Solving Minimum Cost Multi-Commodity Network Flow Problem ...
African Journals Online (AJOL)
ADOWIE PERE
2018-03-23
Mar 23, 2018 ... network-based modeling framework for integrated fixed and mobile ... Minimum Cost Network Flow Problem (MCNFP) and some ..... Unmanned Aerial Vehicle Routing in Traffic. Incident ... Ph.D. Thesis, Dept. of Surveying &.
2012-09-13
46, 1989. [75] S. Melkote and M.S. Daskin . An integrated model of facility location and transportation network design. Transportation Research Part A ... a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT/DS/ENS/12-09 THE AVERAGE NETWORK FLOW PROBLEM...focused thinking (VFT) are used sparingly, as is the case across the entirety of the supply chain literature. We provide a VFT tutorial for supply chain
A polynomial time algorithm for solving the maximum flow problem in directed networks
International Nuclear Information System (INIS)
Tlas, M.
2015-01-01
An efficient polynomial time algorithm for solving maximum flow problems has been proposed in this paper. The algorithm is basically based on the binary representation of capacities; it solves the maximum flow problem as a sequence of O(m) shortest path problems on residual networks with nodes and m arcs. It runs in O(m"2r) time, where is the smallest integer greater than or equal to log B , and B is the largest arc capacity of the network. A numerical example has been illustrated using this proposed algorithm.(author)
A service flow model for the liner shipping network design problem
DEFF Research Database (Denmark)
Plum, Christian Edinger Munk; Pisinger, David; Sigurd, Mikkel M.
2014-01-01
. The formulation alleviates issues faced by arc flow formulations with regards to handling multiple calls to the same port. A problem which has not been fully dealt with earlier by LSNDP formulations. Multiple calls are handled by introducing service nodes, together with port nodes in a graph representation...... of the network and a penalty for not flowed cargo. The model can be used to design liner shipping networks to utilize a container carrier’s assets efficiently and to investigate possible scenarios of changed market conditions. The model is solved as a Mixed Integer Program. Results are presented for the two...
DEFF Research Database (Denmark)
Karsten, Christian Vad; Pisinger, David; Røpke, Stefan
2015-01-01
-commodity network flow problem with transit time constraints which puts limits on the duration of the transit of the commodities through the network. It is shown that for the particular application it does not increase the solution time to include the transit time constraints and that including the transit time...... is essential to offer customers a competitive product. © 2015 Elsevier Ltd. All rights reserved....
A dual exterior point simplex type algorithm for the minimum cost network flow problem
Directory of Open Access Journals (Sweden)
Geranis George
2009-01-01
Full Text Available A new dual simplex type algorithm for the Minimum Cost Network Flow Problem (MCNFP is presented. The proposed algorithm belongs to a special 'exterior- point simplex type' category. Similarly to the classical network dual simplex algorithm (NDSA, this algorithm starts with a dual feasible tree-solution and reduces the primal infeasibility, iteration by iteration. However, contrary to the NDSA, the new algorithm does not always maintain a dual feasible solution. Instead, the new algorithm might reach a basic point (tree-solution outside the dual feasible area (exterior point - dual infeasible tree.
A new cut-based algorithm for the multi-state flow network reliability problem
International Nuclear Information System (INIS)
Yeh, Wei-Chang; Bae, Changseok; Huang, Chia-Ling
2015-01-01
Many real-world systems can be modeled as multi-state network systems in which reliability can be derived in terms of the lower bound points of level d, called d-minimal cuts (d-MCs). This study proposes a new method to find and verify obtained d-MCs with simple and useful found properties for the multi-state flow network reliability problem. The proposed algorithm runs in O(mσp) time, which represents a significant improvement over the previous O(mp 2 σ) time bound based on max-flow/min-cut, where p, σ and m denote the number of MCs, d-MC candidates and edges, respectively. The proposed algorithm also conquers the weakness of some existing methods, which failed to remove duplicate d-MCs in special cases. A step-by-step example is given to demonstrate how the proposed algorithm locates and verifies all d-MC candidates. As evidence of the utility of the proposed approach, we present extensive computational results on 20 benchmark networks in another example. The computational results compare favorably with a previously developed algorithm in the literature. - Highlights: • A new method is proposed to find all d-MCs for the multi-state flow networks. • The proposed method can prevent the generation of d-MC duplicates. • The proposed method is simpler and more efficient than the best-known algorithms
Sample problem calculations related to two-phase flow transients in a PWR relief-piping network
International Nuclear Information System (INIS)
Shin, Y.W.; Wiedermann, A.H.
1981-03-01
Two sample problems related with the fast transients of water/steam flow in the relief line of a PWR pressurizer were calculated with a network-flow analysis computer code STAC (System Transient-Flow Analysis Code). The sample problems were supplied by EPRI and are designed to test computer codes or computational methods to determine whether they have the basic capability to handle the important flow features present in a typical relief line of a PWR pressurizer. It was found necessary to implement into the STAC code a number of additional boundary conditions in order to calculate the sample problems. This includes the dynamics of the fluid interface that is treated as a moving boundary. This report describes the methodologies adopted for handling the newly implemented boundary conditions and the computational results of the two sample problems. In order to demonstrate the accuracies achieved in the STAC code results, analytical solutions are also obtained and used as a basis for comparison
Directory of Open Access Journals (Sweden)
Enrique Castillo
2015-01-01
Full Text Available A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.
Directory of Open Access Journals (Sweden)
Suprayogi Suprayogi
2016-12-01
Full Text Available This paper considers a location problem in a supply chain network. The problem addressed in this paper is motivated by an initiative to develop an efficient supply chain network for supporting the agricultural activities. The supply chain network consists of regions, warehouses, distribution centers, plants, and markets. The products include a set of inbound products and a set of outbound products. In this paper, definitions of the inbound and outbound products are seen from the region’s point of view. The inbound product is the product demanded by regions and produced by plants which flows on a sequence of the following entities: plants, distribution centers, warehouses, and regions. The outbound product is the product demanded by markets and produced by regions and it flows on a sequence of the following entities: regions, warehouses, and markets. The problem deals with determining locations of the warehouses and the distribution centers to be opened and shipment quantities associated with all links on the network that minimizes the total cost. The problem can be considered as a strategic supply chain network problem. A solution approach based on genetic algorithm (GA is proposed. The proposed GA is examined using hypothetical instances and its results are compared to the solution obtained by solving the mixed integer linear programming (MILP model. The comparison shows that there is a small gap (0.23%, on average between the proposed GA and MILP model in terms of the total cost. The proposed GA consistently provides solutions with least total cost. In terms of total cost, based on the experiment, it is demonstrated that coefficients of variation are closed to 0.
Robinson, Julie A.; Tate-Brown, Judy M.
2009-01-01
Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.
Bagchi, Prosenjit
2016-11-01
In this talk, two problems in multiphase biological flows will be discussed. The first is the direct numerical simulation of whole blood and drug particulates in microvascular networks. Blood in microcirculation behaves as a dense suspension of heterogeneous cells. The erythrocytes are extremely deformable, while inactivated platelets and leukocytes are nearly rigid. A significant progress has been made in recent years in modeling blood as a dense cellular suspension. However, many of these studies considered the blood flow in simple geometry, e.g., straight tubes of uniform cross-section. In contrast, the architecture of a microvascular network is very complex with bifurcating, merging and winding vessels, posing a further challenge to numerical modeling. We have developed an immersed-boundary-based method that can consider blood cell flow in physiologically realistic and complex microvascular network. In addition to addressing many physiological issues related to network hemodynamics, this tool can be used to optimize the transport properties of drug particulates for effective organ-specific delivery. Our second problem is pseudopod-driven motility as often observed in metastatic cancer cells and other amoeboid cells. We have developed a multiscale hydrodynamic model to simulate such motility. We study the effect of cell stiffness on motility as the former has been considered as a biomarker for metastatic potential. Funded by the National Science Foundation.
Linear Programming and Network Flows
Bazaraa, Mokhtar S; Sherali, Hanif D
2011-01-01
The authoritative guide to modeling and solving complex problems with linear programming-extensively revised, expanded, and updated The only book to treat both linear programming techniques and network flows under one cover, Linear Programming and Network Flows, Fourth Edition has been completely updated with the latest developments on the topic. This new edition continues to successfully emphasize modeling concepts, the design and analysis of algorithms, and implementation strategies for problems in a variety of fields, including industrial engineering, management science, operations research
International Nuclear Information System (INIS)
Brasch, D.J.
1986-01-01
Chemical and mineral engineering students require texts which give guidance to problem solving to complement their main theoretical texts. This book has a broad coverage of the fluid flow problems which these students may encounter. The fundamental concepts and the application of the behaviour of liquids and gases in unit operation are dealt with. The book is intended to give numerical practice; development of theory is undertaken only when elaboration of treatments available in theoretical texts is absolutely necessary
Directory of Open Access Journals (Sweden)
Jiuping Xu
2012-01-01
Full Text Available The aim of this study is to deal with a minimum cost network flow problem (MCNFP in a large-scale construction project using a nonlinear multiobjective bilevel model with birandom variables. The main target of the upper level is to minimize both direct and transportation time costs. The target of the lower level is to minimize transportation costs. After an analysis of the birandom variables, an expectation multiobjective bilevel programming model with chance constraints is formulated to incorporate decision makers’ preferences. To solve the identified special conditions, an equivalent crisp model is proposed with an additional multiobjective bilevel particle swarm optimization (MOBLPSO developed to solve the model. The Shuibuya Hydropower Project is used as a real-world example to verify the proposed approach. Results and analysis are presented to highlight the performances of the MOBLPSO, which is very effective and efficient compared to a genetic algorithm and a simulated annealing algorithm.
Airport Network Flow Simulator
1978-10-01
The Airport Network Flow Simulator is a FORTRAN IV simulation of the flow of air traffic in the nation's 600 commercial airports. It calculates for any group of selected airports: (a) the landing and take-off (Type A) delays; and (b) the gate departu...
Hardness and Approximation for Network Flow Interdiction
Chestnut, Stephen R.; Zenklusen, Rico
2015-01-01
In the Network Flow Interdiction problem an adversary attacks a network in order to minimize the maximum s-t-flow. Very little is known about the approximatibility of this problem despite decades of interest in it. We present the first approximation hardness, showing that Network Flow Interdiction and several of its variants cannot be much easier to approximate than Densest k-Subgraph. In particular, any $n^{o(1)}$-approximation algorithm for Network Flow Interdiction would imply an $n^{o(1)}...
Computer program for compressible flow network analysis
Wilton, M. E.; Murtaugh, J. P.
1973-01-01
Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.
Generalized network improvement and packing problems
Holzhauser, Michael
2016-01-01
Michael Holzhauser discusses generalizations of well-known network flow and packing problems by additional or modified side constraints. By exploiting the inherent connection between the two problem classes, the author investigates the complexity and approximability of several novel network flow and packing problems and presents combinatorial solution and approximation algorithms. Contents Fractional Packing and Parametric Search Frameworks Budget-Constrained Minimum Cost Flows: The Continuous Case Budget-Constrained Minimum Cost Flows: The Discrete Case Generalized Processing Networks Convex Generalized Flows Target Groups Researchers and students in the fields of mathematics, computer science, and economics Practitioners in operations research and logistics The Author Dr. Michael Holzhauser studied computer science at the University of Kaiserslautern and is now a research fellow in the Optimization Research Group at the Department of Mathematics of the University of Kaiserslautern.
Flows in networks under fuzzy conditions
Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich
2017-01-01
This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...
Physics of flow in weighted complex networks
Wu, Zhenhua
This thesis uses concepts from statistical physics to understand the physics of flow in weighted complex networks. The traditional model for random networks is the Erdoḧs-Renyi (ER.) network, where a network of N nodes is created by connecting each of the N(N - 1)/2 pairs of nodes with a probability p. The degree distribution, which is the probability distribution of the number of links per node, is a Poisson distribution. Recent studies of the topology in many networks such as the Internet and the world-wide airport network (WAN) reveal a power law degree distribution, known as a scale-free (SF) distribution. To yield a better description of network dynamics, we study weighted networks, where each link or node is given a number. One asks how the weights affect the static and the dynamic properties of the network. In this thesis, two important dynamic problems are studied: the current flow problem, described by Kirchhoff's laws, and the maximum flow problem, which maximizes the flow between two nodes. Percolation theory is applied to these studies of the dynamics in complex networks. We find that the current flow in disordered media belongs to the same universality class as the optimal path. In a randomly weighted network, we identify the infinite incipient percolation cluster as the "superhighway", which contains most of the traffic in a network. We propose an efficient strategy to improve significantly the global transport by improving the superhighways, which comprise a small fraction of the network. We also propose a network model with correlated weights to describe weighted networks such as the WAN. Our model agrees with WAN data, and provides insight into the advantages of correlated weights in networks. Lastly, the upper critical dimension is evaluated using two different numerical methods, and the result is consistent with the theoretical prediction.
Topology optimization of flow problems
DEFF Research Database (Denmark)
Gersborg, Allan Roulund
2007-01-01
This thesis investigates how to apply topology optimization using the material distribution technique to steady-state viscous incompressible flow problems. The target design applications are fluid devices that are optimized with respect to minimizing the energy loss, characteristic properties...... transport in 2D Stokes flow. Using Stokes flow limits the range of applications; nonetheless, the thesis gives a proof-of-concept for the application of the method within fluid dynamic problems and it remains of interest for the design of microfluidic devices. Furthermore, the thesis contributes...... at the Technical University of Denmark. Large topology optimization problems with 2D and 3D Stokes flow modeling are solved with direct and iterative strategies employing the parallelized Sun Performance Library and the OpenMP parallelization technique, respectively....
vhv supply networks, problems of network structure
Energy Technology Data Exchange (ETDEWEB)
Raimbault, J
1966-04-01
The present and future power requirements of the Paris area and the structure of the existing networks are discussed. The various limitations that will have to be allowed for to lay down the structure of a regional transmission network leading in the power of the large national transmission network to within the Paris built up area are described. The theoretical solution that has been adopted, and the features of its final achievement, which is planned for about the year 2000, and the intermediate stages are given. The problem of the structure of the National Power Transmission network which is to supply the regional network was studied. To solve this problem, a 730 kV voltage network will have to be introduced.
Flow whitelisting in SCADA networks
DEFF Research Database (Denmark)
Barbosa, Rafael Ramos Regis; Sadre, Ramin; Pras, Aiko
2013-01-01
and the Internet. This paper describes an approach for improving the security of SCADA networks using flow whitelisting. A flow whitelist describes legitimate traffic based on four properties of network packets: client address, server address, server-side port and transport protocol. The proposed approach...
Networks in social policy problems
Scotti, marco
2012-01-01
Network science is the key to managing social communities, designing the structure of efficient organizations and planning for sustainable development. This book applies network science to contemporary social policy problems. In the first part, tools of diffusion and team design are deployed to challenges in adoption of ideas and the management of creativity. Ideas, unlike information, are generated and adopted in networks of personal ties. Chapters in the second part tackle problems of power and malfeasance in political and business organizations, where mechanisms in accessing and controlling informal networks often outweigh formal processes. The third part uses ideas from biology and physics to understand global economic and financial crises, ecological depletion and challenges to energy security. Ideal for researchers and policy makers involved in social network analysis, business strategy and economic policy, it deals with issues ranging from what makes public advisories effective to how networks influenc...
Filtering Undesirable Flows in Networks
Polevoy, G.; Trajanovski, S.; Grosso, P.; de Laat, C.; Gao, X.; Du, H.; Han, M.
2017-01-01
We study the problem of fully mitigating the effects of denial of service by filtering the minimum necessary set of the undesirable flows. First, we model this problem and then we concentrate on a subproblem where every good flow has a bottleneck. We prove that unless P=NP, this subproblem is
Dynamic Flow Management Problems in Air Transportation
Patterson, Sarah Stock
1997-01-01
In 1995, over six hundred thousand licensed pilots flew nearly thirty-five million flights into over eighteen thousand U.S. airports, logging more than 519 billion passenger miles. Since demand for air travel has increased by more than 50% in the last decade while capacity has stagnated, congestion is a problem of undeniable practical significance. In this thesis, we will develop optimization techniques that reduce the impact of congestion on the national airspace. We start by determining the optimal release times for flights into the airspace and the optimal speed adjustment while airborne taking into account the capacitated airspace. This is called the Air Traffic Flow Management Problem (TFMP). We address the complexity, showing that it is NP-hard. We build an integer programming formulation that is quite strong as some of the proposed inequalities are facet defining for the convex hull of solutions. For practical problems, the solutions of the LP relaxation of the TFMP are very often integral. In essence, we reduce the problem to efficiently solving large scale linear programming problems. Thus, the computation times are reasonably small for large scale, practical problems involving thousands of flights. Next, we address the problem of determining how to reroute aircraft in the airspace system when faced with dynamically changing weather conditions. This is called the Air Traffic Flow Management Rerouting Problem (TFMRP) We present an integrated mathematical programming approach for the TFMRP, which utilizes several methodologies, in order to minimize delay costs. In order to address the high dimensionality, we present an aggregate model, in which we formulate the TFMRP as a multicommodity, integer, dynamic network flow problem with certain side constraints. Using Lagrangian relaxation, we generate aggregate flows that are decomposed into a collection of flight paths using a randomized rounding heuristic. This collection of paths is used in a packing integer
A matheuristic for the liner shipping network design problem
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Desaulniers, Guy
2012-01-01
for revenue and transshipment of cargo along with in/decrease of vessel- and operational cost for the current solution. The evaluation functions may be used by heuristics in general to evaluate changes to a network design without solving a large scale multicommodity flow problem.......We present a matheuristic, an integer programming based heuristic, for the Liner Shipping Network Design Problem. The heuristic applies a greedy construction heuristic based on an interpretation of the liner shipping network design problem as a multiple quadratic knapsack problem. The construction...
Finding Elephant Flows for Optical Networks
Fioreze, Tiago; Oude Wolbers, Mattijs; van de Meent, R.; Pras, Aiko
2007-01-01
Optical networks are fast and reliable networks that enable, amongst others, dedicated light paths to be established for elephant IP flows. Elephant IP flows are characterized by being small in number, but long in time and high in traffic volume. Moving these flows from the general IP network to
Solving the minimum flow problem with interval bounds and flows
Indian Academy of Sciences (India)
... with crisp data. In this paper, the idea of Ghiyasvand was extended for solving the minimum ﬂow problem with interval-valued lower, upper bounds and ﬂows. This problem can be solved using two minimum ﬂow problems with crisp data. Then, this result is extended to networks with fuzzy lower, upper bounds and ﬂows.
Topology optimization of Channel flow problems
DEFF Research Database (Denmark)
Gersborg-Hansen, Allan; Sigmund, Ole; Haber, R. B.
2005-01-01
function which measures either some local aspect of the velocity field or a global quantity, such as the rate of energy dissipation. We use the finite element method to model the flow, and we solve the optimization problem with a gradient-based math-programming algorithm that is driven by analytical......This paper describes a topology design method for simple two-dimensional flow problems. We consider steady, incompressible laminar viscous flows at low to moderate Reynolds numbers. This makes the flow problem non-linear and hence a non-trivial extension of the work of [Borrvall&Petersson 2002......]. Further, the inclusion of inertia effects significantly alters the physics, enabling solutions of new classes of optimization problems, such as velocity--driven switches, that are not addressed by the earlier method. Specifically, we determine optimal layouts of channel flows that extremize a cost...
Stochastic cycle selection in active flow networks
Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn
2016-11-01
Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.
Power laws and fragility in flow networks.
Shore, Jesse; Chu, Catherine J; Bianchi, Matt T
2013-01-01
What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence.
Inverse feasibility problems of the inverse maximum flow problems
Indian Academy of Sciences (India)
199–209. c Indian Academy of Sciences. Inverse feasibility problems of the inverse maximum flow problems. ADRIAN DEACONU. ∗ and ELEONOR CIUREA. Department of Mathematics and Computer Science, Faculty of Mathematics and Informatics, Transilvania University of Brasov, Brasov, Iuliu Maniu st. 50,. Romania.
Solving Hub Network Problem Using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Mursyid Hasan Basri
2012-01-01
Full Text Available This paper addresses a network problem that described as follows. There are n ports that interact, and p of those will be designated as hubs. All hubs are fully interconnected. Each spoke will be allocated to only one of available hubs. Direct connection between two spokes is allowed only if they are allocated to the same hub. The latter is a distinct characteristic that differs it from pure hub-and-spoke system. In case of pure hub-and-spoke system, direct connection between two spokes is not allowed. The problem is where to locate hub ports and to which hub a spoke should be allocated so that total transportation cost is minimum. In the first model, there are some additional aspects are taken into consideration in order to achieve a better representation of the problem. The first, weekly service should be accomplished. Secondly, various vessel types should be considered. The last, a concept of inter-hub discount factor is introduced. Regarding the last aspect, it represents cost reduction factor at hub ports due to economies of scale. In practice, it is common that the cost rate for inter-hub movement is less than the cost rate for movement between hub and origin/destination. In this first model, inter-hub discount factor is assumed independent with amount of flows on inter-hub links (denoted as flow-independent discount policy. The results indicated that the patterns of enlargement of container ship size, to some degree, are similar with those in Kurokawa study. However, with regard to hub locations, the results have not represented the real practice. In the proposed model, unsatisfactory result on hub locations is addressed. One aspect that could possibly be improved to find better hub locations is inter-hub discount factor. Then inter-hub discount factor is assumed to depend on amount of inter-hub flows (denoted as flow-dependent discount policy. There are two discount functions examined in this paper. Both functions are characterized by
Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias
2013-04-24
Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.
Advances in multiphase flow and related problems
International Nuclear Information System (INIS)
Papanicolaou, G.
1986-01-01
Proceedings of a workshop in multiphase flow held at Leesburg, Va. in June 1986 representing a cross-disciplinary approach to theoretical as well as computational problems in multiphase flow. Topics include composites, phase transitions, fluid-particle systems, and bubbly liquids
Generalized Riemann problem for reactive flows
International Nuclear Information System (INIS)
Ben-Artzi, M.
1989-01-01
A generalized Riemann problem is introduced for the equations of reactive non-viscous compressible flow in one space dimension. Initial data are assumed to be linearly distributed on both sides of a jump discontinuity. The resolution of the singularity is studied and the first-order variation (in time) of flow variables is given in exact form. copyright 1989 Academic Press, Inc
Directory of Open Access Journals (Sweden)
J. Trdlicka
2010-12-01
Full Text Available This work proposes a distributed algorithm for energy optimal routing in a wireless sensor network. The routing problem is described as a mathematical problem by the minimum-cost multi-commodity network flow problem. Due to the separability of the problem, we use the duality theorem to derive the distributed algorithm. The algorithm computes the energy optimal routing in the network without any central node or knowledge of the whole network structure. Each node only needs to know the flow which is supposed to send or receive and the costs and capacities of the neighboring links. An evaluation of the presented algorithm on benchmarks for the energy optimal data flow routing in sensor networks with up to 100 nodes is presented.
Networks in Social Policy Problems
Vedres, Balázs; Scotti, Marco
2012-08-01
1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.
Supply network configuration—A benchmarking problem
Brandenburg, Marcus
2018-03-01
Managing supply networks is a highly relevant task that strongly influences the competitiveness of firms from various industries. Designing supply networks is a strategic process that considerably affects the structure of the whole network. In contrast, supply networks for new products are configured without major adaptations of the existing structure, but the network has to be configured before the new product is actually launched in the marketplace. Due to dynamics and uncertainties, the resulting planning problem is highly complex. However, formal models and solution approaches that support supply network configuration decisions for new products are scant. The paper at hand aims at stimulating related model-based research. To formulate mathematical models and solution procedures, a benchmarking problem is introduced which is derived from a case study of a cosmetics manufacturer. Tasks, objectives, and constraints of the problem are described in great detail and numerical values and ranges of all problem parameters are given. In addition, several directions for future research are suggested.
Energy Technology Data Exchange (ETDEWEB)
Duran, Ana Cecilia
1990-03-01
This thesis aims to find a better way to solve large scale nonlinear sparse system problems giving special emphasis to load flow in electric power networks. The suggested algorithms are presented 63 refs., 28 figs., 16 tabs.
Integrated network design and scheduling problems :
Energy Technology Data Exchange (ETDEWEB)
Nurre, Sarah G.; Carlson, Jeffrey J.
2014-01-01
We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.
Current-flow efficiency of networks
Liu, Kai; Yan, Xiaoyong
2018-02-01
Many real-world networks, from infrastructure networks to social and communication networks, can be formulated as flow networks. How to realistically measure the transport efficiency of these networks is of fundamental importance. The shortest-path-based efficiency measurement has limitations, as it assumes that flow travels only along those shortest paths. Here, we propose a new metric named current-flow efficiency, in which we calculate the average reciprocal effective resistance between all pairs of nodes in the network. This metric takes the multipath effect into consideration and is more suitable for measuring the efficiency of many real-world flow equilibrium networks. Moreover, this metric can handle a disconnected graph and can thus be used to identify critical nodes and edges from the efficiency-loss perspective. We further analyze how the topological structure affects the current-flow efficiency of networks based on some model and real-world networks. Our results enable a better understanding of flow networks and shed light on the design and improvement of such networks with higher transport efficiency.
Flow whitelisting in SCADA networks
Barbosa, Rafael Ramos Regis; Sadre, Ramin; Pras, Aiko
2013-01-01
Supervisory control and data acquisition (SCADA) networks are commonly deployed in large industrial facilities. Modern SCADA networks are becoming more vulnerable to cyber attacks due to the common use of standard communications protocols and increased interconnections with corporate networks and
Predicting Information Flows in Network Traffic.
Hinich, Melvin J.; Molyneux, Robert E.
2003-01-01
Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)
A Formal Model and Verification Problems for Software Defined Networks
Directory of Open Access Journals (Sweden)
V. A. Zakharov
2013-01-01
Full Text Available Software-defined networking (SDN is an approach to building computer networks that separate and abstract data planes and control planes of these systems. In a SDN a centralized controller manages a distributed set of switches. A set of open commands for packet forwarding and flow-table updating was defined in the form of a protocol known as OpenFlow. In this paper we describe an abstract formal model of SDN, introduce a tentative language for specification of SDN forwarding policies, and set up formally model-checking problems for SDN.
Network structure of subway passenger flows
Xu, Q.; Mao, B. H.; Bai, Y.
2016-03-01
The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.
Flow whitelisting in SCADA networks
Barbosa, Rafael Ramos Regis; Pras, Aiko; Sadre, Ramin
Supervisory Control And Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities. Modern SCADA networks are becoming more vulnerable to network attacks, due to the now common use of standard communication protocols and increased interconnection to
Flow Whitelisting in SCADA Networks
Barbosa, R.R.R.; Pras, Aiko; Sadre, R.
2013-01-01
Supervisory Control And Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities. Modern SCADA networks are becoming more vulnerable to network attacks, due to the now common use of standard communication protocols and increased interconnection to
Organization of signal flow in directed networks
International Nuclear Information System (INIS)
Bányai, M; Bazsó, F; Négyessy, L
2011-01-01
Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps
EVENT, Explosive Transients in Flow Networks
International Nuclear Information System (INIS)
Andrae, R.W.; Tang, P.K.; Bolstad, J.W.; Gregory, W.S.
1985-01-01
1 - Description of problem or function: A major concern of the chemical, nuclear, and mining industries is the occurrence of an explosion in one part of a facility and subsequent transmission of explosive effects through the ventilation system. An explosive event can cause performance degradation of the ventilation system or even structural failures. A more serious consequence is the release of hazardous materials to the environment if vital protective devices such as air filters, are damaged. EVENT was developed to investigate the effects of explosive transients through fluid-flow networks. Using the principles of fluid mechanics and thermodynamics, governing equations for the conservation of mass, energy, and momentum are formulated. These equations are applied to the complete network subdivided into two general components: nodes and branches. The nodes represent boundaries and internal junctions where the conservation of mass and energy applies. The branches can be ducts, valves, blowers, or filters. Since in EVENT the effect of the explosion, not the characteristics of the explosion itself, is of interest, the transient is simulated in the simplest possible way. A rapid addition of mass and energy to the system at certain locations is used. This representation is adequate for all of the network except the region where the explosion actually occurs. EVENT84 is a modification of EVENT which includes a new explosion chamber model subroutine based on the NOL BLAST program developed at the Naval Ordnance Laboratory, Silver Spring, Maryland. This subroutine calculates the confined explosion near-field parameters and supplies the time functions of energy and mass injection. Solid-phase or TNT-equivalent explosions (which simulate 'point source' explosions in nuclear facilities) as well as explosions in gas-air mixtures can be simulated. The four types of explosions EVENT84 simulates are TNT, hydrogen in air, acetylene in air, and tributyl phosphate (TBP or 'red oil
Phase-synchronisation in continuous flow models of production networks
Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael
2006-04-01
To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.
Solving inversion problems with neural networks
Kamgar-Parsi, Behzad; Gualtieri, J. A.
1990-01-01
A class of inverse problems in remote sensing can be characterized by Q = F(x), where F is a nonlinear and noninvertible (or hard to invert) operator, and the objective is to infer the unknowns, x, from the observed quantities, Q. Since the number of observations is usually greater than the number of unknowns, these problems are formulated as optimization problems, which can be solved by a variety of techniques. The feasibility of neural networks for solving such problems is presently investigated. As an example, the problem of finding the atmospheric ozone profile from measured ultraviolet radiances is studied.
A matheuristic for the liner shipping network design problem
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Desaulniers, Guy; Pisinger, David
We present a matheuristic, an integer programming based heuristic, for the liner shipping network design problem. This problem consists of finding a set of container shipping routes defining a capacitated network for cargo transport. The objective is to maximize the revenue of cargo transport...... the available fleet of container vessels. The cargo transports make extensive use of transshipments between routes and the number of transshipments of the cargo flow is decisive for network profitability. Computational results are reported for the benchmark suite LINER-LIB 2012 following the industry standard...... of weekly departures on every schedule. The heuristic shows overall good performance and is able to find high quality solutions within competitive execution times. The matheuristic can also be applied as a decision support tool to improve an existing network by optimizing on a designated subset...
Flow enforcement algorithms for ATM networks
DEFF Research Database (Denmark)
Dittmann, Lars; Jacobsen, Søren B.; Moth, Klaus
1991-01-01
Four measurement algorithms for flow enforcement in asynchronous transfer mode (ATM) networks are presented. The algorithms are the leaky bucket, the rectangular sliding window, the triangular sliding window, and the exponentially weighted moving average. A comparison, based partly on teletraffic...
CIME course on Modelling and Optimisation of Flows on Networks
Ambrosio, Luigi; Helbing, Dirk; Klar, Axel; Zuazua, Enrique
2013-01-01
In recent years flows in networks have attracted the interest of many researchers from different areas, e.g. applied mathematicians, engineers, physicists, economists. The main reason for this ubiquity is the wide and diverse range of applications, such as vehicular traffic, supply chains, blood flow, irrigation channels, data networks and others. This book presents an extensive set of notes by world leaders on the main mathematical techniques used to address such problems, together with investigations into specific applications. The main focus is on partial differential equations in networks, but ordinary differential equations and optimal transport are also included. Moreover, the modeling is completed by analysis, numerics, control and optimization of flows in networks. The book will be a valuable resource for every researcher or student interested in the subject.
Information flow analysis of interactome networks.
Directory of Open Access Journals (Sweden)
Patrycja Vasilyev Missiuro
2009-04-01
Full Text Available Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we
Wood flow problems in the Swedish forestry
Energy Technology Data Exchange (ETDEWEB)
Carlsson, Dick [Forestry Research Inst. of Sweden, Uppsala (Sweden); Roennqvist, M. [Linkoeping Univ. (Sweden). Dept. of Mathematics
1998-12-31
In this paper we give an overview of the wood-flow in Sweden including a description of organization and planning. Based on that, we will describe a number of applications or problem areas in the wood-flow chain that are currently considered by the Swedish forest companies to be important and potential in order to improve overall operations. We have focused on applications which are short term planning or operative planning. We do not give any final results as much of the development is currently ongoing or is still in a planning phase. Instead we describe what kind of models and decision support systems that could be applied in order to improve co-operation within and integration of the wood-flow chain 13 refs, 20 figs, 1 tab
Finite element methods for incompressible flow problems
John, Volker
2016-01-01
This book explores finite element methods for incompressible flow problems: Stokes equations, stationary Navier-Stokes equations, and time-dependent Navier-Stokes equations. It focuses on numerical analysis, but also discusses the practical use of these methods and includes numerical illustrations. It also provides a comprehensive overview of analytical results for turbulence models. The proofs are presented step by step, allowing readers to more easily understand the analytical techniques.
A note on Fenchel cuts for the single-node flow problem
DEFF Research Database (Denmark)
Klose, Andreas
The single-node flow problem, which is also known as the single-sink fixed-charge transportation problem, consists in finding a minimum cost flow from a number of nodes to a single sink. The flow cost comprise an amount proportional to the quantity shipped as well as a fixed charge. In this note......, some structural properties of Fenchel cutting planes for this problem are described. Such cuts might then be applied for solving, e.g., fixed-charge transportation problems and more general fixed-charge network flow problems....
Agricultural informational flow in informal communication networks ...
African Journals Online (AJOL)
Agricultural informational flow in informal communication networks of farmers in Ghana. ... should identify such farmers who can serve as intermediaries between actors to help disseminate information in rural communities. Keywords: key communicators, farmers, rural communities, social networks, extension agents ...
Brain network clustering with information flow motifs
Märtens, M.; Meier, J.M.; Hillebrand, Arjan; Tewarie, Prejaas; Van Mieghem, P.F.A.
2017-01-01
Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands.
Brocade: Optimal flow placement in SDN networks
CERN. Geneva
2015-01-01
Today' network poses several challanges to network providers. These challanges fall in to a variety of areas ranging from determining efficient utilization of network bandwidth to finding out which user applications consume majority of network resources. Also, how to protect a given network from volumetric and botnet attacks. Optimal placement of flows deal with identifying network issues and addressing them in a real-time. The overall solution helps in building new services where a network is more secure and more efficient. Benefits derived as a result are increased network efficiency due to better capacity and resource planning, better security with real-time threat mitigation, and improved user experience as a result of increased service velocity.
Characteristics-based modelling of flow problems
International Nuclear Information System (INIS)
Saarinen, M.
1994-02-01
The method of characteristics is an exact way to proceed to the solution of hyperbolic partial differential equations. The numerical solutions, however, are obtained in the fixed computational grid where interpolations of values between the mesh points cause numerical errors. The Piecewise Linear Interpolation Method, PLIM, the utilization of which is based on the method of characteristics, has been developed to overcome these deficiencies. The thesis concentrates on the computer simulation of the two-phase flow. The main topics studied are: (1) the PLIM method has been applied to study the validity of the numerical scheme through solving various flow problems to achieve knowledge for the further development of the method, (2) the mathematical and physical validity and applicability of the two-phase flow equations based on the SFAV (Separation of the two-phase Flow According to Velocities) approach has been studied, and (3) The SFAV approach has been further developed for particular cases such as stratified horizontal two-phase flow. (63 refs., 4 figs.)
Information Flows in Networked Engineering Design Projects
DEFF Research Database (Denmark)
Parraguez, Pedro; Maier, Anja
Complex engineering design projects need to manage simultaneously multiple information flows across design activities associated with different areas of the design process. Previous research on this area has mostly focused on either analysing the “required information flows” through activity...... networks at the project level or in studying the social networks that deliver the “actual information flow”. In this paper we propose and empirically test a model and method that integrates both social and activity networks into one compact representation, allowing to compare actual and required...... information flows between design spaces, and to assess the influence that these misalignments could have on the performance of engineering design projects....
A measure theoretic approach to traffic flow optimization on networks
Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea
2018-01-01
We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...
Software defined networking with OpenFlow
Azodolmolky, Siamak
2013-01-01
A step-by-step, example-based guide which will help you gain hands-on experience with the platforms and debugging tools on OpenFlow.If you are a network engineer, architect, junior researcher or an application developer, this book is ideal for you. You will need to have some level of network experience, knowledge of broad networking concepts, and some familiarity with day- to- day operation of computer networks. Ideally, you should also be familiar with programing scripting/languages (especially Python and Java), and system virtualization.
Hub location problems in transportation networks
DEFF Research Database (Denmark)
Gelareh, Shahin; Nickel, Stefan
2011-01-01
In this paper we propose a 4-index formulation for the uncapacitated multiple allocation hub location problem tailored for urban transport and liner shipping network design. This formulation is very tight and most of the tractable instances for MIP solvers are optimally solvable at the root node....... also introduce fixed cost values for Australian Post (AP) dataset....
