Scaling analysis of hydrogen flow with carbon dioxide cushion gas in subsurface heterogeneous porous media

Subsurface hydrogen (H₂) storage in geological formations is of growing interest for decarbonization. However, there is a knowledge gap in understanding the multiphase flow involved in this process, which can have a significant impact on the recovery performance of H₂. Therefore, a full-compositional modeling study was conducted to analyze potential issues and to understand the fundamental hydrodynamic mechanisms of H₂ storage. We performed a range of 2D vertical simulations at the decametre scale with a very fine cell size (0.1 m) to observe the detailed flow behaviour of H₂ with carbon dioxide (CO₂) as cushion gas in various flow regimes. Issues such as viscous instability, capillary bypassing, gas trapping and gravity segregation are analysed here. To generalize our calculations, we have validated and applied the scaling theory in the context of subsurface H₂ storage. Since this study is focused on the hydrodynamic behaviour, three dimensionless groups, including aspect factor, capillary/viscous ratio and gravity/viscous ratio were identified to correlate recovery performance between various scales in a fixed heterogeneous system. It was found that H₂ could infiltrate the cushion gas in the proximity of the injectors, meaning that CO₂ is not displaced away from the injectors in a piston-like fashion. As a result, the purity of the back produced H₂ is much degraded, particularly in a viscous-dominated scenario. On the other hand, the injected H₂ mostly accumulates at the top forming a highly restricted mixing zone with CO₂ in the gravity-dominated case. The recovery performance is therefore much improved in this case. Although the gas distribution can be significantly altered by capillary forces leading to bypassed zones, the recovery performance of H₂ is hardly influenced. This is because the back-produced H₂ recovery is not dependent on the sweep efficiency of the gas. H₂ can be back produced following the same paths which were formed during injection.     

Experimental and numerical study on tube-side flow and heat transfer characteristics of superheated vapor flow in catalyst-filled LH2 spiral wound heat exchanger

High energy consumption is considered to be one of the most persistent problems in liquid hydrogen (LH₂) plants. The combination of heat exchanger and ortho-para (O–P) hydrogen conversion has attracted considerable attention as a cutting-edge technology to reduce energy consumption. The flow and heat transfer characteristics of O–P hydrogen conversion catalyst-filled spiral wound heat exchanger (SWHE) were investigated in this study in two steps. In the first step, pressure-drop experiments were performed in a tube filled with porous media. The results indicated that the pressure drop was overestimated when using Ergun's equation. Therefore, a new empirical pressure-drop correlation for a channel filled with O–P catalyst was formulated. Subsequently, a novel heat transfer model was established based on this correlation for further numerical simulations. The distributions of the temperature, pressure, and para hydrogen content in a catalyst-filled tube were determined. In addition, the influence of the flow rate on the heat exchange coefficient and outlet para hydrogen was clarified; it was found that, with an increase in the flow rate, the heat exchange coefficient increased, whereas the outlet para hydrogen content decreased. At a flow rate of 0.5 m³/h, the para hydrogen content increased by 44% after hydrogen flowed through the channel filled with the O–P catalyst. Furthermore, a prediction model for the para hydrogen content with a flow rate range of 0–1.5 m³/h was derived. This study provides promising theoretical evidence for the engineering application of SWHEs filled with O–P catalysts in large-scale hydrogen liquefaction units.     

Applications of sketches in network traffic measurement: A survey

Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions.     

Generation,validation and application of dynamic load profiles in flow measurement using cavitating Herschel–Venturi nozzles

Today, utility meters for water are tested for measurement behavior at stable operating conditions at specified flow rates as part of the approval process. The measurement error that occurs during start and stop or when changing between flow rates may not be taken into account. In addition, there are new technologies whose measuring behavior under real-world conditions is only known to a limited extend. To take these facts into account, a new method has been developed and tested to determine the measurement behavior of water meters under dynamic load profiles as they occur in the real application. For this purpose, a test rig for flow rate measurement was extended by a cavitation nozzle apparatus and the generation of dynamic load profiles was validated. For the cavitation nozzles used, possible factors influencing the flow rate, such as temperature and purity of the water as well as the upstream pressure were investigated. Using different types of domestic water meters, the applicability of the dynamic test procedure was demonstrated and the measurement behavior of the meters was characterised.     

