Time-varying Shape Research Articles

Propulsive efficiency of spatiotemporally asymmetric oscillating appendages at intermediate Reynolds numbers

Many organisms use flexible appendages for locomotion, feeding, and other functional behaviors. The efficacy of these behaviors is determined in large part by the fluid dynamics of the appendage interacting with its environment. For oscillating appendages at low Reynolds numbers, viscosity dominates over inertia, and appendage motion must be spatially asymmetric to generate net flow. At high Reynolds numbers, viscous forces are negligible and appendage motion is often also temporally asymmetric, with a fast power stroke and a slow recovery stroke; such temporal asymmetry does not affect the produced flow at low Reynolds numbers. At intermediate Reynolds numbers, both viscous and inertial forces play non-trivial roles---correspondingly, both spatial and temporal asymmetry can strongly affect overall propulsion. Here we perform experiments on three robotic paddles with different material flexibilities and geometries, allowing us to explore the effects of motion asymmetry (both spatial and temporal) on force production. We show how a flexible paddle's time-varying shape throughout the beat cycle can reorient the direction of the produced force, generating both thrust and lift. We also evaluate the propulsive performance of the paddle by introducing a new quantity, which we term "integrated efficiency". This new definition of propulsive efficiency can be used to directly evaluate an appendage's performance independently from full-body swimming dynamics. Use of the integrated efficiency allows for accurate performance assessment, generalization, and comparison of oscillating appendages in both robotic devices and behaving organisms. Finally, we show that a curved flexible paddle generates thrust more efficiently than a straight paddle, and produces spatially asymmetric motion---thereby improving performance---without the need for complex actuation and controls, opening new avenues for bioinspired technology development.

Estimating Non-Stationary Extreme-Value Probability Distribution Shifts and Their Parameters Under Climate Change Using L-Moments and L-Moment Ratio Diagrams: A Case Study of Hydrologic Drought in the Goat River Near Creston, British Columbia

Here, we investigate the use of rolling-windowed L-moments (RWLMs) and L-moment ratio diagrams (LMRDs) combined with a Multiple Linear Regression (MLR) machine learning algorithm to model non-stationary low-flow hydrological extremes with the potential to simultaneously understand time-variant shape, scale, location, and probability distribution (PD) shifts under climate change. By employing LMRDs, we analyse changes in PDs and their parameters over time, identifying key environmental predictors such as lagged precipitation for September 5-day low-flows. Our findings indicate a significant relationship between total August precipitation L-moment ratios (LMRs) and September 5-day low-flow LMRs (τ2-Precipitation and τ2-Discharge: R2 = 0.675, p-values < 0.001; τ3-Precipitation and τ3-Discharge: R2 = 0.925, p-value for slope < 0.001, intercept not significant with p = 0.451, assuming α = 0.05 and a 31-year RWLM), which we later refine and use for prediction within our MLR algorithm. The methodology, applied to the Goat River near Creston, British Columbia, aids in understanding the implications of climate change on water resources, particularly for the yaqan nuʔkiy First Nation. We find that future low-flows under climate change will be outside the Natural Range of Variability (NROV) simulated from historical records (assuming a constant PD). This study provides insights that may help in adaptive water management strategies necessary to help preserve Indigenous cultural rights and practices and to help sustain fish and fish habitat into the future.

Energy-optimal adaptive artificial potential field method for path planning of free-flying space robots

Aiming at planning a collision-free path for a free-flying space robot (FFSR), an energy-optimal collision avoidance strategy is proposed using the adaptive artificial potential field (AAPF) approach. To address the goals non-reachable with obstacles nearby (GNRON) issues of artificial potential field (APF), an adaptive and secure path planning method is proposed by incorporating a smooth decay function into the repulsive potential field. Meanwhile, a time-varying shaping parameter of attractive potential field is optimized combined with the state-dependent Riccati equation technique to reduce the energy cost of the FFSR. In case the system gets trapped in local minimum, an escape force is elaborately designed to replace artificial potential force based on optimal theory, whose direction vector guides the FFSR to jump out of the local minimum with minimal energy. Finally, simulation results on a planar FFSR demonstrate the effectiveness of the proposed methodology and show improved performance compared with the existing artificial potential field (APF) in terms of escaping local minimum and reducing energy consumption.

