Effect of aspect ratio of elliptical stirred vessel on mixing time and flow field characteristics in the absence of baffles

Elliptical tanks were used as an alternative to circular tanks in order to improve mixing efficiency and reduce mixing time in unbaffled stirred tanks(USTs). Five different aspect ratios of elliptical vessels were designed to compare their mixing time and flow field. Computational fluid dynamics(CFD) simulations were performed using the k–ε model to calculate the mixing time and simulate turbulent flow field features, such as streamline shape, velocity distribution, vortex core region distribution, and turbulent kinetic energy(TKE) transfer. Visualization was also carried out to track the tinctorial evolution of the liquid phase. Results reveal that elliptical stirred tanks can significantly improve mixing performance in USTs. Specifically, the mixing time at an aspect ratio of 2.00 is only 45.3% of the one of a circular stirred tank. Furthermore, the secondary flow is strengthened and the vortex core region increases with the increase of aspect ratio. The axial velocity is more sensitive to the aspect ratio than the circumferential and radial velocity. Additionally, the TKE transfer in elliptical vessels is altered. These findings suggest that elliptical vessels offer a promising alternative to circular vessels for enhancing mixing performance in USTs.

iFlow彩色血流编码成像技术在下肢动脉硬化闭塞症诊断中的应用价值

目的研究iFlow彩色血流编码成像技术在下肢动脉硬化闭塞症(LEASO)诊断中的应用价值。方法选择2022年3月至2023年10月期间确诊的106例LEASO患者作为本研究的LEASO组,以一般资料与LEASO组匹配且无动脉病变的80例志愿者作为对照组。两组受试者均进行数字减影血管造影(DSA)并采用iFlow彩色血流编码成像技术检测股骨头区域和踝关节区域达峰时间(TTP)、计算踝关节区域与股骨头区域TTP的差值,测量踝肱指数(ABI)。结果两组研究对象年龄、性别、体质量指数、吸烟史、高血压病史、糖尿病史、冠心病史、股骨头区域TTP的比较,差异无统计学意义(P>0.05);LEASO组踝关节区域TTP及TTP差值均高于对照组,差异有统计学意义(P<0.05);LEASO组中不同Rutherford分类患者股骨头区域TTP的比较以及左侧病变患者与右侧病变患者股骨头区域TTP、踝关节区域TTP、TTP差值的比较,差异无统计学意义(P>0.05),Rutherford分类越高,踝关节区域TTP及TTP差值越低(P<0.05);经Pearson检验,LEASO患者的踝关节区域TTP、TTP差值与ABI呈负相关(P<0.05);经受试者工作特征(ROC)曲线分析,踝关节区域TTP、TTP差值对LEASO具有诊断效能;经Delong检验,TTP差值诊断的ROC曲线下面积高于踝关节区域TTP(P<0.05)。结论iFlow彩色血流编码成像技术测定踝关节区TTP及TTP差值是诊断LEASO的量化指标。

Dynamic train dwell time forecasting:a hybrid approach to address the influence of passenger flow fluctuations

Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between trains.Accurate estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity estimation.In the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train dispatching.The averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data distributions.Then,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway line.The results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and variances.Further,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,respectively.Based on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell time.However,planned time has positive influences,whereas arrival delay has negative influences.

Experiments on two-phase flow in hydraulic jump on pebbled rough bed:Part 1–Turbulence properties and particle chord time and length

This study reported and discussed turbulence characteristics,such as turbulence intensity,correlation time scales,and advective length scales.The characteristic air–water time scale,including the particle chord time and length and their probability density functions(PDFs),was investigated.The results demonstrated that turbulence intensity was relatively greater on a rough bed in the roller length,whereas further downstream,the decay rate was higher.In addition,the relationship between turbulence intensity and dimensionless bubble count rate reflected an increase in turbulence intensity associated with the number of entrained particles.Triple decomposition analysis(TDA)was performed to determine the contributions of slow and fast turbulent components.The TDA results indicated that,regardless of bed type and inflow conditions,the sum of the band-pass(T'_(u))and high-pass(T″_(u))filtered turbulence intensities was equal to the turbulence intensity of the raw signal data(T_(u)).T″_(u) highlighted a higher turbulence intensity and larger vorticities on the rough bed for an identical inflow Froude number.Additional TDA results were presented in terms of the interfacial velocity,auto-and cross-correlation time scales,and longitudinal advection length scale,with the effects of low-and high-frequency signal components on each highlighted parameter.The analysis of the air chord time indicated an increase in the proportion of small bubbles moving downstream.The second part of this research focused on the basic properties of particle grouping and clustering.

