Flow Evolution Model Research Articles

Generating periodic vortex pairs using flexible structures

In fluid dynamics, a planar starting flow through a narrow slit gives rise to a distinctive fluid mass in the form of counter-rotating vortex pairs, which do not undergo any propulsive detachment, known as ‘pinch-off’, from the tip-attached fluid layer. Our study envisions instigating the ‘pinch-off’ phenomenon in these vortex pairs using flexible plates as the slit edges to enhance momentum transport and self-propagation. In this study, considering a flow evolution model, we show that the growth rate of such ejected vortex pair scales as proportional to the square root of time. Using flexible plates to form the slit, we unearth a critical plate flexibility case with the Cauchy number, Ca=0.01, which induces a ‘pinch-off’ of the resultant vortex pair, a phenomenon absent in the case of rigid plates. We observe a train of vortex pairs generating one after the other, and the time period closely matches the plates’ oscillation period as the plates’ oscillation frequency locks-in with the shedding frequency of the vortex pairs. The streamwise speed of the leading vortex pair varies non-monotonically with Ca, showing an increase in the speed up to Ca≈0.04, and thereafter decreased speed due to upstream propagation of small-sized vortices. The new insights into inducing and controlling vortex pair behaviours pave the way for innovative applications in fluid transport and advanced flow manipulation techniques.

The role of information dissemination in sustaining a stable and Resilient Traffic Network under disruption

ABSTRACT A functioning roadway system is key to any society and economy. Traffic events such as maintenance and accidents reduce roadway capacity and can have immediate, large and lasting impact on traffic conditions. This paper investigates the role of information dissemination as a control tool for reducing the negative effects of a traffic event. It examines how timely information can prevent unnecessary route changes and counteract misinformation, restoring traffic equilibrium faster. Systems that recover equilibrium more rapidly are considered more resilient. A traffic flow evolution model is applied to analyze network behavior post-disruption, with a model parameter interpreted as an information dissemination penetration rate adjustable by operators. Numerical experiments investigate the effects of the penetration rate on travel times, revealing a critical rate for quickly re-establishing a new equilibrium. Beyond this rate, greater traffic oscillations can be expected. The study determines the best information penetration rate to maximize network resilience while ensuring stability.

Modeling the process of slag formation in paste propulsion

The results of modeling the accumulation of slag residue in the combustion chamber of a propulsion system on pasty propellant obtained using a multiphase flow evolution model are presented. The influence of composition solutions on the process of slag formation is established; the significance of this process for the quality of such engines is shown. The nature of the influence of the parameters of the burning process for propellants of the type under consideration on the intensity of slag formation is determined. It is shown that the degree of involvement of metallic fuel in the agglomeration process has the greatest influence on slag formation. It has been established that the most effective "tool" for suppressing slag formation in the combustion chambers of paste propulsion is to change the regularities of the burning process, mainly associated with the formation of condensed products at the surface of the burning propellant.

Direct modeling for computational fluid dynamics and the construction of high-order compact scheme for compressible flow simulations