A magnetically actuated soft robot and its motion regulation

Inspired by molluscs, researchers have developed soft robots with greater freedom of movement and more adaptable to unstructured environments. Herein, a multi-locomotion soft robot based on magnetic composites is proposed. The space variable magnetic field impels the robot to generate a series of time-varying shapes, in order to accomplish all sorts of necessary motion gait. By integrating experimental exploration, theoretical research and finite element analysis, the pose kinematics of the robot are deeply analyzed, yielding an accurate description of its motion characteristics and fundamental laws. On this basis, control strategies are formulated to achieve customized crawling maneuvers and path planning for the robot in response to varying tasks. It is hoped that this research has profound significance for the improvement of traditional robots and the promotion of the development of intelligent devices.

Application of an overset grid method for the performance analysis of flapping airfoils

With the growing importance of renewable energy, the interest in energy-harvesting technologies based on flow-induced vibrations of airfoils has been rekindled in the past few years. Compared to conventional turbines, these devices are centrifugal stress-free and hence they are structurally more robust. They are also environmentally friendly due to the relatively low speeds, thus reducing the impact on flying animals. In order to numerically investigate these types of devices, mesh motion techniques must be used so that the computational grid can adapt to the time-varying shape of the domain and boundaries, thus preserving its robustness and quality. During the last years, many different dynamic mesh approaches have been developed to better predict the behaviour of a flow interacting with solid moving bodies. The aim of the present work is to apply and validate the overset grid method offered by the OpenFOAM software. In this type of mesh, one or more grid blocks are allowed to overlap with other sets of cells to solve the fluid domain with moving bodies, thus showing many potential advantages compared to the other existing dynamic mesh approaches. In the first part of this work, a numerical investigation of the flow over a stationary SD 7003 airfoil at low Reynolds number has been performed using an unsteady RANS approach. The computed results have then been compared to experimental and high-fidelity computational data available from the literature in order to validate the presented model in terms of numerical domain configuration, mesh refinement, and turbulence modelling. Subsequently, unsteady RANS simulations have been performed on the SD 7003 and NACA 0012 airfoils for two different amplitudes of flapping motion, i.e., 30° and 45°. Finally, the results obtained with the OpenFOAM overset grid solver have been compared with the numerical and experimental benchmarks presented by Kurtulus, showing an excellent agreement with both computed and measured data.

English

Reliable data on e-waste generation is important for environmentally sound management systems. This study models e-waste generation from existing data on electrical electronics imports, consumption and e-waste generation from Nigerian households. Structured questionnaires were used to obtain information on Electrical Electronic Equipment (EEE) use, reuse, and disposal from households in Nigeria households. Data from placed on the market (POM) were obtained from United Nations University (UNU) for five EEE types (TV, DVD player, refrigerator, desktop and laptop) in Nigeria between 1995 and 2019 using the apparent consumption method. A forecast up to 2020 and backcasts to 1980 were made based on these data. The lifetime profile for these five EEEs was modeled using the Weibull distribution function characterized by a time-varying shape parameter and a scale parameter. The POM data from 1980 to 2020 and the lifetime of the selected EEE from households were analyzed and fit into the Weibull lifetime distribution functions. The differences between reuse and non-reuse options show that around 54 million units of DVD players; 106 million units of CRT TV; 22 million units of the refrigerator; 11 million units of laptops and 24 million units of desktop computers would have been delayed from transiting into e-waste stream between 1981 and 2020 through reuse options.   Key words: Electronic waste, electrical electronic equipment, lifetime distribution, re-use repair, recycling, Nigeria.

