一种获得交叉口分流系数的新方法—极大熵估计法

本文提出了一种根据交叉口的出入口流量来估计交叉口的分流系数的新方法.它是根据信息论的基本原理,在极大熵的意义下,将一个描述不完全问题转化为一个非线性规划问题,从而求出一个最接近真实分流系数的估计值.     

On the steady solution of non-linear advection equations in steady recirculating flows

Many physical problems like short fiber suspensions flows or viscoelastic flows are modeled by linear and non-linear advection equations. Many of the experimental and industrial flows show often steady recirculating areas which introduce some additional difficulties in the numerical simulation. Actually, the advection equation is supposed to have a steady solution in these steady recirculating flows but neither boundary conditions nor initial conditions are known in such flows. In this paper, we present accurate techniques to solve non-linear advection equations defined in steady recirculating flows. These techniques combine a standard treatment of the non-linearity with a more original treatment of the associated linear problems.     

Flow map layout via spiral trees

Flow maps are thematic maps that visualize the movement of objects, such as people or goods, between geographic regions. One or more sources are connected to several targets by lines whose thickness corresponds to the amount of flow between a source and a target. Good flow maps reduce visual clutter by merging (bundling) lines smoothly and by avoiding self-intersections. Most flow maps are still drawn by hand and only few automated methods exist. Some of the known algorithms do not support edge-bundling and those that do, cannot guarantee crossing-free flows. We present a new algorithmic method that uses edge-bundling and computes crossing-free flows of high visual quality. Our method is based on so-called spiral trees, a novel type of Steiner tree which uses logarithmic spirals. Spiral trees naturally induce a clustering on the targets and smoothly bundle lines. Our flows can also avoid obstacles, such as map features, region outlines, or even the targets. We demonstrate our approach with extensive experiments.     

Decomposition of group flows in regular matroids

In a regular matroidM=(E,C) we discuss two different approaches to group matroid flows. By showing that these two approaches are equivalent we set up a decomposition theory for group matroid flows and derive two algorithms for decomposing group matroid flows. The second one finds so-called positive decomposition, a fact which is highly important in applications. By specializing the results to graphic and co-graphic matroids we generalize some well known results of real-valued network flow theory to group network flows and derive some new results for tensions.     

Circulation analysis and lift placing in hospitals

A method for measuring the efficiency of circulation of traffic within buildings has been developed, applicable to buildings for which the traffic flows are known. A method has also been developed for placing lift banks or escalators so as to maintain an efficient circulation in buildings covering a large ground area.     

Control of swarm behavior in crossing pedestrians based on temporal/spatial frequencies

In the densely-populated urban areas, pedestrian flows often cross each other and congestion is caused. The congestion makes us feel uncomfortable and sometimes leads to pedestrian accidents. To reduce the congestion or the risk of accidents, it is required to control the swarm behavior of pedestrian flows. This paper proposes modeling and controlling method of the crossing pedestrian flows. In the social/urban engineering, it is well known that the swarm behavior with a diagonal stripe pattern emerges in the crossing area of the flows. This is a self-organized phenomenon caused by the local collision avoidance effect of the pedestrians. To control the macroscopic behavior of the flows, we utilize this self-organized phenomenon. Firstly, we propose the continuum model of the crossing pedestrian flows. In the continuum model, the dynamic change of the congestion in the diagonal stripe pattern is simulated as the density. Secondly, the novel control method to improve average flow velocity is proposed based on the model. The proposed method utilizes the dynamic interaction between the diagonal stripe pattern and guides, who are moving in the flows. The authors derive the control algorithm through an analysis on the temporal and spatial frequencies of the crossing flows. The validity is verified with simulations using the continuum model. Moreover, we apply the proposed method to the particle model, assuming the actual pedestrians.     

