Universality and scaling behavior of injected power in elastic turbulence in wormlike micellar gel

We study the statistical properties of spatially averaged global injected power fluctuations for Taylor-Couette flow of a wormlike micellar gel formed by surfactant cetyltrimethylammonium tosylate. At sufficiently high Weissenberg numbers the shear rate, and hence the injected power p(t), at a constant applied stress shows large irregular fluctuations in time. The nature of the probability distribution function (PDF) of p(t) and the power-law decay of its power spectrum are very similar to that observed in recent studies of elastic turbulence for polymer solutions. Remarkably, these non-Gaussian PDFs can be well described by a universal, large deviation functional form given by the generalized Gumbel distribution observed in the context of spatially averaged global measures in diverse classes of highly correlated systems. We show by in situ rheology and polarized light scattering experiments that in the elastic turbulent regime the flow is spatially smooth but random in time, in agreement with a recent hypothesis for elastic turbulence.

An Adaptive Feature Based Low Power Motion Estimation Algorithm

Motion Estimation is one of the most power hungry operations in video coding. While optimal search (eg. full search)methods give best quality, non optimal methods are often used in order to reduce cost and power. Various algorithms have been used in practice that trade off quality vs. complexity. Global elimination is an algorithm based on pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. We propose an adaptive version of the global elimination algorithm that extracts individual macro-block features using Hadamard transform to optimize the search. Performance achieved is close to the full search method and global elimination. Operational complexity and hence power is reduced by 30% to 45% compared to global elimination method.

Improvement of power-system transient stability by phase-shift insertion

Computational studies of the transient stability of a synchronous machine connected to an infinite busbar by a double-circuit transmission line are used to illustrate the effect of relative phase-shift insertion between the machine and its associated power system. This method of obtaining a change in the effective rotor-excitation angle, and thereby the power transfer, is described, together with an outline of possible methods of implementation by a phase-shifting transformer in a power system.

Transmit power Control with ARQ in energy harvesting sensors: a decision-theoretic approach

This paper addresses the problem of finding optimal power control policies for wireless energy harvesting sensor (EHS) nodes with automatic repeat request (ARQ)-based packet transmissions. The EHS harvests energy from the environment according to a Bernoulli process; and it is required to operate within the constraint of energy neutrality. The EHS obtains partial channel state information (CSI) at the transmitter through the link-layer ARQ protocol, via the ACK/NACK feedback messages, and uses it to adapt the transmission power for the packet (re)transmission attempts. The underlying wireless fading channel is modeled as a finite state Markov chain with known transition probabilities. Thus, the goal of the power management policy is to determine the best power setting for the current packet transmission attempt, so as to maximize a long-run expected reward such as the expected outage probability. The problem is addressed in a decision-theoretic framework by casting it as a partially observable Markov decision process (POMDP). Due to the large size of the state-space, the exact solution to the POMDP is computationally expensive. Hence, two popular approximate solutions are considered, which yield good power management policies for the transmission attempts. Monte Carlo simulation results illustrate the efficacy of the approach and show that the approximate solutions significantly outperform conventional approaches.

Global Response Sensitivity Analysis of Randomly Excited Dynamic Structures

The response of structural dynamical systems excited by multiple random excitations is considered. Two new procedures for evaluating global response sensitivity measures with respect to the excitation components are proposed. The first procedure is valid for stationary response of linear systems under stationary random excitations and is based on the notion of Hellinger's metric of distance between two power spectral density functions. The second procedure is more generally valid and is based on the l2 norm based distance measure between two probability density functions. Specific cases which admit exact solutions are presented, and solution procedures based on Monte Carlo simulations for more general class of problems are outlined. Illustrations include studies on a parametrically excited linear system and a nonlinear random vibration problem involving moving oscillator-beam system that considers excitations attributable to random support motions and guide-way unevenness. (C) 2015 American Society of Civil Engineers.

Los dilemas de la acción colectiva global. Un estudio de caso : el movimiento sindical en el MERCOSUR (1991-2012)