Application of the load flow and random flow models for the analysis of power transmission networks
International Nuclear Information System (INIS)
Zio, Enrico; Piccinelli, Roberta; Delfanti, Maurizio; Olivieri, Valeria; Pozzi, Mauro
2012-01-01
In this paper, the classical load flow model and the random flow model are considered for analyzing the performance of power transmission networks. The analysis concerns both the system performance and the importance of the different system elements; this latter is computed by power flow and random walk betweenness centrality measures. A network system from the literature is analyzed, representing a simple electrical power transmission network. The results obtained highlight the differences between the LF “global approach” to flow dispatch and the RF local approach of randomized node-to-node load transfer. Furthermore, computationally the LF model is less consuming than the RF model but problems of convergence may arise in the LF calculation.
Synthesis of a parallel data stream processor from data flow process networks
Zissulescu-Ianculescu, Claudiu
2008-01-01
In this talk, we address the problem of synthesizing Process Network specifications to FPGA execution platforms. The process networks we consider are special cases of Kahn Process Networks. We call them COMPAAN Data Flow Process Networks (CDFPN) because they are provided by a translator called the
On Event Detection and Localization in Acyclic Flow Networks
Suresh, Mahima Agumbe
2013-05-01
Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures have been proven costly and imprecise, particularly when dealing with large-scale distribution systems. In this article, to the best of our knowledge, for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. We propose the idea of using sensors that move along the edges of the network and detect events (i.e., attacks). To localize the events, sensors detect proximity to beacons, which are devices with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensors and beacons deployed) in a predetermined zone of interest, while ensuring a degree of coverage by sensors and a required accuracy in locating events using beacons. We propose algorithms for solving the aforementioned problem and demonstrate their effectiveness with results obtained from a realistic flow network simulator.
Horizontal two phase flow pattern identification by neural networks
International Nuclear Information System (INIS)
Crivelaro, Kelen Cristina Oliveira; Seleghim Junior, Paulo; Hervieu, Eric
1999-01-01
A multiphase fluid can flow according to several flow regimes. The problem associated with multiphase systems are basically related to the behavior of macroscopic parameters, such as pressure drop, thermal exchanges and so on, and their strong correlation to the flow regime. From the industrial applications point of view, the safety and longevity of equipment and systems can only be assured when they work according to the flow regimes for which they were designed to. This implies in the need to diagnose flow regimes in real time. The automatic diagnosis of flow regimes represents an objective of extreme importance, mainly for applications on nuclear and petrochemical industries. In this work, a neural network is used in association to a probe of direct visualization for the identification of a gas-liquid flow horizontal regimes, developed in an experimental circuit. More specifically, the signals produced by the probe are used to compose a qualitative image of the flow, which is promptly sent to the network for the recognition of the regimes. Results are presented for different transitions among the flow regimes, which demonstrate the extremely satisfactory performance of the diagnosis system. (author)
Directory of Open Access Journals (Sweden)
Ирина Александровна Гавриленко
2016-02-01
Full Text Available The approach to automated management of load flow in engineering networks considering functional reliability was proposed in the article. The improvement of the concept of operational and strategic management of load flow in engineering networks was considered. The verbal statement of the problem for thesis research is defined, namely, the problem of development of information technology for exact calculation of the functional reliability of the network, or the risk of short delivery of purpose-oriented product for consumers
Adaptive boundary conditions for exterior flow problems
Boenisch, V; Wittwer, S
2003-01-01
We consider the problem of solving numerically the stationary incompressible Navier-Stokes equations in an exterior domain in two dimensions. This corresponds to studying the stationary fluid flow past a body. The necessity to truncate for numerical purposes the infinite exterior domain to a finite domain leads to the problem of finding appropriate boundary conditions on the surface of the truncated domain. We solve this problem by providing a vector field describing the leading asymptotic behavior of the solution. This vector field is given in the form of an explicit expression depending on a real parameter. We show that this parameter can be determined from the total drag exerted on the body. Using this fact we set up a self-consistent numerical scheme that determines the parameter, and hence the boundary conditions and the drag, as part of the solution process. We compare the values of the drag obtained with our adaptive scheme with the results from using traditional constant boundary conditions. Computati...
Spike Code Flow in Cultured Neuronal Networks.
Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei
2016-01-01
We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.
Spike Code Flow in Cultured Neuronal Networks
Directory of Open Access Journals (Sweden)
Shinichi Tamura
2016-01-01
Full Text Available We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.
CUFID-query: accurate network querying through random walk based network flow estimation.
Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun
2017-12-28
Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive
Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow.
Gao, Zhong-Ke; Zhang, Xin-Wang; Jin, Ning-De; Marwan, Norbert; Kurths, Jürgen
2013-09-01
Characterizing complex patterns arising from horizontal oil-water two-phase flows is a contemporary and challenging problem of paramount importance. We design a new multisector conductance sensor and systematically carry out horizontal oil-water two-phase flow experiments for measuring multivariate signals of different flow patterns. We then infer multivariate recurrence networks from these experimental data and investigate local cross-network properties for each constructed network. Our results demonstrate that a cross-clustering coefficient from a multivariate recurrence network is very sensitive to transitions among different flow patterns and recovers quantitative insights into the flow behavior underlying horizontal oil-water flows. These properties render multivariate recurrence networks particularly powerful for investigating a horizontal oil-water two-phase flow system and its complex interacting components from a network perspective.
Solving Dynamic Battlespace Movement Problems Using Dynamic Distributed Computer Networks
National Research Council Canada - National Science Library
Bradford, Robert
2000-01-01
.... The thesis designs a system using this architecture that invokes operations research network optimization algorithms to solve problems involving movement of people and equipment over dynamic road networks...
Distributed routing algorithms to manage power flow in agent-based active distribution network
Nguyen, H.P.; Kling, W.L.; Georgiadis, G.; Papatriantafilou, M.; Anh-Tuan, L.; Bertling, L.
2010-01-01
The current transition from passive to active electric distribution networks comes with problems and challenges on bi-directional power flow in the network and the uncertainty in the forecast of power generation from grid-connected renewable and distributed energy sources. The power flow management
Monitoring individual traffic flows within the ATLAS TDAQ network
International Nuclear Information System (INIS)
Sjoen, R; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A; Stancu, S; Ciobotaru, M
2010-01-01
The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities and limitations of this diagnostic tool, giving an example of its use in solving system problems that arise during the ATLAS data taking.
Towards Optimal Event Detection and Localization in Acyclic Flow Networks
Agumbe Suresh, Mahima
2012-01-03
Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.
Technology and knowledge flow the power of networks
Trentin, Guglielmo
2011-01-01
This book outlines how network technology can support, foster and enhance the Knowledge Management, Sharing and Development (KMSD) processes in professional environments through the activation of both formal and informal knowledge flows. Understanding how ICT can be made available to such flows in the knowledge society is a factor that cannot be disregarded and is confirmed by the increasing interest of companies in new forms of software-mediated social interaction. The latter factor is in relation both to the possibility of accelerating internal communication and problem solving processes, an
A network flow algorithm to position tiles for LAMOST
International Nuclear Information System (INIS)
Li Guangwei; Zhao Gang
2009-01-01
We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly. To solve this problem, firstly we divide the sky into many small blocks, and we also assume that all the targets that are in the same block have the same position, which is the center of the block. Secondly, we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block. Thirdly, because the network flow algorithm used in this paper is a bipartite network, we do not use the general solution algorithm that was used by SDSS. Instead, we give our new faster solution method for this special network. Compared with the Convergent Mean Shift Algorithm, the network flow algorithm can decrease observation times with improved mean imaging quality. This algorithm also has a very fast running speed. It can distribute millions of targets in a few minutes using a common personal computer.
Approximation algorithms for the parallel flow shop problem
X. Zhang (Xiandong); S.L. van de Velde (Steef)
2012-01-01
textabstractWe consider the NP-hard problem of scheduling n jobs in m two-stage parallel flow shops so as to minimize the makespan. This problem decomposes into two subproblems: assigning the jobs to parallel flow shops; and scheduling the jobs assigned to the same flow shop by use of Johnson's
A new approach in development of data flow control and investigation system for computer networks
International Nuclear Information System (INIS)
Frolov, I.; Vaguine, A.; Silin, A.
1992-01-01
This paper describes a new approach in development of data flow control and investigation system for computer networks. This approach was developed and applied in the Moscow Radiotechnical Institute for control and investigations of Institute computer network. It allowed us to solve our network current problems successfully. Description of our approach is represented below along with the most interesting results of our work. (author)
On-Line Detection of Distributed Attacks from Space-Time Network Flow Patterns
National Research Council Canada - National Science Library
Baras, J. S; Cardenas, A. A; Ramezani, V
2003-01-01
.... The directionality of the change in a network flow is assumed to have an objective or target. The particular problem of detecting distributed denial of service attacks from distributed observations is presented as a working framework...
Fluid Flow in a Porous Tree-Shaped Network
Miguel, A. F.
2014-01-01
Tree-shaped flow networks connect one point to an inﬁnity of points and are everywhere in Nature. These networks often own minimal flow resistance and vessel sizes obey to scaling power-laws. In this paper presents a model for fluid flow through a tree-shaped network with porous tubes. Hagen–Poiseuille flow is assumed for tubes and Darcy flow for the porous wall.
Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models
Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.
2013-12-01
Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.
Monitoring individual traffic flows within the ATLAS TDAQ network
Sjoen, R; Ciobotaru, M; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A
2010-01-01
The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities a...
Inter-flow and intra-flow interference mitigation routing in wireless mesh networks
Houaidia, Chiraz; Idoudi, Hanen; Van den Bossche, Adrien; Saidane, Leila; Val, Thierry
2017-01-01
In this paper, we address the problem of QoS support in an heterogeneous multi-rate wireless mesh network. We propose a new routing metric that provides information about link quality, based on PHY and MAC characteristics, including the link availability, the loss rate and the available bandwidth. This metric allows to apprehend inter-flow interferences and avoid bottleneck formation by balancing traffic load on the links. Based on the conflict graph model and calculation of maximal cliques, ...
Parallel Computation of Unsteady Flows on a Network of Workstations
1997-01-01
Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.
A theory of intelligence: networked problem solving in animal societies
Shour, Robert
2009-01-01
A society's single emergent, increasing intelligence arises partly from the thermodynamic advantages of networking the innate intelligence of different individuals, and partly from the accumulation of solved problems. Economic growth is proportional to the square of the network entropy of a society's population times the network entropy of the number of the society's solved problems.
3D Topology optimization of Stokes flow problems
DEFF Research Database (Denmark)
Gersborg-Hansen, Allan; Dammann, Bernd
of energy efficient devices for 2D Stokes flow. Creeping flow problems are described by the Stokes equations which model very viscous fluids at macro scales or ordinary fluids at very small scales. The latter gives the motivation for topology optimization problems based on the Stokes equations being a model......The present talk is concerned with the application of topology optimization to creeping flow problems in 3D. This research is driven by the fact that topology optimization has proven very successful as a tool in academic and industrial design problems. Success stories are reported from such diverse...
Application of Artificial Neural Networks to Complex Groundwater Management Problems
International Nuclear Information System (INIS)
Coppola, Emery; Poulton, Mary; Charles, Emmanuel; Dustman, John; Szidarovszky, Ferenc
2003-01-01
As water quantity and quality problems become increasingly severe, accurate prediction and effective management of scarcer water resources will become critical. In this paper, the successful application of artificial neural network (ANN) technology is described for three types of groundwater prediction and management problems. In the first example, an ANN was trained with simulation data from a physically based numerical model to predict head (groundwater elevation) at locations of interest under variable pumping and climate conditions. The ANN achieved a high degree of predictive accuracy, and its derived state-transition equations were embedded into a multiobjective optimization formulation and solved to generate a trade-off curve depicting water supply in relation to contamination risk. In the second and third examples, ANNs were developed with real-world hydrologic and climate data for different hydrogeologic environments. For the second problem, an ANN was developed using data collected for a 5-year, 8-month period to predict heads in a multilayered surficial and limestone aquifer system under variable pumping, state, and climate conditions. Using weekly stress periods, the ANN substantially outperformed a well-calibrated numerical flow model for the 71-day validation period, and provided insights into the effects of climate and pumping on water levels. For the third problem, an ANN was developed with data collected automatically over a 6-week period to predict hourly heads in 11 high-capacity public supply wells tapping a semiconfined bedrock aquifer and subject to large well-interference effects. Using hourly stress periods, the ANN accurately predicted heads for 24-hour periods in all public supply wells. These test cases demonstrate that the ANN technology can solve a variety of complex groundwater management problems and overcome many of the problems and limitations associated with traditional physically based flow models
Graphs, Ideal Flow, and the Transportation Network
Teknomo, Kardi
2016-01-01
This lecture discusses the mathematical relationship between network structure and network utilization of transportation network. Network structure means the graph itself. Network utilization represent the aggregation of trajectories of agents in using the network graph. I show the similarity and relationship between the structural pattern of the network and network utilization.
Game Theoretic Problems in Network Economics and Mechanism Design Solutions
Narahari, Y; Narayanam, Ramasuri; Prakash, Hastagiri
2009-01-01
Explores game theoretic modeling and mechanism design for problem solving in Internet and network economics. This monograph contains an exposition of representative game theoretic problems in three different network economics situations and a systematic exploration of mechanism design solutions to these problems.
Numberical Solution to Transient Heat Flow Problems
Kobiske, Ronald A.; Hock, Jeffrey L.
1973-01-01
Discusses the reduction of the one- and three-dimensional diffusion equation to the difference equation and its stability, convergence, and heat-flow applications under different boundary conditions. Indicates the usefulness of this presentation for beginning students of physics and engineering as well as college teachers. (CC)
Hodge Decomposition of Information Flow on Small-World Networks.
Haruna, Taichi; Fujiki, Yuuya
2016-01-01
We investigate the influence of the small-world topology on the composition of information flow on networks. By appealing to the combinatorial Hodge theory, we decompose information flow generated by random threshold networks on the Watts-Strogatz model into three components: gradient, harmonic and curl flows. The harmonic and curl flows represent globally circular and locally circular components, respectively. The Watts-Strogatz model bridges the two extreme network topologies, a lattice network and a random network, by a single parameter that is the probability of random rewiring. The small-world topology is realized within a certain range between them. By numerical simulation we found that as networks become more random the ratio of harmonic flow to the total magnitude of information flow increases whereas the ratio of curl flow decreases. Furthermore, both quantities are significantly enhanced from the level when only network structure is considered for the network close to a random network and a lattice network, respectively. Finally, the sum of these two ratios takes its maximum value within the small-world region. These findings suggest that the dynamical information counterpart of global integration and that of local segregation are the harmonic flow and the curl flow, respectively, and that a part of the small-world region is dominated by internal circulation of information flow.
Hodge decomposition of information flow on small-world networks
Directory of Open Access Journals (Sweden)
Taichi Haruna
2016-09-01
Full Text Available We investigate the influence of the small-world topology on the composition of information flow on networks. By appealing to the combinatorial Hodge theory, we decompose information flow generated by random threshold networks on the Watts-Strogatz model into three components: gradient, harmonic and curl flows. The harmonic and curl flows represent globally circular and locally circular components, respectively. The Watts-Strogatz model bridges the two extreme network topologies, a lattice network and a random network, by a single parameter that is the probability of random rewiring. The small-world topology is realized within a certain range between them. By numerical simulation we found that as networks become more random the ratio of harmonic flow to the total magnitude of information flow increases whereas the ratio of curl flow decreases. Furthermore, both quantities are significantly enhanced from the level when only network structure is considered for the network close to a random network and a lattice network, respectively. Finally, the sum of these two ratios takes its maximum value within the small-world region. These findings suggest that the dynamical information counterpart of global integration and that of local segregation are the harmonic flow and the curl flow, respectively, and that a part of the small-world region is dominated by internal circulation of information flow.
A finite element method for flow problems in blast loading
International Nuclear Information System (INIS)
Forestier, A.; Lepareux, M.
1984-06-01
This paper presents a numerical method which describes fast dynamic problems in flow transient situations as in nuclear plants. A finite element formulation has been chosen; it is described by a preprocessor in CASTEM system: GIBI code. For these typical flow problems, an A.L.E. formulation for physical equations is used. So, some applications are presented: the well known problem of shock tube, the same one in 2D case and a last application to hydrogen detonation
Inverse kinematics problem in robotics using neural networks
Choi, Benjamin B.; Lawrence, Charles
1992-01-01
In this paper, Multilayer Feedforward Networks are applied to the robot inverse kinematic problem. The networks are trained with endeffector position and joint angles. After training, performance is measured by having the network generate joint angles for arbitrary endeffector trajectories. A 3-degree-of-freedom (DOF) spatial manipulator is used for the study. It is found that neural networks provide a simple and effective way to both model the manipulator inverse kinematics and circumvent the problems associated with algorithmic solution methods.
Scaling of peak flows with constant flow velocity in random self-similar networks
Directory of Open Access Journals (Sweden)
R. Mantilla
2011-07-01
Full Text Available A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs with geometrically distributed interior and exterior generators having parameters p_{i} and p_{e}, respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β^{(E} and φ^{(E} that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β^{(E} and φ^{(E} and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ^{(E} and φ with respect to the value of flow velocity and runoff intensity implies an interesting connection between unit
Scaling of peak flows with constant flow velocity in random self-similar networks
Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.
2011-01-01
A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs) with geometrically distributed interior and exterior generators having parameters pi and pe, respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β(E) and φ(E) that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β(E) and φ(E) and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ(E) and φ with respect to the value of flow velocity and runoff intensity implies an interesting connection between unit hydrograph theory and flow dynamics. Our results provide a reference framework to study scaling exponents under more complex scenarios
Complex network problems in physics, computer science and biology
Cojocaru, Radu Ionut
lattice at zero temperature and then we apply this formalism to the K-SAT problem defined in Chapter 1. The phase transition which physicists study often corresponds to a change in the computational complexity of the corresponding computer science problem. Chapter 3 presents phase transitions which are specific to the problems discussed in Chapter 1 and also known results for the K-SAT problem. We discuss the replica method and experimental evidences of replica symmetry breaking. The physics approach to hard problems is based on replica methods which are difficult to understand. In Chapter 4 we develop novel methods for studying hard problems using methods similar to the message passing techniques that were discussed in Chapter 2. Although we concentrated on the symmetric case, cavity methods show promise for generalizing our methods to the un-symmetric case. As has been highlighted by John Hopfield, several key features of biological systems are not shared by physical systems. Although living entities follow the laws of physics and chemistry, the fact that organisms adapt and reproduce introduces an essential ingredient that is missing in the physical sciences. In order to extract information from networks many algorithm have been developed. In Chapter 5 we apply polynomial algorithms like minimum spanning tree in order to study and construct gene regulatory networks from experimental data. As future work we propose the use of algorithms like min-cut/max-flow and Dijkstra for understanding key properties of these networks.
Solving implicit multi-mesh flow and conjugate heat transfer problems with RELAP-7
International Nuclear Information System (INIS)
Zou, L.; Peterson, J.; Zhao, H.; Zhang, H.; Andrs, D.; Martineau, R.
2013-01-01
The fully implicit simulation capability of RELAP-7 to solve multi-mesh flow and conjugate heat transfer problems for reactor system safety analysis is presented. Compared to general single-mesh simulations, the reactor system safety analysis-type of code has unique challenges due to its highly simplified, interconnected, one-dimensional, and zero-dimensional flow network describing multiple physics with significantly different time and length scales. To use the Jacobian-free Newton Krylov-type of solver, preconditioning is generally required for the Krylov method. The uniqueness of the reactor safety analysis-type of code in treating the interconnected flow network and conjugate heat transfer also introduces challenges in providing preconditioning matrix. Typical flow and conjugate heat transfer problems involved in reactor safety analysis using RELAP-7, as well as the special treatment on the preconditioning matrix are presented in detail. (authors)
Employment growth through labor flow networks.
Guerrero, Omar A; Axtell, Robert L
2013-01-01
It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.
Employment growth through labor flow networks.
Directory of Open Access Journals (Sweden)
Omar A Guerrero
Full Text Available It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN. This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.
Optimal Power Flow for resistive DC Network : A Port-Hamiltonian approach
Benedito, Ernest; del Puerto-Flores, D.; Doria-Cerezo, A.; Scherpen, Jacquelien M.A.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri
This paper studies the optimal power flow problem for resistive DC networks. The gradient method algorithm is written in a port-Hamiltonian form and the stability of the resulting dynamics is studied. Stability conditions are provided for general cyclic networks and a solution, when these conditions
Solving network design problems via decomposition, aggregation and approximation
Bärmann, Andreas
2016-01-01
Andreas Bärmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time. Contents Decomposition for Multi-Period Network Design Solving Network Design Problems via Ag...
Flow control and routing techniques for integrated voice and data networks
Ibe, O. C.
1981-10-01
We consider a model of integrated voice and data networks. In this model the network flow problem is formulated as a convex optimization problem. The objective function comprises two types of cost functions: the congestion cost functions, which limit the average input traffic to values compatible with the network conditions; and the rate limitation cost functions, which ensure that all conversations are fairly treated. A joint flow control and routing algorithm is constructed which determines the routes for each conversation, and effects flow control by setting voice packet lengths and data input rates in a manner that achieves optimal tradeoff between each user's satisfaction and the cost of network congestion. An additional congestion control protocol is specified which could be used in conjunction with the algorithm to make the latter respond more dynamically to network congestion.
Radial basis function neural network for power system load-flow
International Nuclear Information System (INIS)
Karami, A.; Mohammadi, M.S.
2008-01-01
This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)
Contribution of Fuzzy Minimal Cost Flow Problem by Possibility Programming
S. Fanati Rashidi; A. A. Noora
2010-01-01
Using the concept of possibility proposed by zadeh, luhandjula ([4,8]) and buckley ([1]) have proposed the possibility programming. The formulation of buckley results in nonlinear programming problems. Negi [6]re-formulated the approach of Buckley by the use of trapezoidal fuzzy numbers and reduced the problem into fuzzy linear programming problem. Shih and Lee ([7]) used the Negi approach to solve a minimum cost flow problem, whit fuzzy costs and the upper and lower bound. ...
PRIVACY PROTECTION PROBLEMS IN SOCIAL NETWORKS
OKUR, M. Cudi
2011-01-01
Protecting privacy has become a major concern for most social network users because of increased difficulties of controlling the online data. This article presents an assessment of the common privacy related risks of social networking sites. Open and hidden privacy risks of active and passive online profiles are examined and increasing share of social networking in these phenomena is discussed. Inadequacy of available legal and institutional protection is demonstrated and the effectiveness of...
Topology Optimization of Large Scale Stokes Flow Problems
DEFF Research Database (Denmark)
Aage, Niels; Poulsen, Thomas Harpsøe; Gersborg-Hansen, Allan
2008-01-01
This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.......This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs....
International Nuclear Information System (INIS)
Gao, Zhong-Ke; Fang, Peng-Cheng; Ding, Mei-Shuang; Yang, Dan; Jin, Ning-De
2015-01-01
We propose a complex network-based method to distinguish complex patterns arising from experimental horizontal oil–water two-phase flow. We first use the adaptive optimal kernel time–frequency representation (AOK TFR) to characterize flow pattern behaviors from the energy and frequency point of view. Then, we infer two-phase flow complex networks from experimental measurements and detect the community structures associated with flow patterns. The results suggest that the community detection in two-phase flow complex network allows objectively discriminating complex horizontal oil–water flow patterns, especially for the segregated and dispersed flow patterns, a task that existing method based on AOK TFR fails to work. - Highlights: • We combine time–frequency analysis and complex network to identify flow patterns. • We explore the transitional flow behaviors in terms of betweenness centrality. • Our analysis provides a novel way for recognizing complex flow patterns. • Broader applicability of our method is demonstrated and articulated
The Determinants of International News Flow: A Network Analysis.
Kim, Kyungmo; Barnett, George A.
1996-01-01
Examines the structure of international news flow and its determinants. Reveals inequality of international news flow between core and periphery, with Western industrialized countries at the center. Finds that the news flow network is structured into eight geographic-linguistic groups. Indicates flow is influenced by a country's economic…
Determination of free boundary problem of flow through porous media
International Nuclear Information System (INIS)
Tavares Junior, H.M.; Souza, A.J. de
1989-01-01
This paper deals with a free boundary problem of flow through porous media, which is solved by simplicial method conbined with mesh refinement. Variational method on fixed domain is utilized. (author)
A multi-scale network method for two-phase flow in porous media
Energy Technology Data Exchange (ETDEWEB)
Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick
2017-08-01
Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.
A multi-scale network method for two-phase flow in porous media
International Nuclear Information System (INIS)
Khayrat, Karim; Jenny, Patrick
2017-01-01
Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.
Using a genetic algorithm to solve fluid-flow problems
International Nuclear Information System (INIS)
Pryor, R.J.
1990-01-01
Genetic algorithms are based on the mechanics of the natural selection and natural genetics processes. These algorithms are finding increasing application to a wide variety of engineering optimization and machine learning problems. In this paper, the authors demonstrate the use of a genetic algorithm to solve fluid flow problems. Specifically, the authors use the algorithm to solve the one-dimensional flow equations for a pipe
Network Model for The Problem of Integer Balancing of a Fourdimensional Matrix
Directory of Open Access Journals (Sweden)
A. V. Smirnov
2016-01-01
Full Text Available The problem of integer balancing of a four-dimensional matrix is studied. The elements of the inner part (all four indices are greater than zero of the given real matrix are summed in each direction and each two- and three-dimensional section of the matrix; the total sum is also found. These sums are placed into the elements where one or more indices are equal to zero (according to the summing directions. The problem is to find an integer matrix of the same structure, which can be produced from the initial one by replacing the elements with the largest previous or the smallest following integer. At the same time, the element with four zero indices should be produced with standard rules of rounding - off. In the article the problem of finding the maximum multiple flow in the network of any natural multiplicity is also studied. There are arcs of three types: ordinary arcs, multiple arcs and multi-arcs. Each multiple and multi-arc is a union of linked arcs, which are adjusted with each other. The network constructing rules are described. The definitions of a divisible network and some associated subjects are stated. There are defined the basic principles for reducing the integer balancing problem of an -dimensional matrix ( to the problem of finding the maximum flow in a divisible multiple network of multiplicity . There are stated the rules for reducing the four-dimensional balancing problem to the maximum flow problem in the network of multiplicity 5. The algorithm of finding the maximum flow, which meets the solvability conditions for the integer balancing problem, is formulated for such a network.
On the Update Problems for Software Defined Networks
Directory of Open Access Journals (Sweden)
V. A. Zakharov
2014-01-01
Full Text Available The designing of network update algorithms is urgent for the development of SDN control software. A particular case of Network Update Problem is that of restoring seamlessly a given network configuration after some packet forwarding rules have been disabled (say, at the expiry of their time-outs. We study this problem in the framework of a formal model of SDN, develop correct and safe network recovering algorithms, and show that in general case there is no way to restore network configuration seamlessly without referring to priorities of packet forwarding rules.
Numerical solution of pipe flow problems for generalized Newtonian fluids
International Nuclear Information System (INIS)
Samuelsson, K.
1993-01-01
In this work we study the stationary laminar flow of incompressible generalized Newtonian fluids in a pipe with constant arbitrary cross-section. The resulting nonlinear boundary value problems can be written in a variational formulation and solved using finite elements and the augmented Lagrangian method. The solution of the boundary value problem is obtained by finding a saddle point of the augmented Lagrangian. In the algorithm the nonlinear part of the equations is treated locally and the solution is obtained by iteration between this nonlinear problem and a global linear problem. For the solution of the linear problem we use the SSOR preconditioned conjugate gradient method. The approximating problem is solved on a sequence of adaptively refined grids. A scheme for adjusting the value of the crucial penalization parameter of the augmented Lagrangian is proposed. Applications to pipe flow and a problem from the theory of capacities are given. (author) (34 refs.)
Secure Wireless Sensor Networks: Problems and Solutions
Directory of Open Access Journals (Sweden)
Fei Hu
2003-08-01
Full Text Available As sensor networks edge closer towards wide-spread deployment, security issues become a central concern. So far, the main research focus has been on making sensor networks feasible and useful, and less emphasis was placed on security. This paper analyzes security challenges in wireless sensor networks and summarizes key issues that should be solved for achieving the ad hoc security. It gives an overview of the current state of solutions on such key issues as secure routing, prevention of denial-of-service and key management service. We also present some secure methods to achieve security in wireless sensor networks. Finally we present our integrated approach to securing sensor networks.
Solving the Liner Shipping Fleet Repositioning Problem with Cargo Flows
DEFF Research Database (Denmark)
Tierney, Kevin; Askelsdottir, Björg; Jensen, Rune Møller
2015-01-01
We solve a central problem in the liner shipping industry called the liner shipping fleet repositioning problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between routes in a liner shipping network. Liner carriers wish...
The Liner Shipping Fleet Repositioning Problem with Cargo Flows
DEFF Research Database (Denmark)
Tierney, Kevin; Jensen, Rune Møller
2012-01-01
We solve an important problem for the liner shipping industry called the Liner Shipping Fleet Repositioning Problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between services in a liner shipping network. Shippers wish...
Schallhorn, Paul; Majumdar, Alok
2012-01-01
This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.
Network Monitoring as a Streaming Analytics Problem
Gupta, Arpit
2016-11-02
Programmable switches make it easier to perform flexible network monitoring queries at line rate, and scalable stream processors make it possible to fuse data streams to answer more sophisticated queries about the network in real-time. Unfortunately, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have network monitoring in the context of streaming; yet, previous work has not closed the loop in a way that allows network operators to perform streaming analytics for network monitoring applications at scale. To achieve this objective, Sonata allows operators to express a network monitoring query by considering each packet as a tuple and efficiently partitioning each query between the switches and the stream processor through iterative refinement. Sonata extracts only the traffic that pertains to each query, ensuring that the stream processor can scale traffic rates of several terabits per second. We show with a simple example query involving DNS reflection attacks and traffic traces from one of the world\\'s largest IXPs that Sonata can capture 95% of all traffic pertaining to the query, while reducing the overall data rate by a factor of about 400 and the number of required counters by four orders of magnitude. Copyright 2016 ACM.
Modelling flow dynamics in water distribution networks using ...
African Journals Online (AJOL)
One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...
Isospectral Flows for the Inhomogeneous String Density Problem
Górski, Andrzej Z.; Szmigielski, Jacek
2018-02-01
We derive isospectral flows of the mass density in the string boundary value problem corresponding to general boundary conditions. In particular, we show that certain class of rational flows produces in a suitable limit all flows generated by polynomials in negative powers of the spectral parameter. We illustrate the theory with concrete examples of isospectral flows of discrete mass densities which we prove to be Hamiltonian and for which we provide explicit solutions of equations of motion in terms of Stieltjes continued fractions and Hankel determinants.
Contribution of Fuzzy Minimal Cost Flow Problem by Possibility Programming
Directory of Open Access Journals (Sweden)
S. Fanati Rashidi
2010-06-01
Full Text Available Using the concept of possibility proposed by zadeh, luhandjula ([4,8] and buckley ([1] have proposed the possibility programming. The formulation of buckley results in nonlinear programming problems. Negi [6]re-formulated the approach of Buckley by the use of trapezoidal fuzzy numbers and reduced the problem into fuzzy linear programming problem. Shih and Lee ([7] used the Negi approach to solve a minimum cost flow problem, whit fuzzy costs and the upper and lower bound. In this paper we shall consider the general form of this problem where all of the parameters and variables are fuzzy and also a model for solving is proposed
Understanding "Understanding" Flow for Network-Centric Warfare: Military Knowledge-Flow Mechanics
National Research Council Canada - National Science Library
Nissen, Mark
2002-01-01
Network-centric warfare (NCW) emphasizes information superiority for battlespace efficacy, but it is clear that the mechanics of how knowledge flows are just as important as those pertaining to the networks and communication...
Complex network analysis of phase dynamics underlying oil-water two-phase flows
Gao, Zhong-Ke; Zhang, Shan-Shan; Cai, Qing; Yang, Yu-Xuan; Jin, Ning-De
2016-01-01
Characterizing the complicated flow behaviors arising from high water cut and low velocity oil-water flows is an important problem of significant challenge. We design a high-speed cycle motivation conductance sensor and carry out experiments for measuring the local flow information from different oil-in-water flow patterns. We first use multivariate time-frequency analysis to probe the typical features of three flow patterns from the perspective of energy and frequency. Then we infer complex networks from multi-channel measurements in terms of phase lag index, aiming to uncovering the phase dynamics governing the transition and evolution of different oil-in-water flow patterns. In particular, we employ spectral radius and weighted clustering coefficient entropy to characterize the derived unweighted and weighted networks and the results indicate that our approach yields quantitative insights into the phase dynamics underlying the high water cut and low velocity oil-water flows. PMID:27306101
Problem solving for wireless sensor networks
Garcia-Hernando, Ana-Belen; Lopez-Navarro, Juan-Manuel; Prayati, Aggeliki; Redondo-Lopez, Luis
2008-01-01
Wireless Sensor Networks (WSN) is an area of huge research interest, attracting substantial attention from industry and academia for its enormous potential and its inherent challenges. This reader-friendly text delivers a comprehensive review of the developments related to the important technological issues in WSN.
Network Monitoring as a Streaming Analytics Problem
Gupta, Arpit; Birkner, Rü diger; Canini, Marco; Feamster, Nick; Mac-Stoker, Chris; Willinger, Walter
2016-01-01
, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have
Bidding for surplus in network allocation problems
Slikker, M.
2007-01-01
In this paper we study non-cooperative foundations of network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some
Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.
Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang
2016-01-01
Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling.
Transitions from Trees to Cycles in Adaptive Flow Networks
DEFF Research Database (Denmark)
Martens, Erik Andreas; Klemm, Konstantin
2017-01-01
-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization...... principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances). We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable......Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real...
Flow-shop scheduling problem under uncertainties: Review and trends
Eliana María González-Neira; Jairo R. Montoya-Torres; David Barrera
2017-01-01
Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of co...
Reliability-oriented multi-resource allocation in a stochastic-flow network
International Nuclear Information System (INIS)
Hsieh, C.-C.; Lin, M.-H.
2003-01-01
A stochastic-flow network consists of a set of nodes, including source nodes which supply various resources and sink nodes at which resource demands take place, and a collection of arcs whose capacities have multiple operational states. The network reliability of such a stochastic-flow network is the probability that resources can be successfully transmitted from source nodes through multi-capacitated arcs to sink nodes. Although the evaluation schemes of network reliability in stochastic-flow networks have been extensively studied in the literature, how to allocate various resources at source nodes in a reliable means remains unanswered. In this study, a resource allocation problem in a stochastic-flow network is formulated that aims to determine the optimal resource allocation policy at source nodes subject to given resource demands at sink nodes such that the network reliability of the stochastic-flow network is maximized, and an algorithm for computing the optimal resource allocation is proposed that incorporates the principle of minimal path vectors. A numerical example is given to illustrate the proposed algorithm
Network capacity auctions: promise and problems
International Nuclear Information System (INIS)
Newbery, David M.
2003-01-01
Well-designed auctions work favorably for allocating idiosyncratic properties efficiently. Auctions are used to allocate entry capacity for United Kingdom gas and inter-connector capacity for electricity in several European Union countries and can work well for allocating existing capacity, though careful auction design is needed to mitigate potential market power. Using auction prices to guide investment decisions in networks is problematic if bidders fear that sub-optimal investment will be compensated by regulatory fiat, lowering future capacity values. (Author)
Heuristics for no-wait flow shop scheduling problem
Directory of Open Access Journals (Sweden)
Kewal Krishan Nailwal
2016-09-01
Full Text Available No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard’s benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard’s instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.
Numerical Leak Detection in a Pipeline Network of Complex Structure with Unsteady Flow
Aida-zade, K. R.; Ashrafova, E. R.
2017-12-01
An inverse problem for a pipeline network of complex loopback structure is solved numerically. The problem is to determine the locations and amounts of leaks from unsteady flow characteristics measured at some pipeline points. The features of the problem include impulse functions involved in a system of hyperbolic differential equations, the absence of classical initial conditions, and boundary conditions specified as nonseparated relations between the states at the endpoints of adjacent pipeline segments. The problem is reduced to a parametric optimal control problem without initial conditions, but with nonseparated boundary conditions. The latter problem is solved by applying first-order optimization methods. Results of numerical experiments are presented.
