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Recently proposed clustering-based methods provide an efficient way for homogenizing heterogeneous materials, yet without concerning the detailed distribution of the mechanical responses. With coarse fields of the clustering-based methods as an initial guess, we develop an iteration strategy to fastly and accurately resolve the displacement, strain and stress based on the Lippmann-Schwinger equation, thereby benefiting the local mechanical analysis such as the detection of the stress concentration. From a simple elastic case, we explore the convergence of the method and give an instruction for the selection of the reference material. Numerical tests show the efficiency and fast convergence of the reconstruction method in both elastic and hyper-elastic materials.

Trailing edge serrations (TESs) are capable of noticeably suppressing the turbulent trailing edge noise induced by rotating wind turbine blades and become an integral part of a blade. However, the challenges involved in the dimensional design of serration height 2

A kinematic chain with two degrees of freedom and one input can have definability of motion only if there is an additional constraint of forces and velocities. Such a chain is a mechanism that has the brand new property of force adaptation.The article presents a kinematic and force analysis of two-mobile adaptive mechanisms and describes the principle of definability of motion.

To explore tunnel effects on ring road traffic flow, a macroscopic urgent-gentle class traffic model is put forward. The model identifies vehicles with urgent and gentle classes, chooses the tunnel speed limit as free flow speed to express the fundamental diagram in the tunnel, and adopts algebraic expressions to describe traffic pressure and sound speed. With two speed trajectories at the Kobotoke tunnel in Japan, the model is validated, with good agreement with observed data. Numerical results indicate that in the case of having no ramp effects, tunnel mean travel time is almost constant dependent on tunnel length. When initial density normalized by jam density is above a threshold of about 0.21, a traffic shock wave originates at the tunnel entrance and propagates backward. Such a threshold drops slightly as a result of on-ramp merging effect, the mean travel time drops as off-ramp diversion effect intensifies gradually. These findings deepen the understanding of tunnel effects on traffic flow in reality.

Ocean basin is modeled as a two-dimensional closed, bounded domain in which the fluid flow is governed by the complex partial differential equations in the flow function. Keeping in view that the ocean currents are non-viscous, no normal flow conditions are used at the basin boundaries. The parameters investigated here are; Coriolis parameter, wind stress coefficient, and latitude. Stochastic differential equations in time scales are solved by deterministic and stochastic methods. Deterministic results concluded that streamlines are symmetric about stagnation point (no flow) for

The emerging push of the differentiable programming paradigm in scientific computing is conducive to training deep learning turbulence models using indirect observations. This paper demonstrates the viability of this approach and presents an end-to-end differentiable framework for training deep neural networks to learn eddy viscosity models from indirect observations derived from the velocity and pressure fields. The framework consists of a Reynolds-averaged Navier--Stokes (RANS) solver and a neural-network-represented turbulence model, each accompanied by its derivative computations. For computing the sensitivities of the indirect observations to the Reynolds stress field, we use the continuous adjoint equations for the RANS equations, while the gradient of the neural network is obtained via its built-in automatic differentiation capability. We demonstrate the ability of this approach to learn the true underlying turbulence closure when one exists by training models using synthetic velocity data from linear and nonlinear closures. We also train a linear eddy viscosity model using synthetic velocity measurements from direct numerical simulations of the Navier--Stokes equations for which no true underlying linear closure exists. The trained deep-neural-network turbulence model showed predictive capability on similar flows.

