Time-varying Direction Research Articles

Biomechanics of Insect Flight Stability and Perturbation Response.

Insects must fly in highly variable natural environments filled with gusts, vortices, and other transient aerodynamic phenomena that challenge flight stability. Furthermore, the aerodynamic forces that support insect flight are produced from rapidly oscillating wings of time-varying orientation and configuration. The instantaneous flight forces produced by these wings are large relative to the average forces supporting body weight. The magnitude of these forces and their time-varying direction add another challenge to flight stability, because even proportionally small asymmetries in timing or magnitude between the left and right wings may be sufficient to produce large changes in body orientation. However, these same large-magnitude oscillating forces also offer an opportunity for unexpected flight stability through nonlinear interactions between body orientation, body oscillation in response to time-varying inertial and aerodynamic forces, and the oscillating wings themselves. Understanding the emergent stability properties of flying insects is a crucial step toward understanding the requirements for evolution of flapping flight and decoding the role of sensory feedback in flight control. Here, we provide a brief review of insect flight stability, with some emphasis on stability effects brought about by oscillating wings, and present some preliminary experimental data probing some aspects of flight stability in free-flying insects.

Chirality reversal with the carrier-envelope phase: A next generation QTAIM interpretation

Simulated circularly-polarized 10 fs laser pulses that induce a mixture of excited states are applied to ethane. Additionally, the carrier-envelope phase (CEP) angle ϕ, that quantifies the relationship between the time-varying direction of electric (E)-field and the amplitude envelope was used to manipulate the mechanical and chiral properties of ethane using Next Generation Quantum Theory of Atoms in Molecules (NG-QTAIM). The chirality assignments were reversed from S to R as the CEP angle ϕ was increased from ϕ = 0.0° to ϕ = 180°. A one-to-one mapping between the CEP angle ϕ and NG-QTAIM trajectories was discovered.

Convergence to Zero of Quadratic Lyapunov Functions for Multiagent Systems in Time-Varying Directed Networks

Convergence to Zero of Quadratic Lyapunov Functions for Multiagent Systems in Time-Varying Directed Networks

Finite-Thrust Lambert Transfer Based on Multistage Constant-Vector Thrust Control

In this work, an efficient multi-stage constant-vector thrust control algorithm is proposed for spacecraft to achieve finite-thrust Lambert transfer considering <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">J</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> perturbation. In contrast to most designs that apply continuous-thrust requiring time-varying direction and the magnitude of the thrust, the proposed control scheme utilizes a multi-stage constant-vector thrust which means the modulus and direction of the thrust are constant in each stage determined by a given set of time nodes dividing the whole transfer time, which reduces the control complexity of the engine. Based on the multi-stage sensitivity matrix, which describes the first-order relationship between the thrust and the change of the orbital elements, a rapid algorithm is presented to obtain the multi-stage constant-vector thrust solution with the required accuracy. Furthermore, the optimization problem of the multi-stage constant-vector thrust solution is established, and the direct optimization method is proposed to obtain an optimal multi-stage constant-vector thrust solution for a given set of time nodes. Based on this approach, the node-sequence optimization method is further proposed to obtain a series of feasible optimized solutions rapidly corresponding to a monotonically increasing time-node sets. Compared with the existing finite-thrust methods, the presented methods balance the fuel consumption and control requirements of the engine because the situation that the engine always needs to change the direction and the magnitude of the thrust could be avoided, which are practical options for engineering applications.