Boosting the output of bottom-electrode droplets energy harvester by a branched electrode

Droplets energy harvesters(DEHs) have attracted tremendous attention and shown great potential in harvesting energy from falling water. Current approaches to enhance the device output through adapting a top-electrode in direct contact with the droplets face the drawbacks of fixed droplet-imping-location and inevitable electrode corrosion. Herein, we proposed an easy but effective way to boost the performance of bottom-electrode DEHs through adapting a partial-electrode configuration. It was found that droplets impinging at the boundary between a blank region and the electrode region, instead of at the electrode region, could improve the output peak voltage and current by more than one order of magnitude, up to 30 V. The mechanism is contributed to that water across the boundary bridges the blank and the electrode region for notable inter-region charge transfer, leading to an enhanced electrostatic induction. The induced peak current is proven to be proportional to the changing rate of droplet area on top of the electrode upon initial overlap, and inversely proportional to the thickness of the polymer film in our test range. Based on these findings, DEH with a branched electrode is designed to harvest energy from falling droplets of random positions, as well as energy from turbulent flow of time-variant shapes with an output voltage up to one hundred volts.

Viscoelastic Thermovibrational Flow Driven by Sinusoidal and Pulse (Square) Waves

The present study aims to probe the role of an influential factor heretofore scarcely considered in earlier studies in the field of thermovibrational convection, that is, the specific time-varying shape of the forcing used to produce fluid motion under the effect of an imposed temperature gradient. Towards this end, two different temporal profiles of acceleration are considered: a classical (sinusoidal) and a pulse (square) wave. Their effects are analyzed in conjunction with the ability of a specific category of fluids to accumulate and release elastic energy, i.e., that of Chilcott–Rallison finitely extensible nonlinear elastic (FENE-CR) liquids. Through solution of the related governing equations in time-dependent, three-dimensional, and nonlinear form for a representative set of parameters (generalized Prandtl number Prg=8, normalized frequency Ω=25, solvent-to-total viscosity ratio ξ=0.5, elasticity number ϑ=0.1, and vibrational Rayleigh number Raω=4000), it is shown that while the system responds to a sinusoidal acceleration in a way that is reminiscent of modulated Rayleigh–Bénard (RB) convection in a Newtonian fluid (i.e., producing a superlattice), with a pulse wave acceleration, the flow displays a peculiar breaking-roll mode of convection that is in between classical (un-modulated) RB in viscoelastic fluids and purely thermovibrational flows. Besides these differences, these cases share important properties, namely, a temporal subharmonic response and the tendency to produce spatially standing waves.

Time-varying output formation-containment control for homogeneous/heterogeneous descriptor fractional-order multi-agent systems

In this paper, the time-varying output formation-containment (TV-OFC) problem of homogeneous and heterogeneous descriptor fractional-order multi-agent systems (DFO-MASs) is investigated. The results obtained in previous works for nonsingular integer-order multi-agent systems can be regarded as particular cases of our results. This control aims at making leaders keep time-varying shape to move and followers move inside the convex hull spanned by leaders simultaneously. First, both the output feedback control strategy and observer-based control algorithm are designed to address the TV-OFC problem of heterogeneous DFO-MASs, where the virtual leader provides the reference trajectory for leaders to achieve the formation tracking. Then, sufficient conditions with less computation complexity are presented and the methods to determine gain matrices of the schemes are proposed for homogeneous and heterogeneous DFO-MASs, so as to achieve the TV-OFC. Finally, numerical examples are given to demonstrate the effectiveness of theoretical conclusions.

