Polyester composite water uptake and organic contaminant release affected by carbon nanofiber reinforcements

The incorporation of carbon nanofiber (CNF) into glass fiber (GF) composites is a potential route to extend polymer composite service‐life and enhance mechanical properties. Under nonstatic conditions, only limited information concerning water uptake and contaminant release properties of nanocomposite materials is currently available. Polyester composites containing GF and oxidized CNF were immersed in water for 30 days under nominal pressure at 23 °C, below the polymer's glass‐transition temperature. Water was analyzed and changed every three days to simulate water chemistry regeneration similar to exposures in flowing systems. Composites with oxidized CNF had greater water sorption capacity and leaching rates than CNF‐free composites. The total mass of organic contaminant released correlated with the amount of water sorbed by each composite (r² = 0.91), although CNF dispersion was found to vary greatly within composites. The greatest and least contaminant release rates were found for the polyester‐CNF and the polyester‐GF composites, respectively. While volatile aromatic resin solvents and stabilizer compounds were detected, their concentrations declined over the 30 day exposure period. We hypothesize that the hydrophilic nature of the oxidized CNF increased the water sorption capacity of the polyester composites. Additional studies are warranted that examine the impact of this phenomenon on composite mechanical and long‐term durability properties. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43724.     

Unconstrained and constrained motion control of a planar two-link structurally flexible robotic manipulator

Unconstrained and constrained motion control of a planar two-link structurally-flexible robotic manipulator are considered in this study. The dynamic model is obtained by using the extended Hamilton's principle and the Galerkin criterion. A method is presented to obtain the linearized equations of motion in Cartesian space for use in designing the control system. The approach to solving the control problem is to use feedforward and feedback control torques. The feedforward torques maneuver the flexible manipulator along a nominal trajectory and the feedback torques minimize any deviations from the nominal trajectory. The feedforward and feedback torques are obtained by solving the inverse dynamics problem for the rigid manipulator and designing linear quadratic Gaussian with loop transfer recovery (LQG/LTR) compensators, respectively. The LQG/LTR design methodology is exploited to design a robust feedback control system that can handle modeling errors and sensor noise, and operate on Cartesian space trajectory errors. Computer simulated results are presented for an example planar, two-link, structurally flexible robotic manipulator. © 1994 John Wiley & Sons, Inc.     

Decentralized control and disturbance attenuation for large-scale nonlinear systems in generalized output-feedback canonical form

A global decentralized robust adaptive output-feedback dynamic compensator is proposed for stabilization, tracking, and disturbance attenuation of the decentralized generalized output-feedback canonical form. This represents the largest class for which decentralized robust adaptive output-feedback tracking and disturbance attenuation results are currently available. The system is allowed to contain unknown parameters multiplying output-dependent nonlinearities, and, also, unknown nonlinearities satisfying certain bounds. Under the assumption that a constant matrix can be found for each subsystem to achieve a certain property, it is shown that reduced-order observers and backstepping controllers can be designed to achieve practical stabilization of the tracking error in each subsystem in the presence of bounded disturbance inputs. Sufficient conditions under which asymptotic tracking and stabilization can be achieved are also obtained. Signal gains from disturbance inputs to tracking errors are presented in the input-to-output-practical-stability and integral-input-to-output-practical-stability frameworks. A particular case in which the standard -gain disturbance attenuation is achieved is also provided.     

Formal Verification Successes at Motorola

Formal tools are either too labor intensive or are completely impractical for industrial-size problems. This paper describes two formal verification tools used within Motorola, Versys2 and CBV, that challenge this assertion. The two tools are being used in current design verification flows and have shown that it is possible to seamlessly integrate formal tools into existing design flows.     