SOCIAL NETWORK OPTIMIZATION A NEW METHAHEURISTIC FOR GENERAL OPTIMIZATION PROBLEMS
Directory of Open Access Journals (Sweden)
Hassan Sherafat
2017-12-01
Full Text Available In the recent years metaheuristics were studied and developed as powerful technics for hard optimization problems. Some of well-known technics in this field are: Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, and Swarm Intelligence, which are applied successfully to many complex optimization problems. In this paper, we introduce a new metaheuristic for solving such problems based on social networks concept, named as Social Network Optimization – SNO. We show that a wide range of np-hard optimization problems may be solved by SNO.
Optimal power flow for distribution networks with distributed generation
Directory of Open Access Journals (Sweden)
Radosavljević Jordan
2015-01-01
Full Text Available This paper presents a genetic algorithm (GA based approach for the solution of the optimal power flow (OPF in distribution networks with distributed generation (DG units, including fuel cells, micro turbines, diesel generators, photovoltaic systems and wind turbines. The OPF is formulated as a nonlinear multi-objective optimization problem with equality and inequality constraints. Due to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties, a probabilisticalgorithm is introduced in the OPF analysis. The Weibull and normal distributions are employed to model the input random variables, namely the wind speed, solar irradiance and load power. The 2m+1 point estimate method and the Gram Charlier expansion theory are used to obtain the statistical moments and the probability density functions (PDFs of the OPF results. The proposed approach is examined and tested on a modified IEEE 34 node test feeder with integrated five different DG units. The obtained results prove the efficiency of the proposed approach to solve both deterministic and probabilistic OPF problems for different forms of the multi-objective function. As such, it can serve as a useful decision-making supporting tool for distribution network operators. [Projekat Ministarstva nauke Republike Srbije, br. TR33046
Controlled neural network application in track-match problem
International Nuclear Information System (INIS)
Baginyan, S.A.; Ososkov, G.A.
1993-01-01
Track-match problem of high energy physics (HEP) data handling is formulated in terms of incidence matrices. The corresponding Hopfield neural network is developed to solve this type of constraint satisfaction problems (CSP). A special concept of the controlled neural network is proposed as a basis of an algorithm for the effective CSP solution. Results of comparable calculations show the very high performance of this algorithm against conventional search procedures. 8 refs.; 1 fig.; 1 tab
Cellular neural networks for the stereo matching problem
International Nuclear Information System (INIS)
Taraglio, S.; Zanela, A.
1997-03-01
The applicability of the Cellular Neural Network (CNN) paradigm to the problem of recovering information on the tridimensional structure of the environment is investigated. The approach proposed is the stereo matching of video images. The starting point of this work is the Zhou-Chellappa neural network implementation for the same problem. The CNN based system we present here yields the same results as the previous approach, but without the many existing drawbacks
Problems in the Deployment of Learning Networks In Small Organizations
Shankle, Dean E.; Shankle, Jeremy P.
2006-01-01
Please, cite this publication as: Shankle, D.E., & Shankle, J.P. (2006). Problems in the Deployment of Learning Networks In Small Organizations. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria:
Information Flow Between Resting-State Networks.
Diez, Ibai; Erramuzpe, Asier; Escudero, Iñaki; Mateos, Beatriz; Cabrera, Alberto; Marinazzo, Daniele; Sanz-Arigita, Ernesto J; Stramaglia, Sebastiano; Cortes Diaz, Jesus M
2015-11-01
The resting brain dynamics self-organize into a finite number of correlated patterns known as resting-state networks (RSNs). It is well known that techniques such as independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method to compute the information flow (IF) between different RSNs from resting-state magnetic resonance imaging. After hemodynamic response function blind deconvolution of all voxel signals, and under the hypothesis that RSNs define regions of interest, our method first uses principal component analysis to reduce dimensionality in each RSN to next compute IF (estimated here in terms of transfer entropy) between the different RSNs by systematically increasing k (the number of principal components used in the calculation). When k=1, this method is equivalent to computing IF using the average of all voxel activities in each RSN. For k≥1, our method calculates the k multivariate IF between the different RSNs. We find that the average IF among RSNs is dimension dependent, increasing from k=1 (i.e., the average voxel activity) up to a maximum occurring at k=5 and to finally decay to zero for k≥10. This suggests that a small number of components (close to five) is sufficient to describe the IF pattern between RSNs. Our method--addressing differences in IF between RSNs for any generic data--can be used for group comparison in health or disease. To illustrate this, we have calculated the inter-RSN IF in a data set of Alzheimer's disease (AD) to find that the most significant differences between AD and controls occurred for k=2, in addition to AD showing increased IF w.r.t. The spatial localization of the k=2 component, within RSNs, allows the characterization of IF differences between AD and controls.
Solving constraint satisfaction problems with networks of spiking neurons
Directory of Open Access Journals (Sweden)
Zeno eJonke
2016-03-01
Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.
A trust region interior point algorithm for optimal power flow problems
Energy Technology Data Exchange (ETDEWEB)
Wang Min [Hefei University of Technology (China). Dept. of Electrical Engineering and Automation; Liu Shengsong [Jiangsu Electric Power Dispatching and Telecommunication Company (China). Dept. of Automation
2005-05-01
This paper presents a new algorithm that uses the trust region interior point method to solve nonlinear optimal power flow (OPF) problems. The OPF problem is solved by a primal/dual interior point method with multiple centrality corrections as a sequence of linearized trust region sub-problems. It is the trust region that controls the linear step size and ensures the validity of the linear model. The convergence of the algorithm is improved through the modification of the trust region sub-problem. Numerical results of standard IEEE systems and two realistic networks ranging in size from 14 to 662 buses are presented. The computational results show that the proposed algorithm is very effective to optimal power flow applications, and favors the successive linear programming (SLP) method. Comparison with the predictor/corrector primal/dual interior point (PCPDIP) method is also made to demonstrate the superiority of the multiple centrality corrections technique. (author)
Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Tao Ren
2012-01-01
Full Text Available This paper considers the m-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.
Algorithms for Scheduling and Network Problems
1991-09-01
time. We already know, by Lemma 2.2.1, that WOPT = O(log( mpU )), so if we could solve this integer program optimally we would be done. However, the...Folydirat, 15:177-191, 1982. [6] I.S. Belov and Ya. N. Stolin. An algorithm in a single path operations scheduling problem. In Mathematical Economics and
Analysing Stagecoach Network Problem Using Dynamic ...
African Journals Online (AJOL)
In this paper we present a recursive dynamic programming algorithm for solving the stagecoach problem. The algorithm is computationally more efficient than the first method as it obtains its minimum total cost using the suboptimal policies of the different stages without computing the cost of all the routes. By the dynamic ...
A neural network approach to the orienteering problem
Energy Technology Data Exchange (ETDEWEB)
Golden, B.; Wang, Q.; Sun, X.; Jia, J.
1994-12-31
In the orienteering problem, we are given a transportation network in which a start point and an end point are specified. Other points have associated scores. Given a fixed amount of time, the goal is to determine a path from start to end through a subset of locations in order to maximize the total path score. This problem has received a considerable amount of attention in the last ten years. The TSP is a variant of the orienteering problem. This paper applies a modified, continuous Hopfield neural network to attack this NP-hard optimization problem. In it, we design an effective energy function and learning algorithm. Unlike some applications of neural networks to optimization problems, this approach is shown to perform quite well.
Analytical methods for heat transfer and fluid flow problems
Weigand, Bernhard
2015-01-01
This book describes useful analytical methods by applying them to real-world problems rather than solving the usual over-simplified classroom problems. The book demonstrates the applicability of analytical methods even for complex problems and guides the reader to a more intuitive understanding of approaches and solutions. Although the solution of Partial Differential Equations by numerical methods is the standard practice in industries, analytical methods are still important for the critical assessment of results derived from advanced computer simulations and the improvement of the underlying numerical techniques. Literature devoted to analytical methods, however, often focuses on theoretical and mathematical aspects and is therefore useless to most engineers. Analytical Methods for Heat Transfer and Fluid Flow Problems addresses engineers and engineering students. The second edition has been updated, the chapters on non-linear problems and on axial heat conduction problems were extended. And worked out exam...
Reconstructing the Hopfield network as an inverse Ising problem
International Nuclear Information System (INIS)
Huang Haiping
2010-01-01
We test four fast mean-field-type algorithms on Hopfield networks as an inverse Ising problem. The equilibrium behavior of Hopfield networks is simulated through Glauber dynamics. In the low-temperature regime, the simulated annealing technique is adopted. Although performances of these network reconstruction algorithms on the simulated network of spiking neurons are extensively studied recently, the analysis of Hopfield networks is lacking so far. For the Hopfield network, we found that, in the retrieval phase favored when the network wants to memory one of stored patterns, all the reconstruction algorithms fail to extract interactions within a desired accuracy, and the same failure occurs in the spin-glass phase where spurious minima show up, while in the paramagnetic phase, albeit unfavored during the retrieval dynamics, the algorithms work well to reconstruct the network itself. This implies that, as an inverse problem, the paramagnetic phase is conversely useful for reconstructing the network while the retrieval phase loses all the information about interactions in the network except for the case where only one pattern is stored. The performances of algorithms are studied with respect to the system size, memory load, and temperature; sample-to-sample fluctuations are also considered.
Flow distributions and spatial correlations in human brain capillary networks
Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy
2015-11-01
The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.
Cilia driven flow networks in the brain
Wang, Yong; Faubel, Regina; Westendorf, Chrsitian; Eichele, Gregor; Bodenschatz, Eberhard
Neurons exchange soluble substances via the cerebrospinal fluid (CSF) that fills the ventricular system. The walls of the ventricular cavities are covered with motile cilia that constantly beat and thereby induce a directional flow. We recently discovered that cilia in the third ventricle generate a complex flow pattern leading to partitioning of the ventricular volume and site-directed transport paths along the walls. Transient and daily recurrent alterations in the cilia beating direction lead to changes in the flow pattern. This has consequences for delivery of CSF components along the near wall flow. The contribution of this cilia-induced flow to overall CSF flow remains to be investigated. The state-of-art lattice Boltzmann method is adapted for studying the CFS flow. The 3D geometry of the third ventricle at high resolution was reconstructed. Simulation of CSF flow without cilia in this geometry confirmed that the previous idea about unidirectional flow does not explain how different components of CSF can be delivered to their various target sites. We study the contribution of the cilia-induced flow pattern to overall CSF flow and identify target areas for site-specific delivery of CSF-constituents with respect to the temporal changes.
Computer network prepared to handle massive data flow
2006-01-01
"Massive quantities of data will soon begin flowing from the largest scientific instrument ever built into an internationl network of computer centers, including one operated jointly by the University of Chicago and Indiana University." (2 pages)
Intelligent Network Flow Optimization (INFLO) prototype acceptance test summary.
2015-05-01
This report summarizes the results of System Acceptance Testing for the implementation of the Intelligent Network : Flow Optimization (INFLO) Prototype bundle within the Dynamic Mobility Applications (DMA) portion of the Connected : Vehicle Program. ...
Validating User Flows to Protect Software Defined Network Environments
Directory of Open Access Journals (Sweden)
Ihsan H. Abdulqadder
2018-01-01
Full Text Available Software Defined Network is a promising network paradigm which has led to several security threats in SDN applications that involve user flows, switches, and controllers in the network. Threats as spoofing, tampering, information disclosure, Denial of Service, flow table overloading, and so on have been addressed by many researchers. In this paper, we present novel SDN design to solve three security threats: flow table overloading is solved by constructing a star topology-based architecture, unsupervised hashing method mitigates link spoofing attack, and fuzzy classifier combined with L1-ELM running on a neural network for isolating anomaly packets from normal packets. For effective flow migration Discrete-Time Finite-State Markov Chain model is applied. Extensive simulations using OMNeT++ demonstrate the performance of our proposed approach, which is better at preserving holding time than are other state-of-the-art works from the literature.
On Event Detection and Localization in Acyclic Flow Networks
Suresh, Mahima Agumbe; Stoleru, Radu; Zechman, Emily M.; Shihada, Basem
2013-01-01
Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against
Network Flow Simulation of Fluid Transients in Rocket Propulsion Systems
Bandyopadhyay, Alak; Hamill, Brian; Ramachandran, Narayanan; Majumdar, Alok
2011-01-01
Fluid transients, also known as water hammer, can have a significant impact on the design and operation of both spacecraft and launch vehicle propulsion systems. These transients often occur at system activation and shutdown. The pressure rise due to sudden opening and closing of valves of propulsion feed lines can cause serious damage during activation and shutdown of propulsion systems. During activation (valve opening) and shutdown (valve closing), pressure surges must be predicted accurately to ensure structural integrity of the propulsion system fluid network. In the current work, a network flow simulation software (Generalized Fluid System Simulation Program) based on Finite Volume Method has been used to predict the pressure surges in the feed line due to both valve closing and valve opening using two separate geometrical configurations. The valve opening pressure surge results are compared with experimental data available in the literature and the numerical results compared very well within reasonable accuracy (< 5%) for a wide range of inlet-to-initial pressure ratios. A Fast Fourier Transform is preformed on the pressure oscillations to predict the various modal frequencies of the pressure wave. The shutdown problem, i.e. valve closing problem, the simulation results are compared with the results of Method of Characteristics. Most rocket engines experience a longitudinal acceleration, known as "pogo" during the later stage of engine burn. In the shutdown example problem, an accumulator has been used in the feed system to demonstrate the "pogo" mitigation effects in the feed system of propellant. The simulation results using GFSSP compared very well with the results of Method of Characteristics.
Flow Regime Identification of Co-Current Downward Two-Phase Flow With Neural Network Approach
International Nuclear Information System (INIS)
Hiroshi Goda; Seungjin Kim; Ye Mi; Finch, Joshua P.; Mamoru Ishii; Jennifer Uhle
2002-01-01
Flow regime identification for an adiabatic vertical co-current downward air-water two-phase flow in the 25.4 mm ID and the 50.8 mm ID round tubes was performed by employing an impedance void meter coupled with the neural network classification approach. This approach minimizes the subjective judgment in determining the flow regimes. The signals obtained by an impedance void meter were applied to train the self-organizing neural network to categorize these impedance signals into a certain number of groups. The characteristic parameters set into the neural network classification included the mean, standard deviation and skewness of impedance signals in the present experiment. The classification categories adopted in the present investigation were four widely accepted flow regimes, viz. bubbly, slug, churn-turbulent, and annular flows. These four flow regimes were recognized based upon the conventional flow visualization approach by a high-speed motion analyzer. The resulting flow regime maps classified by the neural network were compared with the results obtained through the flow visualization method, and consequently the efficiency of the neural network classification for flow regime identification was demonstrated. (authors)
The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
Energy Technology Data Exchange (ETDEWEB)
Kim, M; Leskovec, J
2011-11-14
Network structures, such as social networks, web graphs and networks from systems biology, play important roles in many areas of science and our everyday lives. In order to study the networks one needs to first collect reliable large scale network data. While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomplete with nodes and edges missing. Commonly, only a part of the network can be observed and we would like to infer the unobserved part of the network. We address this issue by studying the Network Completion Problem: Given a network with missing nodes and edges, can we complete the missing part? We cast the problem in the Expectation Maximization (EM) framework where we use the observed part of the network to fit a model of network structure, and then we estimate the missing part of the network using the model, re-estimate the parameters and so on. We combine the EM with the Kronecker graphs model and design a scalable Metropolized Gibbs sampling approach that allows for the estimation of the model parameters as well as the inference about missing nodes and edges of the network. Experiments on synthetic and several real-world networks show that our approach can effectively recover the network even when about half of the nodes in the network are missing. Our algorithm outperforms not only classical link-prediction approaches but also the state of the art Stochastic block modeling approach. Furthermore, our algorithm easily scales to networks with tens of thousands of nodes.
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
An Algorithm for the Mixed Transportation Network Design Problem.
Directory of Open Access Journals (Sweden)
Xinyu Liu
Full Text Available This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA, for solving a mixed transportation network design problem (MNDP, which is generally expressed as a mathematical programming with equilibrium constraint (MPEC. The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE problem. The idea of the proposed solution algorithm (DDIA is to reduce the dimensions of the problem. A group of variables (discrete/continuous is fixed to optimize another group of variables (continuous/discrete alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems and DNDPs (discrete network design problems repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions. Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
Performance of Flow-Aware Networking in LTE backbone
DEFF Research Database (Denmark)
Sniady, Aleksander; Soler, José
2012-01-01
technologies, such as Long Term Evolution (LTE). This paper proposes usage of a modified Flow Aware Networking (FAN) technique for enhancing Quality of Service (QoS) in the all-IP transport networks underlying LTE backbone. The results obtained with OPNET Modeler show that FAN, in spite of being relatively...
Transitions from Trees to Cycles in Adaptive Flow Networks
DEFF Research Database (Denmark)
Martens, Erik Andreas; Klemm, Konstantin
2017-01-01
. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two......Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real......-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization...
Topology optimization of 3D Stokes flow problems
DEFF Research Database (Denmark)
Gersborg-Hansen, Allan; Sigmund, Ole; Bendsøe, Martin P.
fluid mechanics. In future practice a muTAS could be used by doctors, engineers etc. as a hand held device with short reaction time that provides on-site analysis of a flowing substance such as blood, polluted water or similar. Borrvall and Petersson [2] paved the road for using the topology...... particular at micro scales since they are easily manufacturable and maintenance free. Here we consider topology optimization of 3D Stokes flow problems which is a reasonable fluid model to use at small scales. The presentation elaborates on effects caused by 3D fluid modelling on the design. Numerical...
Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.
Bacik, Karol A; Schaub, Michael T; Beguerisse-Díaz, Mariano; Billeh, Yazan N; Barahona, Mauricio
2016-08-01
We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios.
Transitions from Trees to Cycles in Adaptive Flow Networks
Directory of Open Access Journals (Sweden)
Erik A. Martens
2017-11-01
Full Text Available Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances. We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two distinct regions with cyclic and tree-like structures. The location of the boundary between these two regions is determined by the amplitude of the fluctuations. These findings may explain why natural transport networks display cyclic structures in the micro-vascular regions near terminal nodes, but tree-like features in the regions with larger veins.
A Cross Layer Solution to Address TCP Intra-flow Performance Degradation in Multihop Ad hoc Networks
Rakocevic, V.; Hamadani, E.
2008-01-01
Incorporating the concept of TCP end-to-end congestion control for wireless networks is one of the primary concerns in designing ad hoc networks since TCP was primarily designed and optimized based on the assumptions for wired networks. In this study, our interest lies on tackling the TCP instability and in particular intra-flow instability problem since due to the nature of applications in multihop ad hoc networks, connection instability or starvation even for a short period of time can have...
Bi and tri-objective optimization in the deterministic network interdiction problem
International Nuclear Information System (INIS)
Rocco S, Claudio M.; Emmanuel Ramirez-Marquez, Jose; Salazar A, Daniel E.
2010-01-01
Solution approaches to the deterministic network interdiction problem have previously been developed for optimizing a single figure-of-merit of the network configuration (i.e. flow that can be transmitted between a source node and a sink node for a fixed network design) under constraints related to limited amount of resources available to interdict network links. These approaches work under the assumption that: (1) nominal capacity of each link is completely reduced when interdicted and (2) there is a single criterion to optimize. This paper presents a newly developed evolutionary algorithm that for the first time allows solving multi-objective optimization models for the design of network interdiction strategies that take into account a variety of figures-of-merit. The algorithm provides an approximation to the optimal Pareto frontier using: (a) techniques in Monte Carlo simulation to generate potential network interdiction strategies, (b) graph theory to analyze strategies' maximum source-sink flow and (c) an evolutionary search that is driven by the probability that a link will belong to the optimal Pareto set. Examples for different sizes of networks and network behavior are used throughout the paper to illustrate and validate the approach.
Neural network for solving convex quadratic bilevel programming problems.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie
2014-03-01
In this paper, using the idea of successive approximation, we propose a neural network to solve convex quadratic bilevel programming problems (CQBPPs), which is modeled by a nonautonomous differential inclusion. Different from the existing neural network for CQBPP, the model has the least number of state variables and simple structure. Based on the theory of nonsmooth analysis, differential inclusions and Lyapunov-like method, the limit equilibrium points sequence of the proposed neural networks can approximately converge to an optimal solution of CQBPP under certain conditions. Finally, simulation results on two numerical examples and the portfolio selection problem show the effectiveness and performance of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.
New approach for simulating groundwater flow in discrete fracture network
Fang, H.; Zhu, J.
2017-12-01
In this study, we develop a new approach to calculate groundwater flowrate and hydraulic head distribution in two-dimensional discrete fracture network (DFN) where both laminar and turbulent flows co-exist in individual fractures. The cubic law is used to calculate hydraulic head distribution and flow behaviors in fractures where flow is laminar, while the Forchheimer's law is used to quantify turbulent flow behaviors. Reynolds number is used to distinguish flow characteristics in individual fractures. The combination of linear and non-linear equations is solved iteratively to determine flowrates in all fractures and hydraulic heads at all intersections. We examine potential errors in both flowrate and hydraulic head from the approach of uniform flow assumption. Applying the cubic law in all fractures regardless of actual flow conditions overestimates the flowrate when turbulent flow may exist while applying the Forchheimer's law indiscriminately underestimate the flowrate when laminar flows exist in the network. The contrast of apertures of large and small fractures in the DFN has significant impact on the potential errors of using only the cubic law or the Forchheimer's law. Both the cubic law and Forchheimer's law simulate similar hydraulic head distributions as the main difference between these two approaches lies in predicting different flowrates. Fracture irregularity does not significantly affect the potential errors from using only the cubic law or the Forchheimer's law if network configuration remains similar. Relative density of fractures does not significantly affect the relative performance of the cubic law and Forchheimer's law.
Social networking sites: an adjunctive treatment modality for psychological problems.
Menon, Indu S; Sharma, Manoj Kumar; Chandra, Prabha S; Thennarasu, K
2014-07-01
Social networking is seen as a way to enhance social support and feeling of well-being. The present work explores the potentials of social networking sites as an adjunctive treatment modality for initiating treatment contact as well as for managing psychological problems. Interview schedule, Facebook intensity questionnaire were administered on 28 subjects with a combination of 18 males and 10 females. They were taken from the in-patient and out-patient psychiatry setting of the hospital. Facebook was the most popular sites and used to seek emotional support on the basis of the frequent updates of emotional content that users put in their profile; reconciliations, escape from the problems or to manage the loneliness; getting information about illness and its treatment and interaction with experts and also manifested as problematic use. It has implications for developing social networking based adjunctive treatment modality for psychological problems.
Bridging Minds: A Mixed Methodology to Assess Networked Flow.
Galimberti, Carlo; Chirico, Alice; Brivio, Eleonora; Mazzoni, Elvis; Riva, Giuseppe; Milani, Luca; Gaggioli, Andrea
2015-01-01
The main goal of this contribution is to present a methodological framework to study Networked Flow, a bio-psycho-social theory of collective creativity applying it on creative processes occurring via a computer network. First, we draw on the definition of Networked Flow to identify the key methodological requirements of this model. Next, we present the rationale of a mixed methodology, which aims at combining qualitative, quantitative and structural analysis of group dynamics to obtain a rich longitudinal dataset. We argue that this integrated strategy holds potential for describing the complex dynamics of creative collaboration, by linking the experiential features of collaborative experience (flow, social presence), with the structural features of collaboration dynamics (network indexes) and the collaboration outcome (the creative product). Finally, we report on our experience with using this methodology in blended collaboration settings (including both face-to-face and virtual meetings), to identify open issues and provide future research directions.
Progress with multigrid schemes for hypersonic flow problems
International Nuclear Information System (INIS)
Radespiel, R.; Swanson, R.C.
1995-01-01
Several multigrid schemes are considered for the numerical computation of viscous hypersonic flows. For each scheme, the basic solution algorithm employs upwind spatial discretization with explicit multistage time stepping. Two-level versions of the various multigrid algorithms are applied to the two-dimensional advection equation, and Fourier analysis is used to determine their damping properties. The capabilities of the multigrid methods are assessed by solving three different hypersonic flow problems. Some new multigrid schemes based on semicoarsening strategies are shown to be quite effective in relieving the stiffness caused by the high-aspect-ratio cells required to resolve high Reynolds number flows. These schemes exhibit good convergence rates for Reynolds numbers up to 200 X 10 6 and Mach numbers up to 25. 32 refs., 31 figs., 1 tab
Finite element approximation to a model problem of transonic flow
International Nuclear Information System (INIS)
Tangmanee, S.
1986-12-01
A model problem of transonic flow ''the Tricomi equation'' in Ω is contained in IR 2 bounded by the rectangular-curve boundary is posed in the form of symmetric positive differential equations. The finite element method is then applied. When the triangulation of Ω-bar is made of quadrilaterals and the approximation space is the Lagrange polynomial, we get the error estimates. 14 refs, 1 fig
Observation and inverse problems in coupled cell networks
International Nuclear Information System (INIS)
Joly, Romain
2012-01-01
A coupled cell network is a model for many situations such as food webs in ecosystems, cellular metabolism and economic networks. It consists in a directed graph G, each node (or cell) representing an agent of the network and each directed arrow representing which agent acts on which. It yields a system of differential equations .x(t)=f(x(t)), where the component i of f depends only on the cells x j (t) for which the arrow j → i exists in G. In this paper, we investigate the observation problems in coupled cell networks: can one deduce the behaviour of the whole network (oscillations, stabilization, etc) by observing only one of the cells? We show that the natural observation properties hold for almost all the interactions f
Flow-shop scheduling problem under uncertainties: Review and trends
Directory of Open Access Journals (Sweden)
Eliana María González-Neira
2017-03-01
Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.
Neural network modeling for near wall turbulent flow
International Nuclear Information System (INIS)
Milano, Michele; Koumoutsakos, Petros
2002-01-01
A neural network methodology is developed in order to reconstruct the near wall field in a turbulent flow by exploiting flow fields provided by direct numerical simulations. The results obtained from the neural network methodology are compared with the results obtained from prediction and reconstruction using proper orthogonal decomposition (POD). Using the property that the POD is equivalent to a specific linear neural network, a nonlinear neural network extension is presented. It is shown that for a relatively small additional computational cost nonlinear neural networks provide us with improved reconstruction and prediction capabilities for the near wall velocity fields. Based on these results advantages and drawbacks of both approaches are discussed with an outlook toward the development of near wall models for turbulence modeling and control
Network flow of mobile agents enhances the evolution of cooperation
Ichinose, G.; Satotani, Y.; Nagatani, T.
2018-01-01
We study the effect of contingent movement on the persistence of cooperation on complex networks with empty nodes. Each agent plays the Prisoner's Dilemma game with its neighbors and then it either updates the strategy depending on the payoff difference with neighbors or it moves to another empty node if not satisfied with its own payoff. If no neighboring node is empty, each agent stays at the same site. By extensive evolutionary simulations, we show that the medium density of agents enhances cooperation where the network flow of mobile agents is also medium. Moreover, if the movements of agents are more frequent than the strategy updating, cooperation is further promoted. In scale-free networks, the optimal density for cooperation is lower than other networks because agents get stuck at hubs. Our study suggests that keeping a smooth network flow is significant for the persistence of cooperation in ever-changing societies.
Towards Effective Intra-flow Network Coding in Software Defined Wireless Mesh Networks
Donghai Zhu; Xinyu Yang Yang; Peng Zhao; Wei Yu
2016-01-01
Wireless Mesh Networks (WMNs) have potential to provide convenient broadband wireless Internet access to mobile users.With the support of Software-Defined Networking (SDN) paradigm that separates control plane and data plane, WMNs can be easily deployed and managed. In addition, by exploiting the broadcast nature of the wireless medium and the spatial diversity of multi-hop wireless networks, intra-flow network coding has shown a greater benefit in comparison with traditional routing paradigm...
Smooth Information Flow in Temperature Climate Network Reflects Mass Transport
Czech Academy of Sciences Publication Activity Database
Hlinka, Jaroslav; Jajcay, Nikola; Hartman, David; Paluš, Milan
2017-01-01
Roč. 27, č. 3 (2017), č. článku 035811. ISSN 1054-1500 R&D Projects: GA ČR GCP103/11/J068; GA MŠk LH14001 Institutional support: RVO:67985807 Keywords : directed network * causal network * Granger causality * climate network * information flow * temperature network Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.283, year: 2016
Numerical simulation for gas-liquid two-phase flow in pipe networks
International Nuclear Information System (INIS)
Li Xiaoyan; Kuang Bo; Zhou Guoliang; Xu Jijun
1998-01-01
The complex pipe network characters can not directly presented in single phase flow, gas-liquid two phase flow pressure drop and void rate change model. Apply fluid network theory and computer numerical simulation technology to phase flow pipe networks carried out simulate and compute. Simulate result shows that flow resistance distribution is non-linear in two phase pipe network
Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto
2018-01-12
This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.
Pricing and Capacity Planning Problems in Energy Transmission Networks
DEFF Research Database (Denmark)
Villumsen, Jonas Christoffer
strategy. In the Nordic electricity system a market with zonal prices is adopted. We consider the problem of designing zones in an optimal way explicitly considering uncertainty. Finally, we formulate the integrated problem of pipeline capacity expansion planning and transmission pricing in natural gas...... necessitates a radical change in the way we plan and operate energy systems. Another paradigm change which began in the 1990’s for electricity systems is that of deregulation. This has led to a variety of different market structures implemented across the world. In this thesis we discuss capacity planning...... and transmission pricing problems in energy transmission networks. Although the modelling framework applies to energy networks in general, most of the applications discussed concern the transmission of electricity. A number of the problems presented involves transmission switching, which allows the operator...
An outer approximation method for the road network design problem.
Asadi Bagloee, Saeed; Sarvi, Majid
2018-01-01
Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.
Gao, Zhong-Ke; Yang, Yu-Xuan; Cai, Qing; Zhang, Shan-Shan; Jin, Ning-De
2016-06-01
Exploring the dynamical behaviors of high water cut and low velocity oil-water flows remains a contemporary and challenging problem of significant importance. This challenge stimulates us to design a high-speed cycle motivation conductance sensor to capture spatial local flow information. We systematically carry out experiments and acquire the multi-channel measurements from different oil-water flow patterns. Then we develop a novel multivariate weighted recurrence network for uncovering the flow behaviors from multi-channel measurements. In particular, we exploit graph energy and weighted clustering coefficient in combination with multivariate time-frequency analysis to characterize the derived complex networks. The results indicate that the network measures are very sensitive to the flow transitions and allow uncovering local dynamical behaviors associated with water cut and flow velocity. These properties render our method particularly useful for quantitatively characterizing dynamical behaviors governing the transition and evolution of different oil-water flow patterns.
Introduction to Focus Issue: Complex network perspectives on flow systems.
Donner, Reik V; Hernández-García, Emilio; Ser-Giacomi, Enrico
2017-03-01
During the last few years, complex network approaches have demonstrated their great potentials as versatile tools for exploring the structural as well as dynamical properties of dynamical systems from a variety of different fields. Among others, recent successful examples include (i) functional (correlation) network approaches to infer hidden statistical interrelationships between macroscopic regions of the human brain or the Earth's climate system, (ii) Lagrangian flow networks allowing to trace dynamically relevant fluid-flow structures in atmosphere, ocean or, more general, the phase space of complex systems, and (iii) time series networks unveiling fundamental organization principles of dynamical systems. In this spirit, complex network approaches have proven useful for data-driven learning of dynamical processes (like those acting within and between sub-components of the Earth's climate system) that are hidden to other analysis techniques. This Focus Issue presents a collection of contributions addressing the description of flows and associated transport processes from the network point of view and its relationship to other approaches which deal with fluid transport and mixing and/or use complex network techniques.
Constraints of nonresponding flows based on cross layers in the networks
Zhou, Zhi-Chao; Xiao, Yang; Wang, Dong
2016-02-01
In the active queue management (AQM) scheme, core routers cannot manage and constrain user datagram protocol (UDP) data flows by the sliding window control mechanism in the transport layer due to the nonresponsive nature of such traffic flows. However, the UDP traffics occupy a large part of the network service nowadays which brings a great challenge to the stability of the more and more complex networks. To solve the uncontrollable problem, this paper proposes a cross layers random early detection (CLRED) scheme, which can control the nonresponding UDP-like flows rate effectively when congestion occurs in the access point (AP). The CLRED makes use of the MAC frame acknowledgement (ACK) transmitting congestion information to the sources nodes and utilizes the back-off windows of the MAC layer throttling data rate. Consequently, the UDP-like flows data rate can be restrained timely by the sources nodes in order to alleviate congestion in the complex networks. The proposed CLRED can constrain the nonresponsive flows availably and make the communication expedite, so that the network can sustain stable. The simulation results of network simulator-2 (NS2) verify the proposed CLRED scheme.
The application of neural networks to flow regime identification
International Nuclear Information System (INIS)
Embrechts, M.; Yapo, T.C.; Lahey, R.T. Jr.
1993-01-01
This paper deals with the application of a Kohonen map for the identification of two-phase flow regimes where a mixture of gas and fluid flows through a horizontal tube. Depending on the relative flow velocities of the gas and the liquid phase, four distinct flow regimes can be identified: Wavy flow, plug flow, slug flow and annular flow. A schematic of these flow regimes is presented. The objective identification of two-phase flow regimes constitutes an important and challenging problem for the design of safe and reliable nuclear power plants. Previous attempts to classify these flow regimes are reviewed by Franca and Lahey. The authors describe how a Kohonen map can be applied to distinguish between flow regimes based on the Fourier power spectra and wavelet transforms of pressure drop fluctuations. The Fourier power spectra allowed the Kohonen map to identify the flow regimes successfully. In contrast, the Kohonen maps based on a wavelet transform could only distinguish between wavy and annular flows. An analysis of typical two-phase pressure drop data for an air/water mixture in a horizontal pipe is presented. Use of the wavelet transform and the Kohonen feature map are discussed
On generalizations of network design problems with degree bounds
Bansal, N.; Khandekar, R.; Könemann, J.; Nagarajan, V.; Peis, B.
2013-01-01
Iterative rounding and relaxation have arguably become the method of choice in dealing with unconstrained and constrained network design problems. In this paper we extend the scope of the iterative relaxation method in two directions: (1) by handling more complex degree constraints in the minimum
On generalizations of network design problems with degree bounds
N. Bansal (Nikhil); R. Khandekar; J. Könemann (Jochen); V. Nagarajan; B. Peis
2013-01-01
htmlabstractIterative rounding and relaxation have arguably become the method of choice in dealing with unconstrained and constrained network design problems. In this paper we extend the scope of the iterative relaxation method in two directions: (1) by handling more complex degree constraints in
Loan and nonloan flows in the Australian interbank network
Sokolov, Andrey; Webster, Rachel; Melatos, Andrew; Kieu, Tien
2012-05-01
High-value transactions between banks in Australia are settled in the Reserve Bank Information and Transfer System (RITS) administered by the Reserve Bank of Australia. RITS operates on a real-time gross settlement (RTGS) basis and settles payments and transfers sourced from the SWIFT payment delivery system, the Austraclear securities settlement system, and the interbank transactions entered directly into RITS. In this paper, we analyse a dataset received from the Reserve Bank of Australia that includes all interbank transactions settled in RITS on an RTGS basis during five consecutive weekdays from 19 February 2007 inclusive, a week of relatively quiescent market conditions. The source, destination, and value of each transaction are known, which allows us to separate overnight loans from other transactions (nonloans) and reconstruct monetary flows between banks for every day in our sample. We conduct a novel analysis of the flow stability and examine the connection between loan and nonloan flows. Our aim is to understand the underlying causal mechanism connecting loan and nonloan flows. We find that the imbalances in the banks' exchange settlement funds resulting from the daily flows of nonloan transactions are almost exactly counterbalanced by the flows of overnight loans. The correlation coefficient between loan and nonloan imbalances is about -0.9 on most days. Some flows that persist over two consecutive days can be highly variable, but overall the flows are moderately stable in value. The nonloan network is characterised by a large fraction of persistent flows, whereas only half of the flows persist over any two consecutive days in the loan network. Moreover, we observe an unusual degree of coherence between persistent loan flow values on Tuesday and Wednesday. We probe static topological properties of the Australian interbank network and find them consistent with those observed in other countries.
de la Mata, Tamara; Llano, Carlos
2013-07-01
Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.
Ren, Yihui
network and we demonstrate that the changes can propagate globally, affecting traffic several hundreds of miles away. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events. In the second part of the thesis we focus on network deconstruction and community detection problems, both intensely studied topics in network science, using a weighted betweenness centrality approach. We present an algorithm that solves both problems efficiently and accurately and demonstrate that on both benchmark networks and data networks.