Analyzing, modelling, and simulating nonstationary thunderstorm winds in two horizontal orthogonal directions at a point in space

Thunderstorm winds in the horizontal plane are time-varying, resulting in the time-varying alongwind direction and mean wind speed in the alongwind direction. The fluctuating winds in the alongwind and crosswind directions are time-varying as well. The characterization of the mean and fluctuating winds for their simulation in two horizontal orthogonal directions are incomplete or unavailable in the literature. In the present study, we analyze and model the thunderstorm winds with respect to their time- and directional-variation of the alongwind speed and direction, as well as the fluctuating wind components in the alongwind and crosswind directions. For the analysis, we use the continuous harmonic wavelet. We show that the power spectral density (PSD) functions of the fluctuating winds depend on the time-varying mean wind speed. Based on the time-frequency spectral analysis, we propose the PSD functions and lagged coherence functions for the fluctuating thunderstorm winds in the alongwind and crosswind directions. We also present new empirical models for the time-varying alongwind direction and mean wind speed in the alongwind direction. Finally, we suggest the steps to simulate the wind speed in the alongwind and crosswind directions with time-varying directions and provide numerical examples to illustrate the effectiveness of our proposed models.

THz Systems Exploiting Photonics and Communications Technologies

Terahertz (THz) systems open up the possibility of new applications of electromagnetic waves. Enormous bandwidths up to several terahertz enable the development of powerful spectroscopy systems that can provide insights into the structure and material of objects with micrometer resolution. New high power and compact THz time-domain spectroscopy (TDS) systems will be presented. The wide bandwidth also enables high-resolution imaging under far-field conditions to analyze arbitrary objects from a distance. In addition, a near-field system-on-a-chip imaging system is presented that achieves a resolution of 10 μm. Additionally, the application of terahertz waves presents challenges due to the low transmit power of the sources, high attenuation in free space, and the high noise figures of the receivers. These challenges can be overcome by antennas with high gain. Since - depending on the application - spatial scanning or focusing in a time-varying direction is required, beam steering is an essential component of many THz systems. In terms of communications, terahertz carrier frequencies offer wide bandwidths, enabling correspondingly high data rates of 100 Gbit/s and more. As a result, the frequency bands between 250 GHz and 450 GHz have already been identified and/or allocated for communication services and are being discussed as a component of 6G mobile communications. Concepts and demonstrations for 6G terahertz mobile communications will be presented. The high bandwidth of terahertz waves can also be used for high-accuracy indoor localization.

Multibeam Joint Communication and Radar Sensing: Beamforming Design and Interference Cancellation

Multi-beam joint communication and radar (JCR) activates communication beam and sensing beam simultaneously to satisfy both communication and sensing requirements, where the sensing beam is supposed to scan a wide sensing field of view for target detection. However, the sensing beam with time-varying directions may cause severe interference on communication, especially in non-line-of-sight (NLoS) scenario. To address this problem, we propose a multi-beam JCR interference reduction methodology. Firstly, the communication receiver (CRx) utilizes the radar spreading sequences to estimate and eliminate the interference. Then, the transmitter adjusts the beamforming design according to CRx estimation to obtain higher communication beamforming gain. Our proposed methodology could improve the signal-to-interference ratio (SIR) at CRx without the sacrifice of radar detection ability. Simulation results are provided to demonstrate the superiority of the proposed scheme compared to its existing multi-beam JCR counterpart.

Variational Bayesian inference for beamforming

A variational Bayesian method for beamforming is presented. The proposed method aims at estimating the time-varying directions of arrivals (DOAs) of source signals. Sequential estimation is performed based on a random process representation of the unknown DOAs. Since calculating the posterior probability density functions (pdfs) of the individual DOA variables is intractable, we utilize variational Bayesian inference to analytically approximate these posterior pdfs. A von Mises representation enables closed-form integration over approximate DOA pdfs. The proposed algorithm iteratively estimates DOAs, source amplitudes, number of sources, and model parameters. Furthermore, it is grid-less, promotes sparse solutions, and provides an uncertainty characterization for estimated DOAs. For an improved time-varying DOA tracking performance, inference results from previous time steps can be used as prior information for sequential processing. We evaluate the proposed method using simulated data and acoustic data from an underwater source localization experiment.