A Socratic method for validation of measurement-based networking research

Nearly three decades of Internet measurement has resulted in large-scale global infrastructures used by an increasing number of researchers. They have examined various Internet properties in areas such as network infrastructure (routers, links), traffic (measurement at packet, flow, and session level) and applications (DNS, Web, P2P, Online Social Networks, etc.) and presented results in diverse venues. Key related topics like security and privacy have also been explored. There is however a lack of clearly articulated standards that reduce the probability of common mistakes made in studies involving measurements, their analysis and modeling. A community-wide effort is likely to foster fidelity in datasets obtained from measurements and reused in subsequent studies. We present a Socratic approach as steps towards a solution to this problem by enumerating a sequence of questions that can be answered relatively quickly by both measurers and reusers of datasets. To illustrate the applicability and appropriateness of the questions we answer them for a number of past and current measurement studies.     

Deep packet inspection using parallel bloom filters

There is a class of packet processing applications that inspect packets deeper than the protocol headers to analyze content. For instance, network security applications must drop packets containing certain malicious Internet worms or computer viruses carried in a packet payload. Content forwarding applications look at the hypertext transport protocol headers and distribute the requests among the servers for load balancing. Packet inspection applications, when deployed at router ports, must operate at wire speeds. With networking speeds doubling every year, it is becoming increasingly difficult for software-based packet monitors to keep up with the line rates. We describe a hardware-based technique using Bloom filters, which can detect strings in streaming data without degrading network throughput. A Bloom filter is a data structure that stores a set of signatures compactly by computing multiple hash functions on each member of the set. This technique queries a database of strings to check for the membership of a particular string. The answer to this query can be false positive but never a false negative. An important property of this data structure is that the computation time involved in performing the query is independent of the number of strings in the database provided the memory used by the data structure scales linearly with the number of strings stored in it. Furthermore, the amount of storage required by the Bloom filter for each string is independent of its length.     

Graphical models for optimal power flow

Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithm for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. Numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.     

Robust continuous-time smoothers without two-sided stochastic integrals

We consider the problem of fixed-interval smoothing of a continuous-time partially observed nonlinear stochastic dynamical system. Existing results for such smoothers require the use of two-sided stochastic calculus. The main contribution of the paper is to present a robust formulation of the smoothing equations. Under this robust formulation, the smoothing equations are nonstochastic parabolic partial differential equations (with random coefficients) and, hence, the technical machinery associated with two sided stochastic calculus is not required. Furthermore, the robust smoothed state estimates are locally Lipschitz in the observations, which is useful for numerical simulation. As examples, finite dimensional robust versions of the Benes and hidden Markov model smoothers and smoothers for piecewise linear dynamics are derived; these finite-dimensional smoothers do not involve stochastic integrals.     

Global output feedback tracking for nonlinear systems in generalized output-feedback canonical form

A global output feedback dynamic compensator is proposed for stabilization and tracking of a class of systems that are globally diffeomorphic into systems which are in generalized output-feedback canonical form. This form includes as special cases the standard output-feedback canonical form and various other forms considered previously in the literature. Output-dependent nonlinearities are allowed to enter both additively and multiplicatively. Under the assumption that a constant matrix can be found to achieve a certain property, it is shown that a reduced-order observer and a backstepping controller can be designed to achieve asymptotic tracking. For the special case of linear systems, the designed dynamic controller reduces to the standard reduced-order observer and linear controller. This is the first global output-feedback tracking results for this class of systems.     

Opportunistic scheduling for streaming multimedia users in high-speed downlink packet access (HSDPA)

High-speed downlink packet access (HSDPA) achieves high data rates and high spectral efficiency by using adaptive modulation and coding schemes and employing multicode CDMA. In this paper, we present opportunistic algorithms for scheduling HSDPA users and selecting modulation/coding and multicode schemes that exploit channel and buffer variations to increase the probability of uninterrupted media play-out. First, we introduce a stochastic discrete event model for a HSDPA system. By employing the discrete event model, we transform the scheduling problem of providing uninterrupted play-out to a feasibility problem that considers two sets of stochastic quality-of-service (QoS) constraints: stability constraints and robustness constraints. A methodology for obtaining a feasible solution is then proposed by starting with a so-called stable algorithm that satisfies the stability QoS constraints. Next, we present stochastic approximation algorithms that adapt the parameters of the stable algorithm in a way that a feasible point for the robustness QoS is reached within the feasibility region of the stability QoS.