A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.
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Huan Chen
Full Text Available This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN. Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.
A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.
Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong
2015-01-01
This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.
Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem
Man, J.; Li, W.; Zeng, L.; Wu, L.
2015-12-01
The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the Polynomial Chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.
Network Analysis of Students' Use of Representations in Problem Solving
McPadden, Daryl; Brewe, Eric
2016-03-01
We present the preliminary results of a study on student use of representations in problem solving within the Modeling Instruction - Electricity and Magnetism (MI-E&M) course. Representational competence is a critical skill needed for students to develop a sophisticated understanding of college science topics and to succeed in their science courses. In this study, 70 students from the MI-E&M, calculus-based course were given a survey of 25 physics problem statements both pre- and post- instruction, covering both Newtonian Mechanics and Electricity and Magnetism (E&M). For each problem statement, students were asked which representations they would use in that given situation. We analyze the survey results through network analysis, identifying which representations are linked together in which contexts. We also compare the representation networks for those students who had already taken the first-semester Modeling Instruction Mechanics course and those students who had taken a non-Modeling Mechanics course.
Evolving neural networks for strategic decision-making problems.
Kohl, Nate; Miikkulainen, Risto
2009-04-01
Evolution of neural networks, or neuroevolution, has been a successful approach to many low-level control problems such as pole balancing, vehicle control, and collision warning. However, certain types of problems-such as those involving strategic decision-making-have remained difficult for neuroevolution to solve. This paper evaluates the hypothesis that such problems are difficult because they are fractured: The correct action varies discontinuously as the agent moves from state to state. A method for measuring fracture using the concept of function variation is proposed and, based on this concept, two methods for dealing with fracture are examined: neurons with local receptive fields, and refinement based on a cascaded network architecture. Experiments in several benchmark domains are performed to evaluate how different levels of fracture affect the performance of neuroevolution methods, demonstrating that these two modifications improve performance significantly. These results form a promising starting point for expanding neuroevolution to strategic tasks.
The stationary flow in a heterogeneous compliant vessel network
International Nuclear Information System (INIS)
Filoche, Marcel; Florens, Magali
2011-01-01
We introduce a mathematical model of the hydrodynamic transport into systems consisting in a network of connected flexible pipes. In each pipe of the network, the flow is assumed to be steady and one-dimensional. The fluid-structure interaction is described through tube laws which relate the pipe diameter to the pressure difference across the pipe wall. We show that the resulting one-dimensional differential equation describing the flow in the pipe can be exactly integrated if one is able to estimate averages of the Reynolds number along the pipe. The differential equation is then transformed into a non linear scalar equation relating pressures at both ends of the pipe and the flow rate in the pipe. These equations are coupled throughout the network with mass conservation equations for the flow and zero pressure losses at the branching points of the network. This allows us to derive a general model for the computation of the flow into very large inhomogeneous networks consisting of several thousands of flexible pipes. This model is then applied to perform numerical simulations of the human lung airway system at exhalation. The topology of the system and the tube laws are taken from morphometric and physiological data in the literature. We find good qualitative and quantitative agreement between the simulation results and flow-volume loops measured in real patients. In particular, expiratory flow limitation which is an essential characteristic of forced expiration is found to be well reproduced by our simulations. Finally, a mathematical model of a pathology (Chronic Obstructive Pulmonary Disease) is introduced which allows us to quantitatively assess the influence of a moderate or severe alteration of the airway compliances.
Field-effect Flow Control in Polymer Microchannel Networks
Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.
2003-01-01
A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.
Augmented neural networks and problem structure-based heuristics for the bin-packing problem
Kasap, Nihat; Agarwal, Anurag
2012-08-01
In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.
Incremental Optimization of Hub and Spoke Network for the Spokes’ Numbers and Flow
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Yanfeng Wang
2015-01-01
Full Text Available Hub and spoke network problem is solved as part of a strategic decision making process which may have a profound effect on the future of enterprises. In view of the existing network structure, as time goes on, the number of spokes and the flow change because of different sources of uncertainty. Hence, the incremental optimization of hub and spoke network problem is considered in this paper, and the policy makers should adopt a series of strategies to cope with the change, such as setting up new hubs, adjusting the capacity level of original hubs, or closing some original hubs. The objective is to minimize the total cost, which includes the setup costs for the new hubs, the closure costs, and the adjustment costs for the original hubs as well as the flow routing costs. Two mixed-integer linear programming formulations are proposed and analyzed for this problem. China Deppon Logistics as an example is performed to present computational analysis, and we analyze the changes in the solutions driven by the number of spokes and the flow. The tests also allow an analysis to consider the effect of variation in parameters on network.
Process efficiency. Redesigning social networks to improve surgery patient flow.
Samarth, Chandrika N; Gloor, Peter A
2009-01-01
We propose a novel approach to improve throughput of the surgery patient flow process of a Boston area teaching hospital. A social network analysis was conducted in an effort to demonstrate that process efficiency gains could be achieved through redesign of social network patterns at the workplace; in conjunction with redesign of organization structure and the implementation of workflow over an integrated information technology system. Key knowledge experts and coordinators in times of crisis were identified and a new communication structure more conducive to trust and knowledge sharing was suggested. The new communication structure is scalable without compromising on coordination required among key roles in the network for achieving efficiency gains.
Development of objective flow regime identification method using self-organizing neural network
International Nuclear Information System (INIS)
Lee, Jae Young; Kim, Nam Seok; Kwak, Nam Yee
2004-01-01
Two-phase flow shows various flow patterns according to the amount of the void and its relative velocity to the liquid flow. This variation directly affect the interfacial transfer which is the key factor for the design or analysis of the phase change systems. Especially the safety analysis of the nuclear power plant has been performed based on the numerical code furnished with the proper constitutive relations depending highly upon the flow regimes. Heavy efforts have been focused to identify the flow regime and at this moment we stand on relative very stable engineering background compare to the other research field. However, the issues related to objectiveness and transient flow regime are still open to study. Lee et al. and Ishii developed the method for the objective and instantaneous flow regime identification based on the neural network and new index of probability distribution of the flow regime which allows just one second observation for the flow regime identification. In the present paper, we developed the self-organized neural network for more objective approach to this problem. Kohonen's Self-Organizing Map (SOM) has been used for clustering, visualization, and abstraction. The SOM is trained through unsupervised competitive learning using a 'winner takes it all' policy. Therefore, its unsupervised training character delete the possible interference of the regime developer to the neural network training. After developing the computer code, we evaluate the performance of the code with the vertically upward two-phase flow in the pipes of 25.4 and 50.4 cmm I.D. Also, the sensitivity of the number of the clusters to the flow regime identification was made
Directory of Open Access Journals (Sweden)
Hadi Heidari Gharehbolagh
2016-01-01
Full Text Available This study investigates a multiowner maximum-flow network problem, which suffers from risky events. Uncertain conditions effect on proper estimation and ignoring them may mislead decision makers by overestimation. A key question is how self-governing owners in the network can cooperate with each other to maintain a reliable flow. Hence, the question is answered by providing a mathematical programming model based on applying the triangular reliability function in the decentralized networks. The proposed method concentrates on multiowner networks which suffer from risky time, cost, and capacity parameters for each network’s arcs. Some cooperative game methods such as τ-value, Shapley, and core center are presented to fairly distribute extra profit of cooperation. A numerical example including sensitivity analysis and the results of comparisons are presented. Indeed, the proposed method provides more reality in decision-making for risky systems, hence leading to significant profits in terms of real cost estimation when compared with unforeseen effects.
Sonification of network traffic flow for monitoring and situational awareness
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543
Sonification of network traffic flow for monitoring and situational awareness.
Debashi, Mohamed; Vickers, Paul
2018-01-01
Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.
Altered Cerebral Blood Flow Covariance Network in Schizophrenia.
Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui
2016-01-01
Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia.
Two phase flow problems in power station boilers
International Nuclear Information System (INIS)
Firman, E.C.
1974-01-01
The paper outlines some of the waterside thermal and hydrodynamic phenomena relating to design and operation of large boilers in central power stations. The associated programme of work is described with an outline of some results already obtained. By way of introduction, the principal features of conventional and nuclear drum boilers and once-through nuclear heat exchangers are described in so far as they pertain to this area of work. This is followed by discussion of the relevant physical phenomena and problems which arise. For example, the problem of steam entrainment from the drum into the tubes connecting it to the furnace wall tubes is related to its effects on circulation and possible mechanisms of tube failure. Other problems concern the transient associated with start-up or low load operation of plant. The requirement for improved mathematical representation of steady and dynamic performance is mentioned together with the corresponding need for data on heat transfer, pressure loss, hydrodynamic stability, consequences of deposits, etc. The paper concludes with reference to the work being carried out within the C.E.G.B. in relation to the above problems. The facilities employed and the specific studies being made on them are described: these range from field trials on operational boilers to small scale laboratory investigations of underlying two phase flow mechanisms and include high pressure water rigs and a freon rig for simulation studies
Interest communities and flow roles in directed networks: the Twitter network of the UK riots.
Beguerisse-Díaz, Mariano; Garduño-Hernández, Guillermo; Vangelov, Borislav; Yaliraki, Sophia N; Barahona, Mauricio
2014-12-06
Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e. groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer and topic. The study of flows also allows us to generate an interest distance, which affords a personalized view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterized by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks.
Clustering and Flow Conservation Monitoring Tool for Software Defined Networks
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Jesús Antonio Puente Fernández
2018-04-01
Full Text Available Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN is a new concept of network architecture that provides the separation of control plane (controller and data plane (switches in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.
Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.
Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon
2018-04-03
Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.
Towards Effective Intra-flow Network Coding in Software Defined Wireless Mesh Networks
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Donghai Zhu
2016-01-01
Full Text Available Wireless Mesh Networks (WMNs have potential to provide convenient broadband wireless Internet access to mobile users.With the support of Software-Defined Networking (SDN paradigm that separates control plane and data plane, WMNs can be easily deployed and managed. In addition, by exploiting the broadcast nature of the wireless medium and the spatial diversity of multi-hop wireless networks, intra-flow network coding has shown a greater benefit in comparison with traditional routing paradigms in data transmission for WMNs. In this paper, we develop a novel OpenCoding protocol, which combines the SDN technique with intra-flow network coding for WMNs. Our developed protocol can simplify the deployment and management of the network and improve network performance. In OpenCoding, a controller that works on the control plane makes routing decisions for mesh routers and the hop-by-hop forwarding function is replaced by network coding functions in data plane. We analyze the overhead of OpenCoding. Through a simulation study, we show the effectiveness of the OpenCoding protocol in comparison with existing schemes. Our data shows that OpenCoding outperforms both traditional routing and intra-flow network coding schemes.
Exploring the potential of blood flow network data
Poelma, C.
2015-01-01
To gain a better understanding of the role of haemodynamic forces during the development of the cardiovascular system, a series of studies have been reported recently that describe flow fields in the vasculature of model systems. Such data sets, in particular those reporting networks at multiple
Information transmission and signal permutation in active flow networks
Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn
2018-03-01
Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.
Modelling flow dynamics in water distribution networks using ...
African Journals Online (AJOL)
DR OKE
was used for modelling the flow and simulate water demand using a Matlab .... This process requires that the neural network compute the error derivative of the .... Furthermore, Matlab was used as a simulation tool; and the first step was ...
Directory of Open Access Journals (Sweden)
MANAR Y. KASHMOLA
2012-06-01
Full Text Available The development of hybrid algorithms for solving complex optimization problems focuses on enhancing the strengths and compensating for the weakness of two or more complementary approaches. The goal is to intelligently combine the key elements of these approaches to find superior solutions to solve optimization problems. Optimal routing in communication network is considering a complex optimization problem. In this paper we propose a hybrid Hopfield Neural Network (HNN and Tabu Search (TS algorithm, this algorithm called hybrid HNN-TS algorithm. The paradigm of this hybridization is embedded. We embed the short-term memory and tabu restriction features from TS algorithm in the HNN model. The short-term memory and tabu restriction control the neuron selection process in the HNN model in order to get around the local minima problem and find an optimal solution using the HNN model to solve complex optimization problem. The proposed algorithm is intended to find the optimal path for packet transmission in the network which is fills in the field of routing problem. The optimal path that will be selected is depending on 4-tuples (delay, cost, reliability and capacity. Test results show that the propose algorithm can find path with optimal cost and a reasonable number of iterations. It also shows that the complexity of the network model won’t be a problem since the neuron selection is done heuristically.
International Nuclear Information System (INIS)
Hanif, A.; Choudhry, M.A.
2013-01-01
This research work presents a feed forward power flow control strategy in the secondary distribution network working in parallel with a DC type distributed energy resource (DER) unit with SPWM-IGBT Voltage Source Converter (VSC). The developed control strategy enables the VSC to be used as power flow controller at the load bus in the presence of utility supply. Due to the investigated control strategy, power flow control from distributed energy resource (DER) to common load bus is such that power flows to the load without facing any power quality problem. The technique has an added advantage of controlling power flow without having a dedicated power flow controller. The SPWM-IGBT VSC is serving the purpose of dc-ac converter as well as power flow controller. Simulations for a test system using proposed power flow control strategy are carried out using SimPower Systems toolbox of MATLAB at the rate and Simulink at the rate. The results show that a reliable, effective and efficient operation of DC type DER unit in coordination with main utility network can be achieved. (author)
Flow Oriented Channel Assignment for Multi-radio Wireless Mesh Networks
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Niu Zhisheng
2010-01-01
Full Text Available We investigate channel assignment for a multichannel wireless mesh network backbone, where each router is equipped with multiple interfaces. Of particular interest is the development of channel assignment heuristics for multiple flows. We present an optimization formulation and then propose two iterative flow oriented heuristics for the conflict-free and interference-aware cases, respectively. To maximize the aggregate useful end-to-end flow rates, both algorithms identify and resolve congestion at instantaneous bottleneck link in each iteration. Then the link rate is optimally allocated among contending flows that share this link by solving a linear programming (LP problem. A thorough performance evaluation is undertaken as a function of the number of channels and interfaces/node and the number of contending flows. The performance of our algorithm is shown to be significantly superior to best known algorithm in its class in multichannel limited radio scenarios.
Optimal scheduling for distribution network with redox flow battery storage
International Nuclear Information System (INIS)
Hosseina, Majid; Bathaee, Seyed Mohammad Taghi
2016-01-01
Highlights: • A novel method for optimal scheduling of storages in radial network is presented. • Peak shaving and load leveling are the main objectives. • Vanadium redox flow battery is considered as the energy storage unit. • Real data is used for simulation. - Abstract: There are many advantages to utilize storages in electric power system. Peak shaving, load leveling, load frequency control, integration of renewable, energy trading and spinning reserve are the most important of them. Batteries, especially redox flow batteries, are one of the appropriate storages for utilization in distribution network. This paper presents a novel, heuristic and practical method for optimal scheduling in distribution network with flow battery storage. This heuristic method is more suitable for scheduling and operation of distribution networks which require installation of storages. Peak shaving and load leveling is considered as the main objective in this paper. Several indices are presented in this paper for determine the place of storages and also scheduling for optimal use of energy in them. Simulations of this paper are based on real information of distribution network substation that located in Semnan, Iran.
A simulated annealing approach for redesigning a warehouse network problem
Khairuddin, Rozieana; Marlizawati Zainuddin, Zaitul; Jiun, Gan Jia
2017-09-01
Now a day, several companies consider downsizing their distribution networks in ways that involve consolidation or phase-out of some of their current warehousing facilities due to the increasing competition, mounting cost pressure and taking advantage on the economies of scale. Consequently, the changes on economic situation after a certain period of time require an adjustment on the network model in order to get the optimal cost under the current economic conditions. This paper aimed to develop a mixed-integer linear programming model for a two-echelon warehouse network redesign problem with capacitated plant and uncapacitated warehouses. The main contribution of this study is considering capacity constraint for existing warehouses. A Simulated Annealing algorithm is proposed to tackle with the proposed model. The numerical solution showed the model and method of solution proposed was practical.
Some dynamic resource allocation problems in wireless networks
Berry, Randall
2001-07-01
We consider dynamic resource allocation problems that arise in wireless networking. Specifically transmission scheduling problems are studied in cases where a user can dynamically allocate communication resources such as transmission rate and power based on current channel knowledge as well as traffic variations. We assume that arriving data is stored in a transmission buffer, and investigate the trade-off between average transmission power and average buffer delay. A general characterization of this trade-off is given and the behavior of this trade-off in the regime of asymptotically large buffer delays is explored. An extension to a more general utility based quality of service definition is also discussed.
A network flow model for load balancing in circuit-switched multicomputers
Bokhari, Shahid H.
1990-01-01
In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.
Information flow in a network of dispersed signalers-receivers
Halupka, Konrad
2017-11-01
I consider a stochastic model of multi-agent communication in regular network. The model describes how dispersed animals exchange information. Each agent can initiate and transfer the signal to its nearest neighbors, who may pass it farther. For an external observer of busy networks, signaling activity may appear random, even though information flow actually thrives. Only when signal initiation and transfer are at low levels do spatiotemporal autocorrelations emerge as clumping signaling activity in space and pink noise time series. Under such conditions, the costs of signaling are moderate, but the signaler can reach a large audience. I propose that real-world networks of dispersed signalers-receivers may self-organize into this state and the flow of information maintains their integrity.
A modified GO-FLOW methodology with common cause failure based on Discrete Time Bayesian Network
International Nuclear Information System (INIS)
Fan, Dongming; Wang, Zili; Liu, Linlin; Ren, Yi
2016-01-01
Highlights: • Identification of particular causes of failure for common cause failure analysis. • Comparison two formalisms (GO-FLOW and Discrete Time Bayesian network) and establish the correlation between them. • Mapping the GO-FLOW model into Bayesian network model. • Calculated GO-FLOW model with common cause failures based on DTBN. - Abstract: The GO-FLOW methodology is a success-oriented system reliability modelling technique for multi-phase missions involving complex time-dependent, multi-state and common cause failure (CCF) features. However, the analysis algorithm cannot easily handle the multiple shared signals and CCFs. In addition, the simulative algorithm is time consuming when vast multi-state components exist in the model, and the multiple time points of phased mission problems increases the difficulty of the analysis method. In this paper, the Discrete Time Bayesian Network (DTBN) and the GO-FLOW methodology are integrated by the unified mapping rules. Based on these rules, the multi operators can be mapped into DTBN followed by, a complete GO-FLOW model with complex characteristics (e.g. phased mission, multi-state, and CCF) can be converted to the isomorphic DTBN and easily analyzed by utilizing the DTBN. With mature algorithms and tools, the multi-phase mission reliability parameter can be efficiently obtained via the proposed approach without considering the shared signals and the various complex logic operation. Meanwhile, CCF can also arise in the computing process.
Three-Phase Unbalanced Load Flow Tool for Distribution Networks
DEFF Research Database (Denmark)
Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso
2012-01-01
This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....
International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis.
Shen, Bin; Zhang, Jiang; Li, Yixiao; Zheng, Qiuhua; Li, Xingsen
2015-01-01
This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries' roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading "trophic levels" have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows.
Neural network modeling of chaotic dynamics in nuclear reactor flows
International Nuclear Information System (INIS)
Welstead, S.T.
1992-01-01
Neural networks have many scientific applications in areas such as pattern classification and time series prediction. The universal approximation property of these networks, however, can also be exploited to provide researchers with tool for modeling observed nonlinear phenomena. It has been shown that multilayer feed forward networks can capture important global nonlinear properties, such as chaotic dynamics, merely by training the network on a finite set of observed data. The network itself then provides a model of the process that generated the data. Characterizations such as the existence and general shape of a strange attractor and the sign of the largest Lyapunov exponent can then be extracted from the neural network model. In this paper, the author applies this idea to data generated from a nonlinear process that is representative of convective flows that can arise in nuclear reactor applications. Such flows play a role in forced convection heat removal from pressurized water reactors and boiling water reactors, and decay heat removal from liquid-metal-cooled reactors, either by natural convection or by thermosyphons
Network-induced oscillatory behavior in material flow networks and irregular business cycles
Helbing, Dirk; Lämmer, Stefen; Witt, Ulrich; Brenner, Thomas
2004-11-01
Network theory is rapidly changing our understanding of complex systems, but the relevance of topological features for the dynamic behavior of metabolic networks, food webs, production systems, information networks, or cascade failures of power grids remains to be explored. Based on a simple model of supply networks, we offer an interpretation of instabilities and oscillations observed in biological, ecological, economic, and engineering systems. We find that most supply networks display damped oscillations, even when their units—and linear chains of these units—behave in a nonoscillatory way. Moreover, networks of damped oscillators tend to produce growing oscillations. This surprising behavior offers, for example, a different interpretation of business cycles and of oscillating or pulsating processes. The network structure of material flows itself turns out to be a source of instability, and cyclical variations are an inherent feature of decentralized adjustments.
Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Wang Tao
2014-04-01
Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.
Address Translation Problems in IMS Based Next Generation Networks
Directory of Open Access Journals (Sweden)
Balazs Godor
2006-01-01
Full Text Available The development of packed based multimedia networks reached a turning point when the ITU-T and the ETSIhave incorporated the IMS to the NGN. With the fast development of mobile communication more and more services andcontent are available. In contrast with fix network telephony both the services and the devices are personalized in the “mobileworld”. Services, known from the Internet - like e-mail, chat, browsing, presence, etc. – are already available via mobiledevices as well. The IMS originally wanted to exploit both the benefits of mobile networks and the fancy services of theInternet. But today it is already more than that. IMS is the core of the next generation telecommunication networks and abasis for fix-mobile convergent services. The fact however that IMS was originally a “mobile” standard, where IPv6 was notoddity generated some problems for the fix networks, where IPv4 is used. In this article I give an overview of these problemsand mention some solutions as well.
RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks
Energy Technology Data Exchange (ETDEWEB)
Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)
2013-12-25
The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need
Neural Network Predictive Control for Vanadium Redox Flow Battery
Directory of Open Access Journals (Sweden)
Hai-Feng Shen
2013-01-01
Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.
Towards overcoming the Monte Carlo sign problem with tensor networks
Directory of Open Access Journals (Sweden)
Bañuls Mari Carmen
2017-01-01
Full Text Available The study of lattice gauge theories with Monte Carlo simulations is hindered by the infamous sign problem that appears under certain circumstances, in particular at non-zero chemical potential. So far, there is no universal method to overcome this problem. However, recent years brought a new class of non-perturbative Hamiltonian techniques named tensor networks, where the sign problem is absent. In previous work, we have demonstrated that this approach, in particular matrix product states in 1+1 dimensions, can be used to perform precise calculations in a lattice gauge theory, the massless and massive Schwinger model. We have computed the mass spectrum of this theory, its thermal properties and real-time dynamics. In this work, we review these results and we extend our calculations to the case of two flavours and non-zero chemical potential. We are able to reliably reproduce known analytical results for this model, thus demonstrating that tensor networks can tackle the sign problem of a lattice gauge theory at finite density.
Data flow methods for dynamic system simulation - A CSSL-IV microcomputer network interface
Makoui, A.; Karplus, W. J.
1983-01-01
A major problem in employing networks of microcomputers for the real-time simulation of complex systems is to allocate computational tasks to the various microcomputers in such a way that idle time and time lost in interprocess communication is minimized. The research reported in this paper is directed to the development of a software interface between a higher-level simulation language and a network of microcomputers. A CSSL-IV source program is translated to a data flow graph. This graph is then analyzed automatically so as to allocate computing tasks to the various processors.
Reynolds analogy for the Rayleigh problem at various flow modes.
Abramov, A A; Butkovskii, A V
2016-07-01
The Reynolds analogy and the extended Reynolds analogy for the Rayleigh problem are considered. For a viscous incompressible fluid we derive the Reynolds analogy as a function of the Prandtl number and the Eckert number. We show that for any positive Eckert number, the Reynolds analogy as a function of the Prandtl number has a maximum. For a monatomic gas in the transitional flow regime, using the direct simulation Monte Carlo method, we investigate the extended Reynolds analogy, i.e., the relation between the shear stress and the energy flux transferred to the boundary surface, at different velocities and temperatures. We find that the extended Reynolds analogy for a rarefied monatomic gas flow with the temperature of the undisturbed gas equal to the surface temperature depends weakly on time and is close to 0.5. We show that at any fixed dimensionless time the extended Reynolds analogy depends on the plate velocity and temperature and undisturbed gas temperature mainly via the Eckert number. For Eckert numbers of the order of unity or less we generalize an extended Reynolds analogy. The generalized Reynolds analogy depends mainly only on dimensionless time for all considered Eckert numbers of the order of unity or less.
The Granular Blasius Problem: High inertial number granular flows
Tsang, Jonathan; Dalziel, Stuart; Vriend, Nathalie
2017-11-01
The classical Blasius problem considers the formation of a boundary layer through the change at x = 0 from a free-slip to a no-slip boundary beneath an otherwise steady uniform flow. Discrete particle model (DPM) simulations of granular gravity currents show that a similar phenomenon exists for a steady flow over a uniformly sloped surface that is smooth upstream (allowing slip) but rough downstream (imposing a no-slip condition). The boundary layer is a region of high shear rate and therefore high inertial number I; its dynamics are governed by the asymptotic behaviour of the granular rheology as I -> ∞ . The μ(I) rheology asserts that dμ / dI = O(1 /I2) as I -> ∞ , but current experimental evidence is insufficient to confirm this. We show that `generalised μ(I) rheologies', with different behaviours as I -> ∞ , all permit the formation of a boundary layer. We give approximate solutions for the velocity profile under each rheology. The change in boundary condition considered here mimics more complex topography in which shear stress increases in the streamwise direction (e.g. a curved slope). Such a system would be of interest in avalanche modelling. EPSRC studentship (Tsang) and Royal Society Dorothy Hodgkin Fellowship (Vriend).
Prediction of flow boiling curves based on artificial neural network
International Nuclear Information System (INIS)
Wu Junmei; Xi'an Jiaotong Univ., Xi'an; Su Guanghui
2007-01-01
The effects of the main system parameters on flow boiling curves were analyzed by using an artificial neural network (ANN) based on the database selected from the 1960s. The input parameters of the ANN are system pressure, mass flow rate, inlet subcooling, wall superheat and steady/transition boiling, and the output parameter is heat flux. The results obtained by the ANN show that the heat flux increases with increasing inlet sub cooling for all heat transfer modes. Mass flow rate has no significant effects on nucleate boiling curves. The transition boiling and film boiling heat fluxes will increase with an increase of mass flow rate. The pressure plays a predominant role and improves heat transfer in whole boiling regions except film boiling. There are slight differences between the steady and the transient boiling curves in all boiling regions except the nucleate one. (authors)
Modeling flow and transport in fracture networks using graphs
Karra, S.; O'Malley, D.; Hyman, J. D.; Viswanathan, H. S.; Srinivasan, G.
2018-03-01
Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizations of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. The good accuracy and the low computational cost, with O (104) times lower times than
Network flow model of force transmission in unbonded and bonded granular media.
Tordesillas, Antoinette; Tobin, Steven T; Cil, Mehmet; Alshibli, Khalid; Behringer, Robert P
2015-06-01
An established aspect of force transmission in quasistatic deformation of granular media is the existence of a dual network of strongly versus weakly loaded particles. Despite significant interest, the regulation of strong and weak forces through the contact network remains poorly understood. We examine this aspect of force transmission using data on microstructural fabric from: (I) three-dimensional discrete element models of grain agglomerates of bonded subspheres constructed from in situ synchrotron microtomography images of silica sand grains under unconfined compression and (II) two-dimensional assemblies of unbonded photoelastic circular disks submitted to biaxial compression under constant volume. We model force transmission as a network flow and solve the maximum flow-minimum cost (MFMC) problem, the solution to which yields a percolating subnetwork of contacts that transmits the "maximum flow" (i.e., the highest units of force) at "least cost" (i.e., the dissipated energy from such transmission). We find the MFMC describes a two-tier hierarchical architecture. At the local level, it encapsulates intraconnections between particles in individual force chains and in their conjoined 3-cycles, with the most common configuration having at least one force chain contact experiencing frustrated rotation. At the global level, the MFMC encapsulates interconnections between force chains. The MFMC can be used to predict most of the force chain particles without need for any information on contact forces, thereby suggesting the network flow framework may have potential broad utility in the modeling of force transmission in unbonded and bonded granular media.
Queueing network model for obstetric patient flow in a hospital.
Takagi, Hideaki; Kanai, Yuta; Misue, Kazuo
2016-03-03
A queueing network is used to model the flow of patients in a hospital using the observed admission rate of patients and the histogram for the length of stay for patients in each ward. A complete log of orders for every movement of all patients from room to room covering two years was provided to us by the Medical Information Department of the University of Tsukuba Hospital in Japan. We focused on obstetric patients, who are generally hospitalized at random times throughout the year, and we analyzed the patient flow probabilistically. On admission, each obstetric patient is assigned to a bed in one of the two wards: one for normal delivery and the other for high-risk delivery. Then, the patient may be transferred between the two wards before discharge. We confirm Little's law of queueing theory for the patient flow in each ward. Next, we propose a new network model of M/G/ ∞ and M/M/ m queues to represent the flow of these patients, which is used to predict the probability distribution for the number of patients staying in each ward at the nightly census time. Although our model is a very rough and simplistic approximation of the real patient flow, the predicted probability distribution shows good agreement with the observed data. The proposed method can be used for capacity planning of hospital wards to predict future patient load in each ward.
2014-12-01
The report documents policy considerations for the Intelligent Network Flow Optimization (INFLO) connected vehicle applications : bundle. INFLO aims to optimize network flow on freeways and arterials by informing motorists of existing and impen...
Optimization of Gas Flow Network using the Traveling Salesman ...
African Journals Online (AJOL)
The overall goal of this paper is to develop a general formulation for an optimal infrastructure layout design of gas pipeline distribution networks using algorithm developed from the application of two industrial engineering concepts: the traveling salesman problem (TSP) and the nearest neighbor (NN). The focus is on the ...
Distance learning, problem based learning and dynamic knowledge networks.
Giani, U; Martone, P
1998-06-01
This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.
Bridging Inter-flow and Intra-flow Network Coding for Video Applications
DEFF Research Database (Denmark)
Hansen, Jonas; Krigslund, Jeppe; Roetter, Daniel Enrique Lucani
2013-01-01
transmission approach to decide how much and when to send redundancy in the network, and a minimalistic feedback mechanism to guarantee delivery of generations of the different flows. Given the delay constraints of video applications, we proposed a simple yet effective coding mechanism, Block Coding On The Fly...
Non-Newtonian fluid flow in 2D fracture networks
Zou, L.; Håkansson, U.; Cvetkovic, V.
2017-12-01
Modeling of non-Newtonian fluid (e.g., drilling fluids and cement grouts) flow in fractured rocks is of interest in many geophysical and industrial practices, such as drilling operations, enhanced oil recovery and rock grouting. In fractured rock masses, the flow paths are dominated by fractures, which are often represented as discrete fracture networks (DFN). In the literature, many studies have been devoted to Newtonian fluid (e.g., groundwater) flow in fractured rock using the DFN concept, but few works are dedicated to non-Newtonian fluids.In this study, a generalized flow equation for common non-Newtonian fluids (such as Bingham, power-law and Herschel-Bulkley) in a single fracture is obtained from the analytical solutions for non-Newtonian fluid discharge between smooth parallel plates. Using Monte Carlo sampling based on site characterization data for the distribution of geometrical features (e.g., density, length, aperture and orientations) in crystalline fractured rock, a two dimensional (2D) DFN model is constructed for generic flow simulations. Due to complex properties of non-Newtonian fluids, the relationship between fluid discharge and the pressure gradient is nonlinear. A Galerkin finite element method solver is developed to iteratively solve the obtained nonlinear governing equations for the 2D DFN model. Using DFN realizations, simulation results for different geometrical distributions of the fracture network and different non-Newtonian fluid properties are presented to illustrate the spatial discharge distributions. The impact of geometrical structures and the fluid properties on the non-Newtonian fluid flow in 2D DFN is examined statistically. The results generally show that modeling non-Newtonian fluid flow in fractured rock as a DFN is feasible, and that the discharge distribution may be significantly affected by the geometrical structures as well as by the fluid constitutive properties.
Using Alloy to Formally Model and Reason About an OpenFlow Network Switch
Mirzaei, Saber; Bahargam, Sanaz; Skowyra, Richard; Kfoury, Assaf; Bestavros, Azer
2016-01-01
Openflow provides a standard interface for separating a network into a data plane and a programmatic control plane. This enables easy network reconfiguration, but introduces the potential for programming bugs to cause network effects. To study OpenFlow switch behavior, we used Alloy to create a software abstraction describing the internal state of a network and its OpenFlow switches. This work is an attempt to model the static and dynamic behaviour a network built using OpenFlow switches.
A recurrent neural network for solving bilevel linear programming problem.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian
2014-04-01
In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.
A flow level model for wireless multihop ad hoc network throughput
Coenen, Tom Johannes Maria; van den Berg, Hans Leo; Boucherie, Richardus J.
2005-01-01
A flow level model for multihop wireless ad hoc networks is presented in this paper. Using a flow level view, we show the main properties and modeling challenges for ad hoc networks. Considering different scenarios, a multihop WLAN and a serial network with a TCP-like flow control protocol, we
Evolution of weighted complex bus transit networks with flow
Huang, Ailing; Xiong, Jie; Shen, Jinsheng; Guan, Wei
2016-02-01
Study on the intrinsic properties and evolutional mechanism of urban public transit networks (PTNs) has great significance for transit planning and control, particularly considering passengers’ dynamic behaviors. This paper presents an empirical analysis for exploring the complex properties of Beijing’s weighted bus transit network (BTN) based on passenger flow in L-space, and proposes a bi-level evolution model to simulate the development of transit routes from the view of complex network. The model is an iterative process that is driven by passengers’ travel demands and dual-controlled interest mechanism, which is composed of passengers’ spatio-temporal requirements and cost constraint of transit agencies. Also, the flow’s dynamic behaviors, including the evolutions of travel demand, sectional flow attracted by a new link and flow perturbation triggered in nearby routes, are taken into consideration in the evolutional process. We present the numerical experiment to validate the model, where the main parameters are estimated by using distribution functions that are deduced from real-world data. The results obtained have proven that our model can generate a BTN with complex properties, such as the scale-free behavior or small-world phenomenon, which shows an agreement with our empirical results. Our study’s results can be exploited to optimize the real BTN’s structure and improve the network’s robustness.
Information flow in layered networks of non-monotonic units
Schittler Neves, Fabio; Martim Schubert, Benno; Erichsen, Rubem, Jr.
2015-07-01
Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information.
Information flow in layered networks of non-monotonic units
International Nuclear Information System (INIS)
Neves, Fabio Schittler; Schubert, Benno Martim; Erichsen, Rubem Jr
2015-01-01
Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information. (paper)
Mental Health, School Problems, and Social Networks: Modeling Urban Adolescent Substance Use
Mason, Michael J.
2010-01-01
This study tested a mediation model of the relationship with school problems, social network quality, and substance use with a primary care sample of 301 urban adolescents. It was theorized that social network quality (level of risk or protection in network) would mediate the effects of school problems, accounting for internalizing problems and…
Applications of flow-networks to opinion-dynamics
Tupikina, Liubov; Kurths, Jürgen
2015-04-01
Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.
Optimal Power Flow in Multiphase Radial Networks with Delta Connections: Preprint
Energy Technology Data Exchange (ETDEWEB)
Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Low, Steven H. [California Institute of Technology
2017-11-27
This paper focuses on multiphase radial distribution networks with mixed wye and delta connections, and proposes a semidefinite relaxation of the AC optimal power flow (OPF) problem. Two multiphase power-flow models are developed to facilitate the integration of delta-connected generation units/loads in the OPF problem. The first model extends traditional branch flow models - and it is referred to as extended branch flow model (EBFM). The second model leverages a linear relationship between per-phase power injections and delta connections, which holds under a balanced voltage approximation (BVA). Based on these models, pertinent OPF problems are formulated and relaxed to semidefinite programs (SDPs). Numerical studies on IEEE test feeders show that SDP relaxations can be solved efficiently by a generic optimization solver. Numerical evidences indicate that solving the resultant SDP under BVA is faster than under EBFM. Moreover, both SDP solutions are numerically exact with respect to voltages and branch flows. It is also shown that the SDP solution under BVA has a small optimality gap, while the BVA model is accurate in the sense that it reflects actual system voltages.