Effect mechanism of multiple obstacles on non-Newtonian flow in ceramics 3D printing (linear elements)

Direct ink writing (DIW) provides a new way to mould ceramic parts. When a single screw extruder is used to extrude SiC slurry, the deposits caused by low viscosity and the agglomerations resulting from the nonuniform mixing, form the obstacles in the channel, which affect the normal flow of the slurry, theoretical outlet velocity, and interaction with other printing parameters. Therefore, it is necessary to study the mechanism responsible for the effects of the obstacles on the flow. The obstacles are always irregular, which makes it difficult to directly analyse them. Irregular geometries are always composed of linear and/or arcuate elements; therefore, the obstacles can be simplified into regular geometries. In the present work, linear elements are analysed first. Then, an improved MRT LBM (multiple relaxation time lattice Boltzmann method) with a pseudo external force is proposed for the flow analysis. The improved MRT LBM is combined with rheological test data to investigate cases with two obstacles, and the results are applied to reveal the general mechanism in cases with multiple obstacles. The results show that the angles, sizes, and positions of the obstacles are three important factors influencing the flow. To obtain a stable and controllable slurry flow, it is recommended that the first angle θ₁ be an acute angle. In addition, the number of obstacles should be minimized, and the position of the last obstacle should be far away from the outlet.     

Experimental investigation of gas-liquid flow in a vertical venturi installed downstream of a horizontal blind tee flow conditioner and the flow regime transition

A venturi device is commonly used as an integral part of a multiphase flowmeter (MPFM) in real-time oil-gas production monitoring. Partial flow mixing is required by installing the venturi device vertically downstream of a blind tee pipework that conditions the incoming horizontal gas-liquid flow (for an accurate determination of individual phase fraction and flow rate). To study the flow-mixing effect of the blind tee, high-speed video flow visualization of gas-liquid flows has been performed at blind tee and venturi sections by using a purpose-built transparent test rig over a wide range of superficial liquid velocities (0.3–2.4 m/s) and gas volume fractions (10–95%). There is little ‘homogenization’ effect of the blind tee on the incoming intermittent horizontal flow regimes across the tested flow conditions, with the flow remaining intermittent but becoming more axis-symmetric and predictable in the venturi measurement section. A horizontal (blind tee) to vertical (venturi) flow-pattern transition map is proposed based on gas and liquid mass fluxes (weighted by the Baker parameters). Flow patterns can be identified from the mean and variance of a fast electrical capacitance holdup measured at the venturi throat.     

Process Intensification of Living Cationic Polymerization of Isobutylene by a Flow Reaction System

Increasing the reaction temperature of the living cationic polymerization of isobutylene is crucial for industrial production due to the cost of refrigeration. The reaction temperature increase was achieved with an accelerated reaction rate using a flow reaction system. The polymerization conditions, including the flow reactor design, were based on the results of kinetic studies. Utilizing a milli‐scale flow reactor, polyisobutylene, which has a narrow molecular weight distribution, was obtained within a considerably short residence time at a high temperature. Furthermore, it was confirmed that the value of M_w/M_n correlates with the product of the Reynolds number and the angle of collision.     

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.     

Flow modeling of high-viscosity fluids in pipeline infrastructure of oil and gas enterprises

Today, the issues related to solving the problem of finding an effective distribution of oil flows through the system of oil pipelines in order to reduce the total energy consumption are relevant. The solution to this problem is connected with selection of rational pumping modes for various technological sections of oil pipelines using modern methods of mathematical programming or new techniques for improving the energy and transport characteristics of oil.Reducing energy consumption during pumping of crude through oil trunk pipelines can be achieved by various methods. Numerous investigations in this direction are mainly carried out to save energy on separate single-line pipelines. However, due to the development of the network of trunk oil pipelines in the world over the past decades, the issues of energy efficient management of oil flows throughout the entire oil pipeline system of oil and gas enterprises become urgent.This paper analyses parameters for pipeline transport of high-viscosity and heavy oils. The article proposes a method for assessing the rheological properties of oil for further planning of pumping taking into account the preservation of oil quality and an increase in energy and transport characteristics. The proposed solutions and tasks for predicting changes in the viscosity-temperature characteristics of the flow for blends of different oil types are especially relevant in the current conditions of an increase in the share of oil production with complex rheological characteristics. Results of the presented investigations may be used for planning the measures of efficient transportation of high-viscosity and heavy oils.     

An improvement of the Space-Time Image Velocimetry combined with a new denoising method for estimating river discharge

The Space-Time Image Velocimetry (STIV) is a time-averaged velocity measurement method, which takes river surface images as the analysis object, and detects the Main Orientation of Texture (MOT) in a generated Space-Time Image (STI) to obtain one-dimensional velocities on the water surface. The STIV has great potential in real-time monitoring of river flow owing to its high spatial resolution and low time complexity. However, the generated STI contains a lot of noise and interference texture, which is inevitable in practical applications. The practicality of the STIV is severely limited by the low-quality STI. To solve this problem, a denoising method based on the filtering technology is proposed and combined with different texture detection algorithms in this paper. The accuracy of this method is verified through a comparative field experiment with an impellor-style current meter. The experimental results show: (1) By using this new denoising method, the robustness and accuracy of the STIV are significantly improved no matter what kind of texture detection algorithm is adopted; (2) Among all the texture detection algorithms, the FFT-based STIV combined with the new denoising method performs best. The relative errors of the surface velocities are controlled within 6%, and the relative errors of the discharges are controlled within ±4%.