The immersed boundary method has been widely used for simulating flows over complex geometries. However, its accuracy in predicting the statistics of near-wall turbulence has not been fully tested. In this work, we evaluate the capability of the curvilinear immersed boundary (CURVIB) method in predicting near-wall velocity and pressure fluctuations in turbulent channel flows. Simulation results show that quantities including the time-averaged streamwise velocity, the rms (root-mean-square) of velocity fluctuations, the rms of vorticity fluctuations, the shear stresses, and the correlation coefficients of

This study investigates the effect of Reynolds number on the performance of Savonius wind turbine with slotted blades. The turbine performance investigation was based on the torque coefficient (

A simplified surface correction formulation is proposed to diminish the far-field spurious sound generated by the quadrupole source term in Ffowcs Williams and Hawkings (FW-H) integrals. The proposed formulation utilizes the far-field asymptotics of the Green's function to simplify the computation of its high-order derivatives, which circumvents the difficulties reported in the original frequency-domain surface correction formulation. The proposed formulation has been validated by investigating the benchmark case of sound generated by a convecting vortex. The results show that the proposed formulation successfully eliminates the spurious sound. The applications of the proposed formulation to flows with some special parameters are also discussed.

Flexible electrodes have been widely focused on in recent years due to their special mechanical properties, which can be directly integrated onto human soft tissues to actively take effects on human body or passively monitor human vital signs. These flexible electrodes provide a new routine to realize clinical treatment of accurate thermal ablation in the biological tissues via radiofrequency ablation (RFA). Meanwhile, accurately controlling of thermal field is very significant for the thermal ablation in the clinical therapeutics to prevent the healthy tissue from excessive burning. In this paper, both one-dimensional and two-dimensional axisymmetric analytical models for the electrothermal analysis of radiofrequency ablation considering bio-heat transfer are established, which are verified by finite element analysis (FEA) and in vitro experiments on pig skins. In the model, the electrical field and thermal field are both derived analytically to accurately predict the temperature rise in the biological tissues. Furthermore, parameters, such as the blood flow convection in living tissues and thickness of tissue, have obvious effects on the thermal field in the tissues. They may pave the theoretical foundation and provide guidance of RFA with flexible electrodes in the future.

Bedding plane-embedded augmented virtual internal bonds for fracture propagation simulation in shale

To effectively simulate the fracture propagation in shale, the bedding plane (BP) effect is incorporated into the augmented virtual internal bond (AVIB) constitutive relation through BP tensor. Comparing the BP-embedded AVIB with the theory of transverse isotropy, it is found the approach can represent the anisotropic properties induced by parallel BPs. Through the simulation example, it is found that this method can simulate the stiffness anisotropy of shale and can represent the effect of BPs on hydraulic fracture propagation direction. Compared with the BP-embedded VIB, this method can account for the various Poisson's ratio. It provides a feasible approach to simulate the fracture propagation in shale.

Lacking labeled examples of working numerical strategies, adapting an iterative solver to accommodate a numerical issue, e.g., density discontinuities in the pressure Poisson equation, is non-trivial and usually involves a lot of trial and error. Here, we resort to evolutionary neural network. A evolutionary neural network observes the outcome of an action and adapts its strategy accordingly. The process requires no labeled data but only a measure of a network’s performance at a task. Applying neuro-evolution and adapting the Jacobi iterative method for the pressure Poisson equation with density discontinuities, we show that the adapted Jacobi method is able to accommodate density discontinuities.

We analyze the error of large-eddy simulation (LES) in wall pressure fluctuation of a turbulent channel flow. To separate different sources of the error, we conduct both direct numerical simulations (DNS) and LES, and apply an explicit filter on DNS data to obtain filtered DNS (FDNS) data. The error of LES is consequently decomposed into two parts: The first part is the error of FDNS with respect to DNS, which quantifies the influence of the filter operation. The second part is the difference between LES and FDNS induced by the error of LES in velocity field. By comparing the root-mean-square value and the wavenumber-frequency spectrum of the wall pressure fluctuation, it is found that the inaccuracy of the velocity fluctuations is the dominant source that induces the error of LES in the wall pressure fluctuation. The present study provides a basis on future LES studies of the wall pressure fluctuation.