Route Selection Problem Based on Hopfield Neural Network
Directory of Open Access Journals (Sweden)
N. Kojic
2013-12-01
Full Text Available Transport network is a key factor of economic, social and every other form of development in the region and the state itself. One of the main conditions for transport network development is the construction of new routes. Often, the construction of regional roads is dominant, since the design and construction in urban areas is quite limited. The process of analysis and planning the new roads is a complex process that depends on many factors (the physical characteristics of the terrain, the economic situation, political decisions, environmental impact, etc. and can take several months. These factors directly or indirectly affect the final solution, and in combination with project limitations and requirements, sometimes can be mutually opposed. In this paper, we present one software solution that aims to find Pareto optimal path for preliminary design of the new roadway. The proposed algorithm is based on many different factors (physical and social with the ability of their increase. This solution is implemented using Hopfield's neural network, as a kind of artificial intelligence, which has shown very good results for solving complex optimization problems.
Directory of Open Access Journals (Sweden)
Afshin Mehrsai
2013-01-01
Full Text Available Alternative material flow strategies in logistics networks have crucial influences on the overall performance of the networks. Material flows can follow push, pull, or hybrid systems. To get the advantages of both push and pull flows in networks, the decoupling-point strategy is used as coordination mean. At this point, material pull has to get optimized concerning customer orders against pushed replenishment-rates. To compensate the ambiguity and uncertainty of both dynamic flows, fuzzy set theory can practically be applied. This paper has conceptual and mathematical parts to explain the performance of the push-pull flow strategy in a supply network and to give a novel solution for optimizing the pull side employing Conwip system. Alternative numbers of pallets and their lot-sizes circulating in the assembly system are getting optimized in accordance with a multi-objective problem; employing a hybrid approach out of meta-heuristics (genetic algorithm and simulated annealing and fuzzy system. Two main fuzzy sets as triangular and trapezoidal are applied in this technique for estimating ill-defined waiting times. The configured technique leads to smoother flows between push and pull sides in complex networks. A discrete-event simulation model is developed to analyze this thesis in an exemplary logistics network with dynamics.
Algorithm for solving multicriteria problem of appointments on the networks
Directory of Open Access Journals (Sweden)
Yu. V. Bugaeev
2017-01-01
Full Text Available To describe complex projects or various jobs that make up a set of interrelated activities, use the network schedule. Several variants of network models are used. 1. For practical use, the Gantt chart is the most widely used - it is a graphical representation of consecutive intervals of time and the use of resources. 2. The network graph is represented as a graph, where the vertices are an event (or its state at a certain point in time, and the connecting arcs (or edges are works. The graph model is used in the work. In this case, the events (the fact of the completion or the beginning of the work correspond to the vertices of the graph, and the work to the arcs, the orientation of which corresponds to the technology of this process. An important role in the project management model is played by the optimal assignment of performers to the existing list of works. With this formulation of the problem, the total implementation time or the length of the critical path on the graph can be used as a criterion. In this case, the criterion is imposed a restriction on the deadline for the execution of work (or the project as a whole. Thus, the total time spent on the project and the length of the critical path are represented by equally important characteristics of the project implementation, and they should be considered as two equivalent criteria for the multicriteria project management task. We have proposed an algorithm, in general, an approximate determination of the set of Pareto-optimal solutions of a given problem.
MEDUSA - An overset grid flow solver for network-based parallel computer systems
Smith, Merritt H.; Pallis, Jani M.
1993-01-01
Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.
A Sufficient Condition on Convex Relaxation of AC Optimal Power Flow in Distribution Networks
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Wang, Jianhui
2016-01-01
This paper proposes a sufficient condition for the convex relaxation of AC Optimal Power Flow (OPF) in radial distribution networks as a second order cone program (SOCP) to be exact. The condition requires that the allowed reverse power flow is only reactive or active, or none. Under the proposed...... solution of the SOCP can be converted to an optimal solution of the original AC OPF. The efficacy of the convex relaxation to solve the AC OPF is demonstrated by case studies of an optimal multi-period planning problem of electric vehicles (EVs) in distribution networks....... sufficient condition, the feasible sub-injection region (power injections of nodes excluding the root node) of the AC OPF is convex. The exactness of the convex relaxation under the proposed condition is proved through constructing a group of monotonic series with limits, which ensures that the optimal...
Connectivity, flow and transport in network models of fractured media
International Nuclear Information System (INIS)
Robinson, P.C.
1984-10-01
In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed. (author)
International Nuclear Information System (INIS)
Shin, Y.W.; Wiedermann, A.H.
1984-02-01
A method was published, based on the integral method of characteristics, by which the junction and boundary conditions needed in computation of a flow in a piping network can be accurately formulated. The method for the junction and boundary conditions formulation together with the two-step Lax-Wendroff scheme are used in a computer program; the program in turn, is used here in calculating sample problems related to the blowdown transient of a two-phase flow in the piping network downstream of a PWR pressurizer. Independent, nearly exact analytical solutions also are obtained for the sample problems. Comparison of the results obtained by the hybrid numerical technique with the analytical solutions showed generally good agreement. The good numerical accuracy shown by the results of our scheme suggest that the hybrid numerical technique is suitable for both benchmark and design calculations of PWR pressurizer blowdown transients
Recurrence network analysis of experimental signals from bubbly oil-in-water flows
Energy Technology Data Exchange (ETDEWEB)
Gao, Zhong-Ke; Zhang, Xin-Wang; Du, Meng [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Jin, Ning-De, E-mail: ndjin@tju.edu.cn [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2013-02-04
Based on the signals from oil–water two-phase flow experiment, we construct and analyze recurrence networks to characterize the dynamic behavior of different flow patterns. We first take a chaotic time series as an example to demonstrate that the local property of recurrence network allows characterizing chaotic dynamics. Then we construct recurrence networks for different oil-in-water flow patterns and investigate the local property of each constructed network, respectively. The results indicate that the local topological statistic of recurrence network is very sensitive to the transitions of flow patterns and allows uncovering the dynamic flow behavior associated with chaotic unstable periodic orbits.
Recurrence network analysis of experimental signals from bubbly oil-in-water flows
International Nuclear Information System (INIS)
Gao, Zhong-Ke; Zhang, Xin-Wang; Du, Meng; Jin, Ning-De
2013-01-01
Based on the signals from oil–water two-phase flow experiment, we construct and analyze recurrence networks to characterize the dynamic behavior of different flow patterns. We first take a chaotic time series as an example to demonstrate that the local property of recurrence network allows characterizing chaotic dynamics. Then we construct recurrence networks for different oil-in-water flow patterns and investigate the local property of each constructed network, respectively. The results indicate that the local topological statistic of recurrence network is very sensitive to the transitions of flow patterns and allows uncovering the dynamic flow behavior associated with chaotic unstable periodic orbits.
A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions
Lee, Douglas W.; Patek, Stephen D.; Alexandrov, Natalia; Bass, Ellen J.; Kincaid, Rex K.
2010-01-01
This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports.
Energy flow models for the estimation of technical losses in distribution network
International Nuclear Information System (INIS)
Au, Mau Teng; Tan, Chin Hooi
2013-01-01
This paper presents energy flow models developed to estimate technical losses in distribution network. Energy flow models applied in this paper is based on input energy and peak demand of distribution network, feeder length and peak demand, transformer loading capacity, and load factor. Two case studies, an urban distribution network and a rural distribution network are used to illustrate application of the energy flow models. Results on technical losses obtained for the two distribution networks are consistent and comparable to network of similar types and characteristics. Hence, the energy flow models are suitable for practical application.
Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.
Gao, Zhongke; Jin, Ningde
2009-06-01
The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.
Scalable Newton-Krylov solver for very large power flow problems
Idema, R.; Lahaye, D.J.P.; Vuik, C.; Van der Sluis, L.
2010-01-01
The power flow problem is generally solved by the Newton-Raphson method with a sparse direct solver for the linear system of equations in each iteration. While this works fine for small power flow problems, we will show that for very large problems the direct solver is very slow and we present
Evaluation of multilayer perceptron algorithms for an analysis of network flow data
Bieniasz, Jedrzej; Rawski, Mariusz; Skowron, Krzysztof; Trzepiński, Mateusz
2016-09-01
The volume of exchanged information through IP networks is larger than ever and still growing. It creates a space for both benign and malicious activities. The second one raises awareness on security network devices, as well as network infrastructure and a system as a whole. One of the basic tools to prevent cyber attacks is Network Instrusion Detection System (NIDS). NIDS could be realized as a signature-based detector or an anomaly-based one. In the last few years the emphasis has been placed on the latter type, because of the possibility of applying smart and intelligent solutions. An ideal NIDS of next generation should be composed of self-learning algorithms that could react on known and unknown malicious network activities respectively. In this paper we evaluated a machine learning approach for detection of anomalies in IP network data represented as NetFlow records. We considered Multilayer Perceptron (MLP) as the classifier and we used two types of learning algorithms - Backpropagation (BP) and Particle Swarm Optimization (PSO). This paper includes a comprehensive survey on determining the most optimal MLP learning algorithm for the classification problem in application to network flow data. The performance, training time and convergence of BP and PSO methods were compared. The results show that PSO algorithm implemented by the authors outperformed other solutions if accuracy of classifications is considered. The major disadvantage of PSO is training time, which could be not acceptable for larger data sets or in real network applications. At the end we compared some key findings with the results from the other papers to show that in all cases results from this study outperformed them.
Two- and three-index formulations of the minimum cost multicommodity k-splittable flow problem
DEFF Research Database (Denmark)
Gamst, Mette; Jensen, Peter Neergaard; Pisinger, David
2010-01-01
The multicommodity flow problem (MCFP) considers the efficient routing of commodities from their origins to their destinations subject to capacity restrictions and edge costs. Baier et al. [G. Baier, E. Köhler, M. Skutella, On the k-splittable flow problem, in: 10th Annual European Symposium...... of commodities has to be satisfied at the lowest possible cost. The problem has applications in transportation problems where a number of commodities must be routed, using a limited number of distinct transportation units for each commodity. Based on a three-index formulation by Truffot et al. [J. Truffot, C...... on Algorithms, 2002, 101–113] introduced the maximum flow multicommodity k-splittable flow problem (MCkFP) where each commodity may use at most k paths between its origin and its destination. This paper studies the -hard minimum cost multicommodity k-splittable flow problem (MCMCkFP) in which a given flow...
Scaling-Laws of Flow Entropy with Topological Metrics of Water Distribution Networks
Giovanni Francesco Santonastaso; Armando Di Nardo; Michele Di Natale; Carlo Giudicianni; Roberto Greco
2018-01-01
Robustness of water distribution networks is related to their connectivity and topological structure, which also affect their reliability. Flow entropy, based on Shannon’s informational entropy, has been proposed as a measure of network redundancy and adopted as a proxy of reliability in optimal network design procedures. In this paper, the scaling properties of flow entropy of water distribution networks with their size and other topological metrics are studied. To such aim, flow entropy, ma...
Structural Modeling and Characteristics Analysis of Flow Interaction Networks in the Internet
International Nuclear Information System (INIS)
Wu Xiao-Yu; Gu Ren-Tao; Pan Zhuo-Ya; Jin Wei-Qi; Ji Yue-Feng
2015-01-01
Applying network duality and elastic mechanics, we investigate the interactions among Internet flows by constructing a weighted undirected network, where the vertices and the edges represent the flows and the mutual dependence between flows, respectively. Based on the obtained flow interaction network, we find the existence of ‘super flow’ in the Internet, indicating that some flows have a great impact on a huge number of other flows; moreover, one flow can spread its influence to another through a limited quantity of flows (less than 5 in the experimental simulations), which shows strong small-world characteristics like the social network. To reflect the flow interactions in the physical network congestion evaluation, the ‘congestion coefficient’ is proposed as a new metric which shows a finer observation on congestion than the conventional one. (paper)
Institute of Scientific and Technical Information of China (English)
ZHANG Yin; WEI Zhiyuan; ZHANG Yinping; WANG Xin
2017-01-01
Urban heating in northern China accounts for 40％ of total building energy usage.In central heating systems,heat is often transfened from heat source to users by the heat network where several heat exchangers arc installed at heat source,substations and terminals respectively.For given overall heating capacity and heat source temperarure,increasing the terminal fluid temperature is an effective way to improve the thermal performance of such cascade heat exchange network for energy saving.In this paper,the mathematical optimization model of the cascade heat exchange network with three-stage heat exchangers in series is established.Aim at maximizing the cold fluid temperature for given hot fluid temperature and overall heating capacity,the optimal heat exchange area distribution and the medium fluids' flow rates are determined through inverse problem and variation method.The preliminary results show that the heat exchange areas should be distributed equally for each heat exchanger.It also indicates that in order to improve the thernmal performance of the whole system,more heat exchange areas should be allocated to the heat exchanger where flow rate difference between two fluids is relatively small.This work is important for guiding the optimization design of practical cascade heating systems.
Solving Minimum Cost Multi-Commodity Network Flow Problem ...
African Journals Online (AJOL)
ADOWIE PERE
The modelling technique provided a solution that effectively minimized travel ... License (CCL), which permits unrestricted use, distribution, and reproduction in any ... time within urban centers. ... expressed as a mathematical equation and a.
Program for Analyzing Flows in a Complex Network
Majumdar, Alok Kumar
2006-01-01
Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.
Backbone of complex networks of corporations: The flow of control
Glattfelder, J. B.; Battiston, S.
2009-09-01
We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.
Library Automation and Networking in India: Problems and Prospects.
Vyas, S. D.
1997-01-01
Examines the information infrastructure and the impact of information technology in India. Highlights include attempts toward automation; library networking at the national and local level; descriptions of four major networks; library software; and constraints of networking in academic libraries. (LRW)
A decomposition method for network-constrained unit commitment with AC power flow constraints
International Nuclear Information System (INIS)
Bai, Yang; Zhong, Haiwang; Xia, Qing; Kang, Chongqing; Xie, Le
2015-01-01
To meet the increasingly high requirement of smart grid operations, considering AC power flow constraints in the NCUC (network-constrained unit commitment) is of great significance in terms of both security and economy. This paper proposes a decomposition method to solve NCUC with AC power flow constraints. With conic approximations of the AC power flow equations, the master problem is formulated as a MISOCP (mixed integer second-order cone programming) model. The key advantage of this model is that the active power and reactive power are co-optimised, and the transmission losses are considered. With the AC optimal power flow model, the AC feasibility of the UC result of the master problem is checked in subproblems. If infeasibility is detected, feedback constraints are generated based on the sensitivity of bus voltages to a change in the unit reactive power generation. They are then introduced into the master problem in the next iteration until all AC violations are eliminated. A 6-bus system, a modified IEEE 30-bus system and the IEEE 118-bus system are used to validate the performance of the proposed method, which provides a satisfactory solution with approximately 44-fold greater computational efficiency. - Highlights: • A decomposition method is proposed to solve the NCUC with AC power flow constraints • The master problem considers active power, reactive power and transmission losses. • OPF-based subproblems check the AC feasibility using parallel computing techniques. • An effective feedback constraint interacts between the master problem and subproblem. • Computational efficiency is significantly improved with satisfactory accuracy
Weighted complex network analysis of the Beijing subway system: Train and passenger flows
Feng, Jia; Li, Xiamiao; Mao, Baohua; Xu, Qi; Bai, Yun
2017-05-01
In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.
Sensitivity analysis of linear programming problem through a recurrent neural network
Das, Raja
2017-11-01
In this paper we study the recurrent neural network for solving linear programming problems. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate the sensitivity analysis of linear programming problem through the neural network. A detailed example is also presented to demonstrate the performance of the recurrent neural network.
Enhancement of a model for Large-scale Airline Network Planning Problems
Kölker, K.; Lopes dos Santos, Bruno F.; Lütjens, K.
2016-01-01
The main focus of this study is to solve the network planning problem based on passenger decision criteria including the preferred departure time and travel time for a real-sized airline network. For this purpose, a model of the integrated network planning problem is formulated including scheduling
Separation prediction in two dimensional boundary layer flows using artificial neural networks
International Nuclear Information System (INIS)
Sabetghadam, F.; Ghomi, H.A.
2003-01-01
In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)
Unsupervised neural networks for solving Troesch's problem
International Nuclear Information System (INIS)
Raja Muhammad Asif Zahoor
2014-01-01
In this study, stochastic computational intelligence techniques are presented for the solution of Troesch's boundary value problem. The proposed stochastic solvers use the competency of a feed-forward artificial neural network for mathematical modeling of the problem in an unsupervised manner, whereas the learning of unknown parameters is made with local and global optimization methods as well as their combinations. Genetic algorithm (GA) and pattern search (PS) techniques are used as the global search methods and the interior point method (IPM) is used for an efficient local search. The combination of techniques like GA hybridized with IPM (GA-IPM) and PS hybridized with IPM (PS-IPM) are also applied to solve different forms of the equation. A comparison of the proposed results obtained from GA, PS, IPM, PS-IPM and GA-IPM has been made with the standard solutions including well known analytic techniques of the Adomian decomposition method, the variational iterational method and the homotopy perturbation method. The reliability and effectiveness of the proposed schemes, in term of accuracy and convergence, are evaluated from the results of statistical analysis based on sufficiently large independent runs. (interdisciplinary physics and related areas of science and technology)
ComboCoding: Combined intra-/inter-flow network coding for TCP over disruptive MANETs
Directory of Open Access Journals (Sweden)
Chien-Chia Chen
2011-07-01
Full Text Available TCP over wireless networks is challenging due to random losses and ACK interference. Although network coding schemes have been proposed to improve TCP robustness against extreme random losses, a critical problem still remains of DATA–ACK interference. To address this issue, we use inter-flow coding between DATA and ACK to reduce the number of transmissions among nodes. In addition, we also utilize a “pipeline” random linear coding scheme with adaptive redundancy to overcome high packet loss over unreliable links. The resulting coding scheme, ComboCoding, combines intra-flow and inter-flow coding to provide robust TCP transmission in disruptive wireless networks. The main contributions of our scheme are twofold; the efficient combination of random linear coding and XOR coding on bi-directional streams (DATA and ACK, and the novel redundancy control scheme that adapts to time-varying and space-varying link loss. The adaptive ComboCoding was tested on a variable hop string topology with unstable links and on a multipath MANET with dynamic topology. Simulation results show that TCP with ComboCoding delivers higher throughput than with other coding options in high loss and mobile scenarios, while introducing minimal overhead in normal operation.
FLOWNET: A Computer Program for Calculating Secondary Flow Conditions in a Network of Turbomachinery
Rose, J. R.
1978-01-01
The program requires the network parameters, the flow component parameters, the reservoir conditions, and the gas properties as input. It will then calculate all unknown pressures and the mass flow rate in each flow component in the network. The program can treat networks containing up to fifty flow components and twenty-five unknown network pressures. The types of flow components that can be treated are face seals, narrow slots, and pipes. The program is written in both structured FORTRAN (SFTRAN) and FORTRAN 4. The program must be run in an interactive (conversational) mode.
Problems of mixed convection flow regime map in a vertical cylinder
International Nuclear Information System (INIS)
Kang, Gyeong Uk; Chung, Bum Jin
2012-01-01
One of the technical issues by the development of the VHTR is the mixed convection, which is the regime of heat transfer that occurs when the driving forces of both forced and natural convection are of comparable orders of magnitude. In vertical internal flows, the buoyancy force acts upward only, but forced flows can move either upward or downward. Thus, there are two types of mixed convection flows, depending on the direction of the forced flow. When the directions of the forced flow and buoyancy are the same, the flow is a buoyancy aided flow; when they are opposite, the flow is a buoyancy opposed flow. In laminar flows, buoyancy aided flow shows enhanced heat transfer compared to the pure forced convection and buoyancy opposed flow shows impaired heat transfer due to the flow velocity affected by the buoyancy forces. In turbulent flows, however, buoyancy opposed flows shows enhanced heat transfer due to increased turbulence production and buoyancy aided flow shows impaired heat transfer at low buoyancy forces and as the buoyancy increases, the heat transfer restores and at further increases of the buoyancy forces, the heat transfer is enhanced. It is of primary interests to classify which convection regime is mainly dominant. The methods most used to classify between forced, mixed and natural convection have been to refer to the classical flow regime map suggested by Meta is and Eckert. During the course of fundamental literature studies on this topic, it is found that there are some problems on the flow regime map in a vertical cylinder. This paper is to discuss problems identified through reviewing the papers composed in the classical flow regime map. We have tried to reproduce the flow regime map independently using the data obtained from the literatures and compared with the classical flow regime map and finally, the problems on this topic were discussed
A feedback control model for network flow with multiple pure time delays
Press, J.
1972-01-01
A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.
Eigenanalysis of a neural network for optic flow processing
International Nuclear Information System (INIS)
Weber, F; Eichner, H; Borst, A; Cuntz, H
2008-01-01
Flies gain information about self-motion during free flight by processing images of the environment moving across their retina. The visual course control center in the brain of the blowfly contains, among others, a population of ten neurons, the so-called vertical system (VS) cells that are mainly sensitive to downward motion. VS cells are assumed to encode information about rotational optic flow induced by self-motion (Krapp and Hengstenberg 1996 Nature 384 463-6). Recent evidence supports a connectivity scheme between the VS cells where neurons with neighboring receptive fields are connected to each other by electrical synapses at the axonal terminals, whereas the boundary neurons in the network are reciprocally coupled via inhibitory synapses (Haag and Borst 2004 Nat. Neurosci. 7 628-34; Farrow et al 2005 J. Neurosci. 25 3985-93; Cuntz et al 2007 Proc. Natl Acad. Sci. USA). Here, we investigate the functional properties of the VS network and its connectivity scheme by reducing a biophysically realistic network to a simplified model, where each cell is represented by a dendritic and axonal compartment only. Eigenanalysis of this model reveals that the whole population of VS cells projects the synaptic input provided from local motion detectors on to its behaviorally relevant components. The two major eigenvectors consist of a horizontal and a slanted line representing the distribution of vertical motion components across the fly's azimuth. They are, thus, ideally suited for reliably encoding translational and rotational whole-field optic flow induced by respective flight maneuvers. The dimensionality reduction compensates for the contrast and texture dependence of the local motion detectors of the correlation-type, which becomes particularly pronounced when confronted with natural images and their highly inhomogeneous contrast distribution
Directedness of information flow in mobile phone communication networks.
Directory of Open Access Journals (Sweden)
Fernando Peruani
Full Text Available Without having direct access to the information that is being exchanged, traces of information flow can be obtained by looking at temporal sequences of user interactions. These sequences can be represented as causality trees whose statistics result from a complex interplay between the topology of the underlying (social network and the time correlations among the communications. Here, we study causality trees in mobile-phone data, which can be represented as a dynamical directed network. This representation of the data reveals the existence of super-spreaders and super-receivers. We show that the tree statistics, respectively the information spreading process, are extremely sensitive to the in-out degree correlation exhibited by the users. We also learn that a given information, e.g., a rumor, would require users to retransmit it for more than 30 hours in order to cover a macroscopic fraction of the system. Our analysis indicates that topological node-node correlations of the underlying social network, while allowing the existence of information loops, they also promote information spreading. Temporal correlations, and therefore causality effects, are only visible as local phenomena and during short time scales. Consequently, the very idea that there is (intentional information spreading beyond a small vecinity is called into question. These results are obtained through a combination of theory and data analysis techniques.
Curing critical links in oscillator networks as power flow models
International Nuclear Information System (INIS)
Rohden, Martin; Meyer-Ortmanns, Hildegard; Witthaut, Dirk; Timme, Marc
2017-01-01
Modern societies crucially depend on the robust supply with electric energy so that blackouts of power grids can have far reaching consequences. Typically, large scale blackouts take place after a cascade of failures: the failure of a single infrastructure component, such as a critical transmission line, results in several subsequent failures that spread across large parts of the network. Improving the robustness of a network to prevent such secondary failures is thus key for assuring a reliable power supply. In this article we analyze the nonlocal rerouting of power flows after transmission line failures for a simplified AC power grid model and compare different strategies to improve network robustness. We identify critical links in the grid and compute alternative pathways to quantify the grid’s redundant capacity and to find bottlenecks along the pathways. Different strategies are developed and tested to increase transmission capacities to restore stability with respect to transmission line failures. We show that local and nonlocal strategies typically perform alike: one can equally well cure critical links by providing backup capacities locally or by extending the capacities of bottleneck links at remote locations. (paper)
Creating Turbulent Flow Realizations with Generative Adversarial Networks
King, Ryan; Graf, Peter; Chertkov, Michael
2017-11-01
Generating valid inflow conditions is a crucial, yet computationally expensive, step in unsteady turbulent flow simulations. We demonstrate a new technique for rapid generation of turbulent inflow realizations that leverages recent advances in machine learning for image generation using a deep convolutional generative adversarial network (DCGAN). The DCGAN is an unsupervised machine learning technique consisting of two competing neural networks that are trained against each other using backpropagation. One network, the generator, tries to produce samples from the true distribution of states, while the discriminator tries to distinguish between true and synthetic samples. We present results from a fully-trained DCGAN that is able to rapidly draw random samples from the full distribution of possible inflow states without needing to solve the Navier-Stokes equations, eliminating the costly process of spinning up inflow turbulence. This suggests a new paradigm in physics informed machine learning where the turbulence physics can be encoded in either the discriminator or generator. Finally, we also propose additional applications such as feature identification and subgrid scale modeling.
A note on the consensus finding problem in communication networks with switching topologies
Haskovec, Jan
2014-01-01
In this note, we discuss the problem of consensus finding in communication networks of agents with dynamically switching topologies. In particular, we consider the case of directed networks with unbalanced matrices of communication rates. We
Flow model for open-channel reach or network
Schaffranek, R.W.
1987-01-01
Formulation of a one-dimensional model for simulating unsteady flow in a single open-channel reach or in a network of interconnected channels is presented. The model is both general and flexible in that it can be used to simulate a wide range of flow conditions for various channel configurations. It is based on a four-point (box), implicit, finite-difference approximation of the governing nonlinear flow equations with user-definable weighting coefficients to permit varying the solution scheme from box-centered to fully forward. Unique transformation equations are formulated that permit correlation of the unknowns at the extremities of the channels, thereby reducing coefficient matrix and execution time requirements. Discharges and water-surface elevations computed at intermediate locations within a channel are determined following solution of the transformation equations. The matrix of transformation and boundary-condition equations is solved by Gauss elimination using maximum pivot strategy. Two diverse applications of the model are presented to illustrate its broad utility. (USGS)
Directory of Open Access Journals (Sweden)
M Soltani
Full Text Available Modeling of interstitial fluid flow involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. To date, majority of microvascular flow modeling has been done at different levels and scales mostly on simple tumor shapes with their capillaries. However, with our proposed numerical model, more complex and realistic tumor shapes and capillary networks can be studied. Both blood flow through a capillary network, which is induced by a solid tumor, and fluid flow in tumor's surrounding tissue are formulated. First, governing equations of angiogenesis are implemented to specify the different domains for the network and interstitium. Then, governing equations for flow modeling are introduced for different domains. The conservation laws for mass and momentum (including continuity equation, Darcy's law for tissue, and simplified Navier-Stokes equation for blood flow through capillaries are used for simulating interstitial and intravascular flows and Starling's law is used for closing this system of equations and coupling the intravascular and extravascular flows. This is the first study of flow modeling in solid tumors to naturalistically couple intravascular and extravascular flow through a network. This network is generated by sprouting angiogenesis and consisting of one parent vessel connected to the network while taking into account the non-continuous behavior of blood, adaptability of capillary diameter to hemodynamics and metabolic stimuli, non-Newtonian blood flow, and phase separation of blood flow in capillary bifurcation. The incorporation of the outlined components beyond the previous models provides a more realistic prediction of interstitial fluid flow pattern in solid tumors and surrounding tissues. Results predict higher interstitial pressure, almost two times, for realistic model compared to the simplified model.
Soltani, M; Chen, P
2013-01-01
Modeling of interstitial fluid flow involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. To date, majority of microvascular flow modeling has been done at different levels and scales mostly on simple tumor shapes with their capillaries. However, with our proposed numerical model, more complex and realistic tumor shapes and capillary networks can be studied. Both blood flow through a capillary network, which is induced by a solid tumor, and fluid flow in tumor's surrounding tissue are formulated. First, governing equations of angiogenesis are implemented to specify the different domains for the network and interstitium. Then, governing equations for flow modeling are introduced for different domains. The conservation laws for mass and momentum (including continuity equation, Darcy's law for tissue, and simplified Navier-Stokes equation for blood flow through capillaries) are used for simulating interstitial and intravascular flows and Starling's law is used for closing this system of equations and coupling the intravascular and extravascular flows. This is the first study of flow modeling in solid tumors to naturalistically couple intravascular and extravascular flow through a network. This network is generated by sprouting angiogenesis and consisting of one parent vessel connected to the network while taking into account the non-continuous behavior of blood, adaptability of capillary diameter to hemodynamics and metabolic stimuli, non-Newtonian blood flow, and phase separation of blood flow in capillary bifurcation. The incorporation of the outlined components beyond the previous models provides a more realistic prediction of interstitial fluid flow pattern in solid tumors and surrounding tissues. Results predict higher interstitial pressure, almost two times, for realistic model compared to the simplified model.
Open Problems in Network-aware Data Management in Exa-scale Computing and Terabit Networking Era
Energy Technology Data Exchange (ETDEWEB)
Balman, Mehmet; Byna, Surendra
2011-12-06
Accessing and managing large amounts of data is a great challenge in collaborative computing environments where resources and users are geographically distributed. Recent advances in network technology led to next-generation high-performance networks, allowing high-bandwidth connectivity. Efficient use of the network infrastructure is necessary in order to address the increasing data and compute requirements of large-scale applications. We discuss several open problems, evaluate emerging trends, and articulate our perspectives in network-aware data management.
MINET, Transient Fluid Flow and Heat Transfer Power Plant Network Analysis
International Nuclear Information System (INIS)
Van Tuyle, G.J.
2002-01-01
exception of variables which are control system related, such as pump speed, the system represented is closed and accessed only through boundary modules. MINET uses a homogeneous equilibrium model of two-phase flow, supplemented by various two-phase correlations. 3 - Restrictions on the complexity of the problem: Maxima of: 5 heat exchanger options; 3 heat exchanger tube configuration options; 2 turbine stage types. At least one inlet and one outlet boundary must be included in each fluid network. The MINET methodology is geared toward solving one-dimensional flow network problems (e.g., balance of plant) under non-blowdown transient conditions. Pressure waves are not tracked locally. It is implicitly assumed that the propagation of pressure waves in pipes, pumps, heat exchangers, and valves takes place on a time scale much smaller (milliseconds) than the transient of interest (seconds)
An effective fractal-tree closure model for simulating blood flow in large arterial networks.
Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em
2015-06-01
The aim of the present work is to address the closure problem for hemodynamic simulations by developing a flexible and effective model that accurately distributes flow in the downstream vasculature and can stably provide a physiological pressure outflow boundary condition. To achieve this goal, we model blood flow in the sub-pixel vasculature by using a non-linear 1D model in self-similar networks of compliant arteries that mimic the structure and hierarchy of vessels in the meso-vascular regime (radii [Formula: see text]). We introduce a variable vessel length-to-radius ratio for small arteries and arterioles, while also addressing non-Newtonian blood rheology and arterial wall viscoelasticity effects in small arteries and arterioles. This methodology aims to overcome substantial cut-off radius sensitivities, typically arising in structured tree and linearized impedance models. The proposed model is not sensitive to outflow boundary conditions applied at the end points of the fractal network, and thus does not require calibration of resistance/capacitance parameters typically required for outflow conditions. The proposed model convergences to a periodic state in two cardiac cycles even when started from zero-flow initial conditions. The resulting fractal-trees typically consist of thousands to millions of arteries, posing the need for efficient parallel algorithms. To this end, we have scaled up a Discontinuous Galerkin solver that utilizes the MPI/OpenMP hybrid programming paradigm to thousands of computer cores, and can simulate blood flow in networks of millions of arterial segments at the rate of one cycle per 5 min. The proposed model has been extensively tested on a large and complex cranial network with 50 parent, patient-specific arteries and 21 outlets to which fractal trees where attached, resulting to a network of up to 4,392,484 vessels in total, and a detailed network of the arm with 276 parent arteries and 103 outlets (a total of 702,188 vessels
SIPSON--simulation of interaction between pipe flow and surface overland flow in networks.
Djordjević, S; Prodanović, D; Maksimović, C; Ivetić, M; Savić, D
2005-01-01
The new simulation model, named SIPSON, based on the Preissmann finite difference method and the conjugate gradient method, is presented in the paper. This model simulates conditions when the hydraulic capacity of a sewer system is exceeded, pipe flow is pressurized, the water flows out from the piped system to the streets, and the inlets cannot capture all the runoff. In the mathematical model, buried structures and pipelines, together with surface channels, make a horizontally and vertically looped network involving a complex interaction of flows. In this paper, special internal boundary conditions related to equivalent inlets are discussed. Procedures are described for the simulation of manhole cover loss, basement flooding, the representation of street geometry, and the distribution of runoff hydrographs between surface and underground networks. All these procedures are built into the simulation model. Relevant issues are illustrated on a set of examples, focusing on specific parameters and comparison with field measurements of flooding of the Motilal ki Chal catchment (Indore, India). Satisfactory agreement of observed and simulated hydrographs and maximum surface flooding levels is obtained. It is concluded that the presented approach is an improvement compared to the standard "virtual reservoir" approach commonly applied in most of the models.
International Nuclear Information System (INIS)
Nicholson, Charles D.; Barker, Kash; Ramirez-Marquez, Jose E.
2016-01-01
This work develops and compares several flow-based vulnerability measures to prioritize important network edges for the implementation of preparedness options. These network vulnerability measures quantify different characteristics and perspectives on enabling maximum flow, creating bottlenecks, and partitioning into cutsets, among others. The efficacy of these vulnerability measures to motivate preparedness options against experimental geographically located disruption simulations is measured. Results suggest that a weighted flow capacity rate, which accounts for both (i) the contribution of an edge to maximum network flow and (ii) the extent to which the edge is a bottleneck in the network, shows most promise across four instances of varying network sizes and densities. - Highlights: • We develop new flow-based measures of network vulnerability. • We apply these measures to determine the importance of edges after disruptions. • Networks of varying size and density are explored.
Passenger flow analysis of Beijing urban rail transit network using fractal approach
Li, Xiaohong; Chen, Peiwen; Chen, Feng; Wang, Zijia
2018-04-01
To quantify the spatiotemporal distribution of passenger flow and the characteristics of an urban rail transit network, we introduce four radius fractal dimensions and two branch fractal dimensions by combining a fractal approach with passenger flow assignment model. These fractal dimensions can numerically describe the complexity of passenger flow in the urban rail transit network and its change characteristics. Based on it, we establish a fractal quantification method to measure the fractal characteristics of passenger follow in the rail transit network. Finally, we validate the reasonability of our proposed method by using the actual data of Beijing subway network. It has been shown that our proposed method can effectively measure the scale-free range of the urban rail transit network, network development and the fractal characteristics of time-varying passenger flow, which further provides a reference for network planning and analysis of passenger flow.
Efficient network-matrix architecture for general flow transport inspired by natural pinnate leaves.
Hu, Liguo; Zhou, Han; Zhu, Hanxing; Fan, Tongxiang; Zhang, Di
2014-11-14
Networks embedded in three dimensional matrices are beneficial to deliver physical flows to the matrices. Leaf architectures, pervasive natural network-matrix architectures, endow leaves with high transpiration rates and low water pressure drops, providing inspiration for efficient network-matrix architectures. In this study, the network-matrix model for general flow transport inspired by natural pinnate leaves is investigated analytically. The results indicate that the optimal network structure inspired by natural pinnate leaves can greatly reduce the maximum potential drop and the total potential drop caused by the flow through the network while maximizing the total flow rate through the matrix. These results can be used to design efficient networks in network-matrix architectures for a variety of practical applications, such as tissue engineering, cell culture, photovoltaic devices and heat transfer.
Design and Optimisation Problems in Wireless Sensor Networks
Indian Academy of Sciences (India)
Premkumar Karumbu,1.05 ECE,,+91-9448227167
2010-11-14
Nov 14, 2010 ... Wireless Networks of Multifunction Smart Sensors (WSNs). A smart sensor ... Energy and environment management networks in large buildings. Emerging ISA ... Monitoring mobile patients in hospitals and homes. Locating ...
Game Theoretic Solutions to Cyber Attack and Network Defense Problems
National Research Council Canada - National Science Library
Shen, Dan; Chen, Genshe; Cruz, Jr., , Jose B; Blasch, Erik; Kruger, Martin
2007-01-01
.... The protection and defense against cyber attacks to computer network is becoming inadequate as the hacker knowledge sophisticates and as the network and each computer system become more complex...