A Numerical Study on the Effect of the Backflow Hole Position on the Performances of a Self-Priming Pump

A self-priming pump is a centrifugal pump that has the ability to prime itself. Typically, its performance dependson the configuration of its reflux hole. In this study, the ANSYS FLUENT software is used to investigate the effectsof three different radial positions of the reflux hole on gas-liquid two-phase distribution, pressure pulsation, andimp during self-priming. The research results indicate that: (1) The effective channel size for the reflux liquid toenter the volute varies depending on the location of the reflux hole. The effect of the impeller rotation on thereflux liquid becomes more obvious as the setting distance of the reflux aperture decreases. (2) The position ofthe reflux hole significantly affects the gas phase mass fraction inside the impeller, resulting in a significant reductionin the time it takes for the mass fraction to exceed 80%. (3) The position of the reflux hole significantly affectsthe average pressure on each monitoring surface. (4) Placing the reflux hole at a excessively distant radial distancecan result in an excessive vertical component. (5) The self-priming performance of the pump can be improved tosome extent by placing the return hole at a small radial distance.

Residence time distribution of high viscosity fluids falling film flow down outside of industrial-scale vertical wavy wall: Experimental investigation and CFD prediction

The flow behavior of gravity-driven falling film of non-conductive high viscosity polymer fluids on an industrial-scale vertical wavy wall was investigated in terms of film thickness and residence time distribution by numerical simulation and experiment.Falling film flow of high viscosity fluids was found to be steady on a vertical wavy wall in the presence of the large film thickness.The comparison between numerical simulation and experiment for the film thickness both in crest and trough of wavy wall showed good agreement.The simulation results of average residence time of falling film flow with different viscous fluids were also consistent with the experimental results.This work provides the initial insights of how to evaluate and optimize the falling film flow system of polymer fluid.

Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine(SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam.Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.

Is Minimizing Flow Completion Time the Optimal Way in Meeting Flow's Deadline in Datacenter Networks

In modern datacenters, the most common method to solve the network latency problem is to minimize flow completion time during the transmission process. Following the soft real-time nature, the optimization of transport latency is relaxed to meet a flow's deadline in deadline-sensitive services. However, none of existing deadline-sensitive protocols consider deadline as a constraint condition of transmission.They can only simplify the objective of meeting a flow's deadline as a deadline-aware mechanism by assigning a higher priority for tight-deadline constrained flows to finish the transmission as soon as possible, which results in an unsatisfactory effect in the condition of high fan-in degree. It drives us to take a step back and rethink whether minimizing flow completion time is the optimal way in meeting flow's deadline. In this paper, we focus on the design of a soft real-time transport protocol with deadline constraint in datacenters and present a flow-based deadline scheduling scheme for datacenter networks(FBDS).FBDS makes the unilateral deadline-aware flow transmission with priority transform into a compound centralized single-machine deadlinebased flow scheduling decision. In addition, FBDS blocks the flow sets and postpones some flows with extra time until their deadlines to make room for the new arriving flows in order to improve the deadline meeting rate. Our simulation resultson flow completion time and deadline meeting rate reveal the potential of FBDS in terms of a considerable deadline-sensitive transport protocol for deadline-sensitive interactive services.

Bifurcation and stability of an improved time-delayed fluid flow model in internet congestion control

Based on the fluid flow time-delayed model proposed by Misra et al in internet congestion control, one modified time-delayed model is presented, where the influence of the communication delay on the router queue length is investigated in detail. The main advantage of the new model is that its stability domain is larger even without an extra controller. By linear stability analysis and numerical simulation, tbe effectiveness and feasibility of the novel model in internet congestion control are verified.

A Discrete Artificial Bee Colony Algorithm for Minimizing the Total Flow Time in the Blocking Flow Shop Scheduling

A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.

Impact of time lags on diurnal estimates of canopy transpiration and canopy conductance from sap-flow measurements of Populus cathayana in the Qinghai–Tibetan Plateau

Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.