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Seiches are long-period standing waves with a unique period called a natural resonant period, during which the phenomenon of resonance occurs. The occurrence of resonance in coastal areas can cause destruction to surrounding natural and man-made structures. By determining the resonant period of a given basin, we can pinpoint the conditions that allow waves to achieve resonance. In this study, a mathematical model is developed from the shallow water equations to examine seiches and resonances in various types of closed basin. The developed model is solved analytically using the separation of variables method to determine the seiches' fundamental resonant periods. Comparisons between the analytical solutions and experimental measurements for resonant periods are also provided. It is shown that the analytical resonant period confirms the experimental data for closed basin of various geometric profiles. Using a finite volume method on a staggered grid, the model is solved numerically to simulate the wave profile when resonance phenomenon occurs. Through those numerical simulations, we also obtain the fundamental resonant period for each basin which agrees with the derived analytical period.

With the rising of modern data science, data-driven turbulence modeling with the aid of machine learning algorithms is becoming a new promising field. Many approaches are able to achieve better Reynolds stress prediction, with much lower modeling error (

Flexible electronic devices are often subjected to large and repeated deformation, so that their functional components such as metal interconnects need to sustain strains up to tens of percent, which is far beyond the intrinsic deformability of metal materials (~1%). To meet the stringent requirements of flexible electronics, metal/elastomer bilayers, a stretchable structure that consists of a metal film adhered to a stretchable elastomer substrate, have been developed to improve the stretch capability of metal interconnects. Previous studies have predicted that the metal/elastomer bilayers are much more stretchable than freestanding metal films. However, these investigations usually assume perfect bonding between the metal and elastomer layers. In this work, the effect of the metal/elastomer interface with a finite interfacial stiffness on the stretchability of bilayer structures is analyzed. The results show that the assumption of perfect interface (with infinite interfacial stiffness) may lead to an overestimation of the stretchability of bilayer structures. It is also demonstrated that increased adhesion between the metal and elastomer layers can enhance the stretchability of the metal layer.

In the previous studies, the phenomenon that the interstitial fluid (ISF) can flow along tunica adventitia of the arteries and veins in both human and animal bodies was reported. On the basis of these studies, this paper aims to: (i) summarize the basic properties of the ISF flows in the walls of arteries and veins, (ii) combine the basic properties with axiomaticism and abstract the axiom for ISF flows, and (iii) propose three fundamental laws of the ISF flow, (i.e., the existence law, the homotropic law and the reverse law). The three laws provide solid theoretical basement for exploring the kinematic patterns of interstitial fluid flow in the cardiovascular system.

Elastomeric membranes are frequently used in several emerging fields such as soft robotics and flexible electronics. For convenience of the structural design, it is very attractive to find simple analytical solutions to well describe their elastic deformations in response to external loadings. However, both the material/geometrical nonlinearity and the deformation inhomogeneity due to boundary constraints make it much challenging to get an exact analytical solution. In this paper, we focus on the inflation of a pre-stretched elastomeric circular membrane under uniform pressure, and derive an approximate analytical solution of the pressure-volume curve based upon a reasonable assumption on the shape of the inflated membrane. Such an explicit expression enables us to quantitatively design the material and geometrical parameters of the pre-stretched membrane to generate a target pressure-volume curve with prescribed peak point and initial slope. This work would be of help in the simplified mechanical design of structures involving elastomeric membranes.

In recent years, neural networks have become an increasingly powerful tool in scientific computing. The universal approximation theorem asserts that a neural network may be constructed to approximate any given continuous function at desired accuracy. The backpropagation algorithm further allows efficient optimization of the parameters in training a neural network. Powered by GPU's, effective computations for scientific and engineering problems are thereby enabled. In addition, we show that finite element shape functions may also be approximated by neural networks.

This paper presents a quantitative framework to analyze the complexity of folding origami structures from flat membranes. Extensive efforts have realized intricate origami patterns with desired functions such as mechanical properties, packaging efficiency, and deployment behavior. However, the complexity associated with the manufacturing or folding of origami patterns has not been explored. Understanding how difficult origami structures are to make, and how much time they require to form is crucial information to determining the practical feasibility of origami designs and future applications such as robotic origami assembly in space. In this work, we develop this origami complexity metric by modeling the geometric properties and crease formation of the origami structure, from which it outputs crease and pattern complexity values and a prediction of the time to complete the pattern assembly, based on the characteristics of the operator. The framework is experimentally validated by fabricating various Miura-ori origami paper models.