Yang, Shan; Tong, Xiangqian
2016-01-01
Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverte...
Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation
2014-08-01
Software - Defined Networking ( SDN ), when fully realized, offer many improvements over the current rigid and...functionalities like handshake, connection setup, switch management, and security. 15. SUBJECT TERMS OpenFlow, software - defined networking , Cisco ONE, SDN ...innovating packet-forwarding technologies. Network device roles are strictly defined with little or no flexibility. In Software - Defined Networks ( SDNs ),
The transportation management division institutional program: Networking and problem solving
International Nuclear Information System (INIS)
McGinnis, K.A.; Peterson, J.M.
1989-06-01
The US Department of Energy (DOE) has several programs related to transportation. While these programs may have differing missions and legislative authority, the required activities are frequently similar. To ensure a DOE-wide perspective in developing transportation policies and procedures, a DOE Transportation Institutional Task Force (Task Force) has been formed, which is the primary focus of this paper. The Task Force, composed of representatives from each of the major DOE transportation programs, meets periodically to exchange experiences and insights on institutional issues related to Departmental shipping. The primary purpose of the group is to identify opportunities for productive interactions with the transportation community, including interested and affected members of the public. This paper will also focus sharply on the networking of DOE with the State, Tribal, and local officials in fostering better understanding and in solving problems. An example of such activity is the DOE's cooperative agreement with the Energy Task Force of the Urban Consortium. A major effort is to encourage cooperative action in identifying, addressing, and resolving issues that could impede the transportation of radioactive materials
Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun Chris; Wu, Fang-Xiang
2011-05-01
A recurrent neural network is proposed for solving the non-smooth convex optimization problem with the convex inequality and linear equality constraints. Since the objective function and inequality constraints may not be smooth, the Clarke's generalized gradients of the objective function and inequality constraints are employed to describe the dynamics of the proposed neural network. It is proved that the equilibrium point set of the proposed neural network is equivalent to the optimal solution of the original optimization problem by using the Lagrangian saddle-point theorem. Under weak conditions, the proposed neural network is proved to be stable, and the state of the neural network is convergent to one of its equilibrium points. Compared with the existing neural network models for non-smooth optimization problems, the proposed neural network can deal with a larger class of constraints and is not based on the penalty method. Finally, the proposed neural network is used to solve the identification problem of genetic regulatory networks, which can be transformed into a non-smooth convex optimization problem. The simulation results show the satisfactory identification accuracy, which demonstrates the effectiveness and efficiency of the proposed approach.
On Howard's conjecture in heterogeneous shear flow problem
Indian Academy of Sciences (India)
M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22
Department of Mathematics, H.P. University, Shimla 171 005, India. ∗. Sidharth Govt. Degree College, Nadaun, Dist. Hamirpur 177 033 ... in proving it in the case of the Garcia-type [3] flows wherein the basic velocity distribution has a point of ...
Visualization of protein interaction networks: problems and solutions
Directory of Open Access Journals (Sweden)
Agapito Giuseppe
2013-01-01
Full Text Available Abstract Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins and edges (interactions, the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i technology, i.e. availability/license of the software and supported OS (Operating System platforms; (ii interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the
DEFF Research Database (Denmark)
Rawstron, Andy C; Orfao, Alberto; Beksac, Meral
2008-01-01
The European Myeloma Network (EMN) organized two flow cytometry workshops. The first aimed to identify specific indications for flow cytometry in patients with monoclonal gammopathies, and consensus technical approaches through a questionnaire-based review of current practice in participating...
Weinstock, Jeremiah; Burton, Steve; Rash, Carla J; Moran, Sheila; Biller, Warren; Krudelbach, Norman; Phoenix, Natalie; Morasco, Benjamin J
2011-06-01
Gambling help-lines are an essential access point, or frontline resource, for treatment seeking. This study investigated treatment engagement after calling a gambling help-line. From 2000-2007 over 2,900 unique callers were offered an in-person assessment appointment. Logistic regression analyses assessed predictors of (a) accepting the referral to the in-person assessment appointment and (b) attending the in-person assessment appointment. Over 76% of callers accepted the referral and 55% of all callers attended the in-person assessment appointment. This treatment engagement rate is higher than typically found for other help-lines. Demographic factors and clinical factors such as gender, severity of gambling problems, amount of gambling debt, and coercion by legal and social networks predicted engagement in treatment. Programmatic factors such as offering an appointment within 72 hr also aided treatment engagement. Results suggest gambling help-lines can be a convenient and confidential way for many individuals with gambling problems to access gambling-specific treatment. Alternative services such as telephone counseling may be beneficial for those who do not engage in treatment. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
Complex network analysis in inclined oil–water two-phase flow
International Nuclear Information System (INIS)
Zhong-Ke, Gao; Ning-De, Jin
2009-01-01
Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil–water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil–water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network (FPCN) and fluid dynamic complex network (FDCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil–water flow patterns. To investigate the dynamic characteristics of the inclined oil–water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil–water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil–water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice. (general)
Achieving Fair Throughput among TCP Flows in Multi-Hop Wireless Mesh Networks
Hou, Ting-Chao; Hsu, Chih-Wei
Previous research shows that the IEEE 802.11 DCF channel contention mechanism is not capable of providing throughput fairness among nodes in different locations of the wireless mesh network. The node nearest the gateway will always strive for the chance to transmit data, causing fewer transmission opportunities for the nodes farther from the gateway, resulting in starvation. Prior studies modify the DCF mechanism to address the fairness problem. This paper focuses on the fairness study when TCP flows are carried over wireless mesh networks. By not modifying lower layer protocols, the current work identifies TCP parameters that impact throughput fairness and proposes adjusting those parameters to reduce frame collisions and improve throughput fairness. With the aid of mathematical formulation and ns2 simulations, this study finds that frame transmission from each node can be effectively controlled by properly controlling the delayed ACK timer and using a suitable advertised window. The proposed method reduces frame collisions and greatly improves TCP throughput fairness.
A Network Traffic Control Enhancement Approach over Bluetooth Networks
DEFF Research Database (Denmark)
Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun
2003-01-01
This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated solu...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well......This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...
Directory of Open Access Journals (Sweden)
Cheng Xu
2015-01-01
Full Text Available Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk. However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed. The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN models for the prediction of free flow speed and crash risk on the separated bicycle path. Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics were developed. 459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing. The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models. Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics. The findings could contribute for evaluation, planning, and management of bicycle safety.
Xue, Jie; Gui, Dongwei; Zhao, Ying; Lei, Jiaqiang; Zeng, Fanjiang; Feng, Xinlong; Mao, Donglei; Shareef, Muhammad
2016-09-01
The competition for water resources between agricultural and natural oasis ecosystems has become an increasingly serious problem in oasis areas worldwide. Recently, the intensive extension of oasis farmland has led to excessive exploitation of water discharge, and consequently has resulted in a lack of water supply in natural oasis. To coordinate the conflicts, this paper provides a decision-making framework for modeling environmental flows in oasis areas using Bayesian networks (BNs). Three components are included in the framework: (1) assessment of agricultural economic loss due to meeting environmental flow requirements; (2) decision-making analysis using BNs; and (3) environmental flow decision-making under different water management scenarios. The decision-making criterion is determined based on intersection point analysis between the probability of large-level total agro-economic loss and the ratio of total to maximum agro-economic output by satisfying environmental flows. An application in the Qira oasis area of the Tarim Basin, Northwest China indicates that BNs can model environmental flow decision-making associated with agricultural economic loss effectively, as a powerful tool to coordinate water-use conflicts. In the case study, the environmental flow requirement is determined as 50.24%, 49.71% and 48.73% of the natural river flow in wet, normal and dry years, respectively. Without further agricultural economic loss, 1.93%, 0.66% and 0.43% of more river discharge can be allocated to eco-environmental water demands under the combined strategy in wet, normal and dry years, respectively. This work provides a valuable reference for environmental flow decision-making in any oasis area worldwide.
Directory of Open Access Journals (Sweden)
Xiangmin Guan
2015-01-01
Full Text Available Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology.
Network innovation through OpenFlow and SDN principles and design
Hu, Fei
2014-01-01
FUNDAMENTALSSDN /OpenFlow: Concepts and Applications; Ashley Gerrity and Fei HuAn OpenFlow Network Design Cycle; Pedro A. Aranda Gutiřrez and Diego R. LopezDESIGNIP Source Address Validation Solution with OpenFlow Extension and OpenRouter; Jun BiLanguage and Programming in SDN /OpenFlow; Muhammad Farooq and Fei HuControl and Management Software for SDNs; Natalia Castro Fernandes and Luiz Claudio Schara MagalhêsController Architecture and Performance in Software-Defined Networks; Ting Zhang and Fei HuMobile Applications on Global Clouds Using OpenFlow and Software-Defined Networking; Subharth
A Bi-Level Programming Model for the Railway Express Cargo Service Network Design Problem
Directory of Open Access Journals (Sweden)
Boliang Lin
2018-06-01
Full Text Available Service network design is fundamentally crucial for railway express cargo transportation. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and high expected operational incomes. Different configurations of these objectives will have different impacts on the quality of freight transportation services. In this paper, a bi-level programming model for the railway express cargo service network design problem is proposed. The upper-level model forms the optimal decisions in terms of the service characteristics, and the low-level model selects the service arcs for each commodity. The rail express cargo is strictly subject to the service commitment, the capacity restriction, flow balance constraints, and logical relationship constraints among the decisions variables. Moreover, linearization techniques are used to convert the lower-level model to a linear one so that it can be directly solved by a standard optimization solver. Finally, a real-world case study based on the Beijing–Guangzhou Railway Line is carried out to demonstrate the effectiveness and efficiency of the proposed solution approach.
Discrete bat algorithm for optimal problem of permutation flow shop scheduling.
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220
TOUGH Simulations of the Updegraff's Set of Fluid and Heat Flow Problems
Energy Technology Data Exchange (ETDEWEB)
Moridis, G.J.; Pruess (editor), K.
1992-11-01
The TOUGH code [Pruess, 1987] for two-phase flow of water, air, and heat in penneable media has been exercised on a suite of test problems originally selected and simulated by C. D. Updegraff [1989]. These include five 'verification' problems for which analytical or numerical solutions are available, and three 'validation' problems that model laboratory fluid and heat flow experiments. All problems could be run without any code modifications (*). Good and efficient numerical performance, as well as accurate results were obtained throughout. Additional code verification and validation problems from the literature are briefly summarized, and suggestions are given for proper applications of TOUGH and related codes.
The Location-Routing Problem with Full Truckloads in Low-Carbon Supply Chain Network Designing
Directory of Open Access Journals (Sweden)
Cheng Chen
2018-01-01
Full Text Available In recent years, low-carbon supply chain network design has been the focus of studies as the development of low-carbon economy. The location-routing problem with full truckloads (LRPFT is investigated in this paper, which extends the existing studies on the LRP to full truckloads problem within the regional many-to-many raw material supply network. A mathematical model with dual objectives of minimizing total cost and environmental effects simultaneously is developed to determine the number and locations of facilities and optimize the flows among different kinds of nodes and routes of trucks as well. A novel multiobjective hybrid approach named NSGA-II-TS is proposed by combining a known multiobjective algorithm, NSGA-II, and a known heuristics, Tabu Search (TS. A chromosome presentation based on natural number and modified partially mapping crossover operator for the LRPFT are designed. Finally, the computational effectiveness of the hybrid approach is validated by the numerical results and a practical case study is applied to demonstrate the tradeoff between total cost and CO2 emission in the LRPFT.
Energy Technology Data Exchange (ETDEWEB)
Jacob Raglend, I. [School of Electrical Sciences, Noorul Islam University, Kumaracoil 629 180 (India); Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B. [School of Electrical Sciences, Vellore Institute of Technology, Vellore 632 004 (India); Kothari, D.P. [FNAE, FNASC, SMIEEE, Vellore Institute of Technology University, Vellore 632 014 (India)
2010-07-15
A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)
International Nuclear Information System (INIS)
Jacob Raglend, I.; Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B.; Kothari, D.P.
2010-01-01
A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)
Lindner, Michael; Donner, Reik V
2017-03-01
We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a directed network that describes the exchange of mass between distinct regions of the flow domain. By studying different measures characterizing flow network connectivity at different time-scales, we are able to identify the location of dynamically invariant structures and regions of maximum dispersion. Specifically, our approach allows us to delimit co-existing flow regimes with different dynamics. To validate our findings, we compare several network characteristics to the well-established finite-time Lyapunov exponents and apply a receiver operating characteristic analysis to identify network measures that are particularly useful for unveiling the skeleton of Lagrangian chaos.
Directory of Open Access Journals (Sweden)
Ispolatov Iaroslav
2008-10-01
Full Text Available Abstract Background Finding the dominant direction of flow of information in densely interconnected regulatory or signaling networks is required in many applications in computational biology and neuroscience. This is achieved by first identifying and removing links which close up feedback loops in the original network and hierarchically arranging nodes in the remaining network. In mathematical language this corresponds to a problem of making a graph acyclic by removing as few links as possible and thus altering the original graph in the least possible way. The exact solution of this problem requires enumeration of all cycles and combinations of removed links, which, as an NP-hard problem, is computationally prohibitive even for modest-size networks. Results We introduce and compare two approximate numerical algorithms for solving this problem: the probabilistic one based on a simulated annealing of the hierarchical layout of the network which minimizes the number of "backward" links going from lower to higher hierarchical levels, and the deterministic, "greedy" algorithm that sequentially cuts the links that participate in the largest number of feedback cycles. We find that the annealing algorithm outperforms the deterministic one in terms of speed, memory requirement, and the actual number of removed links. To further improve a visual perception of the layout produced by the annealing algorithm, we perform an additional minimization of the length of hierarchical links while keeping the number of anti-hierarchical links at their minimum. The annealing algorithm is then tested on several examples of regulatory and signaling networks/pathways operating in human cells. Conclusion The proposed annealing algorithm is powerful enough to performs often optimal layouts of protein networks in whole organisms, consisting of around ~104 nodes and ~105 links, while the applicability of the greedy algorithm is limited to individual pathways with ~100
A new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.
Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints
Kmet', Tibor; Kmet'ová, Mária
2009-09-01
A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.
An integrated approach to combating flow assurance problems
Energy Technology Data Exchange (ETDEWEB)
Abney, Laurence; Browne, Alan [Halliburton, Houston, TX (United States)
2005-07-01
Any upset to the internal pipe surface of a pipeline can significantly impact both pipeline through-put and energy requirements for maintaining design flow rates. Inefficient flow through pipelines can have a significant negative impact on operating expense (Opex) and the energy requirements necessary to maintain pipeline through-put. Effective flow maintenance helps ensure that Opex remains within budget, processing equipment life is extended and that excessive use of energy is minimized. A number of events can result in debris generation and deposition in a pipeline. Corrosion, hydrate formation, paraffin deposition, asphaltene deposition, development of 'black powder' and scale formation are the most common sources of pipeline debris. Generally, a combination of pigging and chemical treatments is used to remove debris; these two techniques are commonly used in isolation. Incorporation of specialized fluids with enhanced solid-transport capabilities, specialized dispersants, or specialized surfactants can improve the success of routine pigging operations. An array of alternative and often complementary remediation technologies can be used to effect the removal of deposits or even full restrictions from pipelines. These include the application of acids, specialized chemical products, and intrusive interventions techniques. This paper presents a review of methods of integrating existing technologies. (author)
Evaluation of the reliability of transport networks based on the stochastic flow of moving objects
International Nuclear Information System (INIS)
Wu Weiwei; Ning, Angelika; Ning Xuanxi
2008-01-01
In transport networks, human beings are moving objects whose moving direction is stochastic in emergency situations. Based on this idea, a new model-stochastic moving network (SMN) is proposed. It is different from binary-state networks and stochastic-flow networks. The flow of SMNs has multiple-saturated states, that correspond to different flow values in each arc. In this paper, we try to evaluate the system reliability, defined as the probability that the saturated flow of the network is not less than a given demand d. Based on this new model, we obtain the flow probability distribution of every arc by simulation. An algorithm based on the blocking cutset of the SMN is proposed to evaluate the network reliability. An example is used to show how to calculate the corresponding reliabilities for different given demands of the SMN. Simulation experiments of different size were made and the system reliability precision was calculated. The precision of simulation results also discussed
Characterization of fracture networks for fluid flow analysis
International Nuclear Information System (INIS)
Long, J.C.S.; Billaux, D.; Hestir, K.; Majer, E.L.; Peterson, J.; Karasaki, K.; Nihei, K.; Gentier, S.; Cox, L.
1989-06-01
The analysis of fluid flow through fractured rocks is difficult because the only way to assign hydraulic parameters to fractures is to perform hydraulic tests. However, the interpretation of such tests, or ''inversion'' of the data, requires at least that we know the geometric pattern formed by the fractures. Combining a statistical approach with geophysical data may be extremely helpful in defining the fracture geometry. Cross-hole geophysics, either seismic or radar, can provide tomograms which are pixel maps of the velocity or attenuation anomalies in the rock. These anomalies are often due to fracture zones. Therefore, tomograms can be used to identify fracture zones and provide information about the structure within the fracture zones. This structural information can be used as the basis for simulating the degree of fracturing within the zones. Well tests can then be used to further refine the model. Because the fracture network is only partially connected, the resulting geometry of the flow paths may have fractal properties. We are studying the behavior of well tests under such geometry. Through understanding of this behavior, it may be possible to use inverse techniques to refine the a priori assignment of fractures and their conductances such that we obtain the best fit to a series of well test results simultaneously. The methodology described here is under development and currently being applied to several field sites. 4 refs., 14 figs
Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines
Directory of Open Access Journals (Sweden)
Eliana Marcela Peña Tibaduiza
2017-01-01
Full Text Available Context: The flow shop hybrid problem with unrelated parallel machines has been less studied in the academia compared to the flow shop hybrid with identical processors. For this reason, there are few reports about the kind of application of this problem in industries. Method: A literature review of the state of the art on flow-shop scheduling problem was conducted by collecting and analyzing academic papers on several scientific databases. For this aim, a search query was constructed using keywords defining the problem and checking the inclusion of unrelated parallel machines in such definition; as a result, 50 papers were finally selected for this study. Results: A classification of the problem according to the characteristics of the production system was performed, also solution methods, constraints and objective functions commonly used are presented. Conclusions: An increasing trend is observed in studies of flow shop with multiple stages, but few are based on industry case-studies.
International Nuclear Information System (INIS)
Gao Zhong-Ke; Hu Li-Dan; Jin Ning-De
2013-01-01
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. (general)
Reentrant Information Flow in Electrophysiological Rat Default Mode Network.
Jing, Wei; Guo, Daqing; Zhang, Yunxiang; Guo, Fengru; Valdés-Sosa, Pedro A; Xia, Yang; Yao, Dezhong
2017-01-01
Functional MRI (fMRI) studies have demonstrated that the rodent brain shows a default mode network (DMN) activity similar to that in humans, offering a potential preclinical model both for physiological and pathophysiological studies. However, the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we used electrophysiological data to analyze the power spectrum and estimate the directed phase transfer entropy (dPTE) within rat DMN across three vigilance states: wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). We observed decreased gamma powers during SWS compared with WR in most of the DMN regions. Increased gamma powers were found in prelimbic cortex, cingulate cortex, and hippocampus during REMS compared with WR, whereas retrosplenial cortex showed a reverse trend. These changed gamma powers are in line with the local metabolic variation of homologous brain regions in humans. In the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. Our results provide electrophysiological evidence that rat DMN is similar to its human counterpart, and there is a frequency-dependent reentry loop of anterior-posterior information flow within rat DMN, which may offer a mechanism for functional integration, supporting conscious awareness.
Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.
Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi
2016-01-01
Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.
Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks
Directory of Open Access Journals (Sweden)
Yoshiaki Taniguchi
2016-01-01
Full Text Available Software-Defined Networking (SDN has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator’s configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.
Scaling-Laws of Flow Entropy with Topological Metrics of Water Distribution Networks
Directory of Open Access Journals (Sweden)
Giovanni Francesco Santonastaso
2018-01-01
Full Text Available Robustness of water distribution networks is related to their connectivity and topological structure, which also affect their reliability. Flow entropy, based on Shannon’s informational entropy, has been proposed as a measure of network redundancy and adopted as a proxy of reliability in optimal network design procedures. In this paper, the scaling properties of flow entropy of water distribution networks with their size and other topological metrics are studied. To such aim, flow entropy, maximum flow entropy, link density and average path length have been evaluated for a set of 22 networks, both real and synthetic, with different size and topology. The obtained results led to identify suitable scaling laws of flow entropy and maximum flow entropy with water distribution network size, in the form of power–laws. The obtained relationships allow comparing the flow entropy of water distribution networks with different size, and provide an easy tool to define the maximum achievable entropy of a specific water distribution network. An example of application of the obtained relationships to the design of a water distribution network is provided, showing how, with a constrained multi-objective optimization procedure, a tradeoff between network cost and robustness is easily identified.
Combining neural networks and genetic algorithms for hydrological flow forecasting
Neruda, Roman; Srejber, Jan; Neruda, Martin; Pascenko, Petr
2010-05-01
We present a neural network approach to rainfall-runoff modeling for small size river basins based on several time series of hourly measured data. Different neural networks are considered for short time runoff predictions (from one to six hours lead time) based on runoff and rainfall data observed in previous time steps. Correlation analysis shows that runoff data, short time rainfall history, and aggregated API values are the most significant data for the prediction. Neural models of multilayer perceptron and radial basis function networks with different numbers of units are used and compared with more traditional linear time series predictors. Out of possible 48 hours of relevant history of all the input variables, the most important ones are selected by means of input filters created by a genetic algorithm. The genetic algorithm works with population of binary encoded vectors defining input selection patterns. Standard genetic operators of two-point crossover, random bit-flipping mutation, and tournament selection were used. The evaluation of objective function of each individual consists of several rounds of building and testing a particular neural network model. The whole procedure is rather computational exacting (taking hours to days on a desktop PC), thus a high-performance mainframe computer has been used for our experiments. Results based on two years worth data from the Ploucnice river in Northern Bohemia suggest that main problems connected with this approach to modeling are ovetraining that can lead to poor generalization, and relatively small number of extreme events which makes it difficult for a model to predict the amplitude of the event. Thus, experiments with both absolute and relative runoff predictions were carried out. In general it can be concluded that the neural models show about 5 per cent improvement in terms of efficiency coefficient over liner models. Multilayer perceptrons with one hidden layer trained by back propagation algorithm and
FCL: A solution to fault current problems in DC networks
International Nuclear Information System (INIS)
Cointe, Y; Tixador, P; Villard, C
2008-01-01
Within the context of the electric power market liberalization, DC networks have many interests compared to AC ones. New energy landscapes open the way of a diversified production. Innovative interconnection diagrams, in particular using DC buses, are under development. In this case it is not possible to defer the fault current interruption in the AC side. DC fault current cutting remains a difficult problem. FCLs (Fault Current Limiters) enable to limit the current to a preset value, lower than the theoretical short-circuit current. For this application Coated Conductors (CC) offer an excellent opportunity. Due to these promising characteristics we build a test bench and work on the implementation of these materials. The test bench is composed by 10 power amplifiers, to reach 4 kVA in many configurations of current and voltage. We carried out limiting experiments on DyBaCuO CC from EHTS, samples are about five centimeters long and many potential measuring points are pasted on the shunt to estimate the quench homogeneity. Thermal phenomena in FCLs are essential, numerical models are important to calculate the maximum temperatures. To validate these models we measure the CC temperature by depositing thermal sensors (Cu resistance) above the shunt layer and the substrate. An electrical insulation with a low thermal resistivity between the CC and the sensors is necessary. We use a thin layer of Parylene because of its good mechanical and electrical insulation properties at low temperature. The better quench behaviour of CC for temperatures close to the critical temperature has been confirmed. The measurements are in good agreement with simulations, this validates the thermal models
Application of meshless EFG method in fluid flow problems
Indian Academy of Sciences (India)
Meshless method; element-free Galerkin method; steady state analysis; transient ... ﬂuid ﬂow problems using the meshless element-free Galerkin method. The unknown function of velocity u ( x ) is approximated by moving least square ...
Cyclic flow shop scheduling problem with two-machine cells
Directory of Open Access Journals (Sweden)
Bożejko Wojciech
2017-06-01
Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.
Problems in the design of multifunction meteor-radar networks
Nechitailenko, V. A.; Voloshchuk, Iu. I.
The design of meteor-radar networks is examined in connection with the need to conduct experiments on a mass scale in meteor geophysics and astronomy. Attention is given to network architecture features and procedures of communication-path selection in the organization of information transfer, with allowance for the features of the meteor communication link. The meteor link is considered as the main means to ensure traffic in the meteor-radar network.
Self-teaching neural network learns difficult reactor control problem
International Nuclear Information System (INIS)
Jouse, W.C.
1989-01-01
A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits
A two-stage flow-based intrusion detection model for next-generation networks.
Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin
2018-01-01
The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.
Multiphase flow problems on thermofluid safety for fusion reactors
International Nuclear Information System (INIS)
Takase, Kazuyuki
2003-01-01
As the thermofluid safety study for the International Thermonuclear Experimental Reactor (ITER), thermal-hydraulic characteristics of Tokamak fusion reactors under transient events were investigated experimentally and analyzed numerically. As severe transient events an ingress-of-coolant event (ICE) and a loss-of-vacuum event (LOVA) were considered. An integrated ICE test facility was constructed to demonstrate that the ITER safety design approach and parameters are adequate. Water-vapor two-phase flow behavior and performance of the ITER pressure suppression system during the ICE were clarified by the integrated ICE experiments. The TRAC was modified to specify the two-phase flow behavior under the ICE. The ICE experimental results were verified using the modified TRAC code. On the other hand, activated dust mobilization and air ingress characteristics in the ITER vacuum vessel during the LOVA were analyzed using a newly developed analysis code. Some physical models on the motion of dust were considered. The rate of dust released from the vacuum vessel through breaches to the outside was characterized quantitatively. The predicted average pressures in the vacuum vessel during the LOVA were in good agreement with the experimental results. Moreover, direct-contact condensation characteristics between water and vapor inside the ITER suppression tank were observed visually and simulated by the direct two-phase flow analysis. Furthermore, chemical reaction characteristics between vapor and ITER plasma-facing component materials were predicted numerically in order to obtain qualitative estimation on generation of inflammable gases such as hydrogen and methane. The experimental and numerical results of the present studies were reflected in the ITER thermofluid safety design. (author)
Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng
2010-07-01
The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.
Cross-Layer Scheme to Control Contention Window for Per-Flow in Asymmetric Multi-Hop Networks
Giang, Pham Thanh; Nakagawa, Kenji
The IEEE 802.11 MAC standard for wireless ad hoc networks adopts Binary Exponential Back-off (BEB) mechanism to resolve bandwidth contention between stations. BEB mechanism controls the bandwidth allocation for each station by choosing a back-off value from one to CW according to the uniform random distribution, where CW is the contention window size. However, in asymmetric multi-hop networks, some stations are disadvantaged in opportunity of access to the shared channel and may suffer severe throughput degradation when the traffic load is large. Then, the network performance is degraded in terms of throughput and fairness. In this paper, we propose a new cross-layer scheme aiming to solve the per-flow unfairness problem and achieve good throughput performance in IEEE 802.11 multi-hop ad hoc networks. Our cross-layer scheme collects useful information from the physical, MAC and link layers of own station. This information is used to determine the optimal Contention Window (CW) size for per-station fairness. We also use this information to adjust CW size for each flow in the station in order to achieve per-flow fairness. Performance of our cross-layer scheme is examined on various asymmetric multi-hop network topologies by using Network Simulator (NS-2).
Design solutions to interface flow problems. Figures - Tables - Appendices
International Nuclear Information System (INIS)
1986-01-01
All published proposals for the deep level burial of radioactive waste recognise that the access shafts, tunnels and boreholes must be sealed, and that the sealing of these openings plays an integral role in the overall isolation of the waste. Previous studies have identified the interface between the host ground formation and the various sealing materials as potential defects in the overall quality of the waste isolation. The significance of groundwater flow at and near the interface has been assessed for representative conditions in generic repository materials. A range of design options to minimise the significance of flow in the interface zone have been proposed, and the most practical of these options have been selected for quantitative analysis. It has been found that isolated high impermability collars are of limited value unless a highly effective method of minimising ground disturbance during excavation can be developed. It has also been found that control of radionuclide migration by sorptive processes provides an attractive option. The effect of various geometrical arrangements of sorptive materials has been investigated. Consideration has also been given to the particular conditions in the near field, to the behaviour of weak plastic clay host formations and to the mechanical interaction between the backfill material and the host formation
Twopool strategy and the combined compressible/incompressible flow problem
International Nuclear Information System (INIS)
Sienicki, J.J.; Abramson, P.B.
1979-01-01
Most recent numerical modeling of two-phase flow involves an implicit determination of a pressure field upon which computational efficiency is strongly dependent. While cell by cell schemes (which treat the pressures in adjacent cells as known source terms) offer fast running times, permit the use of large time steps limited by a Courant condition restriction based on material velocities, and favor enhanced implicit coupling between the thermodynamic and hydrodynamic variables within individual cells, strong implicit coupling (as obtained with elimination schemes) between pressures in adjacent cells in pure single-phase liquid regions is necessary for the calculation of combined two-phase (compressible)/single-phase (incompressible) flows. The TWOPOOL strategy, which consists of a separation in the determination of a pressure field between the single-phase liquid cells where elimination is used and the two-phase cells where a cell by cell scheme is used, constitutes the fastest running strategy which permits the use of large time steps limited only by a Courant condition restriction based on material velocities
Transnational cocaine and heroin flow networks in western Europe: A comparison.
Chandra, Siddharth; Joba, Johnathan
2015-08-01
A comparison of the properties of drug flow networks for cocaine and heroin in a group of 17 western European countries is provided with the aim of understanding the implications of their similarities and differences for drug policy. Drug flow data for the cocaine and heroin networks were analyzed using the UCINET software package. Country-level characteristics including hub and authority scores, core and periphery membership, and centrality, and network-level characteristics including network density, the results of a triad census, and the final fitness of the core-periphery structure of the network, were computed and compared between the two networks. The cocaine network contains fewer path redundancies and a smaller, more tightly knit core than the heroin network. Authorities, hubs and countries central to the cocaine network tend to have higher hub, authority, and centrality scores than those in the heroin network. The core-periphery and hub-authority structures of the cocaine and heroin networks reflect the west-to-east and east-to-west patterns of flow of cocaine and heroin respectively across Europe. The key nodes in the cocaine and heroin networks are generally distinct from one another. The analysis of drug flow networks can reveal important structural features of trafficking networks that can be useful for the allocation of scarce drug control resources. The identification of authorities, hubs, network cores, and network-central nodes can suggest foci for the allocation of these resources. In the case of Europe, while some countries are important to both cocaine and heroin networks, different sets of countries occupy positions of prominence in the two networks. The distinct nature of the cocaine and heroin networks also suggests that a one-size-fits-all supply- and interdiction-focused policy may not work as well as an approach that takes into account the particular characteristics of each network. Copyright © 2015 Elsevier B.V. All rights reserved.
Spray flow-network flow transition of binary Lennard-Jones particle system
Inaoka, Hajime
2010-07-01
We simulate gas-liquid flows caused by rapid depressurization using a molecular dynamics model. The model consists of two types of Lennard-Jones particles, which we call liquid particles and gas particles. These two types of particles are distinguished by their mass and strength of interaction: a liquid particle has heavier mass and stronger interaction than a gas particle. By simulations with various initial number densities of these particles, we found that there is a transition from a spray flow to a network flow with an increase of the number density of the liquid particles. At the transition point, the size of the liquid droplets follows a power-law distribution, while it follows an exponential distribution when the number density of the liquid particles is lower than the critical value. The comparison between the transition of the model and that of models of percolation is discussed. The change of the average droplet size with the initial number density of the gas particles is also presented. © 2010 Elsevier B.V. All rights reserved.
Spray flow-network flow transition of binary Lennard-Jones particle system
Inaoka, Hajime; Yukawa, Satoshi; Ito, Nobuyasu
2010-01-01
We simulate gas-liquid flows caused by rapid depressurization using a molecular dynamics model. The model consists of two types of Lennard-Jones particles, which we call liquid particles and gas particles. These two types of particles are distinguished by their mass and strength of interaction: a liquid particle has heavier mass and stronger interaction than a gas particle. By simulations with various initial number densities of these particles, we found that there is a transition from a spray flow to a network flow with an increase of the number density of the liquid particles. At the transition point, the size of the liquid droplets follows a power-law distribution, while it follows an exponential distribution when the number density of the liquid particles is lower than the critical value. The comparison between the transition of the model and that of models of percolation is discussed. The change of the average droplet size with the initial number density of the gas particles is also presented. © 2010 Elsevier B.V. All rights reserved.
Olender, M.; Krenczyk, D.
2016-08-01
Modern enterprises have to react quickly to dynamic changes in the market, due to changing customer requirements and expectations. One of the key area of production management, that must continuously evolve by searching for new methods and tools for increasing the efficiency of manufacturing systems is the area of production flow planning and control. These aspects are closely connected with the ability to implement the concept of Virtual Enterprises (VE) and Virtual Manufacturing Network (VMN) in which integrated infrastructure of flexible resources are created. In the proposed approach, the players role perform the objects associated with the objective functions, allowing to solve the multiobjective production flow planning problems based on the game theory, which is based on the theory of the strategic situation. For defined production system and production order models ways of solving the problem of production route planning in VMN on computational examples for different variants of production flow is presented. Possible decision strategy to use together with an analysis of calculation results is shown.
Dynamic shortest path problems : hybrid routing policies considering network disruptions
Sever, D.; Dellaert, N.P.; Woensel, van T.; Kok, de A.G.
2013-01-01
Traffic network disruptions lead to significant increases in transportation costs. We consider networks in which a number of links are vulnerable to these disruptions leading to a significantly higher travel time on these links. For these vulnerable links, we consider known link disruption
Gong, J.; Rossen, W.R.
2014-01-01
Fracture network connectivity and aperture (or conductivity) distribution are two crucial features controlling the flow behavior of fractured formations. The effect of connectivity on flow properties is well documented. We focus here on the influence of fracture aperture distribution. We model a
Gong, J.; Rossen, W.R.
2017-01-01
Fracture network connectivity and aperture (or conductivity) distribution are two crucial features controlling flow behavior of naturally fractured reservoirs. The effect of connectivity on flow properties is well documented. In this paper, however, we focus here on the influence of fracture
OpenFlow Switching Performance using Network Simulator - 3
Sriram Prashanth, Naguru
2016-01-01
Context. In the present network inventive world, there is a quick expansion of switches and protocols, which are used to cope up with the increase in customer requirement in the networking. With increasing demand for higher bandwidths and lower latency and to meet these requirements new network paths are introduced. To reduce network load in present switching network, development of new innovative switching is required. These required results can be achieved by Software Define Network or Trad...
Robust optimal control of material flows in demand-driven supply networks
Laumanns, M.; Lefeber, A.A.J.
2006-01-01
We develop a model based on stochastic discrete-time controlleddynamical systems in order to derive optimal policies for controllingthe material flow in supply networks. Each node in the network isdescribed as a transducer such that the dynamics of the material andinformation flows within the entire
Analysis of network-wide transit passenger flows based on principal component analysis
Luo, D.; Cats, O.; van Lint, J.W.C.
2017-01-01
Transit networks are complex systems in which the passenger flow dynamics are difficult to capture and understand. While there is a growing ability to monitor and record travelers' behavior in the past decade, knowledge on network-wide passenger flows, which are essentially high-dimensional
Numerical analysis of Sakiadis flow problem considering Maxwell nanofluid
Directory of Open Access Journals (Sweden)
Mustafa Meraj
2017-01-01
Full Text Available This article investigates the flow of Maxwell nanofluid over a moving plate in a calm fluid. Novel aspects of Brownian motion and thermophoresis are taken into consideration. Revised model for passive control of nanoparticle volume fraction at the plate is used in this study. The formulated differential system is solved numerically by employing shooting approach together with fourth-fifth-order-Runge-Kutta integration procedure and Newton’s method. The solutions are greatly influenced with the variation of embedded parameters which include the local Deborah number, the Brownian motion parameter, the thermophoresis parameter, the Prandtl number, and the Schmidt number. We found that the variation in velocity distribution with an increase in local Deborah number is non-monotonic. Moreover, the reduced Nusselt number has a linear and direct relationship with the local Deborah number.
Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang
2016-02-01
With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.
LDV-measurements in pipe-flow problems and experiences
International Nuclear Information System (INIS)
Els, H.; Rouve, G.
1985-01-01
Measurements with LDV-technique in circular cross-sections cause optical problems. When not using an index matching fluid, the index differences between air, wall and fluid cause a poor definition. Horizontal beams and vertical beams do not intersect in the same point. This makes two-component measurements impossible and gives a very bad signal quality even at forward-scatter one-component measurements. Besides the index matching, supplementary lenses can solve this problem. Lenses, which perfectly adjust the difference between horizontal and vertical beams, and difficult to calculate and - even more - to manufacture in an average equipped workshop. IWW developed a number of single-curvature lenses, which do not give perfect accordance of the beams, but increase the signal quality distinctively and thus noticeably decrease the needed time to measure a whole grid in the circular cross-section. Besides that, they are easy to produce. These lenses are described and the needed correction formula given in this paper. Other correction techniques are discussed, some measurement results with the used equipment are shown
Element Free Lattice Boltzmann Method for Fluid-Flow Problems
International Nuclear Information System (INIS)
Jo, Jong Chull; Roh, Kyung Wan; Yune, Young Gill; Kim, Hho Jhung; Kwon, Young Kwon
2007-01-01
The Lattice Boltzmann Method (LBM) has been developed for application to thermal-fluid problems. Most of the those studies considered a regular shape of lattice or mesh like square and cubic grids. In order to apply the LBM to more practical cases, it is necessary to be able to solve complex or irregular shapes of problem domains. Some techniques were based on the finite element method. Generally, the finite element method is very powerful for solving two or three-dimensional complex or irregular shapes of domains using the iso-parametric element formulation which is based on a mathematical mapping from a regular shape of element in an imaginary domain to a more general and irregular shape of element in the physical domain. In addition, the element free technique is also quite useful to analyze a complex shape of domain because there is no need to divide a domain by a compatible finite element mesh. This paper presents a new finite element and element free formulations for the lattice Boltzmann equation using the general weighted residual technique. Then, a series of validation examples are presented
Element Free Lattice Boltzmann Method for Fluid-Flow Problems
Energy Technology Data Exchange (ETDEWEB)
Jo, Jong Chull; Roh, Kyung Wan; Yune, Young Gill; Kim, Hho Jhung [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of); Kwon, Young Kwon [US Naval Postgraduate School, New York (United States)
2007-10-15
The Lattice Boltzmann Method (LBM) has been developed for application to thermal-fluid problems. Most of the those studies considered a regular shape of lattice or mesh like square and cubic grids. In order to apply the LBM to more practical cases, it is necessary to be able to solve complex or irregular shapes of problem domains. Some techniques were based on the finite element method. Generally, the finite element method is very powerful for solving two or three-dimensional complex or irregular shapes of domains using the iso-parametric element formulation which is based on a mathematical mapping from a regular shape of element in an imaginary domain to a more general and irregular shape of element in the physical domain. In addition, the element free technique is also quite useful to analyze a complex shape of domain because there is no need to divide a domain by a compatible finite element mesh. This paper presents a new finite element and element free formulations for the lattice Boltzmann equation using the general weighted residual technique. Then, a series of validation examples are presented.
Grid dependency of wall heat transfer for simulation of natural convection flow problems
Loomans, M.G.L.C.; Seppänen, O.; Säteri, J.
2007-01-01
In the indoor environment natural convection is a well known air flow phenomenon. In numerical simulations applying the CFD technique it is also known as a flow problem that is difficult to solve. Alternatives are available to overcome the limitations of the default approach (standard k-e model with
Topology optimization of unsteady flow problems using the lattice Boltzmann method
DEFF Research Database (Denmark)
Nørgaard, Sebastian Arlund; Sigmund, Ole; Lazarov, Boyan Stefanov
2016-01-01
This article demonstrates and discusses topology optimization for unsteady incompressible fluid flows. The fluid flows are simulated using the lattice Boltzmann method, and a partial bounceback model is implemented to model the transition between fluid and solid phases in the optimization problems...
On non-permutation solutions to some two machine flow shop scheduling problems
V. Strusevich (Vitaly); P.J. Zwaneveld (Peter)
1994-01-01
textabstractIn this paper, we study two versions of the two machine flow shop scheduling problem, where schedule length is to be minimized. First, we consider the two machine flow shop with setup, processing, and removal times separated. It is shown that an optimal solution need not be a permutation
Verification of the network flow and transport/distributed velocity (NWFT/DVM) computer code
International Nuclear Information System (INIS)
Duda, L.E.
1984-05-01
The Network Flow and Transport/Distributed Velocity Method (NWFT/DVM) computer code was developed primarily to fulfill a need for a computationally efficient ground-water flow and contaminant transport capability for use in risk analyses where, quite frequently, large numbers of calculations are required. It is a semi-analytic, quasi-two-dimensional network code that simulates ground-water flow and the transport of dissolved species (radionuclides) in a saturated porous medium. The development of this code was carried out under a program funded by the US Nuclear Regulatory Commission (NRC) to develop a methodology for assessing the risk from disposal of radioactive wastes in deep geologic formations (FIN: A-1192 and A-1266). In support to the methodology development program, the NRC has funded a separate Maintenance of Computer Programs Project (FIN: A-1166) to ensure that the codes developed under A-1192 or A-1266 remain consistent with current operating systems, are as error-free as possible, and have up-to-date documentations for reference by the NRC staff. Part of this effort would include verification and validation tests to assure that a code correctly performs the operations specified and/or is representing the processes or system for which it is intended. This document contains four verification problems for the NWFT/DVM computer code. Two of these problems are analytical verifications of NWFT/DVM where results are compared to analytical solutions. The other two are code-to-code verifications where results from NWFT/DVM are compared to those of another computer code. In all cases NWFT/DVM showed good agreement with both the analytical solutions and the results from the other code
Omega-Harmonic Functions and Inverse Conductivity Problems on Networks
National Research Council Canada - National Science Library
Berenstein, Carlos A; Chung, Soon-Yeong
2003-01-01
.... To do this, they introduce an elliptic operator DELTA omega and an omega-harmonic function on the graph, with its physical interpretation being the diffusion equation on the graph, which models an electric network...
On the Eikonal equation in the pedestrian flow problem
Felcman, J.; Kubera, P.
2017-07-01
We consider the Pedestrian Flow Equations (PFEs) as the coupled system formed by the Eikonal equation and the first order hyperbolic system with the source term. The hyperbolic system consists of the continuity equation and momentum equation of fluid dynamics. Specifying the social and pressure forces in the momentum equation we come to the assumption that each pedestrian is trying to move in a desired direction (e.g. to the exit in the panic situation) with a desired velocity, where his velocity and the direction of movement depend on the density of pedestrians in his neighborhood. In [1] we used the model, where the desired direction of movement is given by the solution of the Eikonal equation (more precisely by the gradient of the solution). Here we avoid the solution of the Eikonal equation, which is the novelty of the paper. Based on the fact that the solution of the Eikonal equation has the meaning of the shortest time to reach the exit, we define explicitly such a function in the framework of the Dijkstra's algorithm for the shortest path in the graph. This is done at the discrete level of the solution. As the graph we use the underlying triangulation, where the norm of each edge is density depending and has the dimension of the time. The numerical examples of the solution of the PFEs with and without the solution of the Eikonal equation are presented.
Kim, Jeong-Nam
2018-01-01
This special issue of Health Communication compiles 10 articles to laud the promise and yet confront the problems in the digital networked information society related to public health. We present this anthology of symphony and cacophony of lay individuals' communicative actions in a digital networked information society. The collection of problems and promise of the new digital world may be a cornerstone joining two worlds-pre- and postdigital network society-and we hope this special issue will help better shape our future states of public health.
Second-order design problem in the Ancona geodetic network
International Nuclear Information System (INIS)
Baldi, P.; Ferrari, G.; Postpischl, D.; Unguendoli, M.
1980-01-01
In this note an examination is made of the control network installed in the Ancona area in 1975 for seismotectonic studies. From an analysis of the network there arises the possibility of achieving a considerable improvement in the results by considering a plan of work derived from the a priori analysis of the covariance matrix and improving the atmospheric data fo the correction of electronic distance measurements, by the use of meteorological balloons. (author)
Characterization of IP Flows Eligible for Lambda-Connections in Optical Networks
Fioreze, Tiago; Oude Wolbers, Mattijs; van de Meent, R.; Pras, Aiko
2008-01-01
The advance on data transmission in optical networks has allowed data forwarding decisions to be taken at multiple levels in the protocol stack (e.g., at network and optical levels). With such capability, big IP flows can be moved from the network level and switched completely at the optical level
From "E-flows" to "Sed-flows": Managing the Problem of Sediment in High Altitude Hydropower Systems
Gabbud, C.; Lane, S. N.
2017-12-01
The connections between stream hydraulics, geomorphology and ecosystems in mountain rivers have been substantially perturbed by humans, for example through flow regulation related to hydropower activities. It is well known that the ecosystem impacts downstream of hydropower dams may be managed by a properly designed compensation release or environmental flows ("e-flows"), and such flows may also include sediment considerations (e.g. to break up bed armor). However, there has been much less attention given to the ecosystem impacts of water intakes (where water is extracted and transferred for storage and/or power production), even though in many mountain systems such intakes may be prevalent. Flow intakes tend to be smaller than dams and because they fill quickly in the presence of sediment delivery, they often need to be flushed, many times within a day in Alpine glaciated catchments with high sediment yields. The associated short duration "flood" flow is characterised by very high sediment concentrations, which may drastically modify downstream habitat, both during the floods but also due to subsequent accumulation of "legacy" sediment. The impacts on flora and fauna of these systems have not been well studied. In addition, there are no guidelines established that might allow the design of "e-flows" that also treat this sediment problem, something we call "sed-flows". Through an Alpine field example, we quantify the hydrological, geomorphological, and ecosystem impacts of Alpine water transfer systems. The high sediment concentrations of these flushing flows lead to very high rates of channel disturbance downstream, superimposed upon long-term and progressive bed sediment accumulation. Monthly macroinvertebrate surveys over almost a two-year period showed that reductions in the flushing rate reduced rates of disturbance substantially, and led to rapid macroinvertebrate recovery, even in the seasons (autumn and winter) when biological activity should be reduced
Directory of Open Access Journals (Sweden)
Antonio Costa
2014-07-01
Full Text Available Production processes in Cellular Manufacturing Systems (CMS often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs and Biased Random Sampling (BRS search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.
OpenFlow Extensions for Programmable Quantum Networks
2017-06-19
Introduction 1 2. Background 1 2.1 Quantum Networks 2 2.2 Software -Defined Networks 3 3. Approach 3 3.1 Metadata 4 3.2 Switch 4 3.3 Controller 5... software -defined networks . Stanford (CA): Stanford University HotNets; 2010. 9. Raychev N. Algorithm for switching 4-bit packages in full quantum...applications to communicate. Advances in network protocols and architectures have led to the development of software -defined programmable networks
International Nuclear Information System (INIS)
Karpp, R.R.
1984-01-01
The particle solution of the problem of the symmetric impact of two compressible fluid stream is derived. The plane two-dimensional flow is assumed to be steady, and the inviscid compressible fluid is of the Chaplygin (tangent gas) type. The equations governing this flow are transformed to the hodograph plane where an exact, closed-form solution for the stream function is obtained. The distribution of fluid properties along the plane of symmetry and the shape of free surface streamlines are determined by transformation back to the physical plane. The problem of a compressible fluid jet penetrating an infinite target of similar material is also solved by considering a limiting case of this solution. Differences between compressible and incompressible flows of the type considered are illustrated
Overall Ventilation System Flow Network Calculation for Site Recommendation
International Nuclear Information System (INIS)
Steinhoff, Jeff J.
2001-01-01
The scope of this calculation is to determine ventilation system resistances, pressure drops, airflows, and operating cost estimates for the Site Recommendation (SR) design as detailed in the ''Site Recommendation Subsurface Layout'' (BSC (Bechtel SAIC Company) 2001a). The statutory limit for emplacement of waste in Yucca Mountain is 70,000 metric tons of uranium (MTU) and is considered the base case for this report. The objective is to determine the overall repository system ventilation flow network for the monitoring phase during normal operations and to provide a basis for the system description document design descriptions. Any values derived from this calculation will not be used to support construction, fabrication, or procurement. The work scope is identified in the ''Technical Work Plan for Subsurface Design Section FY01 Work Activities'' (CRWMS M and O 2001, pp. 6 and 13). In accordance with the technical work plan this calculation was prepared in accordance with AP-3.12Q, ''Calculations'' and other procedures invoked by AP-3.12Q. It also incorporates the procedure AP-SI1.Q, ''Software Management''
An analogue of Morse theory for planar linear networks and the generalized Steiner problem
International Nuclear Information System (INIS)
Karpunin, G A
2000-01-01
A study is made of the generalized Steiner problem: the problem of finding all the locally minimal networks spanning a given boundary set (terminal set). It is proposed to solve this problem by using an analogue of Morse theory developed here for planar linear networks. The space K of all planar linear networks spanning a given boundary set is constructed. The concept of a critical point and its index is defined for the length function l of a planar linear network. It is shown that locally minimal networks are local minima of l on K and are critical points of index 1. The theorem is proved that the sum of the indices of all the critical points is equal to χ(K)=1. This theorem is used to find estimates for the number of locally minimal networks spanning a given boundary set
On-line validation of feedwater flow rate in nuclear power plants using neural networks
International Nuclear Information System (INIS)
Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.
1994-01-01
On-line calibration of feedwater flow rate measurement in nuclear power plants provides a continuous realistic value of feedwater flow rate. It also reduces the manpower required for periodic calibration needed due to the fouling and defouling of the venturi meter surface condition. This paper presents a method for on-line validation of feedwater flow rate in nuclear power plants. The method is an improvement of the previously developed method which is based on the use of a set of process variables dynamically related to the feedwater flow rate. The online measurements of this set of variables are used as inputs to a neural network to obtain an estimate of the feedwater flow rate reading. The difference between the on-line feedwater flow rate reading, and the neural network estimate establishes whether there is a need to apply a correction factor to the feedwater flow rate measurement for calculation of the actual reactor power. The method was applied to the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant. The venturi meters used for flow measurements are susceptible to frequent fouling that degrades their measurement accuracy. The fouling effects can cause an inaccuracy of up to 3% relative error in feedwater flow rate reading. A neural network, whose inputs were the readings of a set of reference instruments, was designed to predict both feedwater flow rates simultaneously. A multi-layer feedforward neural network employing the backpropagation algorithm was used. A number of neural network training tests were performed to obtain an optimum filtering technique of the input/output data of the neural networks. The result of the selection of the filtering technique was confirmed by numerous Fast Fourier Transform (FFT) tests. Training and testing were done on data from TMI-1 nuclear power plant. The results show that the neural network can predict the correct flow rates with an absolute relative error of less than 2%
Solution of weakly compressible isothermal flow in landfill gas collection networks
Energy Technology Data Exchange (ETDEWEB)
Nec, Y [Thompson Rivers University, Kamloops, British Columbia (Canada); Huculak, G, E-mail: cranberryana@gmail.com, E-mail: greg@gnhconsulting.ca [GNH Consulting, Delta, British Columbia (Canada)
2017-12-15
Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy–Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein. (paper)
Solution of weakly compressible isothermal flow in landfill gas collection networks
Nec, Y.; Huculak, G.
2017-12-01
Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy-Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein.
Solution of weakly compressible isothermal flow in landfill gas collection networks
International Nuclear Information System (INIS)
Nec, Y; Huculak, G
2017-01-01
Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy–Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein. (paper)
Nonlinear analysis of gas-water/oil-water two-phase flow in complex networks
Gao, Zhong-Ke; Wang, Wen-Xu
2014-01-01
Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination with complex network theory. We systematically carried out gas-water/oil-water two-phase flow experiments for measuring the time series of flow signals which is studied in terms of the mapping from time series to complex networks. Three network mapping methods were proposed for the analysis and identification of flow patterns, i.e. Flow Pattern Complex Network (FPCN), Fluid Dynamic Complex Network (FDCN) and Fluid Structure Complex Network (FSCN). Through detecting the community structure of FPCN based on K-means clustering, distinct flow patterns can be successfully distinguished and identified. A number of FDCN’s under different flow conditions were constructed in order to reveal the dynamical characteristics of two-phase flows. The FDCNs exhibit universal power-law degree distributions. The power-law exponent ...
Micro/Nano-pore Network Analysis of Gas Flow in Shale Matrix.
Zhang, Pengwei; Hu, Liming; Meegoda, Jay N; Gao, Shengyan
2015-08-27
The gas flow in shale matrix is of great research interests for optimized shale gas extraction. The gas flow in the nano-scale pore may fall in flow regimes such as viscous flow, slip flow and Knudsen diffusion. A 3-dimensional nano-scale pore network model was developed to simulate dynamic gas flow, and to describe the transient properties of flow regimes. The proposed pore network model accounts for the various size distributions and low connectivity of shale pores. The pore size, pore throat size and coordination number obey normal distribution, and the average values can be obtained from shale reservoir data. The gas flow regimes were simulated using an extracted pore network backbone. The numerical results show that apparent permeability is strongly dependent on pore pressure in the reservoir and pore throat size, which is overestimated by low-pressure laboratory tests. With the decrease of reservoir pressure, viscous flow is weakening, then slip flow and Knudsen diffusion are gradually becoming dominant flow regimes. The fingering phenomenon can be predicted by micro/nano-pore network for gas flow, which provides an effective way to capture heterogeneity of shale gas reservoir.
The Flow of International Students from a Macro Perspective: A Network Analysis
Barnett, George A.; Lee, Moosung; Jiang, Ke; Park, Han Woo
2016-01-01
This paper provides a network analysis of the international flow of students among 210 countries and the factors determining the structure of this flow. Among these factors, bilateral hyperlink connections between countries and the number of telephone minutes (communication variables) are the most important predictors of the flow's structure,…
Impedance void-meter and neural networks for vertical two-phase flows
International Nuclear Information System (INIS)
Mi, Y.; Li, M.; Xiao, Z.; Tsoukalas, L.H.; Ishii, M.
1998-01-01
Most two-phase flow measurements, including void fraction measurements, depend on correct flow regime identification. There are two steps towards successful identification of flow regimes: one is to develop a non-intrusive instrument to demonstrate area-averaged void fluctuations, the other to develop a non-linear mapping approach to perform objective identification of flow regimes. A non-intrusive impedance void-meter provides input signals to a neural mapping approach used to identify flow regimes. After training, both supervised and self-organizing neural network learning paradigms performed flow regime identification successfully. The methodology presented holds considerable promise for multiphase flow diagnostic and measurement applications. (author)
Mixed hybrid finite elements and streamline computation for the potential flow problem
Kaasschieter, E.F.; Huijben, A.J.M.
1992-01-01
An important class of problems in mathematical physics involves equations of the form -¿ · (A¿¿) = f. In a variety of problems it is desirable to obtain an accurate approximation of the flow quantity u = -A¿¿. Such an accurate approximation can be determined by the mixed finite element method. In
Existence and uniqueness of solution for a model problem of transonic flow
International Nuclear Information System (INIS)
Tangmanee, S.
1985-11-01
A model problem of transonic flow ''the Tricomi equation'' bounded by the rectangular-curve boundary is studied. We transform the model problem into a symmetric positive system and an admissible boundary condition is posed. We show that with some conditions the existence and uniqueness of the solution are guaranteed. (author)
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Blaheta, Radim; Byczanski, Petr; Karátson, J.; Ahmad, B.
2015-01-01
Roč. 280, č. 280 (2015), s. 141-157 ISSN 0377-0427 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : preconditioners * heterogeneous coefficients * regularized saddle point Inner–outer iterations * Darcy flow Subject RIV: BA - General Mathematics Impact factor: 1.328, year: 2015 http://www.sciencedirect.com/science/article/pii/S0377042714005238
Cholet, Cybèle; Charlier, Jean-Baptiste; Moussa, Roger; Steinmann, Marc; Denimal, Sophie
2017-07-01
The aim of this study is to present a framework that provides new ways to characterize the spatio-temporal variability of lateral exchanges for water flow and solute transport in a karst conduit network during flood events, treating both the diffusive wave equation and the advection-diffusion equation with the same mathematical approach, assuming uniform lateral flow and solute transport. A solution to the inverse problem for the advection-diffusion equations is then applied to data from two successive gauging stations to simulate flows and solute exchange dynamics after recharge. The study site is the karst conduit network of the Fourbanne aquifer in the French Jura Mountains, which includes two reaches characterizing the network from sinkhole to cave stream to the spring. The model is applied, after separation of the base from the flood components, on discharge and total dissolved solids (TDSs) in order to assess lateral flows and solute concentrations and compare them to help identify water origin. The results showed various lateral contributions in space - between the two reaches located in the unsaturated zone (R1), and in the zone that is both unsaturated and saturated (R2) - as well as in time, according to hydrological conditions. Globally, the two reaches show a distinct response to flood routing, with important lateral inflows on R1 and large outflows on R2. By combining these results with solute exchanges and the analysis of flood routing parameters distribution, we showed that lateral inflows on R1 are the addition of diffuse infiltration (observed whatever the hydrological conditions) and localized infiltration in the secondary conduit network (tributaries) in the unsaturated zone, except in extreme dry periods. On R2, despite inflows on the base component, lateral outflows are observed during floods. This pattern was attributed to the concept of reversal flows of conduit-matrix exchanges, inducing a complex water mixing effect in the saturated zone
Directory of Open Access Journals (Sweden)
C. Cholet
2017-07-01
Full Text Available The aim of this study is to present a framework that provides new ways to characterize the spatio-temporal variability of lateral exchanges for water flow and solute transport in a karst conduit network during flood events, treating both the diffusive wave equation and the advection–diffusion equation with the same mathematical approach, assuming uniform lateral flow and solute transport. A solution to the inverse problem for the advection–diffusion equations is then applied to data from two successive gauging stations to simulate flows and solute exchange dynamics after recharge. The study site is the karst conduit network of the Fourbanne aquifer in the French Jura Mountains, which includes two reaches characterizing the network from sinkhole to cave stream to the spring. The model is applied, after separation of the base from the flood components, on discharge and total dissolved solids (TDSs in order to assess lateral flows and solute concentrations and compare them to help identify water origin. The results showed various lateral contributions in space – between the two reaches located in the unsaturated zone (R1, and in the zone that is both unsaturated and saturated (R2 – as well as in time, according to hydrological conditions. Globally, the two reaches show a distinct response to flood routing, with important lateral inflows on R1 and large outflows on R2. By combining these results with solute exchanges and the analysis of flood routing parameters distribution, we showed that lateral inflows on R1 are the addition of diffuse infiltration (observed whatever the hydrological conditions and localized infiltration in the secondary conduit network (tributaries in the unsaturated zone, except in extreme dry periods. On R2, despite inflows on the base component, lateral outflows are observed during floods. This pattern was attributed to the concept of reversal flows of conduit–matrix exchanges, inducing a complex water mixing effect
International Nuclear Information System (INIS)
Pouransari, Nasibeh; Maréchal, Francois
2015-01-01
Highlights: • Synthesizing industrial size heat recovery network with match reduction approach. • Targeting TSI with minimum exchange between process subsystems. • Generating a feasible close-to-optimum network. • Reducing tremendously the HLD computational time and complexity. • Generating realistic network with respect to the plant layout. - Abstract: This paper presents a targeting strategy to design a heat recovery network for an industrial plant by dividing the system into subsystems while considering the heat transfer opportunities between them. The methodology is based on a sequential approach. The heat recovery opportunity between process units and the optimal flow rates of utilities are first identified using a Mixed Integer Linear Programming (MILP) model. The site is then divided into a number of subsystems where the overall interaction is resumed by a pair of virtual hot and cold stream per subsystem which is reconstructed by solving the heat cascade inside each subsystem. The Heat Load Distribution (HLD) problem is then solved between those packed subsystems in a sequential procedure where each time one of the subsystems is unpacked by switching from the virtual stream pair back into the original ones. The main advantages are to minimize the number of connections between process subsystems, to alleviate the computational complexity of the HLD problem and to generate a feasible network which is compatible with the minimum energy consumption objective. The application of the proposed methodology is illustrated through a number of case studies, discussed and compared with the relevant results from the literature
A review of scheduling problem and resolution methods in flexible flow shop
Directory of Open Access Journals (Sweden)
Tian-Soon Lee
2019-01-01
Full Text Available The Flexible flow shop (FFS is defined as a multi-stage flow shops with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. This review paper gives a comprehensive exploration review on the FFS scheduling problem and guides the reader by considering and understanding different environmental assumptions, system constraints and objective functions for future research works. The published papers are classified into two categories. First is the FFS system characteristics and constraints including the problem differences and limitation defined by different studies. Second, the scheduling performances evaluation are elaborated and categorized into time, job and multi related objectives. In addition, the resolution approaches that have been used to solve FFS scheduling problems are discussed. This paper gives a comprehensive guide for the reader with respect to future research work on the FFS scheduling problem.
Bilevel programming problems theory, algorithms and applications to energy networks
Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya
2015-01-01
This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.
Marriage in Honey Bees Optimization Algorithm for Flow-shop Problems
Directory of Open Access Journals (Sweden)
Pedro PALOMINOS
2012-01-01
Full Text Available The objective of this work is to make a comparative study of the Marriage in Honeybees Op-timization (MBO metaheuristic for flow-shop scheduling problems. This paper is focused on the design possibilities of the mating flight space shared by queens and drones. The proposed algorithm uses a 2-dimensional torus as an explicit mating space instead of the simulated an-nealing one in the original MBO. After testing different alternatives with benchmark datasets, the results show that the modeled and implemented metaheuristic is effective to solve flow-shop type problems, providing a new approach to solve other NP-Hard problems.
Islam, Mujahidul
A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable
Tests of peak flow scaling in simulated self-similar river networks
Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.
2001-01-01
The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.
Heuristics methods for the flow shop scheduling problem with separated setup times
Directory of Open Access Journals (Sweden)
Marcelo Seido Nagano
2012-06-01
Full Text Available This paper deals with the permutation flow shop scheduling problem with separated machine setup times. As a result of an investigation on the problem characteristics, four heuristics methods are proposed with procedures of the construction sequencing solution by an analogy with the asymmetric traveling salesman problem with the objective of minimizing makespan. Experimental results show that one of the new heuristics methods proposed provide high quality solutions in comparisons with the evaluated methods considered in the literature.
Directory of Open Access Journals (Sweden)
M. F. Akorede
2017-06-01
Full Text Available The intent of power distribution companies (DISCOs is to deliver electric power to their customers in an efficient and reliable manner – with minimal energy loss cost. One major way to minimise power loss on a given power system is to install distributed generation (DG units on the distribution networks. However, to maximise benefits, it is highly crucial for a DISCO to ensure that these DG units are of optimal size and sited in the best locations on the network. This paper gives an overview of a software package developed in this study, called Power System Analysis and DG Optimisation Tool (PFADOT. The main purpose of the graphical user interface-based package is to guide a DISCO in finding the optimal size and location for DG placement in radial distribution networks. The package, which is also suitable for load flow analysis, employs the GUI feature of MATLAB. Three objective functions are formulated into a single optimisation problem and solved with fuzzy genetic algorithm to simultaneously obtain DG optimal size and location. The accuracy and reliability of the developed tool was validated using several radial test systems, and the results obtained are evaluated against the existing similar package cited in the literature, which are impressive and computationally efficient.
Directory of Open Access Journals (Sweden)
Rongsheng Dong
2016-01-01
Full Text Available Evaluating the reliability of Multistate Flow Network (MFN is an NP-hard problem. Ordered binary decision diagram (OBDD or variants thereof, such as multivalued decision diagram (MDD, are compact and efficient data structures suitable for dealing with large-scale problems. Two symbolic algorithms for evaluating the reliability of MFN, MFN_OBDD and MFN_MDD, are proposed in this paper. In the algorithms, several operating functions are defined to prune the generated decision diagrams. Thereby the state space of capacity combinations is further compressed and the operational complexity of the decision diagrams is further reduced. Meanwhile, the related theoretical proofs and complexity analysis are carried out. Experimental results show the following: (1 compared to the existing decomposition algorithm, the proposed algorithms take less memory space and fewer loops. (2 The number of nodes and the number of variables of MDD generated in MFN_MDD algorithm are much smaller than those of OBDD built in the MFN_OBDD algorithm. (3 In two cases with the same number of arcs, the proposed algorithms are more suitable for calculating the reliability of sparse networks.
A matheuristic for the liner shipping network design problem
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Desaulniers, Guy; Pisinger, David
2014-01-01
, while minimizing the cost of operating the network. Liner shipping companies publish a set of routes with a time schedule, and it is an industry standard to have a weekly departure at each port call on a route. A weekly frequency is achieved by deploying several vessels to a single route, respecting...
Analyzing Human Communication Networks in Organizations: Applications to Management Problems.
Farace, Richard V.; Danowski, James A.
Investigating the networks of communication in organizations leads to an understanding of efficient and inefficient information dissemination as practiced in large systems. Most important in organizational communication is the role of the "liaison person"--the coordinator of intercommunication. When functioning efficiently, coordinators maintain…
Inverse problems in eddy current testing using neural network
Yusa, N.; Cheng, W.; Miya, K.
2000-05-01
Reconstruction of crack in conductive material is one of the most important issues in the field of eddy current testing. Although many attempts to reconstruct cracks have been made, most of them deal with only artificial cracks machined with electro-discharge. However, in the case of natural cracks like stress corrosion cracking or inter-granular attack, there must be contact region and therefore their conductivity is not necessarily zero. In this study, an attempt to reconstruct natural cracks using neural network is presented. The neural network was trained through numerical simulated data obtained by the fast forward solver that calculated unflawed potential data a priori to save computational time. The solver is based on A-φ method discretized by using FEM-BEM A natural crack was modeled as an area whose conductivity was less than that of a specimen. The distribution of conductivity in that area was reconstructed as well. It took much time to train the network, but the speed of reconstruction was extremely fast after once it was trained. Well-trained network gave good reconstruction result.
Software defined networks reactive flow programming and load balance switching
Καλλιανιώτης, Νικόλαος; Kallianiotis, Nikolaos
2017-01-01
This project serves as a Master Thesis as the requirements of the master’s programme Master of Digital Communications and Networks. It proposes load balancing algorithms applied to Software-Defined Networks to achieve the best possible resource utilisation of each of the links present in a network. The open-sources Opendaylight project and Floodlight project are used as SDN controllers, and the network is emulated using Mininet software
Energy Technology Data Exchange (ETDEWEB)
Cottrell, R.Les; Logg, Connie; Chhaparia, Mahesh; /SLAC; Grigoriev, Maxim; /Fermilab; Haro, Felipe; /Chile U., Catolica; Nazir, Fawad; /NUST, Rawalpindi; Sandford, Mark
2006-01-25
End-to-End fault and performance problems detection in wide area production networks is becoming increasingly hard as the complexity of the paths, the diversity of the performance, and dependency on the network increase. Several monitoring infrastructures are built to monitor different network metrics and collect monitoring information from thousands of hosts around the globe. Typically there are hundreds to thousands of time-series plots of network metrics which need to be looked at to identify network performance problems or anomalous variations in the traffic. Furthermore, most commercial products rely on a comparison with user configured static thresholds and often require access to SNMP-MIB information, to which a typical end-user does not usually have access. In our paper we propose new techniques to detect network performance problems proactively in close to realtime and we do not rely on static thresholds and SNMP-MIB information. We describe and compare the use of several different algorithms that we have implemented to detect persistent network problems using anomalous variations analysis in real end-to-end Internet performance measurements. We also provide methods and/or guidance for how to set the user settable parameters. The measurements are based on active probes running on 40 production network paths with bottlenecks varying from 0.5Mbits/s to 1000Mbit/s. For well behaved data (no missed measurements and no very large outliers) with small seasonal changes most algorithms identify similar events. We compare the algorithms' robustness with respect to false positives and missed events especially when there are large seasonal effects in the data. Our proposed techniques cover a wide variety of network paths and traffic patterns. We also discuss the applicability of the algorithms in terms of their intuitiveness, their speed of execution as implemented, and areas of applicability. Our encouraging results compare and evaluate the accuracy of our
Buddala, Raviteja; Mahapatra, Siba Sankar
2017-11-01
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.
Parallel algorithms for network routing problems and recurrences
International Nuclear Information System (INIS)
Wisniewski, J.A.; Sameh, A.H.
1982-01-01
In this paper, we consider the parallel solution of recurrences, and linear systems in the regular algebra of Carre. These problems are equivalent to solving the shortest path problem in graph theory, and they also arise in the analysis of Fortran programs. Our methods for solving linear systems in the regular algebra are analogues of well-known methods for solving systems of linear algebraic equations. A parallel version of Dijkstra's method, which has no linear algebraic analogue, is presented. Considerations for choosing an algorithm when the problem is large and sparse are also discussed
Qin, Sitian; Yang, Xiudong; Xue, Xiaoping; Song, Jiahui
2017-10-01
Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimization problem with equality and inequality constraints. It is proved that from any initial state, the state of the proposed neural network reaches the feasible region in finite time and stays there thereafter. It is also proved that the state of the proposed neural network is convergent to an optimal solution of the related problem. Compared with the related existing recurrent neural networks for the pseudoconvex optimization problems, the proposed neural network in this paper does not need the penalty parameters and has a better convergence. Meanwhile, the proposed neural network is used to solve three nonsmooth optimization problems, and we make some detailed comparisons with the known related conclusions. In the end, some numerical examples are provided to illustrate the effectiveness of the performance of the proposed neural network.
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
Liu, Richeng; Li, Bo; Jiang, Yujing; Yu, Liyuan
2018-01-01
solving fluid flow problems in fracture networks.
DEFF Research Database (Denmark)
Parraguez, Pedro; Eppinger, Steven D.; Maier, Anja
2015-01-01
The pattern of information flow through the network of interdependent design activities is thought to be an important determinant of engineering design process results. A previously unexplored aspect of such patterns relates to the temporal dynamics of information transfer between activities...... design process and thus support theory-building toward the evolution of information flows through systems engineering stages. Implications include guidance on how to analyze and predict information flows as well as better planning of information flows in engineering design projects according...
Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems
Majumdar, Alok K.; Ravindran, S. S.
2017-01-01
Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.
The influence of passenger flow on the topology characteristics of urban rail transit networks
Hu, Yingyue; Chen, Feng; Chen, Peiwen; Tan, Yurong
2017-05-01
Current researches on the network characteristics of metro networks are generally carried out on topology networks without passenger flows running on it, thus more complex features of the networks with ridership loaded on it cannot be captured. In this study, we incorporated the load of metro networks, passenger volume, into the exploration of network features. Thus, the network can be examined in the context of operation, which is the ultimate purpose of the existence of a metro network. To this end, section load was selected as an edge weight to demonstrate the influence of ridership on the network, and a weighted calculation method for complex network indicators and robustness were proposed to capture the unique behaviors of a metro network with passengers flowing in it. The proposed method was applied on Beijing Subway. Firstly, the passenger volume in terms of daily origin and destination matrix was extracted from exhausted transit smart card data. Using the established approach and the matrix as weighting, common indicators of complex network including clustering coefficient, betweenness and degree were calculated, and network robustness were evaluated under potential attacks. The results were further compared to that of unweighted networks, and it suggests indicators of the network with consideration of passenger volumes differ from that without ridership to some extent, and networks tend to be more vulnerable than that without load on it. The significance sequence for the stations can be changed. By introducing passenger flow weighting, actual operation status of the network can be reflected more accurately. It is beneficial to determine the crucial stations and make precautionary measures for the entire network’s operation security.
Guidelines on CV networking information flow optimization for Texas.
2017-03-01
Recognizing the fundamental role of information flow in future transportation applications, the research team investigated the quality and security of information flow in the connected vehicle (CV) environment. The research team identified key challe...
Li, Man; Wang, Yanhui; Jia, Limin
2017-01-01
Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.
Directory of Open Access Journals (Sweden)
Man Li
Full Text Available Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.
Application of neural networks and cellular automata to calorimetric problems
Energy Technology Data Exchange (ETDEWEB)
Brenton, V; Fonvieille, H; Guicheney, C; Jousset, J; Roblin, Y; Tamin, F; Grenier, P
1994-09-01
Computing techniques based on parallel processing have been used to treat the information from the electromagnetic calorimeters in SLAC experiments E142/E143. Cluster finding and separation of overlapping showers are performed by a cellular automaton, pion and electron identification is done by using a multilayered neural network. Both applications are presented and their resulting performances are shown to be improved compared to more standard approaches. (author). 9 refs.; Submitted to Nuclear Instruments and Methods (NL).
