Flow-induced vibration (FIV) of a circular cylinder with an attached splitter plate in a laminar flow with Re = 100 is studied numerically. First, the mechanical model along with mathematical formulations is proposed to describe the fluid-structure interaction (FSI) between the elastically supported cylinder–plate body and the surrounding flow. Subsequently, an FSI solution procedure is developed based on the characteristic-based split finite element method, and its accuracy and stability are validated using vortex-induced vibrations (VIVs) of a plain circular cylinder with benchmark solutions. Finally, using FSI simulations, effects of the plate length (L), reduced velocity, mass ratio and damping coefficient on the dynamic response, fluid load, and flow pattern of the cylinder–plate assembly are investigated in detail. As the plate length increases from L/D = 0–1.5 (D is the cylinder diameter), three FIV modes are observed successively: VIV, coupled VIV and galloping, and separated VIV and galloping, along with three vortex modes in the wake: 2S (two separated vortices in one cycle), P+S (a vortex pair and a separated vortex in one cycle), and 2P (two vortex pairs in one cycle). Moreover, it is found that the lift components generated from the splitter plate and the cylinder behave, respectively, as the driving force and the suppressing force of galloping, and the transition from VIV to galloping can be taken as a result of the competition between them. The cylinder–plate model presented could be taken as a benchmark model demonstrating the VIV-galloping interaction and applied to the design of novel FSI-based energy harvesters.

Proper design decoupling in the context of Axiomatic Design (AD) is essential to transforming customer needs to functional requirements, design parameters, and process variables using matrices. It is common that design decoupling is performed by adopting methods that are philosophically and methodologically different from AD, such as TRIZ. However, transformation of coupling problems following the approach lacks a uniform description for design coupling and also a systematic methodology for decoupling. This article presents a novel method that allows problems involving design coupling to be described by their attributes using the basic concepts of Extenics. The resulted descriptions are well-defined in the basic-element form with a set of uniform characteristics, enabling the decoupling process to be general, structured and effective in search for the knowledge needed for solving the coupling problem. Three decoupled models each exploring AD and Extenics for following a particular decoupling direction of AD are considered. A comprehensive analysis along with a few illustrative examples is considered to illustrate the validity of the decoupling method which is a synergy of AD with Extenics.

The human brain is a complex network whose ensemble time evolution is directed by the cumulative interactions of its cellular components, such as neurons and glia cells. Coupled through chemical neurotransmission and receptor activation, these individuals interact with one another to varying degrees by triggering a variety of cellular activity from internal biological reconfigurations to external interactions with other network agents. Consequently, such local dynamic connections mediating the magnitude and direction of influence cells have on one another are highly nonlinear and facilitate, respectively, nonlinear and potentially chaotic multicellular higher-order collaborations. Thus, as a statistical physical system, the nonlinear culmination of local interactions produces complex global emergent network behaviors, enabling the highly dynamical, adaptive, and efficient response of a macroscopic brain network. Microstate reconfigurations are typically facilitated through synaptic and structural plasticity mechanisms that alter the degree of coupling (magnitude of influence) neurons have upon each other, dictating the type of coordinated macrostate emergence in populations of neural cells. These can emerge in the form of local regions of synchronized clusters about a center frequency composed of individual neural cell collaborations as a fundamental form of collective organization. A single mode of synchronization is insufficient for the computational needs of the brain. Thus, as neural components influence one another (cellular components, multiple clusters of synchronous populations, brain nuclei, and even brain regions), different patterns of neural behavior interact with one another to produce an emergent spatiotemporal spectral bandwidth of neural activity corresponding to the dynamical state of the brain network. Furthermore, hierarchical and self-similar structures support these network properties to operate effectively and efficiently. Neuroscience has come a long way since its inception; however, a comprehensive and intuitive understanding of how the brain works is still amiss. It is becoming evident that any singular perspective upon the grandiose biophysical complexity within the brain is inadequate. It is the purpose of this paper to provide an outlook through a multitude of perspectives, including the fundamental biological mechanisms and how these operate within the physical constraints of nature. Upon assessing the state of prior research efforts, in this paper, we identify the path future research effort should pursue to inspire progress in neuroscience.

Micro-milling is inherently unstable and chattering with aberrational tool vibrations. While the time response is bounded, however, micro-milling can become unstably broadband and chaotic in the frequency domain, inadvertently rendering poor tolerance and frequent tool damage. A novel simultaneous time-frequency control theory is applied to negate the various nonlinear dynamic instabilities including tool chatter and tool resonance displayed by a multi-dimensional, time-delayed micro-milling model. The time and frequency responses of the force and vibration of the model agree well with the experimental results published by Jun et al. A multi-variable control scheme is realized by implementing two independent controllers in parallel to follow a target signal representing the desired micro-milling state of stability. The control of unstable cutting at high spindle speeds ranging from 63,000 to 180,000 rpm and different axial depth-of-cuts are investigated using phase portrait, Poincaré section, and instantaneous frequency (IF). The time-frequency control scheme effectively restores dynamic instabilities, including repelling manifold and chaotic response, back to an attracting limit cycle or periodic motion of reduced vibration amplitude and frequency response. The force magnitude of the dynamically unstable cutting process is also reduced to the range of stable cutting.

The various responses of a silicon wafer excited by a femtosecond pulsed laser are investigated. A multi-time scale axisymmetric model that governs the transport dynamics in silicon is presented based on the relaxation-time approximation of the Boltzmann equation. Temperature-dependent multi-phonons, free-carrier absorptions, and the recombination and impact ionization processes are considered using a set of balance equations. The mechanical response of the lattice is described by momentum equations. To solve the model of 17 coupled time-dependent partial differential equations without having to be concerned with non-physical oscillations in the solution, an implicit finite difference scheme on a staggered grid is developed. The staggered finite difference scheme allows velocities and first-order spatial derivative terms to be calculated at locations midway between two consecutive grid points, and shear stresses to be evaluated at the center of each element. A multi-time-scale approach involving the use of varying time steps ranging from 5 fs to 5 ps is implemented to successfully obtain time integration results up to 10 ns.