Improving Target Detection Ability Based on Time Invariant and Dot-Shape Beamforming in TMRC-FDA-MIMO Radar

Frequency diverse array and multiple-input multiple-output (FDA-MIMO) radar is studied more to realise the joint estimation of range and angle. However, the estimation performance of target parameters for linear FDA radar with an identical frequency increment and multiple-input multiple-output (IFI-FDA-MIMO) and logarithmically increased frequency offset linear interval, and multiple-input multiple-output (LIFO-FDA-MIMO) is fundamentally limited by the periodic range-time variation and time-variant dot shape beampattern respectively. In this article, we proposed a joint range and angle estimation algorithm based on a new waveform synthesis model of time modulation and rang compensation FDA-MIMO (TMRC-FDA-MIMO). The emulation results demonstrate that the improved scheme achieves the goal of time-invariant, dot-shaped and low sidelobe beampattern, which is optimised by a new accelerated particle swarm optimisation (NAPSO) algorithm. The performance of target estimation under the Cramer Rao lower bound (CRLB), and the root means square errors (RMSE) of the radar system is analysed. Moreover, the mathematical formula derivation and numerical results verify the performance of the proposed algorithm, which shows that TMRC-FDA-MIMO radar system is superior to others mentioned above.

Interaction between time-varying tone inharmonicity, fundamental frequency and spectral shape affects felt tension and timbral semantics

Musically induced tension has been the subject of thorough study in the music cognition literature but its relationship with timbre is still poorly investigated. This study examines how the dynamic variation of a tone’s inharmonicity may affect a number of auditory qualities, namely brightness, roughness and mass along with felt tension under different acoustical conditions (i.e., F0, spectral shape and type of inharmonicity). Fifty-six musically trained participants gave real-time continuous ratings on eight time-varying stimuli upon the aforementioned qualities. Static ratings over the initial purely harmonic parts of the stimuli were also obtained by a subgroup of the listening panel. The fundamental frequency exhibits the strongest influence on the responses of the four qualities, followed by the type of inharmonicity and the spectral shape to a lesser degree. The profile patterns of mass and brightness proved to be strong predictors for tension profile patterns while the roughness profile magnitudes show a significant main effect on the magnitude of tension profiles. Overall, these results demonstrate that time-varying inharmonicity affects continuous responses on both timbral semantics and tension, while indicating that felt tension may be influenced by underlying timbral qualities in a dynamic context.

Fully distributed time-varying formation tracking control of linear multi-agent systems with input delay and disturbances

Abstract This paper investigates the time-varying formation tracking (TVFT) control problem considering a constant input delay and unknown external disturbances for the general linear multi-agent system (MAS) under a directed communication graph containing a spanning tree. To achieve that, a new time-varying shape format is firstly proposed. Then, a disturbance observer (DO) is introduced to compensate the unknown disturbance effect. After that, the Artstein’s model reduction technique is adopted and modified to design a state predictor in order to transform the MAS with a delayed input into a delay-free system. Fourthly, an adaptive observer (AO), which is used to estimate the designed state predictor, is proposed by using the neighbors’ information such as the inputs, time-varying shapes, DOs, AOs and relative state measurements. The convergence of closed-loop system is guaranteed by the designed algebraic Riccati equation. The whole controller requires no eigenvalue information of the Laplacian matrix of communication graph, thus is fully distributed. Finally, the effectiveness of proposed fully distributed controller (FDC) is verified by numerical examples and factors influencing FDC performances are analyzed.

Distributed Electric Field Induces Orientations of Nanosheets to Prepare Hydrogels with Elaborate Ordered Structures and Programmed Deformations.