Computational fluid dynamics is a direct modeling of physical laws in a discretized space. The basic physical laws include the mass, momentum and energy conservations, numerical scale-consistent transport process, and similar domain of dependence and influence in the physical and the numerical wave propagations. Therefore, a physically soundable numerical scheme should be a compact one which involves the closest neighboring cells within the domain of dependence for the solution update under a CFL number (∼1). In order to keep the compactness of the scheme and be high-order, subcell flow distributions or the equivalent degrees of freedom beyond the cell averaged flow variables are needed, such as the gradients of the flow variables inside each control volume. Under the above consideration, the direct use of Riemann solver as the evolution model doesn't provide such a mechanism. High-order dynamic evolution process should be used to update the time accurate cell-averaged flow variables and their gradients. The direct modeling of flow evolution under generalized initial condition will be developed. In order to provide reliable cell averaged flow variables and their gradients for the compact data reconstruction, the evolution process is constructed to provide possible discontinuous time-dependent flow variables across a cell interface. At the same time, the time accurate flux function at a cell interface can become a discontinuous function of time in its evolution process. Same as the spatial limiter in the conventional computational fluid dynamics methods, such as the total variation diminishing and weighted essentially non-oscillatory methods, the temporal limiter for the time accurate flux function is designed as well. The direct modeling method in this paper will update flow variables differently on both sides of a cell interface and nonlinearly limit the high-order time derivatives of the flux function in case of shock wave passing through a cell interface within a time step. The direct modeling method unifies the concepts of nonlinear limiters in spatial data reconstruction and temporal flux transport. The equivalent treatment of space and time makes the compact gas-kinetic scheme be super robust and accurate for the compressible flow simulation. At the same time, the 4th to 8th-order compact schemes can use a large CFL number (∼0.8) in flow computation, even for the hypersonic flow simulation.

Temporal and Spatial Evolution of Passenger Flow in an Urban Rail Transit Network During Station Closure

In this study, we focused on the evolution of passenger flow in an urban rail transit network in both temporal and spatial dimensions under the event of station closure. We constructed an extended space-time-state hyper network so that we could utilize a better-defined three-dimensional solution space to describe passenger behaviors and pedestrian characters. The space-time-state network was extended by adding dummy arcs and setting the “block space-time domain” based on the original spatiotemporal network. Based on the extended space-time-state hyper network, a passenger flow evolution model that aimed to minimize the usage cost during station closure was established considering the strict capacity constraints (including corridor passing capacity, platform load capacity and train transport capacity). For a large-scale urban rail network, we developed a decomposition solution framework in which the Lagrangian relaxation and semi-assignment algorithms were adopted. A real-world instance was implemented based on the Beijing subway network with complete smart card data for each passenger for his/her origin and destination, while the specific space-time trajectories of all passengers and time-dependent passenger volumes in trains and transfer corridors were estimated. The results of a numerical experiment suggest that the proposed passenger flow evolution method can provide a rich set of passenger volume inferences for advanced transit planning and management applications, such as passenger flow control, passenger flow guidance, and real- time train scheduling.

Hydrochemical characteristics and functions of groundwater in southern Laizhou Bay based on the multivariate statistical analysis approach

Influenced by paleoclimate, paleogeography and hydrogeology, groundwater with different total dissolved solids (TDS) levels, such as freshwater, brackish water, saline water and brine, widely occurs across southern Laizhou Bay (SLB) . Due to groundwater overexploitation, several groundwater depression cones have gradually formed since the 1970s, resulting in saline water intrusion. In this study, the multivariate statistical analysis (MSA) approach was adopted to identify the hydrochemical characteristics of shallow groundwater (SG) and deep groundwater (DG) in the SLB. Moreover, we applied Gibbs diagrams, hydrochemical facies evolution diagrams (HFE-Diagram) and ion proportion relations to analyze the factors influencing the hydrochemical characteristics. The results showed that hydrochemical zonation of the various water types (ranging from Ca-HCO3 to Na-Cl) from south to north was mainly controlled by migration and mixing of saline water with regional groundwater. Based on the MSA results and hydrochemical characteristics, SG functional areas were divided into the groundwater flow zone, intense groundwater mixing zone and groundwater-seawater interaction zone, and DG functional areas were divided into the groundwater flow zone, groundwater mixing zone and underground brine storage zone. Finally, SG and DG groundwater flow evolution models were developed . The comprehensive method proposed in this study combines the MSA approach with regional geological characteristics and provides a reference for the evaluation of complex multiaquifer systems and analysis of the groundwater evolution characteristics in other regions.