Resonance modulation vibration mechanism of equally-spaced planetary gearbox with a localized fault on sun gear

The vibration signal of the planetary gearbox shows complicated modulation sidebands no matter the gear is normal or fault. It leads to a challenge in the fault diagnosis, especially for the localized faults which stimulate resonance modulation phenomena. To reveal the resonance modulation mechanism of sun gear’s localized fault, the vibration signal model is built based on the convolution of transient impact force and transfer function of the planetary gearbox. Three prominent transfer paths including modal parameters of the flexible ring gear or housing are involved to obtain resonance modulation sidebands. A projection function is used to model the time-varying direction of transient impact force. Resonance modulation sidebands of a single planet gear meshing is first deduced, and then the sidebands related to multiply planet gears meshing. The resonance modulation of localized fault on sun gear are concluded to be consist of three groups of sidebands. The proposed model is verified by the good consistency between simulation and experimental testing on a commodity planetary gearbox. It contributes an important and effective frequency indicator to confirm the condition of planetary gearboxes.

A new measurement association mapping strategy for DOA tracking

To solve the problem of the time-varying direction of arrival (DOA) in uniform linear array (ULA), a novel DOA tracking method based on generalized label multi-Bernoulli (GLMB) filter is proposed. Since the measurement value is a superimposed data, which will lead to the mismatch of measurement association mapping (MAP) in the GLMB filter updated step. To solve this issue, we propose a new measurement association mapping (NMAP) strategy, which redefines the MAP between the target and the measurement. Furthermore, particle filter is given to approximate the posterior distribution of the GLMB filter, and the likelihood function is replaced by the multi-signal classification (MUSIC) spatial spectrum function. Finally, by exponential weighting of the likelihood function, the number of particles in the high likelihood region increases, making the pruning and merging of the GLMB filter more effective. Compared with the existing methods, the proposed method is superior to other algorithms in tracking the source's state and estimating the number of sources.

State-space modeling of sound source directivity: An experimental study of the violin and the clarinet

A method is presented for simulating the free-field, frequency-dependent directivity of linear sound sources for use in real-time within geometric acoustic environments. The method, which is applied to modeling the directivity of a violin body and a clarinet air column from experimental acoustic data in this study, is based on using minimum-phase measurements to design a state-space filter, allowing the interactive simulation of a time-varying number of radiated sound wavefronts, each toward a time-varying direction. With applicability in sound synthesis and/or auralization within virtual environments, where sound sources change position and orientation dynamically, techniques are proposed for modeling and simulating directivity profiles on perceptual frequency axes with alternatives for representing directivity on a per-vibration-mode basis while incorporating relative phase terms or by reduced-order efficient representations comprising separate components for the signature resonant structure and the associated directivity on an adjustable frequency resolution.

State-space simulation of sound source directivity for interactive geometric acoustics

A method is proposed for simulating the frequency-dependent directivity of sound sources for use in interactive geometric acoustic rendering applications. The method is based on using measurements to design a state-space filter allowing the interactive simulation of a time-varying number of radiated sound wavefronts, each towards a time-varying direction. With applicability in sound synthesis or auralization within virtual environments where sound sources dynamically change position and orientation, techniques are proposed for modeling and simulating directivity profiles on perceptually motivated warped frequency axes, along with alternatives for representing directivity on a per-vibration-mode basis or by reduced-order efficient representations. We demonstrate the method by using experimental acoustic data to simulate the directivity of a violin body and a clarinet air column.

Distributed Optimal Economic Environmental Dispatch for Microgrids Over Time-Varying Directed Communication Graph

This paper investigates the combined economic environmental dispatch problem of Microgrids in a distributed manner. In order to optimize the competing agminated operation cost and environmental impact objectives simultaneously, a distributed method which combines the distributed consensus based algorithm with dynamic weights is proposed to assign the energy among generation units, energy storage units, and load units. By this method, each unit only needs to share its local information among neighbours, thus it offers better flexibility, robustness and privacy. Besides, different from existing distributed optimization algorithms, the proposed algorithm can solve the multi-objective problem over time-varying directed communication graph with a fixed step-size. Furthermore, it is proved that the proposed algorithm can converge to the optimal solution if the step-size does not exceed some upper bound. The simulation results show that the proposed method can simultaneously coordinate the two conflicting goals of the economic and environmental aspects of Microgrids, and obtain the entire Pareto front, effectively reducing operating costs and pollutant emissions. The advantage of convergence speed is also shown compared with some distributed algorithms.