Living organisms use musculatures with spatially distributed anisotropic structures to actuate deformations and locomotion with fascinating functions. Replicating such structural features in artificial materials is of great significance yet remains a big challenge. Here, a facile strategy is reported to fabricate hydrogels with elaborate ordered structures of nanosheets (NSs) oriented under a distributed electric field. Multiple electrodes are distributed with various arrangements in the precursor solution containing NSs and gold nanoparticles. A complex electric field induces sophisticated orientations of the NSs that are permanently inscribed by subsequent photo-polymerization. The resultant anisotropic nanocomposite poly(N-isopropylacrylamide) hydrogels exhibit rapid deformation upon heating or photoirradiation, owing to the fast switching of permittivity of the media and electric repulsion between the NSs. The complex alignments of NSs and anisotropic shape change of discrete regions result in programmed deformation of the hydrogels into various configurations. Furthermore, locomotion is realized by a spatiotemporal light stimulation that locally triggers time-variant shape change of the composite hydrogel with complex anisotropic structures. Such a strategy on the basis of the distributed electric-field-generated ordered structures should be applicable to gels, elastomers, and thermosets loaded with other anisotropic particles or liquid crystals, for the design of biomimetic/bioinspired materials with specific functionalities.

A consumption-based asset pricing model with disappointment aversion and uncertainty shocks

We study a consumption-based asset pricing model with ‘good’ and ‘bad’ uncertainties. Good and bad uncertainties are characterized by two gamma distributions with time-varying shape parameters and they respectively represent potentially fat-tailed, skewed positive and negative innovations to consumption growth. The representative agent has generalized disappointment aversion preferences. We show that disappointment aversion is important for generating a low risk-free rate and high equity premium, and additionally, while the influence of the elasticity of intertemporal substitution (EIS) on equity premium is negligible, the EIS is important for delivering reasonable implications on the market prices of the two uncertainty components.

Time-domain induced polarization forward modeling and an apparent spectral parameter solution based on the Weibull growth model

The application of the Cole-Cole model within time-domain induced polarization (TDIP) forward field modeling shows that the model parameters can characterize time-varying states of the TDIP field and support observed data analysis. The Cole-Cole model contains real and imaginary parts, and it requires a frequency-to-time conversion for TDIP forward modeling. However, the TDIP field is usually expressed by a real number, and its intuitive time-varying states field intensity increases with charging time. Therefore, the forward model should be constructed in a simpler form. We have aimed to develop a forward model using mathematical functions not based on physical principles. The Weibull (WB) growth model, which is primarily used to describe the time-varying curve features in regression analysis, is introduced into the basic algorithm of the TDIP forward model. Subsequently, a forward expression of the TDIP effect is established. Based on the time-varying shape and scale parameters, this expression describes the time-varying rate and relaxation states of the TDIP fields. Furthermore, based on the extensively used conjugate gradient optimization, an apparent WB parameter scheme is initiated to calculate the spectral parameters that represent the relaxation and time-varying rate obtained from the multi-time-channel TDIP data. Finally, this scheme is applied to interpret the different simulated and actual TDIP data. The results demonstrate that the WB growth model can be used for the TDIP forward model without involving physical principles, the model parameters without specific physical significance can be used to represent the time-varying states of TDIP fields, and apparent WB parameters can be used to discern different TDIP observed data. The setting of the TDIP forward model and model parameters can actually be more flexible and diverse, so as to obtain simpler forward expressions and ensure a highly efficient inverse solution.

Shape turnpike for linear parabolic PDE models

We introduce and study the turnpike property for time-varying shapes, within the viewpoint of optimal control. We focus here on second-order linear parabolic equations where the shape acts as a source term and we seek the optimal time-varying shape that minimizes a quadratic criterion. We first establish existence of optimal solutions under some appropriate sufficient conditions. We then provide necessary conditions for optimality in terms of adjoint equations and, using the concept of strict dissipativity, we prove that state and adjoint satisfy the measure-turnpike property, meaning that the extremal time-varying solution remains essentially close to the optimal solution of an associated static problem. We show that the optimal shape enjoys the exponential turnpike property in terms of Hausdorff distance for a Mayer quadratic cost. We illustrate the turnpike phenomenon in optimal shape design with several numerical simulations.

A Decentralized Low-Chattering Sliding Mode Formation Flight Controller for a Swarm of UAVs.