A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

Based on the price-quantity adjustment behaviour principle of disequilibrium theory, the route choices of travellers are also affected by a quantity signal known as traffic flow, while the route cost is considered as a price signal in economics. Considering the quantity signal’s effect among travellers, a new route comfort choice behaviour criterion and its corresponding equilibrium condition are established. The network travellers are classified into three groups according to their route choice behaviour: travellers in the first group choose the shortest route following the route rapidity behaviour criterion with complete information forming the UE (user equilibrium) pattern, travellers in the second group choose the most comfortable route following the route comfort behaviour criterion with complete information forming the QUE (quantity adjustment user equilibrium) pattern, and travellers in the third group choose a route according to their perceived travel time with incomplete information forming the SUE (stochastic user equilibrium) pattern. The traffic flows of all three groups converge to a new UE-QUE-SUE mixed equilibrium flow pattern after interaction. To depict the traveller-diversified choice behaviour and the traffic flow interaction process, a mixed equilibrium traffic flow evolution model is formulated. After defining the route comfort indicator and the corresponding user equilibrium state, the equilibrium conditions of the three group flows are given under a mixed equilibrium pattern. In addition, an equivalent mathematical programming of the mixed equilibrium traffic flow evolution model is proposed to demonstrate that the developed model converges to the mixed equilibrium state. Finally, numerical examples are examined to evaluate the effect of route comfort proportions on the traffic network flow evolution and analyse the performance of the proposed model.

A novel framework for automated monitoring and analysis of high density pedestrian flow

Pedestrian traffic is an important subject of surveillance to ensure public safety and traffic management, which may benefit from intelligent and continuous analysis of pedestrian videos. State-of-the-art methods for intelligent pedestrian surveillance have a number of limitations in automating and deriving useful information of high-density pedestrian traffic (HDPT) using closed circuit television (CCTV) images. This work introduces an automatic and improved HDPT surveillance system by integrating and optimizing multiple computational steps to predict pedestrian distribution from input video frames. A fast and efficient particle image velocimetry (PIV) technique is proposed to yield pedestrian velocities. A machine learning regressor model, boosted Ferns, is used to improve pedestrian count and density estimation: an essential metric for HDPT analysis. A camera perspective model is proposed to improve the speed and position estimates of HDPT by projecting 2D image pixels to 3D world-coordinate dat. All these functional improvements in HDPT velocity and displacement estimations are used as inputs to a sophisticated pedestrian flow evolution model, PEDFLOW to predict HDPT distribution at a future time point, which is a crucial information for pedestrian traffic management. The predicted and simulated HDPT properties (density, velocity) obtained using the proposed framework show low errors when compared to the ground truth data. The proposed framework is computationally efficient, suitable for multiple camera feeds with HDPT videos, and capable of rapidly analyzing and predicting flows of thousands of pedestrians. The paper shows one of the first steps towards fully integrated CCTV-based automated HDPT management system.

Network Traffic Flow Evolution Model Based on Disequilibrium Theory

The disequilibrium theory in economics is used to depict the network traffic flow evolution process from disequilibrium to equilibrium. Three path choice behavior criteria are proposed, and the equilibrium traffic flow patterns formed by these three criteria are defined as price regulation user equilibrium, quantity regulation user equilibrium, and price-quantity regulation user equilibrium, respectively. Based on the principle of price-quantity regulation user equilibrium, the method of network tatonnement process is used to establish a network traffic flow evolution model. The unique solution of the evolution model is proved by using Picard’s existence and uniqueness theorem, and the stability condition of the unique solution is derived based on stability theorem of nonlinear system. Through numerical experiments, the evolution processes of network traffic flow under different regulation modes are analyzed. The results show that all the single price regulation, single quantity regulation, and price-quantity regulation can simulate the evolution process of network traffic flow. Price-quantity regulation is the combination of price regulation user equilibrium and quantity regulation user equilibrium, which thus can simulate the evolution process of network traffic flow with multiple user class.

