Cranking planar mechanisms on a microcomputer

This paper presents a new method for analyzing the motion of planar mechanisms with an arbitrary number of members and degrees of freedom. This method uses the complex vector notation introduced by Raven to derive the kinematic equations for the position, the velocity and the acceleration of the whole mechanism in matrix form. These matrix equations have m× n dimensions for a mechanism with m members and n joints and are solved by the Gauss-Jordan reduction method. The solution determines the velocity and the acceleration of the joints, and the angular velocity and acceleration of the members. These quantities are subsequently used to generate the new position of the mechanism after a time interval Δt. This approach also permits a direct generation of coupler curves. The simplicity of the method allows the use of small scale desktop computers with a CRT or plotter graphics capability for the illustration of the results. This feature makes the method especially attractive for design and educational purposes.     

The preconditioned variational methods for solving large linear systems

The implementation of the Preconditioned Conjugate Gradient method for the solution of large linear systems arising from the discretization of differential operators, requires the predetermination of only one iteration parameter. The numerical determination of the optimal value of this constant parameter, involve the spectral bounds of some matrices and can be obtained in O(N²) sine function evaluations, where 1/N is the discretization mesh size. It is shown that this parameter can be chosen in a stable manner in O(1) operations per iteration, if it is allowed to vary with the iteration index from information derived from the gradient parameters.     

Computational study of double-gate graphene nano-ribbon transistors

The ballistic performance of graphene nanoribbon (GNR) MOSFETs with different width of armchair GNRs is examined using a real-space quantum simulator based on the Non-equilibrium Green’s Function (NEGF) approach, self-consistently coupled to a 3D Poisson’s equation for electrostatics. GNR MOSFETs show promising device performance, in terms of low subthreshold swing and small drain-induced-barrier-lowing due to their excellent electrostatics and gate control (single monolayer). However, the quantum tunneling effects play an import role in the GNR device performance degradation for wider width GNR MOSFETs due to their reduced bandgap. At 2.2 nm width, the OFF current performance is completely dominated by tunneling currents, making the OFF-state of the device difficult to control.     

Distributed Kalman filters with adaptive strategy for linear time‐varying interconnected systems

We consider the problem of distributed state estimation over a sensor network in which a set of nodes collaboratively estimates the state of a continuous‐time linear time‐varying system. In particular, our work focuses on the benefits of weight adaptation of the interconnection gains in distributed Kalman filters. To this end, an adaptation strategy is proposed with the adaptive laws derived via a Lyapunov‐redesign approach. The justification for the gain adaptation stems from a desire to adapt the pairwise difference of state estimates as a function of their agreement, thereby enforcing an interconnection‐dependent gain. In the proposed scheme, an adaptive gain for each pairwise difference of the interconnection terms is used in order to address edge‐dependent differences in the state estimates. Accounting for node‐specific differences, a special case of the scheme is also presented, where it uses a single adaptive gain in each node estimate and which uniformly penalizes all pairwise differences of state estimates in the interconnection term. The filter gains can be designed either by standard Kalman filter or Luenberger observer to construct the adaptive distributed Kalman filter or adaptive distributed Luenberger observer. Stability of the schemes has been shown, and it is not restricted by the graph topology and therefore the schemes are applicable to both directed and undirected graphs. The proposed algorithms offer a significant reduction in communication costs associated with information flow by the nodes. Finally, numerical studies are presented to illustrate the performance and effectiveness of the proposed adaptive distributed Kalman filters. Copyright © 2015 John Wiley & Sons, Ltd.     

Power Factor Enhancement by Inhomogeneous Distribution of Dopants in Two-Phase Nanocrystalline Systems

In this work, we describe a novel idea that allows for high thermoelectric power factors in two-phase materials that are heavily doped with an inhomogeneous distribution of dopants. We show that a concurrent increase of the electrical conductivity and Seebeck coefficient and a consequent increase of the power factor can be achieved in such systems. To explain the concept, we employ a semiclassical one-dimensional model that considers both electron and phonon transport through a series connection of two-phases of the material. We discuss microscopic characteristics of the material and the formation of the two phases (grains and grain boundaries in our case) by the inhomogeneous distribution of dopants in the polycrystalline material. Our theoretical investigation reveals that: (1) the improvement in the Seebeck coefficient can be attributed to carrier filtering due to the energy barriers at the grain boundaries, and to the difference in the lattice thermal conductivity of the grains and grain boundaries, and (2) the improvement in the electrical conductivity is a result of a high Fermi level in the grains. This allows high energy carriers to contribute to transport, which increases the impurity scattering limited mean-free-path, and increases the conductivity in the grains and thus in the whole material. Such an unexpected concurrent increase of the electrical conductivity and the Seebeck coefficient was recently observed in heavily boron-doped polycrystalline silicon of grain sizes <100 nm in which a silicon-boride phase is formed around the grain boundaries. We provide a simple 1D model that explains the behavior of this system, indicating processes that can take place in heavily doped nanocrystalline materials.     

Modeling of graphitization kinetics during peritectic melting of tungsten carbide

A dynamic computational model developed within the context of the classical theory of phase evolution is applied to the W-C system to simulate the kinetics of graphite nucleation during non-equilibrium peritectic melting of WC. The kinetic variables used in the model are obtained directly from the free energy formulations that characterize the stable and metastable equilibria between WC, liquid, and graphite. The isothermal kinetic analysis suggests that transformation time decreases monotonically with increasing superheat such that the minimum transformation time occurs at the metastable congruent melting point of WC (˜3107 K). To crystallize 1 ppm of graphite, the minimum transformation time is computed to be ˜2 ns. The non-isothermal kinetic analysis suggests that under moderate to high heating rates (10⁴-10⁶ K/s) graphitization is completed at superheats of 40-50 K, while under ultra-high heating rates (˜10⁸ K/s) graphitization remains incomplete giving rise to metastable congruent melting of WC.     

Computation of metastable phases in tungsten-carbon system

Metastable phase equilibria in the W-C system are presented in the vicinity of the metastable reactions involving W₂C, WC_1−x , and WC. Metastable phase boundaries were obtained by reproducing the stable boundaries using optimized Gibbs energy formulations and extrapolating them into regions of metastability. Four metastable reactions were obtained: a metastable congruent melting reaction of WC at 3106 K, a metastable eutectic reaction between WC_1−x and graphite at 2995 K, a metastable eutectic reaction between W₂C and WC at 2976 K, and a metastable eutectic reaction between W₂C and graphite at 2925 K. The reaction enthalpies and entropies associated with these transitions are also computed using the available Gibbs energy data. Furthermore, possible kinetic paths that could lead to metastability are discussed.     

Semi-solid induction forging of metallic glass matrix composites

Metallic glasses have high strengths but are inherently brittle. To overcome this shortfall, metallic glass composites can be created by growing soft, crystalline particles in the glass to make it tougher. Processing these composites is difficult by any known method because they oxidize badly in open air and have high viscosity. This article describes a one-step casüng process by which complex components can be made, opening the possibility for commercial and military hardware produced from high-strength toughened glassy composites.