Resumen: Este trabajo analiza la acción colectiva sindical postnacional en el MERCOSUR en un período histórico signado por profundas mutaciones políticas, económicas, y productivas sociales (1991-2012) a partir de los relatos y representaciones de sus protagonistas. El trabajo cualitativo intentará explicar la configuración del sindicalismo internacional en la globalización, y describir las estrategias del movimiento obrero mercosureño. La metodología cualitativa ilustra un trabajo de campo a partir de entrevistas en profundidad a 34 sindicalistas del Mercosur, y entrevistas adicionales a tres representantes de la Confederación Sindical de las Américas, dos empresarios del Mercosur, un especialista académico en la dimensión sociolaboral de la integración regional y un representante de la OIT en la región. La metodología de análisis e interpretación de dichas entrevistas ha sido la teoría fundamentada, entendida como la técnica más idónea de aprehender los procesos sociales a través de las voces de los líderes obreros, comprender su realidad, sus representaciones y sistema de valores, sus ideas y su acción colectiva. La literatura de los movimientos sociales en la globalización capitalista ha puesto el énfasis en la emergencia de nuevos colectivos cuyos reclamos se concentran en el reconocimiento (Fraser y Honneth, 2006) de sus identidades que el modelo fordista de producción pareció invisibilizar y soslayar ante la primacía de las prácticas económicas y demandas distributivas. Esta tesis conjuga una perspectiva dualista y demuestra que las estrategias de reconocimiento y las reivindicaciones de redistribución de tipo clasista se resignificaron en el escenario postnacional a través de la Coordinadora de Centrales Sindicales del Cono Sur –CCSCS- (subregional) y, con un desarrollo menor: los Sindicatos Globales (FSI, GUFs) en la acción sectorial [1991-2012]. Para arribar al núcleo configurativo de sus representaciones y su sistema de valores, la investigación transitó por los sentidos y significados del trabajo, las mutaciones productivas y de las condiciones del trabajo, las teorías del fin del trabajo, la precarización y la representación de los trabajadores más frágiles: mujeres, jóvenes y migrantes. En un segundo orden se interpeló sobre la gobernanza mundial, los organismos internacionales, el régimen normativo internacional, la civilización capitalista, para luego abordar el estudio específico del Mercosur y la acción obrera en dicho proceso. El núcleo determinó que para los representantes obreros la acción colectiva sindical debe ser postnacional y su objetivo es limitar la globalización capitalista neoliberal. La CCSCS conformó desde sus inicios un movimiento capaz de elevarse al rango supranacional para representar la voz de los trabajadores del MERCOSUR. La pluralidad configuró su mayor virtud durante sus primeros 20 años, reconociendo una experiencia de aprendizaje de tolerancia y respeto, que ellos definen como la unidad en la diversidad. Esta entidad constituye un patrimonio único como paradigma del sindicalismo postnacional. Los sindicatos del Cono Sur adoptaron diversas modalidades de acción colectiva: a) reactiva (con repertorios de insubordinación, de lucha y resistencia al modelo neoliberal), b) proactiva (con repertorios de incidencia normativa en el MERCOSUR) y c) participativa (con repertorios de producción propositiva de incidencia en la dimensión social del MERCOSUR). Su acción colectiva reactiva, normativa y propositiva fue eficaz a mediano plazo para participar e incidir en el MERCOSUR, crear una dimensión social del bloque y dotar de derechos normativos a los ciudadanos de la región. Su acción tuvo un sentido político de gran poder instituyente, con capacidad movilización y alta exposición pública. Sin embargo, en la segunda década su lógica de construcción quedó subordinada a los procesos nacionales y a los partidos gobernantes, dejó de ser performativa y de creación política, dirimiéndose en la esfera social junto a otros movimientos sociales emergentes, y provocó un ciclo de desmovilización. Simultáneamente, emergió con fuerza otra modalidad de sindicalismo postnacional con la fusión y refundación de los Sindicatos Globales. Su acción sectorial contribuye a restaurar las demandas de distribución que habían quedado soslayadas, pero esta tesis manifiesta que los protagonistas afirman que sus marcos de acción colectiva deberán ser conjuntos para ser exitosa. El sindicalismo postnacional en el MERCOSUR se define a sí mismos como agente de desarrollo, protagonista del modelo socioproductivo, pero también como vehículo partícipe de la democracia y de una matriz sustentable de desarrollo

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Dinámica de las Redes Virtuales de Fabricación Global en la Industria Aeronáutica

[ES] Las redes virtuales de fabricación global (RVFGs) están formadas por empresas independientes las cuales establecen entre sí relaciones de tipo horizontal y vertical, pudiendo incluso ser competidores, donde no es necesario mantener internamente grandes recursos fabriles sino gestionar y compartir eficientemente los recursos de la red.

The global human security index: Can disaggregations help us to forge progress?

A Human Security Index (HIS) enumerating 200 countries was introduced in 2008. A community-level HSI is under development in the USA. Coastal communities face large disparities in components of human security. How can a HSI support improved policies/services (such as environmental or public health forecasts or warnings) for improving lives? Several issues are discussed. (PDF contains 4 pages)