Numerical modeling of flow evolution for an internal solitary wave propagating over a submerged ridge

Numerical simulations are performed to investigate the flow evolution of a depression ISW propagating over a submerged ridge. A finite volume based Cartesian grid method is adopted to solve the Reynolds averaged Navier–Stokes equations using a k−ε model for the turbulent closure. Results reveal a significant transient clockwise vortex and an internal hydraulic jump emerging on the front slope of the obstacle, during the wave–obstacle interaction. This interaction generates an asymmetrical interface and pycnocline thickness on both sides of the obstacle. During this process, the amplitude and velocity of the leading waveform increase transiently, but both quickly decrease once the wave passes the obstacle. As the ridge slope decreases, the wave–ridge interaction weakens, as well as the strength of vorticity and turbulent kinetic energy. In addition, the wave may affect the nutrient transport on the front slope to a maximum depth about 50% height of the obstacle or about 1.78 times of the incident wave amplitude when a large ISW breaks on the slope.

Cluster-based reduced-order modelling of a mixing layer

AbstractWe propose a novel cluster-based reduced-order modelling (CROM) strategy for unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger’s group (Burkardt, Gunzburger & Lee,Comput. Meth. Appl. Mech. Engng, vol. 196, 2006a, pp. 337–355) and transition matrix models introduced in fluid dynamics in Eckhardt’s group (Schneider, Eckhardt & Vollmer,Phys. Rev. E, vol. 75, 2007, art. 066313). CROM constitutes a potential alternative to POD models and generalises the Ulam–Galerkin method classically used in dynamical systems to determine a finite-rank approximation of the Perron–Frobenius operator. The proposed strategy processes a time-resolved sequence of flow snapshots in two steps. First, the snapshot data are clustered into a small number of representative states, called centroids, in the state space. These centroids partition the state space in complementary non-overlapping regions (centroidal Voronoi cells). Departing from the standard algorithm, the probabilities of the clusters are determined, and the states are sorted by analysis of the transition matrix. Second, the transitions between the states are dynamically modelled using a Markov process. Physical mechanisms are then distilled by a refined analysis of the Markov process, e.g. using finite-time Lyapunov exponent (FTLE) and entropic methods. This CROM framework is applied to the Lorenz attractor (as illustrative example), to velocity fields of the spatially evolving incompressible mixing layer and the three-dimensional turbulent wake of a bluff body. For these examples, CROM is shown to identify non-trivial quasi-attractors and transition processes in an unsupervised manner. CROM has numerous potential applications for the systematic identification of physical mechanisms of complex dynamics, for comparison of flow evolution models, for the identification of precursors to desirable and undesirable events, and for flow control applications exploiting nonlinear actuation dynamics.

Network Traffic Flow Evolution Model Considering OD Demand Mutation

Abstract Considering such a fact that the traffic demand freshly entering a network does not have perfect information about traffic condition and then might choose travel routes randomly, we propose an improved network traffic flow evolution model in this article. The model's properties and fixed points are investigated. The fixed points of the model, which are different from traditional user equilibrium state or part user equilibrium state, can better formulate the result of traffic flow assignment in realization. Simulation results obtained from a grid network show that the model can be used to approximately model the process of realizing user equilibrium state, the network flow can indeed evolve to one or more fixed points, and the initial values of all available path flows can be zero.

Chaos and bifurcation in dynamical evolution process of traffic assignment with flow “mutation”

Considering such a fact that the traffic demands freshly entering a network do not have perfect information about traffic condition and may then choose routes randomly, in this paper, we present an improved network traffic flow evolution model. The model’s properties and fixed points are investigated. Numerical results obtained from a grid network show that the system can converge to one or more fixed points without requiring of positive route flows at initial time, and can be used to approximately simulate the process of realizing user equilibrium state. It is found that oscillations and such apparently irregular behaviors as chaos occur when the model parameter representing intensity of adjusting route flow and OD demand exceeds some values. Bifurcation diagrams of some route flows and OD demands with respect to this model parameter are presented.