A power laws-based reconstruction approach to end-to-end network traffic

To obtain accurately end-to-end network traffic is a significantly difficult and challenging problem for network operators, although it is one of the most important input parameters for network traffic engineering. With the development of current network, the characteristics of networks have changed a lot. In this paper, we exploit the characteristics of origin-destination flows and thus grasp the properties of end-to-end network traffic. An important and amazing find of our work is that the sizes of origin-destination flows obey the power laws. Taking advantage of this characteristic, we propose a novel approach to select partial origin-destination flows which are to be measured directly. In terms of the known traffic information, we reconstruct all origin-destination flows via compressive sensing method. In detail, here, we combine the power laws and the constraints of compressive sensing (namely restricted isometry property) together to build measurement matrix and pick up the partial origin-destination flows. Furthermore, we build a reconstruction model from the known information corresponding to compressive sensing reconstruction algorithms. Finally, we reconstruct all origin-destination flows from the observed results by solving the reconstruction model. And we provide numerical simulation results to validate the performance of our method using real backbone network traffic data. It illustrates that our method can recover the end-to-end network traffic more accurately than previous methods.     

Performances of upwind methods in predicting shear-like flows

Upwind methods are considered as the most appropriate numerical tools for predicting high speed flows. However, disturbing problems may arise in dealing with shear-like flows such as boundary layers. Here, the fluid dynamics is dominated by the diffusion processes and the convective terms, which are estimated through an upwind method, have to play a secondary and almost negligible role. Unfortunately, the presence of density and velocity gradients inside boundary layers introduces, in some upwind method, purely numerical effects. In some methods, the boundary layer region may grow, unphysically, beyond the correct thickness because of a spurious dissipation generated by an incorrect evaluation of the convective terms. In other methods, pressure oscillations may appear inside the boundary layer. Such situations, well known in the scientific community, can be properly analyzed by developing a linearized form of the first order scheme for the Euler conservation laws in a particular problem, with the evaluation of the fluxes made as dictated by the formulation of each upwind method. This analysis provides suggestions and hints useful to understand and predict the behavior of an upwind method in simulating shear-like flows.     

The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.     

Enforcing Minimum-Cost Multicast Routing against Selfish Information Flows

We study multicast in a noncooperative environment where information flows selfishly route themselves through the cheapest paths available. The main challenge is to enforce such selfish multicast flows to stabilize at a socially optimal operating point incurring minimum total edge cost, through appropriate cost allocation and other economic measures, with replicable and encodable properties of information flows considered. We show that known cost allocation schemes are not sufficient. We provide a shadow-price-based cost allocation for networks without capacity limits and show that it enforces minimum-cost multicast. This improves previous result where a 2-approximate multicast flow is enforced. For capacitated networks, computing cost allocation by ignoring edge capacities will not yield correct results. We show that an edge tax scheme can be combined with a cost allocation to strictly enforce optimal multicast flows in this more realistic case. If taxes are not desirable, they can be returned to flows while maintaining weak enforcement of the optimal flow. We relate the taxes to VCG payment schemes and discuss an efficient primal-dual algorithm that simultaneously computes the taxes, the cost allocation, and the optimal multicast flow, with potential of fully distributed implementations.     

Finite Element Computation of KPP Front Speeds in Cellular and Cat’s Eye Flows

We compute the front speeds of the Kolmogorov-Petrovsky-Piskunov (KPP) reactive fronts in two prototypes of periodic incompressible flows (the cellular flows and the cat’s eye flows). The computation is based on adaptive streamline diffusion methods for the advection-diffusion type principal eigenvalue problem associated with the KPP front speeds. In the large amplitude regime, internal layers form in eigenfunctions. Besides recovering known speed growth law for the cellular flow, we found larger growth rates of front speeds in cat’s eye flows due to the presence of open channels, and the front speed slowdown due to either zero Neumann boundary condition at domain boundaries or frequency increase of cat’s eye flows.     

Non-Darcy flow in disordered porous media: A lattice Boltzmann study

It is well known that the Darcy law is insufficient for describing high-rate flows in porous media. However, it is still an open problem to establish a universal form for the nonlinear correction to Darcy law. In this work, we will investigate numerically the non-Darcy effect on incompressible flows through disordered porous media. Numerical simulations at pore-scale level are carried out with the Reynolds number varying from 0.02 to 30, which covers the Darcy and non-Darcy flow regimes. Three regimes are identified for flow through porous media, i.e., a linear Darcy regime at vanishing Reynolds number, a cubic transitional or weak inertial regime at low but finite Reynolds number, and a quadratic Forchheimer or strong inertial regime at larger Reynolds numbers. Finally, a general correlation is proposed to include the non-Darcy effect, as an extension to the common empirical expressions.     