Transit time ultrasound perivascular flow probe technology is superior to MR imaging on hepatic blood flow measurement in a porcine model

Background: The hepatic hemodynamics is an essential parameter in surgical planning as well as in various disease processes. The transit time ultrasound(TTUS) perivascular flow probe technology is widely used in clinical practice to evaluate the hepatic inflow, yet invasive. The phase-contrast-MRI(PC-MRI) is not invasive and potentially applicable in assessing the hepatic blood flow. In the present study, we compared the hepatic inflow rates using the PC-MRI and the TTUS probe, and evaluated their predictive value of post-hepatectomy adverse events. Methods: Eighteen large white pigs were anaesthetized for PC-MRI and approximately 75% hepatic resection was performed under a unified protocol. The blood flow was measured in the hepatic artery(Qha), the portal vein(Qpv), and the aorta above the celiac trunk(Qca) using PC-MRI, and was compared to the TTUS probe. The Bland-Altman method was conducted and a partial least squares regression(PLS) model was implemented. Results: The mean Qpv measured in PC-MRI was 0.55 ± 0.12 L/min, and in the TTUS probe was 0.74 ± 0.17 L/min. Qca was 1.40 ± 0.47 L/min in the PC-MRI and 2.00 ± 0.60 L/min in the TTUS probe. Qha was 0.17 ± 0.10 L/min in the PC-MRI, and 0.13 ± 0.06 L/min in the TTUS probe. The Bland-Altman method revealed that the estimated bias of Qca in the PC-MRI was 32%(95% CI:-49% to 15%); Qha 17%(95% CI:-15% to 51%); and Qpv 40%(95% CI:-62% to 18%). The TTUS probe had a higher weight in predicting adverse outcomes after 75% resection compared to the PC-MRI( β= 0.35 and 0.43 vs β = 0.22 and 0.07, for tissue changes and premature death, respectively). Conclusions: There is a tendency of the PC-MRI to underestimate the flow measured by the TTUS probes. The TTUS probe measures are more predictive of relevant post-hepatectomy outcomes.

Modeling on Residence Time Distribution in Subsurface Flow Constructed Wetlands by Multi Flow Dispersion Model

As an important design factor for constructed wetlands,hydraulic retention time and its distribution will affect the treatment performance.Instantaneously injected sodium chloride tracers were used to obtain residence time distributions of the lab scale subsurface flow constructed wetland.Considering the presence of trailing and multiple peaks of the tracer breakthrough curve,the multi flow dispersion model(MFDM)was used to fit the experimental tracer breakthrough curves.According to the residual sum of squares and comparison between the experimental values and simulated values of the tracer concentration,MFDM could fit the residence time distribution(RTD)curve satisfactorily,the results of which also reflected the layered structure of wetland cells,thus to give reference for application of MFDM to the same kind of subsurface flow constructed wetlands.

Application of time–frequency entropy from wake oscillation to gas–liquid flow pattern identification

Gas–liquid two-phase flow abounds in industrial processes and facilities. Identification of its flow pattern plays an essential role in the field of multiphase flow measurement. A bluff body was introduced in this study to recognize gas–liquid flow patterns by inducing fluid oscillation that enlarged differences between each flow pattern. Experiments with air–water mixtures were carried out in horizontal pipelines at ambient temperature and atmospheric pressure. Differential pressure signals from the bluff-body wake were obtained in bubble, bubble/plug transitional, plug, slug, and annular flows. Utilizing the adaptive ensemble empirical mode decomposition method and the Hilbert transform, the time–frequency entropy S of the differential pressure signals was obtained. By combining S and other flow parameters, such as the volumetric void fraction β, the dryness x, the ratio of density φ and the modified fluid coefficient ψ, a new flow pattern map was constructed which adopted S（1–x）φ and （1–β）ψ as the vertical and horizontal coordinates, respectively. The overall rate of classification of the map was verified to be 92.9% by the experimental data. It provides an effective and simple solution to the gas–liquid flow pattern identification problems.