Analysis of Turbulent Mixing Jets in a Large Scale Tank

Flow evolution models were developed to evaluate the performance of the new advanced design mixer pump for sludge mixing and removal operations with high-velocity liquid jets in one of the large-scale Savannah River Site waste tanks, Tank 18. This paper describes the computational model, the flow measurements used to provide validation data in the region far from the jet nozzle, and the extension of the computational results to real tank conditions through the use of existing sludge suspension data. A computational fluid dynamics approach was used to simulate the sludge removal operations. The models employed a three-dimensional representation of the tank with a two-equation turbulence model. Both the computational approach and the models were validated with onsite test data reported here and literature data. The model was then extended to actual conditions in Tank 18 through a velocity criterion to predict the ability of the new pump design to suspend settled sludge. A qualitative comparison with sludge removal operations in Tank 18 showed a reasonably good comparison with final results subject to significant uncertainties in actual sludge properties.

QUALITATIVE ANAYSIS OF THE BDSPN MODEL THROUGH ITS ASSOCIATED DISCRETE PETRI NET

The BDSPN model is a class of Petri nets introduced for the modelling, analysis and performance evaluation of discrete event systems with batch behaviours. It is particularly suitable for the modelling of flow evolution in batches of variable sizes in a system with activities performed in batch modes. In this paper, the analysis of the BDSPN model through its associated discrete Petri net is studied. It is shown that although a BDSPN and its associated discrete Petri net behave differently, there are several common qualitative properties between the two models.

Day-to-day vehicular flow dynamics in intelligent transportation network

In this paper, a flow evolution model is developed by using the dynamical system approach for a vehicular network equipped with predicted travel information. The concerned system variables, path flow, and predicted minimal travel time of an origin-destination (OD) pair, are measured on the peak-hour-average base for each day. The time change rates of these two variables are formulated as a system of ordinary differential equations under the assumption of daily learning and adaptive processes for commuters. By incorporating the total perceived travel time loss (or saving) into the proposed models, time change rates of path flows are generated with a flow-related manner to prevent path flow dynamics from being insensible to traffic congestion which had been formulated in the existing studies. Heterogeneous models with various user adjusting sensitivities and predicted travel information are also presented. Equilibrium solutions of the proposed network dynamics satisfy the Wardrop user equilibria and are proved to be asymptotically stable by using the stability theorem of Lyapunov. The issue of existence and uniqueness of solutions is proved both on the lemma of Lipschitz condition and the fundamental theorem of ordinary differential equations. In addition, some simple examples are demonstrated to show the asymptotic behaviors of the proposed models numerically.

Numerical simulation of the thermal maturation, oil generation and migration in the Songliao Basin, Northeastern China

The discovery of the giant Daqing oil field in the Songliao Basin led to the realisation of the significant petroleum potential of non-marine basins. In order to reconstruct the basin evolution and oil formation, an integrated organic geochemical-basin modelling study along a regional transect across the Songliao Basin was conducted. It provided a regional heat flow evolution model, and revealed post-orogenic or late syn-orogenic maturation in the Central Depression and pre-orogenic maturation in the Southeast Uplift Zone. Kinetic parameters of petroleum generation for the lacustrine source formations are the basis for the simulation of oil generation and migration in the Songliao Basin. Using the principle activation energy peaking at 54 kcal/mol and a pre-exponential factor of about 4.2·10 27 Ma −1, the simulation obtained a relatively good match with the measured transformation ratios. The Qingshankou Formation in the West and East Central Depressions constituted the major source in the basin. Major oil generation, migration and accumulation occurred during the Early Tertiary. In the West Central Depression, the generated oils migrated upwards into the Yaojia Formation followed by the updip migration into the Daqing Anticline and towards the local structural high along the West Slope. In contrast, the oil migration in the East Central Depression was dominated by the downward movement from the lower member of the Qingshankou Formation followed by the updip migration towards the Caoyang Anticline. The simulated oil accumulations are in good agreement with discovered oil fields, implying a potential application of the model for prediction and evaluation of new exploration targets in the basin.