Rapid computation of far-field statistics for random obstacle scattering

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the computation of the expected far-field pattern and the expected scattered wave away from the scatterer as well as the computation of the corresponding variances. To that end, we introduce an artificial interface, which almost surely contains all realizations of the random scatterer. At this interface, we directly approximate the second order statistics, i.e., the expectation and the variance, of the Cauchy data by means of boundary integral equations. From these quantities, we are able to rapidly evaluate statistics of the scattered wave everywhere in the exterior domain, including the expectation and the variance of the far-field. By employing a low-rank approximation of the Cauchy data's two-point correlation function, we drastically reduce the cost of the computation of the scattered wave's variance. Numerical results are provided in order to demonstrate the feasibility of the proposed approach

Tuning the Filter Responses with Graphene Based Resonators

Graphene-metal combined waveguide resonators were proposed earlier, as a solution for obtaining frequency tunable resonator responses at the sub-millimeter-wave frequencies. A methodology for combining these waveguide resonators into the frequency tunable filters has been studied subsequently. Here, we discuss the possibilities and limitations of this type of waveguide resonators, illustrated by several examples of tunable filter designs

Design methodology for graphene tunable filters at the sub–millimeter–wave frequencies

Tunable components and circuits, allowing for the fast switching between the states of operation, are among the basic building blocks for future communications and other emerging applications. Based on the previous thorough study of graphene based resonators, the design methodology for graphene tunable filters has been devised, outlined, as well as explained through an example of the fifth order filter. The desired filtering responses can be achieved with the material loss not higher than the loss corresponding to the previously studied single resonators, depending mostly on the quantity of graphene per resonator. The proposed design method relies on the detailed design space mapping; obtained data gives an immediate assessment of the feasibility of specifications with a particular filter order, maximal passband ripple level, desired bandwidth, and acceptable losses. The design process could be further automated by the knowledge based approach using the collected design space data

Proton therapy Monte Carlo SRNA-VOX code

The most powerful feature of the Monte Carlo method is the possibility of simulating all individual particle interactions in three dimensions and performing numerical experiments with a preset error. These facts were the motivation behind the development of a general-purpose Monte Carlo SRNA program for proton transport simulation in technical systems described by standard geometrical forms (plane, sphere, cone, cylinder, cube). Some of the possible applications of the SRNA program are: (a) a general code for proton transport modeling, (b) design of accelerator-driven systems, (c) simulation of proton scattering and degrading shapes and composition, (d) research on proton detectors; and (e) radiation protection at accelerator installations. This wide range of possible applications of the program demands the development of various versions of SRNA-VOX codes for proton transport modeling in voxelized geometries and has, finally, resulted in the ISTAR package for the calculation of deposited energy distribution in patients on the basis of CT data in radiotherapy. All of the said codes are capable of using 3-D proton sources with an arbitrary energy spectrum in an interval of 100 keV to 250 MeV

Distributed Consensus Control of DFIGs with Storage for Wind Farm Power Output Regulation

Today the state-of-the-art (SoA) wind generators (WGs) are the double-fed induction (DFIGs) with integrated storage devices. In the future, these WGs are expected to be one of the largest producers of renewable energy worldwide. In this paper, we propose a distributed control methodology for solving the problem of coordinating and controlling a group of SoA WGs to attain fast wind farm (WF) power output regulation with each storage device providing the same amount of power, i.e with equal sharing among the storage devices. Our proposed methodology introduces a consensus protocol for coordinating the grid-side converters (GSCs), whose dynamical equations constitute their closed-loop dynamics, and a particular closed-loop form for the interfacing capacitor dynamics. We establish stability of these closed-loop dynamics by leveraging singular perturbation and Lyapunov theories, proving that with these closed-loop dynamics DFIGs accomplish their assigned control objectives. Finally, we analytically construct a distributed and a Control Lyapunov Function (CLF) -based control law for the GSC and the DCDC converter respectively, which jointly lead to the desired closed-loop dynamics. We demonstrate the effectiveness of our methodology through simulations on the IEEE 24-bus reliability test system (RTS)

The Parallel Implementation of the Waveform Relaxation Method for the Simulation of Structure-Preserved Power Systems

Several results pertaining to the partitioning of the waveform relaxation (WR) algorithm for dynamic simulation are presented. The WR algorithm is extended to a structure-preserving power system model in which the loads are retained. This results in a system of differential/algebraic equations (DAEs). Power systems are shown to exhibit several dynamic characteristics which make them suitable for simulation by the WR method. A heuristic method for determining a fault-dependent partitioning of the power system for parallel implementation is given

The Parallel Implementation of the Waveform Relaxation Method for Transient Stability Simulations

In this paper, the authors extend the results of their earlier paper on waveform relamtion (WR), which is a parallel algorithm for transient stability analysis. The WR algorithm is extended to a structure-preserving power system model in which the loads are retained. This results in a system of differential/ algebraic equations (DAEs). Power systems exhibit several unique dynamic properties which may be exploited in an advantageous manner by the WR algorithm. This leads to a greater computational efficiency than most other direct methods of simulation. This paper presents several theoretical results as well as computational results on parallel implementation

The Waveform Relaxation Method for Systems of Differential/Algebraic Equations

An extension of the waveform relaxation (WR) algorithm to systems of differential/algebraic equations (DAE) is presented. Although this type of application has been explored earlier in relation to VLSI circuits, the algorithm has not been generalized to include the vast array of DAE system structures. The solvability and convergence requirements of the WR algorithm for higher-index systems are established. Many systems in robotics and control applications are modeled with DAE systems having an index greater than two. Computer simulation of these systems has been hampered by numerical integration methods which perform poorly and must be explicitly tailored to the system. The WR algorithm presents a means by which these systems may be more efficiently simulated by breaking them into weakly coupled subsystems, many of which will no longer retain the limiting high-index properties

Homeostatic Modulation of Stimulation-Dependent Plasticity in Human Motor Cortex

Since recently, it is possible, using noninvasive cortical stimulation, such as the protocol of paired associative stimulation (PAS), to induce the plastic changes in the motor cortex, in humans that mimic Hebb's model of learning. Application of TMS conjugated with peripheral electrical stimulation at strictly coherent temporal manner lead to convergence of inputs in the sensory-motor cortex, with the consequent synaptic potentiation or weakening, if applied repetitively. However, when optimal interstimulus interval (ISI) for induction of LTP-like effects is applied as a single pair, Motor evoked potential (MEP) amplitude inhibition is observed, the paradigm known as short-latency afferent inhibition (SLAI). Aiming to resolve this paradox, PAS protocols were applied, with 200 repetitions of TMS pulses paired with median nerve electrical stimulation, at ISI equal to individual latencies of evoked response of somatosensory cortex (N-20) (PASLTP), and at ISI of N-20 shortened for 5 msec (PASLTD) protocols that mimic LTP-like changes in the human motor cortex. MEP amplitudes before, during and after interventions were measured as an indicator based on output signals originating from the motor system. Post-intervention MEP amplitudes following the TMS protocols of PASLTP and PASLTD were facilitated and depressed, respectively, contrary to MEP amplitudes during intervention. During PASLTP MEP amplitudes were significantly decreased in case of PASLTP, while in the case of PASLTD an upward trend was observed. In conclusions, a possible explanation for the seemingly paradoxical effect of PAS can be found in the mechanism of homeostatic modulation of plasticity. Those findings indicate the existence of complex relationships in the development of plasticity induced by stimulation, depending on the level of the previous motor cortex excitability