Error control and mesh optimization for high-order finite element approximation of incompressible viscous flow

We discuss the use of a posteriori error estimates for high-order finite element methods during simulation of the flow of incompressible viscous fluids. The correlation between the error estimator and actual error is used as a criterion for the error analysis efficiency. We show how to use the error estimator for mesh optimization which improves computational efficiency for both steady-state and unsteady flows. The method is applied to two-dimensional problems with known analytical solutions (Jeffrey-Hamel flow) and more complex flows around a body, both in a channel and in an open domain.     

Mesoscale simulations of particulate flows with parallel distributed Lagrange multiplier technique

Fluid particulate flows are common phenomena in nature and industry. Modeling of such flows at micro and macro levels as well establishing relationships between these approaches are needed to understand properties of the particulate matter. We propose a computational technique based on the direct numerical simulation of the particulate flows. The numerical method is based on the distributed Lagrange multiplier technique following the ideas of Glowinski et al. [16] and Patankar [30]. Each particle is explicitly resolved on an Eulerian grid as a separate domain, using solid volume fractions. The fluid equations are solved through the entire computational domain, however, Lagrange multiplier constrains are applied inside the particle domain such that the fluid within any volume associated with a solid particle moves as an incompressible rigid body. Mutual forces for the fluid-particle interactions are internal to the system. Particles interact with the fluid via fluid dynamic equations, resulting in implicit fluid-rigid body coupling relations that produce realistic fluid flow around the particles (i.e., no-slip boundary conditions). The particle-particle interactions are implemented using explicit force-displacement interactions for frictional inelastic particles similar to the DEM method of Cundall et al. [10] with some modifications using a volume of an overlapping region as an input to the contact forces. The method is flexible enough to handle arbitrary particle shapes and size distributions. A parallel implementation of the method is based on the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library, which allows handling of large amounts of rigid particles and enables local grid refinement. Accuracy and convergence of the presented method has been tested against known solutions for a falling particle as well as by examining fluid flows through stationary particle beds (periodic and cubic packing). To evaluate code performance and validate particle contact physics algorithm, we performed simulations of a representative experiment conducted at the U.C. Berkeley Thermal Hydraulic Lab for pebble flow through a narrow opening.     

A new convolution algorithm for loss probability analysis in multiservice networks

Performance analysis in multiservice loss systems generally focuses on accurate and efficient calculation methods for traffic loss probability. Convolution algorithm is one of the existing efficient numerical methods. Exact loss probabilities are obtainable from the convolution algorithm in systems where the bandwidth is fully shared by all traffic classes; but not available for systems with trunk reservation, i.e. part of the bandwidth is reserved for a special class of traffic. A proposal known as asymmetric convolution algorithm (ACA) has been made to overcome the deficiency of the convolution algorithm. It obtains an approximation of the channel occupancy distribution in multiservice systems with trunk reservation. However, the ACA approximation is only accurate with two traffic flows; increased approximation errors are observed for systems with three or more traffic flows.In this paper, we present a new Permutational Convolution Algorithm (PCA) for loss probability approximation in multiservice systems with trunk reservation. This method extends the application of the convolution algorithm and overcomes the problems of approximation accuracy in systems with a large number of traffic flows. It is verified that the loss probabilities obtained by PCA are very close to the exact solutions obtained by Markov chain models, and the accuracy outperforms the ACA approximation.     

Task assignment with work-conserving migration

In this paper we a present a task assignment policy suited to environments (such as high-volume web serving clusters) where local centralised dispatchers are utilised to distribute tasks amongst back-end hosts offering mirrored services, with negligible cost work-conserving migration available between hosts. The TAPTF-WC (Task Assignment based on Prioritising Traffic Flows with Work-Conserving Migration) policy was specifically created to exploit such environments. As such, TAPTF-WC exhibits consistently good performance over a wide range of task distribution scenarios due to its flexible nature, spreading the work over multiple hosts when prudent, and separating short task flows from large task flows via the use of dual queues. Tasks are migrated in a work-conserving manner, reducing the penalty associated with task migration found in many existing policies such as TAGS and TAPTF which restart tasks upon migration. We find that the TAPTF-WC policy is well suited for load distribution under a wide range of different workloads in environments where task sizes are not known a priori and negligible cost work-conserving migration is available.     