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Display Method: |

2021, 11(2): 73 -80.
doi: 10.1016/j.taml.2021.100223

The placement of pressure taps on the surface of the wind tunnel test model is an important means to obtain the surface pressure distribution. However, limited by space location and experimental cost, it is difficult to arrange enough pressure measuring taps on the surface of complex models to obtain complete pressure distribution information, thus it is impossible to obtain accurate lift and moment characteristics through integration. The paper proposes a refined reconstruction method of airfoil surface pressure based on compressed sensing, which can reconstruct the pressure distribution with high precision with less pressure measurement data. Tests on typical airfoil subsonic flow around flow show that the accuracy of lift and moment after the pressure integration reconstructed by 4-8 measuring points can meet the requirements of the national military standard. The algorithm is robust to noise, and provides a new idea for obtaining accurate force data from sparse surface pressure tests in engineering.

2021, 11(2): 81 -88.
doi: 10.1016/j.taml.2021.100224

We investigate the evolution of interfacial gravity-capillary waves propagating along the interface between two dielectric fluids under the action of a horizontal electric field. There is a uniform background flow in each layer, and the relative motion tends to induce Kelvin-Helmholtz (KH) instability. The combined effects of gravity, surface tension and electrically induced forces are all taken into account. Under the short-wave assumption, the expansion and truncation method of Dirichlet-Neumann (DN) operators is applied to derive a reduced dynamical model. When KH instability is suppressed linearly by a considerably large electric field, our numerical results reveal that in certain regions of parameter space, nonlinear symmetric traveling wave solutions can be found near the minimum phase speed. Additionally, the detailed bifurcation structures are presented together with typical wave profiles.

2021, 11(2): 89 -93.
doi: 10.1016/j.taml.2021.100232

Two kinds of analytical solutions are derived through Laplace transform for the equation that governs wave-induced suspended sediment concentration with linear sediment diffusivity under two kinds of bottom boundary conditions, namely the reference concentration (Dirichlet) and pickup function (Numann), based on a variable transformation that is worked out to transform the governing equation into a modified Bessel equation. The ability of the two analytical solutions to describe the profiles of suspended sediment concentration is discussed by comparing with different experimental data. And it is demonstrated that the two analytical solutions can well describe the process of wave-induced suspended sediment concentration, including the amplitude and phase and vertical profile of sediment concentration. Furthermore, the solution with boundary condition of pickup function provides better results than that of reference concentration in terms of the phase-dependent variation of concentration.

2021, 11(2): 94 -98.
doi: 10.1016/j.taml.2021.100233

The complexity of the Portevin-Le Chatelier (PLC) effect in an Al alloy at different temperatures was analyzed by modified multiscale entropy. The results show that three evolutions of entropy with scale factor, i.e., near zero, monotonically increasing and peak-shape, were observed corresponding to the smooth curves, type-A serrations and type-B/-C serrations, respectively. The scale factor at the peak was one-third of the average serration period. The sample entropy increased initially and then decreased with temperature, which was opposite to the critical strain. It is also suggested that the type-A serrations corresponded to self-organized criticality and the type-B/-C serrations corresponded to chaos through the evolutions of entropy with scale factor.

2021, 11(2): 99 -108.
doi: 10.1016/j.taml.2021.100235

The impact attenuator is an essential system in both race cars and urban vehicles. The structure of an impact attenuator serves as a safety barrier between the impacted surface and the driver in an accident. Attenuator materials tend to have a high price; thus, alternative materials were explored in the current work, i.e., used cans from food and beverage containers. The study deployed a nonlinear finite element algorithm to calculate a series of impacts on the attenuator structures. The thickness of the cans and velocity of the impact were considered as the main parameters. Analysis results concluded that the attenuator's average energy was 16000 J for a can thickness of 1 mm. This value is more than two times the 0.5 mm thick used cans. The attenuator's new design was then matched with an attenuator regulation, and the results surpassed the standard value of 7350 J.