Investigating changes in global tropical cyclone storm frequency and intensity

Understanding fluctuations in tropical cyclone activity along United States shores and abroad becomes increasingly important as coastal managers and planners seek to save lives, mitigate damage, and plan for resilience in the face of changing storminess and sea-level rise. Tropical cyclone activity has long been of concern to coastal areas as they bring strong winds, heavy rains, and high seas. Given projections of a warming climate, current estimates suggest that not only will tropical cyclones increase in frequency, but also in intensity (maximum sustained winds and minimum central pressures). An understanding of what has happened historically is an important step in identifying potential future changes in tropical cyclone frequency and intensity. The ability to detect such changes depends on a consistent and reliable global tropical cyclone dataset. Until recently no central repository for historical tropical cyclone data existed. To fill this need, the International Best Track Archive for Climate Stewardship (IBTrACS) dataset was developed to collect all known global historical tropical cyclone data into a single source for dissemination. With this dataset, a global examination of changes in tropical cyclone frequency and intensity can be performed. Caveats apply to any historical tropical cyclone analysis however, as the data contributed to the IBTrACS archive from various tropical cyclone warning centers is still replete with biases that may stem from operational changes, inhomogeneous monitoring programs, and time discontinuities. A detailed discussion of the difficulties in detecting trends using tropical cyclone data can be found in Landsea et al. 2006. The following sections use the IBTrACS dataset to show the global spatial variability of tropical cyclone frequency and intensity. Analyses will show where the strongest storms typically occur, the regions with the highest number of tropical cyclones per decade, and the locations of highest average maximum wind speeds. (PDF contains 3 pages)

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Feira de São Cristóvão: uma incursão sobre os estudos na área e a tentativa de aproximação à relação global-local

O presente trabalho se propõe fazer uma aproximação aos estudos sobre a tradicionalmente chamada Feira de São Cristóvão, levando em consideração a relação entre os agentes partícipes e a dinâmica no espaço. O objetivo é compreender melhor a força que move os atores no sentido da mudança da forma da feira para a forma do Centro Luiz Gonzaga de Tradições Nordestinas (CLGTN), e assim me aproximar da seguinte questão: Por que uma forma de comércio como a modelada na Feira de São Cristóvão, popularmente conhecida como feira dos paraíbas, sobrevive à força das mudanças operadas no ramo, dando lugar aos sofistificados shopping-centers? Para isso, faço uma aproximação ao estado de arte da pesquisa na área com base nas seguintes categorias de análise: a Feira como forma de produção do espaço e a relação Forma-Conteúdo, a relação espaço-identidade na feira e a relação entre agentes internos e externos no Espaço. Vendo a migração como movimento responsável pela constituição de um espaço social e territorialmente diferenciado do nordestino na cidade do Rio de Janeiro, é por ela que inicio a exposição. Esta se continua com a análise dos trabalhos escolhidos para estudo, via as categorias indicadas e, com um capítulo no qual procuro repensar a feira a partir da relação global-local que vem referenciando as reflexões acumuladas na área do urbano a partir da segunda metade do século XX. Por fim, concluo observando que a permanência da feira se deve a um duplo movimento de resistência-absorção que, se redefinindo no tempo e no espaço, não consegue, entretanto, apagar os traços da tradição que lhe deu origem.

Distributed Control and Optimization for Communication and Power Systems

We are at the cusp of a historic transformation of both communication system and electricity system. This creates challenges as well as opportunities for the study of networked systems. Problems of these systems typically involve a huge number of end points that require intelligent coordination in a distributed manner. In this thesis, we develop models, theories, and scalable distributed optimization and control algorithms to overcome these challenges.

This thesis focuses on two specific areas: multi-path TCP (Transmission Control Protocol) and electricity distribution system operation and control. Multi-path TCP (MP-TCP) is a TCP extension that allows a single data stream to be split across multiple paths. MP-TCP has the potential to greatly improve reliability as well as efficiency of communication devices. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate a new algorithm Balia (balanced linked adaptation) which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new proposed algorithm Balia with existing MP-TCP algorithms.

Our second focus is on designing computationally efficient algorithms for electricity distribution system operation and control. First, we develop efficient algorithms for feeder reconfiguration in distribution networks. The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. We propose a heuristic algorithm that is based on the recently developed convex relaxation of the optimal power flow problem. The algorithm is efficient and can successfully computes an optimal configuration on all networks that we have tested. Moreover we prove that the algorithm solves the feeder reconfiguration problem optimally under certain conditions. We also propose a more efficient algorithm and it incurs a loss in optimality of less than 3% on the test networks.

Second, we develop efficient distributed algorithms that solve the optimal power flow (OPF) problem on distribution networks. The OPF problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally OPF is solved in a centralized manner. With increasing penetration of volatile renewable energy resources in distribution systems, we need faster and distributed solutions for real-time feedback control. This is difficult because power flow equations are nonlinear and kirchhoff's law is global. We propose solutions for both balanced and unbalanced radial distribution networks. They exploit recent results that suggest solving for a globally optimal solution of OPF over a radial network through a second-order cone program (SOCP) or semi-definite program (SDP) relaxation. Our distributed algorithms are based on the alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative methods, the proposed solutions exploit the problem structure that greatly reduce the computation time. Specifically, for balanced networks, our decomposition allows us to derive closed form solutions for these subproblems and it speeds up the convergence by 1000x times in simulations. For unbalanced networks, the subproblems reduce to either closed form solutions or eigenvalue problems whose size remains constant as the network scales up and computation time is reduced by 100x compared with iterative methods.