Sequential sparse Bayesian learning for time-varying direction of arrival.

This paper presents methods for the estimation of the time-varying directions of arrival (DOAs) of signals emitted by moving sources. Following the sparse Bayesian learning (SBL) framework, prior information of unknown source amplitudes is modeled as a multi-variate Gaussian distribution with zero-mean and time-varying variance parameters. For sequential estimation of the unknown variance, we present two sequential SBL-based methods that propagate statistical information across time to improve DOA estimation performance. The first method heuristically calculates the parameters of an inverse-gamma hyperprior based on the source signal estimate from the previous time step. In addition, a second sequential SBL method is proposed, which performs a prediction step to calculate the prior distribution of the current variance parameter from the variance parameter estimated at the previous time step. The SBL-based sequential processing provides high-resolution DOA tracking capabilities. Performance improvements are demonstrated by using simulated data as well as real data from the SWellEx-96 experiment.

Multitemporal analysis of ambient noise polarization to characterize site response in the town of Amatrice, shattered by the 2016 central Italy earthquake

SUMMARYThe Mw 6.0 earthquake that hit central Italy on 2016 August 24 caused an abnormally high level of destruction in the town of Amatrice. In order to clarify the role of site response in causing such a disaster, a series of ambient noise recordings acquired in the aftermath of the event are analysed here to identify site resonance properties from the ratios H/V between horizontal and vertical amplitudes of ground motion. Although the noise data acquisition was limited by the emergency management activities, the use of a new analysis technique, which isolates the contribution of Rayleigh waves to the noise wavefield and averages instantaneous estimates of H/V ratios, provided more stable results compared to the standard Nakamura's technique based on mean spectral ratios. The results demonstrated the occurrence of significant resonance phenomena, but without an obvious correlation with the spatial distribution of damage severity. It is apparent that the damage severity was also influenced by some additional local factors related to building vulnerability. Moreover, the time-series analysis revealed seasonal variations in the Rayleigh wave ellipticity curves likely related to the water content changes in the surface deposits and their influence on the Poisson coefficient. Finally, the new method proved capable of recognizing time-varying directions of Rayleigh wave propagation. This capability could be exploited to support other passive seismic methods (e.g. ReMi), whose results’ reliability is limited by the lack of control on wave direction origin.

A Privacy Preserving Distributed Optimization Algorithm for Economic Dispatch Over Time-Varying Directed Networks

The economic dispatch problem (EDP) plays a fundamental and significant role in smart grids. Its purpose is to decide the output power of every generator in smart grids for achieving the minimal generation cost. With advantages in flexibility, robustness, and scalability, it is desirable to apply distributed optimization methods to solve EDPs. In most existing distributed optimization approaches, all generators explicitly exchange their states with neighbors to obtain the optimal solution, which may result in disclosing the privacy information of generators. This problem becomes worse if there are some adversaries aimed at inferring privacy information from the communication network for nefarious purposes. For privacy preservation, a privacy preserving distributed optimization algorithm over time-varying directed communication networks is proposed in this article by adding conditional noises to the exchanged states. It is proved that this proposed algorithm is able to solve the EDP. Moreover, the convergence rate and privacy analysis of the proposed algorithm are also shown in this article. An example is provided to confirm the effectiveness of this proposed algorithm.