2021, 11(2): 109 -118.
doi: 10.1016/j.taml.2021.100236

In this paper, we provide exact fast Fourier transform (FFT)-based numerical bounds for the elastic properties of composites having arbitrary microstructures. Two bounds, an upper and a lower, are derived by considering usual variational principles based on the strain and the stress potentials. The bounds are computed by solving the Lippmann-Schwinger equation together with the shape coefficients which allow an exact description of the microstructure of the composite. These coefficients are the exact Fourier transform of the characteristic functions of the phases. In this study, the geometry of the microstructure is approximated by polygonals (two-dimensional (2D) objects) and by polyhedrons (three-dimensional (3D) objects) for which exact expressions of the shape coefficients are available. Various applications are presented in the paper showing the relevance of the approach. In the first benchmark example, we consider the case of a composite with fibers. The effective elastic coefficients ares derived and compared, considering the exact shape coefficient of the circular inclusion and its approximation with a polygonal. Next, the homogenized elastic coefficients are derived for a composite reinforced by 2D flower-shaped inclusions and with 3D toroidal-shaped inclusions. Finally, the method is applied to polycristals considering Voronoi tessellations for which the description with polygonals and polyhedrons becomes exact. The comparison with the original FFT method of Moulinec and Suquet is provided in order to show the relevance of these numerical bounds.

2021, 11(2): 119 -122.
doi: 10.1016/j.taml.2021.100237

We propose a theoretical model for spatial variations of the temperature variance

2021, 11(2): 123 -127.
doi: 10.1016/j.taml.2021.100239

Impact of viscous sublayer scale roughness elements on large scale flows have not been fully understood and require high resolution 3D flow measurements to unravel. However, existing approaches fail to provide sufficient resolution for such measurements to fully resolve the sublayer. In this study, we use digital Fresnel reflection holography to capture 3D flows within the viscous sublayer at sub-viscous resolutions. The measurement highlights the presence of novel flow structures at the scale of the sublayer, with strong spanwise meandering motions, of 2-3 viscous wall units, indicating a highly unsteady and accelerating flow within. The probability distribution of accelerations shows a stretched exponential shapes characteristic of highly intermittent turbulence seen under isotropic flows. The presence of flow structures even at the scale of the sublayer, i.e., below

2021, 11(2): 128 -133.
doi: 10.1016/j.taml.2021.100240

The laser-induced porous graphene (LIG) prepared in a straightforward fabrication method is presented, and its applications in stretchable strain sensors to detect the applied strain are also explored. The LIG formed on the polyimide/polydimethylsiloxane (PI/PDMS) composite exhibits a naturally high stretchability (over 30%), bypassing the transfer printing process compared to the one prepared by laser scribing on PI films. The PI/PDMS composite with LIG shows tunable mechanical and electronic performances with different PI particle concentrations in PDMS. The good cyclic stability and almost linear response of the prepared LIG's resistance with respect to tensile strain provide its access to wearable electronics. To improve the PDMS/PI composite stretchability, we designed and optimized a kirigami-inspired strain sensor with LIG on the top surface, dramatically increasing the maximum strain value that in linear response to applied strain from 3% to 79%.

2019, 9(6): 339-352
doi: 10.1016/j.taml.2019.06.001

2019, 9(4): 236-245
doi: 10.1016/j.taml.2019.03.004

2020, 10(3): 141-142
doi: 10.1016/j.taml.2020.01.041

2020, 10(2): 116-119
doi: 10.1016/j.taml.2020.01.015

2020, 10(5): 327-332
doi: 10.1016/j.taml.2020.01.051

2018, 8(4): 252-256
doi: 10.1016/j.taml.2018.04.006

2020, 10(6): 377-381
doi: 10.1016/j.taml.2020.01.055

2018, 8(5): 299-303
doi: 10.1016/j.taml.2018.05.007

2021, 11(1): 1-1
doi: 10.1016/j.taml.2021.100238