In this paper, a nonlinear robust formation flight controller for a swarm of unmanned aerial vehicles (UAVs) is presented. It is based on the virtual leader approach and is capable of achieving and maintaining a formation with time-varying shape. By using a decentralized architecture, the local controller in each UAV uses information only from the UAV itself, its neighbors, and from the virtual leader. Also, a synchronization control objective provides a mechanism to weight between the fleet achieving the desired formation shape, that is, achieving the desired relative position between the UAVs, and each UAV achieving its desired absolute position. The use of a combination of a sliding mode controller and a low pass filter reduces the usual chattering effect, providing a smooth control signal while maintaining robustness. Simulation results show the effectiveness of the proposed decentralized controller.

Simultaneous tracking of a maneuvering ship and its wake using Gaussian processes

Maneuvering ship tracking has applications in maritime surveillance and the performance of tracking algorithms is affected by background clutter and ship-generated wake. Previous works consider the wake as a form of clutter with some specific spatial distribution. In this paper, the Kelvin wake, which assumes that the ship-generated wake is V-shaped, is modelled as an extended target with an irregular and time-varying shape. Thus, the problem of maneuvering ship tracking in the presence of wake becomes a special multiple target tracking problem, where the ship is a point target and the wake is an extended target. A Gaussian Processes based Multiple Model Joint Probabilistic Data Association (GP-MM-JPDA) method is proposed to estimate the ship state and the wake state simultaneously. Two versions of the GP-MM-JPDA are implemented. The first one can be applied to most multiple target tracking problems and the second one is designed especially for the ship tracking problem. Both versions can improve the ship tracking performance. In addition, the proposed methods can also infer the ship length using the estimated wake angle, which facilitates ship classification. Simulation results show the effectiveness of the proposed methods.

Multisphere Method for Flexible Conducting Space Objects: Modeling and Experiments

In the last two decades, concepts have been developed to harness electrostatic forces and torques to enable novel missions, including coulomb formation flying, inflating membrane structures, and detumbling and reorbiting debris touchlessly. The need for faster-than-real-time modeling of the electrostatic forces and torques in these missions has led to the development of the multisphere method (MSM) in which the electrostatic field generated by a charged body is approximated through the use of a series of optimally placed and sized conducting spheres. Although the prior work assumed the charged body was rigid, this paper extends the use of the MSM to flexible shapes. An example of the effectiveness of the MSM approach is explored by matching analytical models of the electric field and capacitance about a line of charge, and then deforming it into a ring while still matching analytic models. However, the core underlying assumption of the shape surface being a conductor remains. The limits of this model are tested via experimental comparison of a thin strip of aluminized Mylar in a constant electric field with the flexible MSM model. Although the new flexible MSM is good at modeling time-varying shapes of pure conductors, the charged thin Mylar sheet dynamics are strongly influenced by dielectric polarization and charge self-emission due to the sharp edges.

Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition.

The detection and tracking of human landmarks in video streams has gained in reliability partly due to the availability of affordable RGB-D sensors. The analysis of such time-varying geometric data is playing an important role in the automatic human behavior understanding. However, suitable shape representations as well as their temporal evolution, termed trajectories, often lie to nonlinear manifolds. This puts an additional constraint (i.e., nonlinearity) in using conventional Machine Learning techniques. As a solution, this paper accommodates the well-known Sparse Coding and Dictionary Learning approach to study time-varying shapes on the Kendall shape spaces of 2D and 3D landmarks. We illustrate effective coding of 3D skeletal sequences for action recognition and 2D facial landmark sequences for macro- and micro-expression recognition. To overcome the inherent nonlinearity of the shape spaces, intrinsic and extrinsic solutions were explored. As main results, shape trajectories give rise to more discriminative time-series with suitable computational properties, including sparsity and vector space structure. Extensive experiments conducted on commonly-used datasets demonstrate the competitiveness of the proposed approaches with respect to state-of-the-art.