Doppler distortion elimination using short-time sparse singular value decomposition strategy for wayside acoustic source fault diagnosis

With the rapid development of transportation, wayside condition monitoring and fault diagnosis of key acoustic sources has attracted considerable attentions because of low cost and high efficiency. However, serious Doppler distortion exists in the wayside acquired signals when the monitored moving source passes by the system at high velocity, which makes it difficult for condition monitoring and fault diagnosis. This paper presents a novel method involving short-time sparse singular value decomposition to eliminate Doppler distortion in the wayside acquired signals based on a microphone array. The procedure of the proposed short-time sparse singular value decomposition is performed as follows. First, the Doppler distorted array signals are decomposed into a series of array segments by a sliding window with a proper window length. Afterwards, the time-varying direction of arrival of the corresponding array segments is acquired by individual sparse singular value decomposition. Then the fitting time-varying directions of arrival and time-domain interpolation resampling are employed to correct the Doppler distorted signals for recovering the objective characteristic frequency. Simulation analysis has validated that under heavy background noise situation, better localization accuracy and effectiveness of the proposed short-time sparse singular value decomposition could be achieved in comparison with other strategies like short-time multiple signal classification. Besides, the real data cases have verified the effectiveness of the proposed method, which shows great potential applications in wayside condition monitoring and fault diagnosis system for moving vehicles, trains, planes, etc.

Distributed Consensus Optimization in Multiagent Networks With Time-Varying Directed Topologies and Quantized Communication.

This paper considers solving a class of optimization problems which are modeled as the sum of all agents' convex cost functions and each agent is only accessible to its individual function. Communication between agents in multiagent networks is assumed to be limited: each agent can only interact information with its neighbors by using time-varying communication channels with limited capacities. A technique which overcomes the limitation is to implement a quantization process to the interacted information. The quantized information is first encoded as a binary sequence at the side of each agent before sending. After the binary sequence is received by the neighboring agent, corresponding decoding scheme is utilized to resume the original information with a certain degree of error which is caused by the quantization process. With the availability of each agent's encoding states (associated with its out-channels) and decoding states (associated with its in-channels), we devise a set of distributed optimization algorithms that generate two iterative sequences, one of which converges to the optimal solution and the other of which reaches to the optimal value. We prove that if the parameters satisfy some mild conditions, the quantization errors are bounded and the consensus optimization can be achieved. How to minimize the number of quantization level of each connected communication channel in fixed networks is also explored thoroughly. It is found that, by properly choosing system parameters, one bit information exchange suffices to ensure consensus optimization. Finally, we present two numerical simulation experiments to illustrate the efficacy of the algorithms as well as to validate the theoretical findings.

Broadband and three-dimensional vibration energy harvesting by a non-linear magnetoelectric generator

Vibration, widely existing in an ambient environment with a variety of forms and wide-range of scales, recently becomes an attractive target for energy harvesting. However, its time-varying directions and frequencies render a lack of effective energy technology to scavenge it. Here, we report a rationally designed nonlinear magnetoelectric generator for broadband and multi-directional vibration energy harvesting. By using a stabilized three-dimensional (3D) magnetic interaction and spring force, the device working bandwidth was largely broadened, which was demonstrated both experimentally and theoretically. The multidirectional vibration energy harvesting was enabled by three identical suspended springs with equal intersection angles, which are all connected to a cylindrical magnet. Numerical simulations and experimental results show that the nonlinear harvester can sustain large-amplitude oscillations over a wide frequency range, and it can generate power efficiently in an arbitrary direction. Moreover, the experimental data suggest that the proposed nonlinear energy harvester has the potential to scavenge vibrational energy over a broad range of ambient frequencies in 3D space.

Local Stable and Unstable Manifolds and Their Control in Nonautonomous Finite-Time Flows

It is well-known that stable and unstable manifolds strongly influence fluid motion in unsteady flows. These emanate from hyperbolic trajectories, with the structures moving nonautonomously in time. The local directions of emanation at each instance in time is the focus of this article. Within a nearly autonomous setting, it is shown that these time-varying directions can be characterised through the accumulated effect of velocity shear. Connections to Oseledets spaces and projection operators in exponential dichotomies are established. Availability of data for both infinite and finite time-intervals is considered. With microfluidic flow control in mind, a methodology for manipulating these directions in any prescribed time-varying fashion by applying a local velocity shear is developed. The results are verified for both smoothly and discontinuously time-varying directions using finite-time Lyapunov exponent fields, and excellent agreement is obtained.