two-phase flow but also helpful for stable operation and economic efficiency of process industry. Combining canonical variate analysis (CVA) and Gaussian mixture model (GMM), a strategy called multi-CVA-GMM is proposed for flow state monitoring in gas-water two-phase flow. CVA is used to extract flow state features from the perspective of correlation between historical data and future data, which solves the cross correlation and temporal correlation of multi-sensor measurement data. GMM calculates the possibility that the current flow state belongs to each typical flow pattern and judges the current flow state by probability indicators. It is conducive to follow-up use of Bayesian inference probability and Mahalanobis distance-based (BID) indicator for flow state monitoring, which avoids repeated traversal of multiple CVA-GMM models and improves the efficiency of the monitoring process. The probability indicators can also be used to analyze transition flow states. The method combining the probabilistic idea of GMM with the deterministic idea of multimodal modeling can accurately identify the current flow state and effectively monitor the evolution of flow state. The multi-CVA-GMM method is validated by using the measured data of the horizontal flow loop of gas-water two-phase flow experimental facility, and its effectiveness is proved.     

Comments on “Study and application of discharge calibration for submerged radial gates” by Guo X., Guo Y., Wang T., Fu H., Li J. Flow Meas. Instrum. 78 (2021) 101912, https://doi.org/10.1016/j.flowmeasinst.2021.101912

This paper discusses the capability of Guo et al.'s (2021) equations to determine the discharge of radial gates under submerged flow conditions. It was concluded that Guo et al.'s (2021) equations are associated with error reduction compared to the Incomplete Self-Similarity (ISS) theory and the calibration method. However, it does not have a significant advantage over Energy-Momentum (E-M) approach. Employing E-M principles, new equations were proposed to determine the discharge of radial gates, which has some advantages compared to Guo et al. (2021), such as (1) error reduction under partially and fully submerged flow conditions, (2) least dependence on the empirical constants, (3) uniformity of form over the entire submerged condition, and (4) no need to classify the submerged flow. Field calibration showed that the proposed equations in the present study for a single gate predict the discharge of parallel radial gates with a mean absolute error of less than 4.5% subject to the submerged operation of all open gates.     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

The use of bio-diesel based additive as rheology improver and pour point depressant of Nigerian waxy crude

The chemical method has proved to be the most effective mitigating method of wax deposition in petroleum system as it deals with the root cause of wax formation. Most of the commercial chemicals in the industry are very expensive and toxic. This paper aims the use of biodiesel based additives for improving the rheological behavior and pour points of waxy crude from Nigeria field. The biodiesels derived additives gave better performance than the commercial chemical and the seed oils as greatly improvement in rheology and pour point values of the waxy crude were observed     

Crystal-field engineering of ultrabroadband mid-infrared emission in Co2+-doped nano-chalcogenide glass composites

Tunable and ultrabroadband mid-infrared (MIR) emissions in the range of 2.5–4.5 μm are firstly reported from Co²⁺-doped nano-chalcogenide (ChG) glass composites. The composites embedded with a variety of binary (ZnS, CdS, ZnSe) and ternary (ZnCdS, ZnSSe) ChG nanocrystals (NCs) can be readily obtained by a simple one-step thermal annealing method. They are highly transparent in the near- and mid-infrared wavelength region. Low-cost and commercially available Er³⁺-doped fiber lasers can be used as the excitation source. By crystal-field engineering of the embedded NCs through cation- or anion-substitution, the emission properties of Co²⁺ including its emission peak wavelength and bandwidth can be tailored in a broad spectral range. The phenomena can be accounted for by crystal-field theory. Such nano-ChG composites, perfectly filling the 3–4 μm spectral gap between the oscillations of Cr²⁺ and Fe²⁺ doped IIVI ChG crystals, may find important MIR photonic applications (e.g., gas sensing), or can be used directly as an efficient pump source for Fe²⁺: IIVI crystals which are suffering from lack of pump sources.     

以用户为中心的可见光通信协作传输中训练资源分配算法

以用户为中心的可见光通信协作传输是近年来出现的新架构,这导致虚拟小区之间出现重叠。为避免导频污染问题,每个虚拟小区中的光接入点(AP)或者虚拟小区中选择相同AP的用户发送的训练序列应该是正交的。针对可见光通信中以用户为中心的协作网络,研究训练资源的正交分配问题,提出了一种新的导频分配算法,联合导频分配和用户选择问题,以期最大限度地增加虚拟小区内可被接入的用户数。分析和仿真结果表明,该导频分配方案可以有效改善导频污染问题,提高训练资源利用率,并且相比已有的导频分配方案,性能有所改进。     

Transparent niobate glass-ceramics for optical limiting

The construction of nonlinear optical materials featuring asymmetric transmission of light is of great technological importance for various applications, including optical switching and optical power limiting. A significant challenge is the scalable fabrication of material candidates with good photochemical stability, high optical transmittance, and excellent optical limiting performance. Here, we present a nanocrystallization avenue for constructing hybrid optical limiting materials that exhibit ultrafast and robust optical limiting performance. The experimental results show that the controllable relaxation of a niobate glass may lead to the clustering of Nb-O units and contracting of the bandgap. It results in the notable improvement in nonlinear optical properties, including the enhanced saturation irradiance (380 GW/cm²), doubly increased nonlinear coefficient, and decreased limiting threshold (200 GW/cm²). Our results suggest a promising material that exhibits promising applications for protecting eyes and sensitive components from laser-induced damage.