Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels

In this paper we propose and analyze a distributed algorithm for achieving globally optimal decisions, either estimation or detection, through a self-synchronization mechanism among linearly coupled integrators initialized with local measurements. We model the interaction among the nodes as a directed graph with weights (possibly) dependent on the radio channels and we pose special attention to the effect of the propagation delay occurring in the exchange of data among sensors, as a function of the network geometry. We derive necessary and sufficient conditions for the proposed system to reach a consensus on globally optimal decision statistics. One of the major results proved in this work is that a consensus is reached with exponential convergence speed for any bounded delay condition if and only if the directed graph is quasi-strongly connected. We provide a closed form expression for the global consensus, showing that the effect of delays is, in general, the introduction of a bias in the final decision. Finally, we exploit our closed form expression to devise a double-step consensus mechanism able to provide an unbiased estimate with minimum extra complexity, without the need to know or estimate the channel parameters.Comment: To be published on IEEE Transactions on Signal Processin

A review of in-situ loading conditions for mathematical modelling of asymmetric wind turbine blades

This paper reviews generalized solutions to the classical beam moment equation for solving the deflexion and strain fields of composite wind turbine blades. A generalized moment functional is presented to effectively model the moment at any point on a blade/beam utilizing in-situ load cases. Models assume that the components are constructed from inplane quasi-isotropic composite materials of an overall elastic modulus of 42 GPa. Exact solutions for the displacement and strains for an adjusted aerofoil to that presented in the literature and compared with another defined by the Joukowski transform. Models without stiffening ribs resulted in deflexions of the blades which exceeded the generally acceptable design code criteria. Each of the models developed were rigorously validated via numerical (Runge-Kutta) solutions of an identical differential equation used to derive the analytical models presented. The results obtained from the robust design codes, written in the open source Computer Aided Software (CAS) Maxima, are shown to be congruent with simulations using the ANSYS commercial finite element (FE) codes as well as experimental data. One major implication of the theoretical treatment is that these solutions can now be used in design codes to maximize the strength of analogues components, used in aerospace and most notably renewable energy sectors, while significantly reducing their weight and hence cost. The most realistic in-situ loading conditions for a dynamic blade and stationary blade are presented which are shown to be unique to the blade optimal tip speed ratio, blade dimensions and wind speed

Design of conditions for emergence of self-replicators

A self-replicator is usually understood to be an object of definite form that promotes the conversion of materials in its environment into a nearly identical copy of itself. The challenge of engineering novel, micro- or nano-scale self-replicators has attracted keen interest in recent years, both because exponential amplification is an attractive method for generating high yields of specific products, and also because self-reproducing entities have the potential to be optimized or adapted through rounds of iterative selection. Substantial steps forward have been achieved both in the engineering of particular self-replicating molecules, and also in characterizing the physical basis for possible mechanisms of self-replication. At present, however, there is need for a theoretical treatment of what physical conditions are most conducive to the emergence of novel self-replicating structures from a reservoir of building blocks on a desired time-scale. Here we report progress in addressing this need. By analyzing the dynamics of a generic class of heterogeneous particle mixtures whose reaction rates emerge from basic physical interactions, we demonstrate that the spontaneous discovery of self-replication is controlled by relatively generic features of the chemical space, namely: the dispersion in the distribution of reaction timescales and bound-state energies. Based on this analysis, we provide quantitative criteria that may aid experimentalists in designing a system capable of producing self-replicators, and in estimating the likely timescale for exponential growth to start.Comment: Supplementary Information is under the Ancillary Files ---