Application of neural networks and cellular automata to calorimetric problems
International Nuclear Information System (INIS)
Brenton, V.; Fonvieille, H.; Guicheney, C.; Jousset, J.; Roblin, Y.; Tamin, F.; Grenier, P.
1994-09-01
Computing techniques based on parallel processing have been used to treat the information from the electromagnetic calorimeters in SLAC experiments E142/E143. Cluster finding and separation of overlapping showers are performed by a cellular automaton, pion and electron identification is done by using a multilayered neural network. Both applications are presented and their resulting performances are shown to be improved compared to more standard approaches. (author)
Analysis of multimedian problems on time dependent networks
Salman, F Sibel
1994-01-01
Ankara : The Department of Industrial Engineering and the Institute of Enginering and Science of Bilkent Univ., 1994. Thesis (Master's) -- Bilkent University, 1994. Includes bibliographical references leaves 81-85. Time dependency arises in transportation and computer-communication networks due to factors such as time varying demand, traffic intensity, and road conditions. This necessitates a locational decision to be based on an analysis involving a time horizon. In this st...
Multicast backup reprovisioning problem for Hamiltonian cycle-based protection on WDM networks
Din, Der-Rong; Huang, Jen-Shen
2014-03-01
As networks grow in size and complexity, the chance and the impact of failures increase dramatically. The pre-allocated backup resources cannot provide 100% protection guarantee when continuous failures occur in a network. In this paper, the multicast backup re-provisioning problem (MBRP) for Hamiltonian cycle (HC)-based protection on WDM networks for the link-failure case is studied. We focus on how to recover the protecting capabilities of Hamiltonian cycle against the subsequent link-failures on WDM networks for multicast transmissions, after recovering the multicast trees affected by the previous link-failure. Since this problem is a hard problem, an algorithm, which consists of several heuristics and a genetic algorithm (GA), is proposed to solve it. The simulation results of the proposed method are also given. Experimental results indicate that the proposed algorithm can solve this problem efficiently.
Directory of Open Access Journals (Sweden)
M. A. Karakuts
2015-01-01
Full Text Available The basic problems of route network and aircraft fleet optimization and its role in airline strategic planning are considered. Measures to improve the methods of its implementation are proposed.
Interacting with Users in Social Networks: The Follow-back Problem
2016-05-02
These functions are known as network centrali- ties. They quantify how central a vertex is to the problem at hand, with the definition of centrality ...56 4.2.2 Twitter networks . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.2.3 Network centrality policies...tool can hinder the free movement of alternative ideas and information and thus can be analyzed through the A2/AD paradigm. Non-state adversaries have
Symposium Connects Government Problems with State of the Art Network Science Research
2015-10-16
Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering
Multi-frequency complex network from time series for uncovering oil-water flow structure.
Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan
2015-02-04
Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.
Yoo, Peter E; Hagan, Maureen A; John, Sam E; Opie, Nicholas L; Ordidge, Roger J; O'Brien, Terence J; Oxley, Thomas J; Moffat, Bradford A; Wong, Yan T
2018-03-08
Performing voluntary movements involves many regions of the brain, but it is unknown how they work together to plan and execute specific movements. We recorded high-resolution ultra-high-field blood-oxygen-level-dependent signal during a cued ankle-dorsiflexion task. The spatiotemporal dynamics and the patterns of task-relevant information flow across the dorsal motor network were investigated. We show that task-relevant information appears and decays earlier in the higher order areas of the dorsal motor network then in the primary motor cortex. Furthermore, the results show that task-relevant information is encoded in general initially, and then selective goals are subsequently encoded in specifics subregions across the network. Importantly, the patterns of recurrent information flow across the network vary across different subregions depending on the goal. Recurrent information flow was observed across all higher order areas of the dorsal motor network in the subregions encoding for the current goal. In contrast, only the top-down information flow from the supplementary motor cortex to the frontoparietal regions, with weakened recurrent information flow between the frontoparietal regions and bottom-up information flow from the frontoparietal regions to the supplementary cortex were observed in the subregions encoding for the opposing goal. We conclude that selective motor goal encoding and execution rely on goal-dependent differences in subregional recurrent information flow patterns across the long-range dorsal motor network areas that exhibit graded functional specialization. © 2018 Wiley Periodicals, Inc.
Computation of optimal transport and related hedging problems via penalization and neural networks
Eckstein, Stephan; Kupper, Michael
2018-01-01
This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a finite dimensional one which corresponds to optimizing a neural network with smooth objective function. We present numerical examples from optimal transport, martingale optimal transport, portfolio optimization under uncertainty and generative adversa...
Brands, Ties; van Berkum, Eric C.
2014-01-01
The optimization of infrastructure planning in a multimodal network is defined as a multi-objective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. Decision variables are the location of park and ride facilities, train
Cappelli, Daniele; Mansour, Nagi N.
2012-01-01
Separation can be seen in most aerodynamic flows, but accurate prediction of separated flows is still a challenging problem for computational fluid dynamics (CFD) tools. The behavior of several Reynolds Averaged Navier-Stokes (RANS) models in predicting the separated ow over a wall-mounted hump is studied. The strengths and weaknesses of the most popular RANS models (Spalart-Allmaras, k-epsilon, k-omega, k-omega-SST) are evaluated using the open source software OpenFOAM. The hump ow modeled in this work has been documented in the 2004 CFD Validation Workshop on Synthetic Jets and Turbulent Separation Control. Only the baseline case is treated; the slot flow control cases are not considered in this paper. Particular attention is given to predicting the size of the recirculation bubble, the position of the reattachment point, and the velocity profiles downstream of the hump.
Comparison of neural networks for solving the travelling salesman problem
Maire, La B.F.J.; Mladenov, V.M.
2012-01-01
The TSP deals with finding a shortest path through a number of cities. This seemingly simple problem is hard to solve because of the amount of possible solutions. Which is why methods that give a good suboptimal solution in a reasonable time are generally used. In this paper three methods were
Adolescent problem behavior in school : the role of peer networks
Geven, S.A.J.
2016-01-01
Adolescence is a notable period during which a considerable share of students tends to engage in problem behavior in school. Students for example skip class, fail to do their best in school, or have serious arguments with their teachers. A student’s decision to engage in such behavior is not usually
On the Integrated Job Scheduling and Constrained Network Routing Problem
DEFF Research Database (Denmark)
Gamst, Mette
This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...
Heuristic approach to the passive optical network with fibre duct ...
African Journals Online (AJOL)
Integer programming, network flow optimisation, passive optical network, ... This paper uses concepts from network flow optimisation to incorporate fibre duct shar ... [4] studied the survivable constrained ConFL problem and solved a number of.
Operator splitting method for simulation of dynamic flows in natural gas pipeline networks
Dyachenko, Sergey A.; Zlotnik, Anatoly; Korotkevich, Alexander O.; Chertkov, Michael
2017-12-01
We develop an operator splitting method to simulate flows of isothermal compressible natural gas over transmission pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy-Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where natural gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.
2012-06-01
The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...
National Research Council Canada - National Science Library
Mitchell, Jason
2003-01-01
.... This model is used to study the effect of communication delays on the performance of an iteractive network flow optimization model that results in a sequence of linear programs for the optimal...
2012-11-01
The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...
Huang, Darong; Bai, Xing-Rong
Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.
2015-06-01
This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and : Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale : demonstration of ...
Dual plane problems for creeping flow of power-law incompressible medium
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Dmitriy S. Petukhov
2016-09-01
Full Text Available In this paper, we consider the class of solutions for a creeping plane flow of incompressible medium with power-law rheology, which are written in the form of the product of arbitrary power of the radial coordinate by arbitrary function of the angular coordinate of the polar coordinate system covering the plane. This class of solutions represents the asymptotics of fields in the vicinity of singular points in the domain occupied by the examined medium. We have ascertained the duality of two problems for a plane with wedge-shaped notch, at which boundaries in one of the problems the vector components of the surface force vanish, while in the other—the vanishing components are the vector components of velocity, We have investigated the asymptotics and eigensolutions of the dual nonlinear eigenvalue problems in relation to the rheological exponent and opening angle of the notch for the branch associated with the eigenvalue of the Hutchinson–Rice–Rosengren problem learned from the problem of stress distribution over a notched plane for a power law medium. In the context of the dual problem we have determined the velocity distribution in the flow of power-law medium at the vertex of a rigid wedge, We have also found another two eigenvalues, one of which was determined by V. V. Sokolovsky for the problem of power-law fluid flow in a convergent channel.
Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç
2017-10-01
This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Zhao, Haoran
2016-01-01
Renewable energies are increasingly integrated in electric distribution networks and will cause severe overvoltage issues. Smart grid technologies make it possible to use coordinated control to mitigate the overvoltage issues and the optimal power flow (OPF) method is proven to be efficient...... in the applications such as curtailment management and reactive power control. Nonconvex nature of the OPF makes it difficult to solve and convex relaxation is a promising method to solve the OPF very efficiently. This paper investigates the geometry of the power flows and the convex-relaxed power flows when high...
Directory of Open Access Journals (Sweden)
Jilian Wu
2013-01-01
Full Text Available We discuss several stabilized finite element methods, which are penalty, regular, multiscale enrichment, and local Gauss integration method, for the steady incompressible flow problem with damping based on the lowest equal-order finite element space pair. Then we give the numerical comparisons between them in three numerical examples which show that the local Gauss integration method has good stability, efficiency, and accuracy properties and it is better than the others for the steady incompressible flow problem with damping on the whole. However, to our surprise, the regular method spends less CPU-time and has better accuracy properties by using Crout solver.
The Planar Sandwich and Other 1D Planar Heat Flow Test Problems in ExactPack
Energy Technology Data Exchange (ETDEWEB)
Singleton, Jr., Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-01-24
This report documents the implementation of several related 1D heat flow problems in the verification package ExactPack [1]. In particular, the planar sandwich class defined in Ref. [2], as well as the classes PlanarSandwichHot, PlanarSandwichHalf, and other generalizations of the planar sandwich problem, are defined and documented here. A rather general treatment of 1D heat flow is presented, whose main results have been implemented in the class Rod1D. All planar sandwich classes are derived from the parent class Rod1D.
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Xiaohui Lin
2017-01-01
Full Text Available Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1 no control strategy, (2 boundary control, and (3 boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.
Energy Technology Data Exchange (ETDEWEB)
Deister, F.; Hirschel, E.H. [Univ. Stuttgart, IAG, Stuttgart (Germany); Waymel, F.; Monnoyer, F. [Univ. de Valenciennes, LME, Valenciennes (France)
2003-07-01
An automatic adaptive hybrid Cartesian grid generation and simulation system is presented together with applications. The primary computational grid is an octree Cartesian grid. A quasi-prismatic grid may be added for resolving the boundary layer region of viscous flow around the solid body. For external flow simulations the flow solver TAU from the ''deutsche zentrum fuer luft- und raumfahrt (DLR)'' is integrated in the simulation system. Coarse grids are generated automatically, which are required by the multilevel method. As an application to an internal problem the thermal and dynamic modeling of a subway station is presented. (orig.)
Kawai, T.
Among the topics discussed are the application of FEM to nonlinear free surface flow, Navier-Stokes shallow water wave equations, incompressible viscous flows and weather prediction, the mathematical analysis and characteristics of FEM, penalty function FEM, convective, viscous, and high Reynolds number FEM analyses, the solution of time-dependent, three-dimensional and incompressible Navier-Stokes equations, turbulent boundary layer flow, FEM modeling of environmental problems over complex terrain, and FEM's application to thermal convection problems and to the flow of polymeric materials in injection molding processes. Also covered are FEMs for compressible flows, including boundary layer flows and transonic flows, hybrid element approaches for wave hydrodynamic loadings, FEM acoustic field analyses, and FEM treatment of free surface flow, shallow water flow, seepage flow, and sediment transport. Boundary element methods and FEM computational technique topics are also discussed. For individual items see A84-25834 to A84-25896
Managing BTSs to Solve Handover Problem in Mobile Network
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Wael Etaiwi
2011-01-01
Full Text Available Handover is a key solution that improves the telecommunication services using GSM by assure the continual service delivery between two mobiles regardless of location's changes of the sender or receiver, and now GSM technology becomes applicable all over the world and the customers become more satisfied to the dealer's services delivery, But Handover suffers from a major problem refers to the limitation of hardware capacity of the BTS (Base Transfer Station. This approach consists of three schemes, the first one based on reserve an extra ports for handover purposes by implementing a software solution that control BTS ports. The second alternative scheme based on channel exchange between adjacent BTSs by shifting a chosen allocated signal to another adjacent free BTS and then allocating the new signal to the new free port. The third schema depends on carrying the Handover problem to another BTS to solve it if it didn't solved in the second schema.
Jordan, Katy; Weller, Martin
2018-01-01
The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a large-scale dataset published by Nature Publishing Group detailing the results of a survey about academics use of online social networking services. An ope...
Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J
2013-06-01
Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset
An analytical solution to the heat transfer problem in thick-walled hunt flow
International Nuclear Information System (INIS)
Bluck, Michael J; Wolfendale, Michael J
2017-01-01
Highlights: • Convective heat transfer in Hunt type flow of a liquid metal in a rectangular duct. • Analytical solution to the H1 constant peripheral temperature in a rectangular duct. • New H1 result demonstrating the enhancement of heat transfer due to flow distortion by the applied magnetic field. • Analytical solution to the H2 constant peripheral heat flux in a rectangular duct. • New H2 result demonstrating the reduction of heat transfer due to flow distortion by the applied magnetic field. • Results are important for validation of CFD in magnetohydrodynamics and for implementation of systems code approaches. - Abstract: The flow of a liquid metal in a rectangular duct, subject to a strong transverse magnetic field is of interest in a number of applications. An important application of such flows is in the context of coolants in fusion reactors, where heat is transferred to a lead-lithium eutectic. It is vital, therefore, that the heat transfer mechanisms are understood. Forced convection heat transfer is strongly dependent on the flow profile. In the hydrodynamic case, Nusselt numbers and the like, have long been well characterised in duct geometries. In the case of liquid metals in strong magnetic fields (magnetohydrodynamics), the flow profiles are very different and one can expect a concomitant effect on convective heat transfer. For fully developed laminar flows, the magnetohydrodynamic problem can be characterised in terms of two coupled partial differential equations. The problem of heat transfer for perfectly electrically insulating boundaries (Shercliff case) has been studied previously (Bluck et al., 2015). In this paper, we demonstrate corresponding analytical solutions for the case of conducting hartmann walls of arbitrary thickness. The flow is very different from the Shercliff case, exhibiting jets near the side walls and core flow suppression which have profound effects on heat transfer.
A network-flow based valve-switching aware binding algorithm for flow-based microfluidic biochips
DEFF Research Database (Denmark)
Tseng, Kai-Han; You, Sheng-Chi; Minhass, Wajid Hassan
2013-01-01
-flow based resource binding algorithm based on breadth-first search (BFS) and minimum cost maximum flow (MCMF) in architectural-level synthesis. The experimental results show that our methodology not only makes significant reduction of valve-switching activities but also diminishes the application completion......Designs of flow-based microfluidic biochips are receiving much attention recently because they replace conventional biological automation paradigm and are able to integrate different biochemical analysis functions on a chip. However, as the design complexity increases, a flow-based microfluidic...... biochip needs more chip-integrated micro-valves, i.e., the basic unit of fluid-handling functionality, to manipulate the fluid flow for biochemical applications. Moreover, frequent switching of micro-valves results in decreased reliability. To minimize the valve-switching activities, we develop a network...
Self-sustained oscillations in blood flow through a honeycomb capillary network.
Davis, J M; Pozrikidis, C
2014-09-01
Numerical simulations of unsteady blood flow through a honeycomb network originating at multiple inlets and terminating at multiple outlets are presented and discussed under the assumption that blood behaves as a continuum with variable constitution. Unlike a tree network, the honeycomb network exhibits both diverging and converging bifurcations between branching capillary segments. Numerical results based on a finite difference method demonstrate that as in the case of tree networks considered in previous studies, the cell partitioning law at diverging bifurcations is an important parameter in both steady and unsteady flow. Specifically, a steady flow may spontaneously develop self-sustained oscillations at critical conditions by way of a Hopf bifurcation. Contrary to tree-like networks comprised entirely of diverging bifurcations, the critical parameters for instability in honeycomb networks depend weakly on the system size. The blockage of one or more network segments due to the presence of large cells or the occurrence of capillary constriction may cause flow reversal or trigger a transition to unsteady flow.
Agribusiness networks in Bulgaria: Design and creative problem-solving
Directory of Open Access Journals (Sweden)
Doitchinova Julia
2017-01-01
Full Text Available With the increasing integration of the global economy and the complex challenges of the business environment it is becoming crucial to focus and gain a full understanding on the role of the value chains' structure and functioning. This particularly refers to the countries from the post-communist Europe and their transformation and progress achieved in marketization and democratization. The present paper is purposeful towards providing an overall framework for assessment of the different forms of network structures in the agricultural sector and to identify as well their capacity to counteract market restrictions, and to benefit form the opportunities of the agribusiness development. The methodological framework bases on the transaction costs economics and the 4C concept. The paper presents methodology at two stages, where results of expert assessment and evaluation at national and regional level led to selection of three case studies to be presented in certain sectors of agribusiness.
Assessment of network inference methods: how to cope with an underdetermined problem.
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Caroline Siegenthaler
Full Text Available The inference of biological networks is an active research area in the field of systems biology. The number of network inference algorithms has grown tremendously in the last decade, underlining the importance of a fair assessment and comparison among these methods. Current assessments of the performance of an inference method typically involve the application of the algorithm to benchmark datasets and the comparison of the network predictions against the gold standard or reference networks. While the network inference problem is often deemed underdetermined, implying that the inference problem does not have a (unique solution, the consequences of such an attribute have not been rigorously taken into consideration. Here, we propose a new procedure for assessing the performance of gene regulatory network (GRN inference methods. The procedure takes into account the underdetermined nature of the inference problem, in which gene regulatory interactions that are inferable or non-inferable are determined based on causal inference. The assessment relies on a new definition of the confusion matrix, which excludes errors associated with non-inferable gene regulations. For demonstration purposes, the proposed assessment procedure is applied to the DREAM 4 In Silico Network Challenge. The results show a marked change in the ranking of participating methods when taking network inferability into account.
A two-layer recurrent neural network for nonsmooth convex optimization problems.
Qin, Sitian; Xue, Xiaoping
2015-06-01
In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with existing neural network models, the proposed neural network has a low model complexity and avoids penalty parameters. It is proved that from any initial point, the state of the proposed neural network reaches the equality feasible region in finite time and stays there thereafter. Moreover, the state is unique if the initial point lies in the equality feasible region. The equilibrium point set of the proposed neural network is proved to be equivalent to the Karush-Kuhn-Tucker optimality set of the original optimization problem. It is further proved that the equilibrium point of the proposed neural network is stable in the sense of Lyapunov. Moreover, from any initial point, the state is proved to be convergent to an equilibrium point of the proposed neural network. Finally, as applications, the proposed neural network is used to solve nonlinear convex programming with linear constraints and L1 -norm minimization problems.
A point implicit time integration technique for slow transient flow problems
Energy Technology Data Exchange (ETDEWEB)
Kadioglu, Samet Y., E-mail: kadioglu@yildiz.edu.tr [Department of Mathematical Engineering, Yildiz Technical University, 34210 Davutpasa-Esenler, Istanbul (Turkey); Berry, Ray A., E-mail: ray.berry@inl.gov [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States); Martineau, Richard C. [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States)
2015-05-15
Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very
A point implicit time integration technique for slow transient flow problems
International Nuclear Information System (INIS)
Kadioglu, Samet Y.; Berry, Ray A.; Martineau, Richard C.
2015-01-01
Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very
Parallel patterns determination in solving cyclic flow shop problem with setups
Directory of Open Access Journals (Sweden)
Bożejko Wojciech
2017-06-01
Full Text Available The subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP. We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.
A Special Class of Univalent Functions in Hele-Shaw Flow Problems
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Paula Curt
2011-01-01
Full Text Available We study the time evolution of the free boundary of a viscous fluid for planar flows in Hele-Shaw cells under injection. Applying methods from the theory of univalent functions, we prove the invariance in time of Φ-likeness property (a geometric property which includes starlikeness and spiral-likeness for two basic cases: the inner problem and the outer problem. We study both zero and nonzero surface tension models. Certain particular cases are also presented.
Consensus problem in directed networks of multi-agents via nonlinear protocols
International Nuclear Information System (INIS)
Liu Xiwei; Chen Tianping; Lu Wenlian
2009-01-01
In this Letter, the consensus problem via distributed nonlinear protocols for directed networks is investigated. Its dynamical behaviors are described by ordinary differential equations (ODEs). Based on graph theory, matrix theory and the Lyapunov direct method, some sufficient conditions of nonlinear protocols guaranteeing asymptotical or exponential consensus are presented and rigorously proved. The main contribution of this work is that for nonlinearly coupled networks, we generalize the results for undirected networks to directed networks. Consensus under pinning control technique is also developed here. Simulations are also given to show the validity of the theories.
End-to-End Traffic Flow Modeling of the Integrated SCaN Network
Cheung, K.-M.; Abraham, D. S.
2012-05-01
In this article, we describe the analysis and simulation effort of the end-to-end traffic flow for the Integrated Space Communications and Navigation (SCaN) Network. Using the network traffic derived for the 30-day period of July 2018 from the Space Communications Mission Model (SCMM), we generate the wide-area network (WAN) bandwidths of the ground links for different architecture options of the Integrated SCaN Network. We also develop a new analytical scheme to model the traffic flow and buffering mechanism of a store-and-forward network. It is found that the WAN bandwidth of the Integrated SCaN Network is an important differentiator of different architecture options, as the recurring circuit costs of certain architecture options can be prohibitively high.
A non-penalty recurrent neural network for solving a class of constrained optimization problems.
Hosseini, Alireza
2016-01-01
In this paper, we explain a methodology to analyze convergence of some differential inclusion-based neural networks for solving nonsmooth optimization problems. For a general differential inclusion, we show that if its right hand-side set valued map satisfies some conditions, then solution trajectory of the differential inclusion converges to optimal solution set of its corresponding in optimization problem. Based on the obtained methodology, we introduce a new recurrent neural network for solving nonsmooth optimization problems. Objective function does not need to be convex on R(n) nor does the new neural network model require any penalty parameter. We compare our new method with some penalty-based and non-penalty based models. Moreover for differentiable cases, we implement circuit diagram of the new neural network. Copyright © 2015 Elsevier Ltd. All rights reserved.
A constructive logic for services and information flow in computer networks
Borghuis, V.A.J.; Feijs, L.M.G.
2000-01-01
In this paper we introduce a typed -calculus in which computer networks can be formalized and directed at situations where the services available on the network are stationary, while the information can flow freely. For this calculus, an analogue of the ‘propositions-as-types ’interpretation of
Dynamic logics of networks: Information flow and the spread of opinion
Christoff, Z.L.
2016-01-01
This thesis uses logical tools to investigate a number of basic features of social networks and their evolution over time, including flow of information and spread of opinions. Part I contains the preliminaries, including an introduction to the basic phenomena in social networks that call for a
Applying the flow-capturing location-allocation model to an authentic network: Edmonton, Canada
M.J. Hodgson (John); K.E. Rosing (Kenneth); A.L.G. Storrier (Leontien)
1996-01-01
textabstractTraditional location-allocation models aim to locate network facilities to optimally serve demand expressed as weights at nodes. For some types of facilities demand is not expressed at nodes, but as passing network traffic. The flow-capturing location-allocation model responds to this
High order methods for incompressible fluid flow: Application to moving boundary problems
Energy Technology Data Exchange (ETDEWEB)
Bjoentegaard, Tormod
2008-04-15
Fluid flows with moving boundaries are encountered in a large number of real life situations, with two such types being fluid-structure interaction and free-surface flows. Fluid-structure phenomena are for instance apparent in many hydrodynamic applications; wave effects on offshore structures, sloshing and fluid induced vibrations, and aeroelasticity; flutter and dynamic response. Free-surface flows can be considered as a special case of a fluid-fluid interaction where one of the fluids are practically inviscid, such as air. This type of flows arise in many disciplines such as marine hydrodynamics, chemical engineering, material processing, and geophysics. The driving forces for free-surface flows may be of large scale such as gravity or inertial forces, or forces due to surface tension which operate on a much smaller scale. Free-surface flows with surface tension as a driving mechanism include the flow of bubbles and droplets, and the evolution of capillary waves. In this work we consider incompressible fluid flow, which are governed by the incompressible Navier-Stokes equations. There are several challenges when simulating moving boundary problems numerically, and these include - Spatial discretization - Temporal discretization - Imposition of boundary conditions - Solution strategy for the linear equations. These are some of the issues which will be addressed in this introduction. We will first formulate the problem in the arbitrary Lagrangian-Eulerian framework, and introduce the weak formulation of the problem. Next, we discuss the spatial and temporal discretization before we move to the imposition of surface tension boundary conditions. In the final section we discuss the solution of the resulting linear system of equations. (Author). refs., figs., tabs
Directory of Open Access Journals (Sweden)
Jeng-Fung Chen
2014-11-01
Full Text Available The accuracy of reservoir flow forecasting has the most significant influence on the assurance of stability and annual operations of hydro-constructions. For instance, accurate forecasting on the ebb and flow of Vietnam’s Hoabinh Reservoir can aid in the preparation and prevention of lowland flooding and drought, as well as regulating electric energy. This raises the need to propose a model that accurately forecasts the incoming flow of the Hoabinh Reservoir. In this study, a solution to this problem based on neural network with the Cuckoo Search (CS algorithm is presented. In particular, we used hydrographic data and predicted total incoming flows of the Hoabinh Reservoir over a period of 10 days. The Cuckoo Search algorithm was utilized to train the feedforward neural network (FNN for prediction. The algorithm optimized the weights between layers and biases of the neuron network. Different forecasting models for the three scenarios were developed. The constructed models have shown high forecasting performance based on the performance indices calculated. These results were also compared with those obtained from the neural networks trained by the particle swarm optimization (PSO and back-propagation (BP, indicating that the proposed approach performed more effectively. Based on the experimental results, the scenario using the rainfall and the flow as input yielded the highest forecasting accuracy when compared with other scenarios. The performance criteria RMSE, MAPE, and R obtained by the CS-FNN in this scenario were calculated as 48.7161, 0.067268 and 0.8965, respectively. These results were highly correlated to actual values. It is expected that this work may be useful for hydrographic forecasting.
Jordan, Katy; Weller, Martin
2018-01-01
The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a…
A Branch and Cut algorithm for the container shipping network design problem
DEFF Research Database (Denmark)
Reinhardt, Line Blander; Pisinger, David
2012-01-01
The network design problem in liner shipping is of increasing importance in a strongly competitive market where potential cost reductions can influence market share and profits significantly. In this paper the network design and fleet assignment problems are combined into a mixed integer linear...... programming model minimizing the overall cost. To better reflect the real-life situation we take into account the cost of transhipment, a heterogeneous fleet, route dependant capacities, and butterfly routes. To the best of our knowledge it is the first time an exact solution method to the problem considers...
Flow Formulation-based Model for the Curriculum-based Course Timetabling Problem
DEFF Research Database (Denmark)
Bagger, Niels-Christian Fink; Kristiansen, Simon; Sørensen, Matias
2015-01-01
problem. This decreases the number of integer variables signicantly and improves the performance compared to the basic formulation. It also shows competitiveness with other approaches based on mixed integer programming from the literature and improves the currently best known lower bound on one data...... instance in the benchmark data set from the second international timetabling competition.......In this work we will present a new mixed integer programming formulation for the curriculum-based course timetabling problem. We show that the model contains an underlying network model by dividing the problem into two models and then connecting the two models back into one model using a maximum ow...
Flow-Based Network Management: A Report from the IRTF NMRG Workshop
de Oliveira Schmidt, R.; Sadre, R.; Hendriks, Luuk
This is the report on the Workshop on Flow-Based Network Management, held within the 37th IRTF NMRG meeting, during IETF 93, on 24th July 2015, in Prague, Czech Republic. Following the tradition of the IRTF NMRG, the workshop focused on technologies, developments, and challenges of using flow-level
Modeling of pulsatile flow-dependent nitric oxide regulation in a realistic microvascular network.
Wang, Ruofan; Pan, Qing; Kuebler, Wolfgang M; Li, John K-J; Pries, Axel R; Ning, Gangmin
2017-09-01
Hemodynamic pulsatility has been reported to regulate microcirculatory function. To quantitatively assess the impact of flow pulsatility on the microvasculature, a mathematical model was first developed to simulate the regulation of NO production by pulsatile flow in the microcirculation. Shear stress and pressure pulsatility were selected as regulators of endothelial NO production and NO-dependent vessel dilation as feedback to control microvascular hemodynamics. The model was then applied to a real microvascular network of the rat mesentery consisting of 546 microvessels. As compared to steady flow conditions, pulsatile flow increased the average NO concentration in arterioles from 256.8±93.1nM to 274.8±101.1nM (Pflow as compared to steady flow conditions. Network perfusion and flow heterogeneity were improved under pulsatile flow conditions, and vasodilation within the network was more sensitive to heart rate changes than pulse pressure amplitude. The proposed model simulates the role of flow pulsatility in the regulation of a complex microvascular network in terms of NO concentration and hemodynamics under varied physiological conditions. Copyright © 2017 Elsevier Inc. All rights reserved.
Field effect control of electro-osmotic flow in microfluidic networks
van der Wouden, E.J.
2006-01-01
This thesis describes the development of a Field Effect Flow Control (FEFC) system for the control of Electro Osmotic Flow (EOF) in microfluidic networks. For this several aspects of FEFC have been reviewed and a process to fabricate microfluidic channels with integrated electrodes has been
Nœtinger, B.
2015-02-01
Modeling natural Discrete Fracture Networks (DFN) receives more and more attention in applied geosciences, from oil and gas industry, to geothermal recovery and aquifer management. The fractures may be either natural, or artificial in case of well stimulation. Accounting for the flow inside the fracture network, and accounting for the transfers between the matrix and the fractures, with the same level of accuracy is an important issue for calibrating the well architecture and for setting up optimal resources recovery strategies. Recently, we proposed an original method allowing to model transient pressure diffusion in the fracture network only [1]. The matrix was assumed to be impervious. A systematic approximation scheme was built, allowing to model the initial DFN by a set of N unknowns located at each identified intersection between fractures. The higher N, the higher the accuracy of the model. The main assumption was using a quasi steady state hypothesis, that states that the characteristic diffusion time over one single fracture is negligible compared with the characteristic time of the macroscopic problem, e.g. change of boundary conditions. In that context, the lowest order approximation N = 1 has the form of solving a transient problem in a resistor/capacitor network, a so-called pipe network. Its topology is the same as the network of geometrical intersections between fractures. In this paper, we generalize this approach in order to account for fluxes from matrix to fractures. The quasi steady state hypothesis at the fracture level is still kept. Then, we show that in the case of well separated time scales between matrix and fractures, the preceding model needs only to be slightly modified in order to incorporate these fluxes. The additional knowledge of the so-called matrix to fracture transfer function allows to modify the mass matrix that becomes a time convolution operator. This is reminiscent of existing space averaged transient dual porosity models.
A.R. Ansari; B. Hossain; B. Koren (Barry); G.I. Shishkin (Gregori)
2007-01-01
textabstractWe investigate the model problem of flow of a viscous incompressible fluid past a symmetric curved surface when the flow is parallel to its axis. This problem is known to exhibit boundary layers. Also the problem does not have solutions in closed form, it is modelled by boundary-layer
Wireless Sensor Networks - Node Localization for Various Industry Problems
International Nuclear Information System (INIS)
Derr, Kurt; Manic, Milos
2015-01-01
Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothing (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications
Non-intrusive reduced order modeling of nonlinear problems using neural networks
Hesthaven, J. S.; Ubbiali, S.
2018-06-01
We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.
Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz
2017-01-01
This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.
Totaro, M; Valentini, P; Costa, A L; Giorgi, S; Casini, B; Baggiani, A
2018-01-01
In hospital water systems legionellae may be resistant to disinfectants in pipework, which is a problem particularly in areas where there is low flow or stagnation of water. We evaluated legionella colonization of a water network of an Italian hospital after time flow taps (TFTs) installation in proximity to dead legs. The water volume flushed was 64 L/day from May 2016, and 192 L/day from December 2016. Before TFTs installation, Legionella pneumophila sg2-14 was detected in all points (4 × 10 4 ± 3.1 × 10 4 cfu/L). All sites remained positive (2.9 × 10 4 ± 1.9 × 10 4 cfu/L) through November 2016. From December 2016 legionella persisted in one point only (2 × 10 2 to 6.8 × 10 3 cfu/L). TFTs with chemical disinfection may reduce legionella colonization associated with dead legs. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
Water Pipeline Network Analysis Using Simultaneous Loop Flow ...
African Journals Online (AJOL)
2013-03-01
Mar 1, 2013 ... *Department of Mechanical Engineering, Michael Okpara University of Agriculture, Umudike, Nigeria ... significant fluid acceleration, the behavior of a network can be ... world water day centers on water and food security as.
A local search heuristic for the Multi-Commodity k-splittable Maximum Flow Problem
DEFF Research Database (Denmark)
Gamst, Mette
2014-01-01
, a local search heuristic for solving the problem is proposed. The heuristic is an iterative shortest path procedure on a reduced graph combined with a local search procedure to modify certain path flows and prioritize the different commodities. The heuristic is tested on benchmark instances from...
Energy Technology Data Exchange (ETDEWEB)
1979-01-01
The booklet presents the full text of 13 contributions to a Colloquium held at Karlsruhe in Sept. 1979. The main topics of the papers are the evaluation of mathematical models to solve flow problems in tide water, seas, rivers, groundwater and in the earth atmosphere. See further hints under relevant topics.
Stable Galerkin versus equal-order Galerkin least-squares elements for the stokes flow problem
International Nuclear Information System (INIS)
Franca, L.P.; Frey, S.L.; Sampaio, R.
1989-11-01
Numerical experiments are performed for the stokes flow problem employing a stable Galerkin method and a Galerkin/Least-squares method with equal-order elements. Error estimates for the methods tested herein are reviewed. The numerical results presented attest the good stability properties of all methods examined herein. (A.C.A.S.) [pt
The Cauchy problem for a model of immiscible gas flow with large data
Energy Technology Data Exchange (ETDEWEB)
Sande, Hilde
2008-12-15
The thesis consists of an introduction and two papers; 1. The solution of the Cauchy problem with large data for a model of a mixture of gases. 2. Front tracking for a model of immiscible gas flow with large data. (AG) refs, figs
Application of neural networks to validation of feedwater flow rate in a nuclear power plant
International Nuclear Information System (INIS)
Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.
1993-01-01
Feedwater flow rate measurement in nuclear power plants requires periodic calibration. This is due to the fact that the venturi surface condition of the feedwater flow rate sensor changes because of a chemical reaction between the surface coating material and the feedwater. Fouling of the venturi surface, due to this chemical reaction and the deposits of foreign materials, has been observed shortly after a clean venturi is put in operation. A fouled venturi causes an incorrect measurement of feedwater flow rate, which in turn results in an inaccurate calculation of the generated power. This paper presents two methods for verifying incipient and continuing fouling of the venturi of the feedwater flow rate sensors. Both methods are based on the use of a set of dissimilar process variables dynamically related to the feedwater flow rate variable. The first method uses a neural network to generate estimates of the feedwater flow rate readings. Agreement, within a given tolerance, of the feedwater flow rate instrument reading, and the corresponding neural network output establishes that the feedwater flow rate instrument is operating properly. The second method is similar to the first method except that the neural network predicts the core power which is calculated from measurements on the primary loop, rather than the feedwater flow rates. This core power is referred to the primary core power in this paper. A comparison of the power calculated from the feedwater flow measurements in the secondary loop, with the calculated and neural network predicted primary core power provides information from which it can be determined whether fouling is beginning to occur. The two methods were tested using data from the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant
Sefidgar, Mostafa; Soltani, M; Raahemifar, Kaamran; Bazmara, Hossein
2015-01-01
A solid tumor is investigated as porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multiscale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. The mathematical method involves processes such as blood flow through vessels and solute and fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model predicts.
A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Mostafa Khorramizadeh
2015-01-01
Full Text Available The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.
A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates
Directory of Open Access Journals (Sweden)
Tao Ren
2015-01-01
Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.