Multi-relaxation time lattice Boltzmann simulation of inertial secondary flow in a curved microchannel

The inertial secondary flow is particularly important tbr hydrodynamic lbcusing and particle manipulation m biomed- ical research. In this paper, the development of the inertial secondary flow structure in a curved microchannel was investi- gated by the multi relaxation time lattice Boltzmann equation model with a force term. The numerical results indicate that the viscous and inertial competition dominates the development of secondary flow structure development. The Reynolds number, Dean number, and the cross section aspect ratio influence significantly on the development of the secondary vor- texes. Both the intensity of secondary flow and the distance between the normalized vortex centers are functions of Dean numbers but independent of channel curvature radius. In addition, the competition mechanism between the viscous and inertial effects were discussed by performing the particle focusing experiments. The present investigation provides an improved understanding of the development of inertial secondary flows in curved microchannels.

Flow zone distribution and mixing time in a Peirce-Smith copper converter

Peirce-Smith copper converting involves complex multiphase flow and mixing.In this work,the flow zone distribution and mixing time in a Peirce-Smith copper converter were investigated in a 1:5 scaled cold model.Flow field distribution,including dead,splashing,and strong-loop zones,were measured,and a dimensionless equation was established to determine the correlation of the effects of stirring and mixing energy with an error of<5%.Four positions in the bath,namely,injection,splashing,strong-loop,and dead zones,were selected to add a hollow salt powder tracer and measure the mixing time.Injecting a quartz flux through tuyeres or into the backflow point of the splashing wave through a chute was recommended instead of adding it through a crane hopper from the top of the furnace to improve the slag-making reaction.

Exploring the Evolution of Passenger Flow and Travel Time Reliability with the Expanding Process of Metro System Using Smartcard Data

Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for analysis.Results showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.

Markov transition probability-based network from time series for characterizing experimental two-phase flow

We generate a directed weighted complex network by a method based on Markov transition probability to represent an experimental two-phase flow. We first systematically carry out gas-liquid two-phase flow experiments for measuring the time series of flow signals. Then we construct directed weighted complex networks from various time series in terms of a network generation method based on Markov transition probability. We find that the generated network inherits the main features of the time series in the network structure. In particular, the networks from time series with different dynamics exhibit distinct topological properties. Finally, we construct two-phase flow directed weighted networks from experimental signals and associate the dynamic behavior of gas-liquid two-phase flow with the topological statistics of the generated networks. The results suggest that the topological statistics of two-phase flow networks allow quantitative characterization of the dynamic flow behavior in the transitions among different gas-liquid flow patterns.

Quantitative Assessment of Coronary Flow Reserve by the Variables of Time-Intensity Curve with Myocardial Contrast Echocardiography

The reliability and reliable indexes of q ua ntitative assessment of coronary flow reserve (CFR) by using time intensity cur ve (TIC) via myocardial contrast echocardiography were investigated. The TIC var iables were obtained by employing acoustic densitometry (AD) technique before an d after acetylcholine (Ach) injection in 12 dogs. Meanwhile, the correlation be tween these variables and CFR was analyzed. Among the variables derived from TIC , peak intensity (PI), area under the curve (AUC) and descending slope (DS) were increased significantly ( P <0.05) with the increase of coronary blood flow a fter Ach injection. Conversely, time to peak (TP), half time of descent (HT) , and mean transit time (MTT) were decreased remarkably ( P <0.0001). Th e P I and AUC ratios from post to pre Ach injection were strongly associated with CFR with the correlation coefficient (r) being 0.8366 and 0.8824, respectively. It is reliable by using the variables derived from TIC with myocardial contrast echocardiography to quantitatively evaluate regional myocardial CFR. The PI an d AUC ratios from post to pre Ach injection are the reliable indexes for quan titative assessment of CFR.

Evolving a Bayesian network model with information flow for time series interpolation of multiple ocean variables

Based on Bayesian network (BN) and information flow (IF),a new machine learning-based model named IFBN is put forward to interpolate missing time series of multiple ocean variables. An improved BN structural learning algorithm with IF is designed to mine causal relationships among ocean variables to build network structure. Nondirectional inference mechanism of BN is applied to achieve the synchronous interpolation of multiple missing time series. With the IFBN,all ocean variables are placed in a causal network visually,making full use of information about related variables to fill missing data. More importantly,the synchronous interpolation of multiple variables can avoid model retraining when interpolative objects change. Interpolation experiments show that IFBN has even better interpolation accuracy,effectiveness and stability than existing methods.