Three-dimensional numerical simulations of viscoelastic flows – predictability and accuracy

In this paper, fully three-dimensional (3-D) numerical simulations of viscoelastic flows using an implicit finite volume method are discussed with the focus on the predictability and accuracy of the method. The viscoelastic flow problems involving the stress singularity, including plane stick–slip flow, the flow past a junction in a channel, and the 3-D edge flow, are used to test the ability of the method to predict the singularity features with accuracy. The accuracy of the numerical predictions is judged by comparing with the known asymptotic behaviour for Newtonian fluids and some viscoelastic fluids, and the investigations are extended to the viscoelastic cases with unknown singular behaviour. The Phan-Thien–Tanner (PTT) model, and in some cases, the upper-convected Maxwell (UCM) model, are used to describe viscoelastic fluids. The numerical results with mesh refinement show that the accuracy is quite satisfactory, especially for Newtonian flows. For viscoelastic flows, the asymptotic results for the flow around a re-entrant corner for the UCM as well as the PTT fluid are reproduced numerically. In the stick–slip flow, a Newtonian-like asymptotic behaviour is predicted for the UCM fluid. In edge flow, it is verified numerically that the kinematics are Newtonian for viscoelastic fluids described by models with a constant viscosity and a zero second normal stress difference. For viscoelastic fluids described by the models with a shear-thinning viscosity and zero second normal stress difference, the fluid behaves like a power-law fluid, and the difference from its Newtonian kinematics is localized in the region near the singularity, and to capture the asymptotic behaviour, a parameter-dependent mesh has to be used. With the 3-D simulations, it is confirmed that in edge flow, the flow around the edge could not be rectilinear, and some secondary flows on the plane normal to the primary flow direction are expected for viscoelastic fluids described by the models with a shear-dependent second normal stress difference, such as the full PTT model. The strength of the secondary flows will depend on the level of the departure of the second normal stress difference from a fixed constant multiple of viscosity of the fluid.     

Hybrid imperialist competitive algorithm,variable neighborhood search,and simulated annealing for dynamic facility layout problem

Today’s manufacturing plants tend to be more flexible due to rapid changes in product mix and market demand. Therefore, this paper investigates the problem of location and relocation (when there are changes incurred to the material flows between departments) manufacturing facilities such that the total cost of material flows and relocation costs are minimized. This problem is known as the dynamic facility layout problem (DFLP), which is a general case of static facility layout problem. This paper proposes a robust and simply structured hybrid technique based on integrating three meta-heuristics: imperialist competitive algorithms, variable neighborhood search, and simulated annealing, to efficiently solve the DFLP. The novel aspect of the proposed algorithm is taking advantage of features of all above three algorithms together. To test the efficiency of our algorithm, a data set from the literature is used for the experimental purpose. The results obtained are quite promising in terms of solution quality for most of the test problems.     

Solution properties and approximate Riemann solvers for two-layer shallow flow models

The 4 × 4 system of governing equations for two-layer shallow flow models is known to exhibit particular behaviours such as loss of hyperbolicity under certain flow configurations. An eigenvalue analysis of the conservation part of the equations shows that the loss of hyperbolicity is due only to the reaction exerted by each fluid onto the other at the interface between the fluids. Three Riemann solvers derived from the HLL formalism are presented. In the first solver, the pressure-induced terms are accounted for by the source term; in the second solver, they are incorporated into the fluxes; the third solver uses the same formulation as the first, except that the mass and momentum balance for the bottom layer are replaced with the balance equations for the system formed by the two layers as a whole. Numerical results using the three solvers are presented for (1) static conditions such as two fluids of identical densities at rest above each other, (2) dam-break flows involving the collapse of a body of light fluid over a uniform layer of a denser fluid, and (3) Liska and Wendroff’s ill-posed test cases [24] involving two-layer flows over a topographic bump. The three solvers produce quasi-undistinguishable results for the dam-break flows, and produce sharp solutions over the full range of density ratio, from 0 to 1. However, only the third solver allows a strict preservation of static configurations. Moreover, a method is proposed to assess the convergence of the numerical solutions in the configurations for which no analytical solution can be obtained.